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Viewstar TM Actemium Cegelec GmbH Product-Catalog Issued: 03.11.2014 Version: [V0.1]
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Page 1: Viewstar - Actemium · PDF file37 1.2.21 Training and Simulation Software ... ViewstarTM Product Catalog Chapter I: Viewstar ICS - SCADA 3 1. SCADA 1.1.Viewstar ICS Main Features –

ViewstarTM

Actemium Cegelec GmbH

Product-Catalog

Issued: 03.11.2014Version: [V0.1]

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.

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Editorial

All copyright and other intellectual property rights to the design, text, graphics, imag-es, pictures, photos or other content of this brochure, shall belong to Actemium Cegelec GmbH only. Any use of publishing, as a whole or in parts thereof, as well as any reproduc-tion of images or other contents, must have the prior written consent of Actemium Cegelec GmbH. The indices of “Viewstar” and “Viewstar Pipeline Cockpit” are registered trademarks of Actemium Cegelec GmbH, and protected as such against any unauthorized use.

Any use, any permanent or temporary reproduction (as a whole or in parts), any of the acts of loading, displaying, running, transmitting, storing or the translation, adaptation, ar-rangement and any other alteration and the reproduction of the results thereof, any use of the original or copies of the content for distribution purposes and any form of distribution to the public, including rental, communication to the public or making available for the public is only permitted subject to our express prior consent in writing. Infringements (in particular copyright and personal rights) may be pursued under civil and penal law.

Actemium Cegelec GmbH does not assume responsibility for the completeness, suitability and correctness of these contents or for any particular results achieved in treating or pro-cessing the products. For the purpose of use please contract Actemium Cegelec GmbH for clarification.

Contact:

Actemium Cegelec GmbH

Colmarer Straße 5

60528 Frankfurt am Main/Germany

[email protected]

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Index of Contents

• ViewstarTM- Product Catalog .................................................................................................................... 1• Chapter I: Viewstar ICS - SCADA ........................................................................................................... 31. SCADA ...................................................................................................................................................... 3 1.1. Viewstar ICS Main Features – Overview .................................................................................... 3 1.2. Viewstar ICS Features – Detail ........................................................................................................ 5 1.2.1 OnlineConfiguration ......................................................................................................... 5 1.2.2 Redundancy ........................................................................................................................... 6 1.2.3 Disaster Recovery System ................................................................................................ 7 1.2.4 Distributed Systems ......................................................................................................... 10 1.2.5 Web Client ........................................................................................................................... 11 1.2.6 Ultralight Client .................................................................................................................. 11 1.2.7 Excel Report ........................................................................................................................ 12 1.2.8 Communication Center .................................................................................................. 12 1.2.9 Advanced Maintenance Suite (AMS) ........................................................................ 14 1.2.10 Video ........................................................................................................................................15 1.2.11 GIS Viewer ........................................................................................................................... 18 1.2.12 Authentication via Kerberos ......................................................................................... 19 1.2.13 Encryption ........................................................................................................................... 19 1.2.14 Multilingual support ........................................................................................................ 20 1.3. Viewstar ICS Gateway .................................................................................................................... 21 1.3.1. Overview .............................................................................................................................. 21 1.3.2. Communication Technologies ..................................................................................... 22 1.3.3. Platforms .............................................................................................................................. 23 1.4. Viewstar ICS Add-Ons ................................................................................................................... 24 1.4.1. Interface to a Data Warehouse (Customer Database) ......................................... 24 1.4.2. Data Interface to external pipeline simulation software ................................... 25 1.4.3. Blocking Messages in the event of Flutter Signals .............................................. 25 1.4.4. Dynamic Screen Generation ......................................................................................... 25 1.4.5. Disaster Recovery System for Distributed Systems ............................................. 25

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• Chapter II: .................................................................................................................................................. 28• Viewstar ICS Technology Packages ................................................................................................... 281. Viewstar ICS PipelineCockpitTM ........................................................................................................... 29 1.1 Viewstar ICS Oil ................................................................................................................................. 29 1.2.15 Leak Detection ................................................................................................................... 30 1.1.1.1 Mass Balance ...................................................................................................................... 30 1.1.1.2 Dynamic Mass Balance ................................................................................................... 30 1.1.1.3 Pressure Drop Gradient Monitoring .......................................................................... 31 1.1.1.4 PressureProfileMonitoring .......................................................................................... 31 1.1.1.5 Pressure Drop Monitoring ............................................................................................ 31 1.1.1.6 Min / Max Pressure during non-pumping periods ............................................. 32 1.1.1.7 Leak (tightness) Testing according to the PT Method ....................................... 32 1.2.16 Leak Location ..................................................................................................................... 33 1.1.2.1 Leak Location according to the Runtime Method ............................................... 33 1.1.2.2 Leak Location by means of Error Calculations ...................................................... 33 1.2.17 Stress Analysis and Residual Life Time Calculation ............................................. 34 1.2.18 Route Control Management ........................................................................................ 35 1.2.19 Batch Tracking ......................................................................................................................35 1.2.20 Scraper Tracking ................................................................................................................ 37 1.2.21 Training and Simulation Software .............................................................................. 372. Equations, models, methods ............................................................................................................... 38 2.1. Basic equations .................................................................................................................................. 39 2.1.1. Conservation of mass, momentum and energy ................................................... 40 2.1.1.1. Conservation of mass (equation of continuity) ..................................... 40 2.1.1.2. Conservation of momentum (equation of motion) ............................. 40 2.1.1.3. Conservation of energy .................................................................................. 40 2.1.2. Further equations ............................................................................................................. 41 2.1.2.1. Cross section ....................................................................................................... 41 2.1.2.2. Acoustic velocity ................................................................................................ 41 2.1.2.3. Thermal equation of state .............................................................................. 42 2.1.2.4. Quasi-steady friction ........................................................................................ 42

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2.1.3. Flow processes in pipelines .......................................................................................... 42 2.2. Flow processes in systems ........................................................................................................... 44 2.3. Units as well as spatial and temporal discretization ........................................................... 47 2.4. Mixing and transport processes - tracking ........................................................................... 48 2.4.1. Mixing processes .............................................................................................................. 48 2.4.2. Temperature transport ................................................................................................... 49 2.4.3. Transport processes in pipelines ................................................................................ 49 2.5. Thermodynamic properties of real gase s .............................................................................. 51 2.5.1. Enthalpy und entropy ..................................................................................................... 51 2.5.2. Specificheat ....................................................................................................................... 52 2.5.3. Polytropic and isentropic exponents ........................................................................ 53 2.5.4. Isentropic and polytropic head ................................................................................... 54 2.6. Selected equipment components .............................................................................................. 54 2.6.1. Compressor and characteristic map ........................................................................... 54 2.6.2. Pressure regulator and characteristic curve ........................................................... 58 2.7. Model Quality .................................................................................................................................... 62 2.8. Simulation instances ...................................................................................................................... 66 2.9. Nomenclature (Englisch) / Nomenklatur (German) ........................................................... 69 2.9.1. Greek Letters / Griechische Buchstaben ................................................................. 69 2.9.2. Latin Letters / Lateinische Buchstaben u. Abkürzungen .................................. 70 2.10. Tableoffigures ................................................................................................................... 763. Viewstar ICS TAS ........................................................................................................................................ 77 3.1 Introduction ........................................................................................................................................ 77 3.2 Fields of Application ....................................................................................................................... 77 3.2.1 System Structure ............................................................................................................... 78 3.2.2 TypicalTankDepotConfiguration .............................................................................. 79 3.3 Function Modules ........................................................................................................................... 81 3.3.1 Administrative Data Management AdminNET ...................................................... 81 3.3.2 Tank Depot Management / Control .......................................................................... 833.4 Example Screenshots of the SCADA System Graphics ............................................................... 84

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ViewstarTM Product Catalog 1

VINCI Energies, a subsidiary of the VINCI Group, is a global provider of energy and infor-mation technology services operating in four business lines: industry, infrastructure, the service sector and telecommunications.

VINCI is a global player in cencessions and construction, employing 191.000 people in about 100 countries.

Optimizing your sites, developing new markets, coping with technical and regulatory con-straints,enhancingresponsiveness,safetyandquality,boostingenergyefficiency,theim-provement of your performance is the heart of your projects.

To address this complex and demanding reality, VINCI Energies has developed a brand 100 % dedicated to industry: Actemium.

The Actemium network’s size and organizational structure, broad range of expertise and abilitytosharefeedbackenableitsteamstocommittoofferingandimplementinnovationsolutions and services that create added value.

Actemium has more than 50 years of experience in supplying automation solutions for the oil, gas and water industries worldwide and creating added value based thru the Viewstar Automation platform.

In this document we describe our scope of Viewstar™ comprising not only the general au-tomation with SCADA systems, but also special technological software solutions for the oil, gas and water industries.

Viewstar™- Product Catalog

Actemium Cegelec GmbH Viewstar™ - Product-Catalog 1

Viewstar™- Product Catalog

VINCI Energies, a subsidiary of the VINCI Group, is a global provider of energy and information technology services operating in four business lines: industry, infrastructure, the service sector and telecommunications.

VINCI is a global player in cencessions and construction, employing 191 000 people in about 100 countries.

Optimizing your sites, developing new markets, coping with technical and regulatory constraints, enhancing responsiveness, safety and quality, boosting energy efficiency, the improvement of your performance is the heart of your projects.

To address this complex and demanding reality, VINCI Energies has developed a brand 100 % dedicated to industry: Actemium.

The Actemium network’s size and organizational structure, broad range of expertise and ability to share feedback enable its teams to commit to offering and implement innovation solutions and services that create added value.

Actemium has more than 50 years of experience in supplying automation solutions for the oil, gas and water industries worldwide and creating added value based thru the Viewstar Automation platform.

In this document we describe our scope of Viewstar™ comprising not only the general automation with SCADA systems, but also special technological software solutions for the oil, gas and water industries.

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Actemium Cegelec GmbH2

Benefitforourcustomers,solutionoutofonehand,andautomationfunctionsaccessedthrough one system, Actemiums PipelineCockpit, designed as an open platform from oper-ation to optimization.

Onecommonoperatorinterfacefordifferentrequirementsforoperation,dispatching,maintenance and optimization of a pipeline as well as the required functions behind.

The PipelineCockpit will be an integrated part of a SCADA System, contained in one tool or closed linked to it.

The PipelineCockpit will be further developed for Gas Pipeline Applications as well as for GasExploration(GasfieldCockpit).

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ViewstarTM Product Catalog · Chapter I: Viewstar ICS - SCADA 3

1. SCADA

1.1. Viewstar ICS Main Features – OverviewAll those who have responsibilities for the planning and realisation of industrial-scale pro-cesses - such as transportation and distribution of oil, gas and water or the operation of compressor or pumping stations, gas or oil storage, water and sewage technology plants – arefacingonecommonrequirement:useofprocesscontrolsystemsthateffectively,safelyand economically monitor and control the facilities by using the most modern technology.

Our product Viewstar Integrated Control System, short Viewstar ICS, is a basis for a fu-ture-oriented solution of these individual challenges.

Viewstar ICS realises plant visualisation, process data acquisition and analysis, control, alarming, reporting and status functions. For the oil and gas industry and the operators of water or districted heating networks, our company provides apart from the standard SCA-DA functionality also technological applications.

Tofulfilthevariouscustomerrequirementsregardingoperatingsystemourproductisbased on the three major systems like Windows, Linux and Solaris.

This document describes state-of-the-art main features a modern SCADA system like View-star ICS provides.

These are:

• Object oriented Design Object-orientation in data model and graphical editor.

• Integrated Graphic Editor The graphical editor is part of the Viewstar ICS HMI (human machine interface).

• OnlineConfiguration Datamodelandgraphicalinterfacecanbemodifiedwithoutsysteminterruption.

• Redundancy Redundancy is an integral part of Viewstar ICS. The most common case is, however, the du-plication of hard and software. Reliability is achieved in Viewstar ICS using a redundant sys-tem with hot standby.

Chapter I: Viewstar ICS - SCADA

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Actemium Cegelec GmbH4

• Disaster Recovery System A second (redundant) Viewstar ICS server system in “warm standby” mode as emergency backup system.

• Distributed System Distributed systems are two or more autonomous Viewstar ICS systems connected via a network.

• Web Client Supports the visualization and operation of Viewstar ICS panels within all common web browsers on personal computers or selective mobile end devices (notebooks, net books) that are connected to the network.

• Ultralight Client Via tablet or mobile phones the pipeline can be monitored and controlled without any in-stallation on the devices.

• Excel Report ReportingwithMicrosoftExcel.WithanAddInaflexiblereportgeneratorandreportview-er is available in a well-known environment.

• Communication Center A modern alarm management/remote alerting and communication with current standards andusingdifferentmedia,likevoicemail,SMS,andemail.

• Advanced Maintenance Suite Easilyparametricalsoftwaretoolforefficientplanning,management,realizationandcon-trol of maintenance work and equipment failures. All events can be evaluated via statistics and communicated via reports.

• Video For display of video streams on an operator station, i.e. the visualization and control of video components, such as cameras, encoders / decoders, network video recorders and monitors.

• GIS Viewer Display of facility objects on a map. For a well-arranged view and intuitive navigation for widespread systems.

• Authentication via Kerberos Third-party authentication protocol, based on Kerberos.

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ViewstarTM Product Catalog · Chapter I: Viewstar ICS - SCADA 5

• Encryption The encryption of scripts/libraries protects the project knowledge and work.

• Multilingual support A running Viewstar ICSsystemcanbeoperatedindifferentlanguages,thatis,oneandthesamesystemcanbeoperatedfromdifferentterminalsindifferentlanguagesandtheter-minals can switch between languages.

1.2. Viewstar ICS Features – Detail

• Object Oriented Design Signalsaretreatedwithrespectoftheiroriginalaffiliation,i.e.datapointelementsofade-vice are represented in a hierarchical structure and are treated as a whole throughout the system. That includes graphical objects which go together with data model objects. Chang-es in the prototype are inherited by all its copies.

• Integrated Graphic Editor

Actemium Cegelec GmbH Viewstar™ - Product-Catalog

5

1.2. Viewstar ICS Features – Detail

• Object Oriented Design

Signals are treated with respect of their original affiliation, i.e. data point elements of a device are represented in a hierarchical structure and are treated as a whole throughout the system. That includes graphical objects which go together with data model objects. Changes in the prototype are inherited by all its copies.

• Integrated Graphic Editor

Picture 1: Overview of GraphicEditor

The Graphical Editor provides tools for creating and parameterizing graphic objects. It has a direct interface to the data model configuration tool and is likewise object-oriented.

1.2.1 Online Configuration

Viewstar ICS allows performing most engineering steps online:

• Creation / modification of data point types

• Creation / modification of data points

• Drawing / modification of panels, symbols

Picture 1: Overview of GraphicEditor

The Graphical Editor provides tools for creating and parameterizing graphic objects. It has adirectinterfacetothedatamodelconfigurationtoolandislikewiseobject-oriented.

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Actemium Cegelec GmbH6

1.2.1. Online Configuration

Viewstar ICS allows performing most engineering steps online:

• Creation/modificationofdatapointtypes

• Creation/modificationofdatapoints

• Drawing/modificationofpanels,symbols

• Creation/modificationofscripts

• Modificationinconfiguration

No restart of the application required. Engineering without any interrupts in operation.

1.2.2. Redundancy

The high availability requirements of plant constructors and operators as well as the pro-cess and data security can be covered with the redundancy concept of Viewstar ICS. The exactconfigurationoftheredundantcomputersystemvariesduetothedifferentrequire-ments. The most common case is, however, the duplication of hard and software. Redun-dancy is an integral part of Viewstar ICS.

Reliability is achieved in Viewstar ICS using a redundant system with hot standby. Hot standby is a hardware independent solution for high availability. The hot standby concept uses two servers connected to each other. Both servers are operating permanently and are subject to same functional demands (only one server is, however, always active. The second server synchronizes the data at runtime with the primary unit). If the active server fails the systemswitches“onthefly”tothepassiveserver,whichtakesovercontrolandbecomesthe active server. As a result, access to data or functions is always guaranteed.

Furthermore there is the split mode for the redundancy. In the split mode the redundant servers are separated. A system remains “active”, runs normal and takes care of the operat-ingterminals.Thesecondservercanbeusedfortestsofnewconfigurationsandforcon-figurations.Thereafterthestateautomaticallyreturnstonormal(redundancy)onthebasisofanarbitraryserver(keeptheoriginalconfigurationorestablishthenewconfiguration).

A redundant Viewstar ICSsystemfulfilsthefollowingtasks:

• Fast and correct switching in case of errors

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ViewstarTM Product Catalog · Chapter I: Viewstar ICS - SCADA 7

• Balancing of dynamic data at runtime

• Balancing of the historical data after the project start (Recovery)

• Continuouscontrolofdifferentcomponentsonbothsystems(Manager,RAM memory, disk space, arbitrary data points)

• Theweightingofthecomponentscanbeconfiguredaccordingtothe case = “Error state”

• Interpretation of the system state and administration of the active/passive state

• Automatic(ifactivated)synchronizationoffilesbetweenthesystems,whenthe system was in split mode before.

Advantages of redundancy in Viewstar ICS:

• Reliability via hot standby

• Increase of data security via double data records in two separated databases.

• Testofnewconfigurationsandconfigurationswithoutinterferingtheoperation.

• Guarantee of best possible plant security via avoiding of operation interruptions.

1.2.3. Disaster Recovery System

Actemium Cegelec GmbH Viewstar™ - Product-Catalog

7

• Automatic (if activated) synchronization of files between the systems, when the system was in split mode before.

Advantages of redundancy in Viewstar ICS:

• Reliability via hot standby

• Increase of data security via double data records in two separated databases.

• Test of new configurations and configurations without interfering the operation.

• Guarantee of best possible plant security via avoiding of operation interruptions.

1.2.3 Disaster Recovery System

Picture 2: Sytem architecture of Disaster Recovery System

High availability and reliability are becoming more important in automation technology. Even a short breakdown can result in significant costs and security risks. This can be prevented with the aid of the Viewstar ICS Disaster Recovery System.

As a management system, Viewstar ICS system has an integrated Hot Standby Redundancy Concept. With this, the high demands of system authors and operators for availability as well as process and data security can be covered. It is a security concept that consists of two interconnected servers. Both are permanently operational and are subject to the same functional stresses. Only one server is always active. The

Picture 2: Sytem architecture of Disaster Recovery System

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Actemium Cegelec GmbH8

High availability and reliability are becoming more important in automation technology. Evenashortbreakdowncanresultinsignificantcostsandsecurityrisks.Thiscanbepre-vented with the aid of the Viewstar ICS Disaster Recovery System.

As a management system, Viewstar ICS system has an integrated Hot Standby Redundan-cy Concept. With this, the high demands of system authors and operators for availability as well as process and data security can be covered. It is a security concept that consists of two interconnected servers. Both are permanently operational and are subject to the same functional stresses. Only one server is always active. The second passive server synchroniz-esthedataatruntime.Ifaunitfails,a“flyingswitch-over”isexecutedandtheserverthatwas passive until then takes over the control.

Aim of the Disaster Recovery System: The redundancy concept is extended by a Warm Standby System, so that the operability of the system nevertheless remains maintained on the other system even in the event of a complete failure or shutdown in the course of e.g. maintenance on the redundant system. Thus, the data loss and the idle time are kept as low as possible. This is achieved by a second system, the so called secondary server system(SSS),beingassignedtothefirstredundantHotStandbySystem(primary server system; PSS) and a “Warm Standby” being implemented between the two systems. This means that the data between the two systems is permanently synchronized.

This has two advantages:

(1) In the case of a complete system failure, the system remains operable.

(2) The historical data can be retrospectively synchronized.

The main demand on the Disaster Recovery System is to keep data loss, inoperability and the idle time from the side of the management system as low as possible. In order to guarantee this, a constant synchronization of the online and parameterization data be-tween the PSS (Primary Server System) and the SSS (Secondary Server System) is essential. Since the quantity of this data is, however, very extensive and is linked to the size of the project,thesystemoperatorortheintegratorshouldmanageanddefinethescaleandthesynchronization interval between the two systems as far as possible.

The following functions are provided by the Disaster Recovery System:

• Synchronisation of the online data changes between PSS and SSS at runtime.

• Synchronisation of the alarm status (acknowledgement status, acknowledgement time, acknowledgment user) between PSS and SSS at runtime.

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ViewstarTM Product Catalog · Chapter I: Viewstar ICS - SCADA 9

• Cyclical synchronisation of the parameterization changes (alert handling, data point functions, etc.) between PSS and SSS.

• Automatic (cyclical) or manually triggered synchronisation of the project files (panel files,controlscriptsandlibraries,datapointlists,colordatabases,graphicfilesandim-ages, text catalogues).

• Synchronisation of the historical data (via Sybase or Oracle packages) after triggering by the user after an SSS system failure or an interruption in the connection between PSS and SSS.

• Synchronization of the user administration (user data).

• Automatic switchover between PSS and SSS and automatic/manual shift-in between SSS and PSS.

• Working with a user interface that is either connected to the PSS or to the SSS (two differentfilelinksarenecessaryonthedesktop)ispossible.

• Automatic switchover at the client between the user interface of the PSS and the SSS to the currently running system (two user interfaces active in parallel), if a second UI li-censeisavailable.Otherwiseamanualstartofthefirstsystemisrequired,ifthishasbroken down.

Normal Operation Mode

Inthenormaloperationmode,thePSSsystemsupportstheconnectiontothefielddevices(or master control station with OPC UA port) and updates all values to the SSS.

On the work station, there are two possibilities:

• Two Viewstar ICS user interfaces are started. One has a connection to the PSS and the other to the SSS. The UI of the managing system runs in the foreground. All panel switchovers from this UI are automatically communicated to the other UI (this is visible for the user only then, when the connection to the PSS has failed), so that both SCADA user interfaces always have the same image displayed.

• A Viewstar ICS user interface that supports the connection to the PSS is started or a Viewstar ICS user interface is started that supports the connection to the SSS. The de-cision is made by the user after the connection to the active system is lost. The user re-trievesanotification,whentheothersystembecomespassiveagainandthentheuser

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interface with the connection to the other system has to be opened.

PSS (Primary Server System)

The PSS consists of a redundant Viewstar ICS system, in which diverse drivers and con-trolmanagersrunandthereforemaintainandfurtherprocessthecurrentdataofthefielddevices (or FrontEnd). Between the two servers within the primary server system, the Hot Standby Concept is dominant.

SSS (Secondary Server System)

The SSS is intended for management in case of a complete failure of the PSS or mainte-nance on the PSS. It is also a redundant Viewstar ICS system that has the same parameter-ized drivers and control managers as the PSS. Considered from a simple point of view, it is areflectionofthePSS.

Normally,theSSShasnoconnectiontothefielddevices(orFrontEnd)andalsodoesnotcarry out calculation procedures (except for Viewstar ICS internal calculations such as error quantifiers,compressions,etc.).Nevertheless,theprocessdataisavailablewithaverylowdelay on this system, since the values of the data points and the alarm status are continual-ly communicated from the PSS.

If both computers of the PSS fail, the servers of the SSS take over the complete monitoring and control of the project. For the user, this simply means a short interruption in the oper-ationoftheapplicationbeforetheSSStakesoverthecontrol,thenconfigurestheconnec-tiontothefielddevices(orFrontEnd)andprovidesthecurrentvaluesfortheuser.

If the server that failed on the PSS takes the operation again, the Disaster Recovery System executes the reverse data migration. During such a fallback switchover, the Viewstar ICS managers are started again on the PSS and the data is synchronized with the current data on the SSS. Furthermore, in the course of a fallback procedure, the historical data can also be synchronized. Thereby it is made certain that all changes that occurred after the failover are also available on the PSS.

1.2.4. Distributed Systems

The Distributed function of the Viewstar ICS system allows connecting two or more auton-omous Viewstar ICS systems via a network. Each subsystem of a distributed system can be configuredeitherassingle-stationsystemormultiple-stationsystemineachcaseredun-

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dant or not redundant.The distributed function of the Viewstar ICS system is intended for solving the following problems:

• Connecting several stand-alone Viewstar ICS systems

• Increased performance (increase of the entire performance and number of the DPEs via load sharing on several computers)

• 1 central system and “unoccupied” subsystems

Each system processes and displays data (values and alerts) of other systems. It is possible to access online values, alerts and history of each system by using distributed systems in Viewstar ICS (“distributed database”).

Advantages of distributed systems in Viewstar ICS:

• Flexibility and scalability

• Increased performance: parallel processing, load sharing

• Fault tolerance: availability increase of the complete system

Complete identical systems (data point types and data points) have to be parameterized only once.

1.2.5. Web Client

By the means of the Web Client the Viewstar ICS system supports the visualization and op-eration of Viewstar ICS panels within all common web browsers on personal computers or selective mobile end devices (notebooks, net books) that are connected to the network.

From technical point of view the Viewstar ICS Web Client is a plug-in, which is download-ed via the web browser (which is used on the client) and then displays a SCADA UI manag-er embedded in the HTML web site. Thus, a Viewstar ICS installation on the client computer is not required (except the needed Web Client plug-in).

The Viewstar ICS Web Client is a Viewstar ICS front-end client and does not need local in-stalled project data. All data required for visualization and for control is downloaded as needed from the server via an HTTP download and is stored in the cache directory on the client.

The Viewstar ICS Web Server is started on separate computer hardware. Its web access is

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shieldedbyfirewalls.TheViewstarICS Web Clients connect to the Web Server instead of directly to the SCADA server.

1.2.6. Ultralight Client

This ultralight client is a computer client for web browsers. You do not need to install any software or plug-in. With the aid of the Viewstar ICS Pocket Client, panels can be displayed in the most common web browsers, which support JavaScript, on the client. The compati-ble panels could easily be created with the script wizard.

The principle of the Viewstar ICS Ultralight Client is similar to the Web Client but has the following advantages:

• For the use of the Ultralight Client neither the installation of a web plug-in nor other ad-ditional software on the client is required.

• Panels can be displayed within the web browser that supports JavaScript on mobile end devices like mobile phones, Tablets, notebooks, etc.

• A lower bandwidth is needed, as once the plant panel was loaded only value changes in messages of collected values are transferred from the web server to the browser.

1.2.7. Excel Report

Viewstar ICS Excel Report is an MS Excel extension for integrated data analysis and report generation using Viewstar ICS archive data.

Viewstar ICS reports are generated in 2 steps. First of all create a template (.xlt) for the re-ports.Inthisstepusethetemplatetodefinehowareportwilllookandwhatdatawillbedisplayed where.

In the next step reports are created, opened and saved. It is possible to generate reports automaticallybydefiningascheduleforwhenaparticularreportshouldbegenerated.Furthermore, it is possible to add printing and saving procedures in this schedule, to be performed at regular intervals.

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1.2.8. Communication Center

The Communication Center of the Viewstar ICS system stands for a modern alarm manage-ment/remotealertingandcommunicationwithcurrentstandardsandusingdifferentme-dia.Theincreasedneedofsecurityinthefieldofautomationandprocesscontrolrequiresa guarantee of the high quality and availability of the personnel at a plant. A remote alert-ing system is used at plants also for several other reasons:

• Falling budgets for the personnel expenses

• High costs for night and weekend times in case of 24 hour shifts

• Transition to stand-by duty models in many industry sectors

• Increasing number of unoccupied or partly occupied plants

• The wish of many operators to get location independent information

The use of the Communication Center guarantees an easy use and integration at already existing or new plants. The personnel resources directly on the spot can be decreased con-siderably and lead to a prevention of hard and physiological unpleasant working times for thepersonnel.TheCommunicationCentercreatessynergiesbyusingdifferentinterfacesfor the remote alerting via the control system.

The media SMS and e-mail is covered by the Viewstar ICS Communication Center.

Essential in conjunction with the Communication Center are above all the time and event controlled alarms that have to be interpreted by the personnel at the main computer and thus lead to the necessary steps for the trouble shooting. The communication via the Com-munication Center can be bidirectional. This means that not only the control system is ac-tiveincaseofadisturbanceandinformsspecificpersonsaboutthependingalarmsbuttheon-call duty can get information about the process state at all times.

TheclassificationwhoisinformedaboutaproblemviatheCommunicationCentercanbemade via static call lists (this means the system tries to reach the persons according to the orderdefinedinthelist)orviashifts(thismeansthatthesystemtriestoreachapersonre-sponsible at a particular time). In both cases further persons who should be informed if the listorapersoncannotbereachedataparticulartimecanbedefined.

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The general process in case of a disturbance and forwarding to the user looks as follows:

(1) A disturbance occurs at the plant and is detected

(2) Control system establishes contact to the employee

(3) Alarm information is transferred

(4)User(employee)verifiesthereceipt

(5) The employee decides depending on the complexity of the disturbance (also in case of a greater distance to the plant concrete measures can be taken in order to avert pos-sible dangers):

• Temporarily no measure necessary (await further development)

• Obtain further information via a mobile end device

• Measures via remote maintenance access

• Prompt on the spot duty at the plant

Advantages of the communication center:

• Rapid information via fault reports of a plant round the clock

• Comprehensive recording/quality proof of the states at the plant

• Locationindependenceduringthenotification

• Transition to partly unoccupied plants

• Easy handling and integration into already existing plants

• Preparationofcost-effectivecommunicationmedia/enddevices(Telephone,Cellphone)

• Bidirectional communication with the control system - either the control system informs the user in case of a disturbance or a user gets the information of the current process states at the control system

• Possibility to acknowledge occurred alarms via the communication center

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1.2.9. Advanced Maintenance Suite (AMS)

AMS supports you to plan, manage, execute, document and control all your maintenance tasks.

Theperfecttoolforefficientmaintenancemanagement:

• Reduced down times

• Faster trouble-shooting

• Efficientutilizationofresources

• Optimized spare part management

• Learning system

• Reduction of administrative tasks

AMS supports interworking across all involved departments. Events are monitored and dis-played in real-time. At any time you know what is going on. AMS automatically transforms eventsintoworkorders.Eachinterventionbecomestraceableandtriggersapredefinedworkflow.Requiredqualificationsareallocatedtotheequipmentandthetechnicians.

User and target groups

• Maintenance manager

• Dispatcher

• Technician

• Spare part and tools store employees

• External technicians

Maintenance types

• Operation-based Maintenance Theinterventionistriggeredwhenadevicehasreachedapredefinedlevelofoperatinghours or operating cycles. After the intervention the interval starts again.

• Operation-based life cycle Like „Operation-based maintenance“, but including replacement of the device.

• Time-based Maintenance Theinterventionistriggeredafterapredefinedtimerrange,withoutrespectofrunninghours. After the intervention the timer range starts again.

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• Time-based life cycle Like „Time-based maintenance“, but with replacement of the device.

• Scheduled Maintenance Similar to „Time-based maintenance“, but the intervention is triggered at an exact pre-defineddate.Aftertheinterventionanewdateisset.

• Scheduled life cycle Like „Scheduled maintenance“, but with replacement of the device.

Spare part management

• Work orders include overview about all required spare parts and tools

• Predefinedamountofrequiredspareparts

• Recording of consumed spare parts

• Reports enable to generate list of spare part and tools

Solution database

• Experience from daily business will be reused –permanent growing solution compe-tence

• Accumulated knowledge -available for anyone at any time

• Continuous improvement of work orders and resource operations

1.3.5.1. Video

Viewstar ICS Video management system is used for the operation, observation and con-trol of cameras and crossbars via either an operator keyboard or computer keyboard and mouse.Therefore,comprehensivemonitoringandcontrolofcomplexfacilities(e.g.trafficrequirements) is possible from just one operator station. Thereby, problem situations can be recognized earlier and the user can react to them correspondingly.

The data basis for Viewstar ICS Video framework forms the data model of Viewstar ICS Video. Viewstar ICS Video driver assumes the communication to the video world.

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Viewstar ICS Video framework provides the following components:

• Video Widget for displaying video streams

• Graphic symbols for visualization of video objects in panels

• Diagnosis and overview panel

• Panels for parameterization, creation and status overview of individual video objects in the Object Explorer

• CTRL functions for managing and controlling video options and objects

The following operating possibilities are supported:

• Simple selection of a camera via camera lists, camera ranges, site plans or direct number selection.

• Opening of a camera image on a video monitor or of several camera images on a moni-torwallinpredefinedcameragroups.

• Control of Pan-Tilt Zoom cameras via buttons, a keyboard or an operator keyboard.

• Composing single images or quad-images (4-fold image display)

• Starting and stopping the recording of video streams of individual cameras or camera groups.

• Playback, burning and deleting of video recordings.

Viewstar ICS Video is composed of three components

• Viewstar ICS Video framework

• Viewstar ICS Video EWO

• Viewstar ICS Video manager

Viewstar ICS Video supports a maximum of 2 video monitors per workstation and one operator keyboard for controlling cameras and for operating a monitoring wall. In the standard application, a workstation consists of an operator monitor and a video monitor as well as an operator keyboard. The video monitors are addressed by the operator keyboard as an entity with Monitor 1.

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Viewstar ICS Video Framework

In the Viewstar ICS Video framework, all components for creating the SCADA application are provided for the integrator. The framework contains status panels, parameterization panels for every video object, graphic symbols and functionalities such as the automatic opening of cameras in the case of a failure. The Viewstar ICS Video framework also con-tains all of the data points and CTRL components necessary for using Viewstar ICS Video.

Viewstar ICS Video EWO

A EWO (External Widget Object) is a graphic object (a widget) that is created by the inte-grator and can be embedded into a SCADA panel. A EWO is similar to ActiveX in Windows, yet is platform-independent.

The Viewstar ICS Video EWO contains all of the components that are necessary for the display of live images and videos from network video recorders. Additionally it contains ready-made SCADA panels for displaying quad and single images.

Viewstar ICS Video Manager

The Viewstar ICS Video manager communicates with the following peripheral devices:

• Error indicator driver - communicates with an encoder and shows texts in the case of an error message.

• Pan-Tilt Zoom unit driver - communicates with an encoder and is used for communi-cating control commands.

• Decoder driver - communicates with the monitor wall via the POSA protocol and with the decoder for assigning image sources.

• Network video recorder driver - communicates with a network video recorder and is used for communicating control commands.

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1.2.11. GIS ViewerThe GIS Viewer provides the cartographic representation of objects in Viewstar ICS. This

feature provides numerous advantages, particularly in geographical distributed systems, likeinWater,Traffic,Oil&GasorEnergy.

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1.2.11 GIS Viewer

The GIS Viewer provides the cartographic representation of objects in Viewstar ICS. This feature provides numerous advantages, particularly in geographical distributed systems, like in Water, Traffic, Oil & Gas or Energy.

Picture 3: Overview of GIS System

Functions:

• Displaying maps which are available in the ESRI Shape file format.

• Displaying Viewstar ICS objects (symbols, texts, color changes and/or process values) in different map layers.

• Number of layers unlimited.

• Automatic zoom to pending warnings or alarms.

• Manual zoom (+, - and zoom of an area).

• Easy navigation to plant panels and to the alarm / event screen

Individual geographic areas can be precisely monitored through automatic or manual zoom right down to device level. Should system components be in warning or alarm status this is signified by color, form, symbol, or character on the respective map, allowing fast and precise navigation to the interuption. This Viewstar ICS feature gains more informative value through combination of cartographic information with actual

Picture 3: Overview of GIS System

Functions:

• DisplayingmapswhichareavailableintheESRIShapefileformat.

• Displaying Viewstar ICS objects (symbols, texts, color changes and/or process values) in differentmaplayers.

• Number of layers unlimited.

• Automatic zoom to pending warnings or alarms.

• Manual zoom (+, - and zoom of an area).

• Easy navigation to plant panels and to the alarm / event screen

Individual geographic areas can be precisely monitored through automatic or manual zoom right down to device level. Should system components be in warning or alarm sta-tusthisissignifiedbycolor,form,symbol,orcharacterontherespectivemap,allowingfast

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and precise navigation to the interuption. This Viewstar ICS feature gains more informative value through combination of cartographic information with actual status signals of the plant.Amuchmoreefficientprojectdesignisalsoachievedthroughdynamicmapmaterialrather than static map frames.

Mapscanbeobtainedfrommanydifferentvendors(e.g.:ESRI-EnvironmentalSystemsRe-search Institute).

1.2.12. Authentication via Kerberos

In a more and more networking world, a Viewstar ICSsystemcouldbeexposedtodifferenttypes of attacks. An unauthorized SCADA system could connect to the distribution manag-er or hackers could try to manipulate Viewstar ICS messages.

Inordertopreventeavesdroppingordifferenttypesofattacks,measurestosecureau-thentication and to protect Viewstar ICS systems from such attacks have been developed. The Kerberos based authentication allows each Viewstar ICS component to verify the iden-tity of another component. Viewstar ICS servers verify the identity of clients and clients verify the identity of servers. More than that, Kerberos is able to ensure that messages are notmodifiedduringtransmission(preventingacapturereplayattack)andcanevenbeen-crypted.

The Kerberos protocol is built on symmetric key cryptography and requires a trusted third party, the Key Distribution Center (KDC). The identity of an entity (user, computer, compo-nent) is proven by using tickets. Clients pass a ticket, issued by the trusted third party KDC, totheserver.Theserververifiestheticketandthustheidentityoftheclient.Uponclient’srequest, the server sends a proof of its identity to the client and the client can verify the identity of the server.

Session keys are used for the communication between a client and a server. Kerberos gen-erates a session key that is used to secure the communication between the server and the client. The sent messages are signed and can be encrypted.

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1.2.13. Encryption

The encryption of panels and scripts/libraries (in the following the term “scripts” is used) al-lows encrypting panels or scripts and thus protect your knowledge and work. Thereby, it is guaranteedthatunauthorizedpersonshavenoaccesstoyourdefinedfunctionsandmakeno changes in panels.

Ifyoudonotwanttoprovideyourscriptsorpanels,forexample,ofaspecificfeaturedi-rectly you can also encrypt the panels and scripts and set a license requirement. This meansthatadefinedlicensekeywordhastoexistintheshieldfileinordertousethespe-cificfeature(panels,scripts).Thisprovidesaprofitableadvantagewhendeliveringexten-sions of Viewstar ICSthatwereimplementedwithbigeffortandhighcosts.

1.2.14. Multilingual support

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1.2.14 Multilingual support

Picture 4: Multilingual text in faceplates

Viewstar ICS system is designed to provide both Active Language Support and Multi Language Support.

Native Language Support means that the user can operate his system in his own language with the support of Viewstar ICS thus processing figures, dates, and others in familiar formats, that is, the user works with a particular locale.

Multi Language Support means that a running Viewstar ICS system can be operated in different languages, that is, one and the same system can be operated from different terminals in different languages and the terminals can switch between languages.

In order to parameterize this multi-language capability, Viewstar ICS supports automatic translation by means of translation tables. In particular:

• Texts in files are stored in a cross-platform format.

• Viewstar ICS has a central setting specifying what languages or locales are used by the current system.

• Texts are input and output in several languages in the user interface.

• Language dependent texts are created in dictionaries.

• Panels are printed in the desired language.

• Translations may be imported and exported.

• The translator tool supports online translation.

Picture 4: Multilingual text in faceplates

Viewstar ICS system is designed to provide both Active Language Support and Multi Lan-guage Support.

Native Language Support means that the user can operate his system in his own lan-guage with the support of Viewstar ICSthusprocessingfigures,dates,andothersinfamil-iar formats, that is, the user works with a particular locale.

Multi Language Support means that a running Viewstar ICS system can be operated in differentlanguages,thatis,oneandthesamesystemcanbeoperatedfromdifferentter-

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minalsindifferentlanguagesandtheterminalscanswitchbetweenlanguages.

In order to parameterize this multi-language capability, Viewstar ICS supports automatic translation by means of translation tables. In particular:

• Textsinfilesarestoredinacross-platformformat.

• Viewstar ICS has a central setting specifying what languages or locales are used by the current system.

• Texts are input and output in several languages in the user interface.

• Language dependent texts are created in dictionaries.

• Panels are printed in the desired language.

• Translations may be imported and exported.

• The translator tool supports online translation.

1.3. Viewstar ICS Gateway

1.3.1 Overview

Viewstar ICS Gateway (formerly Viewstar RCI Gateway; RCI: Remote Control Interface) is a solution for connection of complex process data to your existing or new SCADA systems.

The process communication system is rarely renewed at the same time together with the SCADA system. Preferably, several generations are skipped in order not to put the stability of the existing process automation at risk.

For this reason, it may be necessary to take the following system conditions and parame-ters into account when realising a new SCADA system:

• Collectionofproductiondataindifferentsubsystems

• Differenttransferandcommunicationsystemsfordifferentpartsofaplant

• IntegrationofprocessandtelemetrycontroldatafromdifferentsystemsintotheSCA-DA system

• Complexand/orhierarchicalautomationstructureswithdifferentSCADAsystems

Viewstar ICS Gateway is a comfortable solution for all these and many other requirements for the connection of process data to be met for your SCADA system.

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Processorremotetelemetrydataisoftengeneratedbydifferentcontrolsystemsalongaproduction chain or through extensive remote telemetry control processes.

Viewstar ICSGatewayshelpyoutooptimallyandeffectivelyminimisethecostsforthein-tegrationofdifferentautomationworlds.

Your Advantage when Using Actemium’s Viewstar ICS Gateways

• Standardised front end server for your SCADA technology.

• State-of-the-art technology: Redundancy for LAN and other system components are available

• Can also be used as PLC or a substation front end

• Support of almost all communication systems such as dedicated lines, party lines, AWD, VSAT, radio, PCM or SDH networks, …

• Runs on a customized Linux operating system, therefore more rubust and less fail-ure-proned than devices based on full MS Windows installations.

1.3.2. Communication Technologies

Controlsystemsoftenspeakdifferentlanguagesrespectivelyarenotequippedwithin-terfaces utilizing standardised communication protocols such as IEC 60870-5-101/104 or ModbusTCP/RTU.

Viewstar ICS Gateways support a wide range of communication protocols of the process and telemtry control technology:

• IEC60870-5-101/104

• Modicon Modbus series family

• AEG Modnet series family

• AEG Seab 1F

• GT2100

• ABB RP570/571

• Siemens Sinaut ST1, 7

• CIP (Common Interface Protocol)

….

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Moreover,therearemanydifferentkindsofphysicaltransfertechnologies,withwhichtheViewstar ICS Gateways can cope with, such as

• Serial dedicated lines

• Serial dial up lines

• Satellite links

• GPRS

• GSM

Thesoftwarehasamodularstructure,allowingdifferentprotocolstobeusedperViewstarICS Gateway or new features or protocols to be integrated into your application more easily.

UsingstandardisedsoftwarelibrariesandAPIsenablescustomer-specificextensions.

1.3.3. Platforms

Viewstar ICS Gateways are available as embedded and PC versions.

The embedded version is a compact solution without any moving parts for DIN rail mount-ing and supports usually two to four serial interfaces according to RS-232/485 standard as well as one to four Ethernet LANs.

The PC platform is used when a bigger number of interfaces are required. In this respect, wesupportconfigurationswithupto64serialinterfacesandseveralEthernetcardsbymeans of which several hundreds of stations can be coupled via TCP.

SuSe Linux or RedHat Enterprise Linux is used as the operating system.

One or several control systems can be connected by means of simple or redundant Fast Ethernet LANs. Among others, Viewstar ICS Gateways support the protocols IEC 60870-5-104 and Modbus TCP.

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1.4. Viewstar ICS Add-Ons

The Viewstar ICS Add-Ons are a collection of proprietary solutions for customer require-ments in various projects. They are managed centrally by us and are available for all projects.

1.4.1. Interface to a Data Warehouse (Customer Database)

Customers can operate so-called data warehouses (SQL database) for data access from their own specialist departments and for external customers. Viewstar ICS provides to this data-base archive data such as results, gas data, counter values and gas quality information.

The interface ensures that data is transferred correctly.

In this respect,

• server redundancy

• the status of the main control center as well as the backup control center

are taken into account.

The data warehouse is based on a Sybase database cluster including replication between the main and the backup conroll centers.

Thedataflowiscarriedoutinthreesteps:

• Export of the Viewstar ICSarchiveintofiles

• TransferofthesefilestotheSIGOsystem

• ImportofthefilesintotheSIGOsystem

1.4.2. Data Interface to external pipeline simulation software

Data transfer between Viewstar ICS and special external simulation software might require programms written in Java. These programms use both the Viewstar ICS API and that of the simulation software to transfer current data and archive data between the servers.

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1.4.3. Blocking Messages in the event of Flutter Signals

In case an input signal changes more than ten times within 30 seconds, it is blocked, i.e. an entry, “too many changes – BLOCKED”, is entered into the event archive. All following changes are no longer written into the event archive. From then on, blocked signals are permanently monitored and only unblocked, if no further changes have occurred e within 20 minutes. In that case the entry “Blocking deactivated” is written into the event archive.

Byreviewingtheeventarchiveorthelogfilesoftherespectivecontrolmanager,itcanbedeterminedwhichinputsignalsflutterhowoften.

1.4.4. Dynamic Screen Generation

Dynamic Screen Generation according to the Assignment Matrix or Types of Stations:

For technical reasons in respect to the communication system, new stations can often only beconnectedtothesystemofthelocalcontrolcenterofaspecificdistrict.However,thenewstation is actually managed and in respect to control from another district. Therefore, it must bepossibletoassignstationstodifferentareasintheViewstarICS communication system.

1.4.5. Disaster Recovery System for Distributed Systems

High availability and reliability (failure safety) have always been important factors in the fieldofautomationtechnology.Evenashort-termfailuremayresultinsignificantcostsandsafety risks.

Our communication system is already equipped with a hot-standby redundancy concept. In this concept, the high requirements set by system manufacturers and operating companies for availability as well as process reliability and data security can be covered. This concept is a safety concept consisting of two servers which are connected to each other. Both serv-ers are constantly in operation and subject to the same functional stress and load. At all times, only one server is active. The second, passive server synchronises the data at runt-ime.Ifaunitfails,a“flyingchangeover”takesplacesandthepassiveservertakesoverthecontrol operation.

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With the disaster recovery system, the redundancy concept is extended to include a warm standby system, which means that the operability of the system is still maintained in the event of a complete failure or a complete shutdown, such as in the course of maintenance workcarriedoutonthefirstredundantsystem.Thelossofdataandthedowntimearekeptas low as possible by assigning a second system, a so-called “secondary server system”, to thefirstredundanthot-standbysystemandrealisinga“warm-standbysystem”betweenthetwosystems.Thismeansthatthedataaresynchronisedbetweenthesystemsatdefin-able intervals.

This entails two advantages:

• In the event of the complete failure of a system, the plant can still be operated.

• The historical data can be synchronised again afterwards.

In contrast to the standard version of our control system, the functionality of such a disas-ter recovery system was developed and realised for one of our customers without the inte-gration of an Oracle database.

The main system of the customer system consists of a distributed control system currently with seven redundant Viewstar ICS servers. The backup control center, several hundred km away, is structured identically. The workstations in the two control centers can be connect-ed to either the main station or backup center

Synchronisation takes place for:

• Data model (at least daily)

• User database

• System-specificdatapoints(spontaneous)

Screens and scripts are distributed manually for this customer, since they are changed only rarely.

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Chapter II:Viewstar ICS Technology Packages

Overview

Viewstar TM has a modular design and can thus be adjusted to the respective require-ments. It consists of extensive SCADA functionalities (Viewstar ICS) as well as various tech-nology packages (Viewstar ICS Technology Packages).

Only the interaction of the individual sub-components results in the Viewstar TM and of-fers much more than a common SCADA system.

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1. Viewstar ICS PipelineCockpit™

The PipelineCockpitTM of the Viewstar ICS Technology Packages is the central hub in order to access the most important information regarding operation, maintenance, simulation, optimisation and training and comprises of special functions for both the oil and the gas industry.

1.1. Viewstar ICS OilThe Viewstar ICS Oil Technology Package was designed to monitor and control oil pipe-lines.

The functions are TÜV-tested and comply with TRFL (Technische Regel für Rohrfernleitungen [Technical Rule for Pipelines]).Itallowsquickaccesstoallrelevantsystemdataandoffersreliable error detection and evaluation in order to prevent malfunctions and avoid conse-quential damage.

It can be used for the following areas of application:

• Liquids/fluids

• For single- and multi-product pipelines

• For simple transport pipelines up to highly complex networks

• Fornewpipelinesorfortheretrofittingofexistingpipelines

The Viewstar ICS OilTechnologyPackageoffersthefollowingfunctionalities:

• Leak detection and location (steady state and non- steady state operatings )

• Leak testing

• Stress analysis and residual life time calculation

• Route control management

• Batch tracking / scraper tracking

• Training and simulation software

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1.1.1. Leak Detection

• Severaldifferentmethodsareusedforleakdetection.

• Mass balance

• Dynamic mass balance

• Pressure drop gradient monitoring during pump operation

• Pressureprofilemonitoringduringpumpoperation

• Pressuredrop monitoring during non pumping period

• Min / max pressure during non-pumping periods

• Leak (tightness) testing according to the PT method

1.1.1.1. Mass Balance

The program is used to detect losses during steady state pumping operation. For this pur-pose, it uses the quantity signals of the counters, i.e. the source and sink counter.

The sources are the feed points for the pipeline, e.g. tank depots with a pumping station. The sinks are the targets, i.e. the recipients of the transported product, e.g. tank depots, airports etc.

For each mode of operation, the quantity comparison program separately subtracts the quantities of the sinks from the quantities of the sources, accumulates the deviations, indi-cates them and checks them for warning level or alarm limit value violations.

1.1.1.2. Dynamic Mass Balance

The program is used to detect losses during the non- steady state pumping operation, i.e. during the start up or shut down of the pipeline pump operations.

Itisamodel-basedmethod,bymeansofwhichthedifferenceofthequantitiesfedanddischarged per time unit is compared to the temporal changes in the pipeline content cal-culatedduringtheprocess.Ifthisbalancingresultsindeficitsexceedingadefinedandcon-figurablethresholdvalue,analarmisgeneratedandshownintheSCADAsystem.

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1.1.1.3. Pressure Drop Gradient Monitoring

The program is used to detect losses during the steady state pump operation. It uses spon-taneous pressure changes (pressure drop gradients) made available by the remote control sub-stations with timestamps.

Theprogramisabletomonitorseveralmodesofoperation(max.numberisaconfigurablefactor) at the same time.

The remote control sub-stations monitor the pressure measurement values with respect to pressuredropgradients.Iftheyexceedaconfigurablelimitvalue,analarmisgeneratedinthe SCADA system.

This method is applied to locate leaks during steady state operation (see chapter Leak Lo-cation).

1.1.1.4. Pressure Profile Monitoring

The program is used to detect losses during steady state pump operation. It uses pressure changes which do not occur during steady state operation.

Ifnofurthergradientmessagesarereceivedafterasettlingtimehasexpired,theprofilemonitoring program enters the “monitoring active” status. Then, the application ignores the gradient messages.

It saves the current pressure values as reference values and starts the correction time countdown. After the parametrisable correction time of 30 minutes (example value) has ex-pired, the application overwrites the reference values with the current actual values (updat-ing). This action eliminates process-related pressure changes such as rising tank counter-pressure.

1.1.1.5. Pressure Drop Monitoring

The program is used to detect losses during the non pumping period . It monitors pressure changes which cannot be ascribed to temperature changes. To this end, it determines the leakage rate based on the pressure and temperature measurement values and monitors it.

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Ifthedetermineddeviationexceedsaconfigurablelimitvalue(e.g.-2bar),theapplicationchecks if this pressure change is related to the temperature. For this purpose, it initiates a calculation according to the PT method.

1.1.1.6. Min / Max Pressure during non-pumping periods

The program monitors pipeline segments for minimum pressures (pressure can fall below vapour pressure in the geographical hight points of the pipeline) as well as for maximum pressures(pressurerisecausedbythermaleffects).

1.1.1.7. Leak (tightness) Testing according to the PT Method

The program is used to detect creeping losses during the non pumping periods . It doc-uments the pressure and temperature curves during testing, determines the leakage rate based on the start and end values and marks limit transgressions in the protocol.

Regular leak testing is a requirement set by the approving authority.

The application saves the values pressure P1 and average temperature T1 as start values for each selected measuring point. Then, the acquisition cycle time of four (4) hours, for in-stance, starts.

After the acquisition cycle time has expired, the application saves the values pressure P and average temperature T in a protocol for each section. During the entire pressure wave monitoring, the operator can select the table of the saved values with the respective time saved. Based on these values, the operator can observe the trend and, if necessary, initiate termination in case of an unfavourable tendency.

1.1.2. Leak Location

The following methods are used for leak detection:

• Leaklocationaccordingtotheruntimedifferencemethod

• Leak location by means of error calculations

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1.1.2.1. Leak Location according to the Runtime Method

The program detects the location of leakages during steady state operation.

It uses the same pressure drop gradients as the pressure drop gradient monitoring during thepumpoperation.Inordertoconfirmtheleak,flowrategradientsareusedinaddition.

Theprogramisabletomonitorseveralmodesofoperation(max.numberisaconfigurablefactor) at the same time.

Intheeventofaleak,theinputmassflowbranchesinaleakmassflowandtheoutputmassflowreducedbytheleakmassflow.Thisresultsinachangedpressuredistributionalong the pipeline. Caused by this pressure distribution change, a pressure wave propa-gates axially within the pipeline in both directions, whereby its intensity depends on the spontaneity of the leak and its size.

Thedifferentpassingtimesoftheheadofthepressurewave,runningwithprimaryprod-uct-specificvelocityofpropagationinthestationsalongthepipeline,allowthedirectde-tection of the origin of the pressure wave and thus the point of leakage.

1.1.2.2. Leak Location by means of Error Calculations

The program detects the location of leakages during non- steady state operation.

Tothisend,theerrorcalculations“sourcedifference(eQIp)”and“sinkdifference(eQOp)”areused.Fortheerrorparameter“sourcedifference(eQIp)”,themeasuredflowrateisre-lated to the value calculated from the network model. The same is carried out for the error parameter“sinkdifference(eQOp)”.

Intheeventofaleakage,thereisashiftintherelationbetweenthe“sourcedifference(eQIp)”andthe“sinkdifference(eQOp)”,sincetheleakageflowescapesviatheleak.Bymeans of the percentage shift of the error calculations, the location of leakage can be de-termined.

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1.1.3. Stress Analysis and Residual Life Time Calculation

The program provides the basic data for the assessment of the pipeline ageing due to load cycles and thus for the calculation of the remaining service life.

The software consists of an acquisition and an evaluation module.

Acquisition Module

TheacquisitionmoduleobtainsthepressurevaluescyclicallyfromthetrendbuffersoftheSCADAsystemandentersthemintoASCIIfiles.Thus,thecontinuouspressurecurveisavailable for later evaluation for each month.

IntheSCADAsystem,thevaluesareprocessedaccordingtoconfigurableprocessingin-structions. Each relevant pressure measuring point is subject to gradient monitoring. In the event of a violation, the SCADA system sets a status bit. This measure marks pressure changes that are physically impossible for evaluation.

Evaluation Module

The evaluation module works independently of the acquisition module. It is initiated manu-allybymeansofadialogueandaccessestheASCIIfile(s)oftherespectivepressuremeas-uring point.

Processing the Hysteresis

As long as a pressure value develops in one direction (rising or dropping), no hysteresis im-pact is taken into account – i.e. value changes in the same direction are accepted regard-less of the size. A change in the direction, however, is detected only if the new value has amounted more than the hysteresis in the opposite direction.

Evaluation of the pressure data

Asafirststep,allvaluesthatfallwithinthescopeofthehysteresisimpactaresortedout.Measured values with the “gradient violation” status are hidden.

Then the pressure ranges are counted according to DIN 45667.

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1.1.4. Route Control Management

The program manages and monitors the pumping routes as well as the pipeline segment statuses.Itisusedtooperateanddisplaypumpingroutesaswellasallowingtheirconfig-uration .

During pumping operation, a distinction is made between the following operating modes:

• Pumping from a source to a sink

• Pumping with pump-through operation from a source to a sink with pump-through operation and possibly pressure increase via one or several intermediate stations

• Splitting operations from a source to several sinks

• Changingofroutesonthefly Changing between several pump routes without stopping the pump operation.

1.1.5. Batch Tracking

Theprogramisusedformulti-productpipelinesbymeansofwhichdifferentproductswithdifferentvolumes(batches)aretransportedatthesametimeinoneandthesamepipeline.

Theprogramallowsoperatorstodefinebatchesandalsoprovidesthemwithanoverviewof the batch positions in the network. It supports the operators in tracking their transport tasks. In the SCADA system, the batches are presented in the form of horizontal bars in so-called pipeline section screens.

After the “Batch Info” button has been clicked, an information window opens in the top screen area. It includes:

• Product

• Source

• Batch name

• Batch status

• Volume in the segment

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• Current volume

• Nominal volume

• Position of the batch (indicated by a start point and an end point)

• Start time

• Projected time of arrival, target and density

1.1.6. Scraper Tracking

The program is used to track scapers (so-called PIGs) in the pipeline.

Tothisend,abatchwiththequantityof1isconfiguredinBatchTracking.Then,trackingiscarried out as described in chapter Batch Tracking.

1.1.7. Training and Simulation Software

The Operating department can analyse actual operations and develop and test ideas for improved target operations, every day and playfully. The SCADA system monitors and op-erates as before. The PipelineCockpit analyses, understands and improves.

A decision in favour of the PipelineCockpit is a decision in favour of a realistic simulation model of the entire pipeline system. A model which permanently accompanies the system, just like the SCADA system itself.

The person operating a system with a SCADA system has one task. The person who devel-ops the simulation model for this system and is also in charge of it at the same time and as regards content has two tasks. A pipeline operating company needs a lot of time, stamina and extremely experienced service providers – only in this way can they use the simulation inasustainablemannerandwithprofitablesuccess.

With ViewStar ICS and the PipelineCockpit, process management and control, simulation and optimization fuse into one solution.

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2. Equations, models, methods

Introduction

Pipeline systems are complex and an important integral part of the global infrastructure.

In future, a realistic hydraulic model of the entire system will be used for pipelines prior to each relevant investment and operational decision.

The reasons for this are:

• Demands for increase in performance and/or reduction in costs

• The question as to what scope is available in order to increase throughput and/or re-duceoperatingcostswithoutendangeringsafetycanonlybeanalysedandverifiedbymeans of a simulation of the entire system.

• Optimum modes of operation

• Whether a system has already been used optimally or not, whether a mode of operation supposed to be better is indeed better and, above all, whether it can also be realised in practice without endangering the reliability, availability and safety of the system can only be examined by means of model calculations.

• Implementation hold-ups regarding automation

• The communication technology possibilities of optimally operating a system with min-imum personnel resources, provided by automation and remote monitoring today, are far greater than the degree of automation and optimisation usually implemented in the systems throughout the system. These implementation hold-ups can only be caught up with by using models: Only with model-based hydraulic engineering is it possible to provide automation concepts that are valid throughout the system.

• Implementation hold-ups regarding rehabilitation

• Several pipeline systems built decades ago have reached the end of their life cycles and must in parts be rehabilitated or renewed comprehensively. At the same time, however, demands and requirements have changed, which means that rehabilitation cannot be carried out on the basis of former plans. The problem of optimally migrating a pipeline

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system in its future would be hard solved without using a model.

• New generations

• Today,engineersareworkingincommunicationandcontrolstationsandinthefieldofengineering for whom it is a matter of course – i.e. state-of-the-art – to be able to fall back upon a realistic simulation model of the entire system. This applies to both plan-ning and during operations.

• Return on Investment

• It is also a matter of course for these engineers, since they know that the investment costs required for models, simulation software and model maintenance, although very high, are low compared to the costs usually involved when taking investment and oper-ational decisions for pipelines. Backing up decisions objectively using models and op-timisingthempayoffquicklyandverifiably.Today,engineersareoftennolongerreadyto take on responsibility for decisions which have not been backed up additionally using models.

The following chapter provides an overview of the equations and methods which the Pipe-lineCockpitisbasedoninordertocalculatepressureandflowratevaluesofapipelinesys-tem realistically.

This document addresses operators and experts who intend to use and design Pipeline-Cockpit simulations in control centers in order to operate their facilities safely, performant-ly and at optimal costs.

Anessentialprerequisiteforusingthesimulationfunctionsefficientlyisgivenbyacompre-hensive knowledge of the inner workings of the process model and its functionality.

The operator in the control center using these simulations does not necessarily need to have this knowledge. The expert, however, who provides and optimizes simulations for his facilities and trains operators, has to know the inner workings.

2.1. Basic equations

The PipelineCockpit simulation is applicable to water, raw oil and product pipelines as well asgaspipelinesandpipelinesystemsfilledwithfluids1 in general.

1 Fluid is the generic name for liquids and gases

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The simulation of dynamical (time-dependent, unsteady) processes in pipeline systems is based on the conservation laws for mass, momentum and energy. These non-linear partial differentialequationsdescribetheflowprocessesofliquidsaswellasgasesthroughpipe-lines.

2.1.1. Conservation of mass, momentum and energy

ThePipelineCockpitsimulationisbasedonaone-dimensionalstreamfilamenttheorywithcrosssectionaveragedstatevariables.Theresultingdifferentialformsofthebalanceequa-tions are outlined in the following.

2.1.1.1. Conservation of mass (equation of continuity)

2.1.1.2. Conservation of momentum (equation of motion)

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2.1.1. Conservation of mass, momentum and energy

The PipelineCockpit simulation is based on a one-dimensional stream filament theory with cross section averaged state variables. The resulting differential forms of the balance equations are outlined in the following.

2.1.1.1. Conservation of mass (equation of continuity)

T 2F barotrop p

1 1E c

p T

1 ddt

1 K 1 Kdp dT 1 dA v 0p dt T dt A dt x

κ = =ρ⋅ α

ρρ

− + ∂− + + =∂

(1)

2.1.1.2. Conservation of momentum (equation of motion) fR

A

v vv v 1 pv g sint x x D 2

ρ⋅

∂ ∂ ∂ λ+ = − ⋅ − ⋅ α − ⋅∂ ∂ ρ ∂

(2)

2.1.1.3. Conservation of energy

fRA

T

1

v1 K 0

3p

p p

F

T vdT dp 1 q p Adt c dt c A A t D 2

⋅+ ≅

α ⋅ ∂ λ − = + + ⋅ ρ ⋅ ρ ⋅ ρ ⋅ ∂

(3)

with

( )radial,Ein radial,Aus

0

'radial axial D S HC

q q

axial diffusionradial conduction xdx

Tq q q k T T Ax x

∂∂

∂ ∂ = + = − ⋅ − + λ ⋅ ⋅ ∂ ∂

(4)

Equation (3) formulated as transport equation reads

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2.1.1. Conservation of mass, momentum and energy

The PipelineCockpit simulation is based on a one-dimensional stream filament theory with cross section averaged state variables. The resulting differential forms of the balance equations are outlined in the following.

2.1.1.1. Conservation of mass (equation of continuity)

T 2F barotrop p

1 1E c

p T

1 ddt

1 K 1 Kdp dT 1 dA v 0p dt T dt A dt x

κ = =ρ⋅ α

ρρ

− + ∂− + + =∂

(1)

2.1.1.2. Conservation of momentum (equation of motion) fR

A

v vv v 1 pv g sint x x D 2

ρ⋅

∂ ∂ ∂ λ+ = − ⋅ − ⋅ α − ⋅∂ ∂ ρ ∂

(2)

2.1.1.3. Conservation of energy

fRA

T

1

v1 K 0

3p

p p

F

T vdT dp 1 q p Adt c dt c A A t D 2

⋅+ ≅

α ⋅ ∂ λ − = + + ⋅ ρ ⋅ ρ ⋅ ρ ⋅ ∂

(3)

with

( )radial,Ein radial,Aus

0

'radial axial D S HC

q q

axial diffusionradial conduction xdx

Tq q q k T T Ax x

∂∂

∂ ∂ = + = − ⋅ − + λ ⋅ ⋅ ∂ ∂

(4)

Equation (3) formulated as transport equation reads

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2.1.1.3. Conservation of energy

Equation (3) formulated as transport equation reads

Thisreformulationillustratesthecorrelationbetweentemperatureandpressureprofileswhich is essential for gas pipelines.

2.1.2. Further equations

2.1.2.1. Cross section

Theflowcrosssectioninapipelinechangeswiththepressurewhichthepipelineissubject-ed to (and with the temperature of the pipe wall which itself depends on the temperature of the medium in the pipeline).

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2.1.1. Conservation of mass, momentum and energy

The PipelineCockpit simulation is based on a one-dimensional stream filament theory with cross section averaged state variables. The resulting differential forms of the balance equations are outlined in the following.

2.1.1.1. Conservation of mass (equation of continuity)

T 2F barotrop p

1 1E c

p T

1 ddt

1 K 1 Kdp dT 1 dA v 0p dt T dt A dt x

κ = =ρ⋅ α

ρρ

− + ∂− + + =∂

(1)

2.1.1.2. Conservation of momentum (equation of motion) fR

A

v vv v 1 pv g sint x x D 2

ρ⋅

∂ ∂ ∂ λ+ = − ⋅ − ⋅ α − ⋅∂ ∂ ρ ∂

(2)

2.1.1.3. Conservation of energy

fRA

T

1

v1 K 0

3p

p p

F

T vdT dp 1 q p Adt c dt c A A t D 2

⋅+ ≅

α ⋅ ∂ λ − = + + ⋅ ρ ⋅ ρ ⋅ ρ ⋅ ∂

(3)

with

( )radial,Ein radial,Aus

0

'radial axial D S HC

q q

axial diffusionradial conduction xdx

Tq q q k T T Ax x

∂∂

∂ ∂ = + = − ⋅ − + λ ⋅ ⋅ ∂ ∂

(4)

Equation (3) formulated as transport equation reads

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( )

3

12p T

heat exchange friction heat ther modynamic

vT T q p pc v K vt x A D t x

∂ ∂ λ ∂ ∂ ρ ⋅ ⋅ + = + ⋅ρ ⋅ + + ⋅ + ∂ ∂ ∂ ∂

(5)

This reformulation illustrates the correlation between temperature and pressure profiles which is essential for gas pipelines.

2.1.2. Further equations

2.1.2.1. Cross section

( )1 1 2 RR

dA D ² dp dTA s E

− ν= ⋅ + + ν ⋅ ⋅β ⋅ (6)

The flow cross section in a pipeline changes with the pressure which the pipeline is subjected to (and with the temperature of the pipe wall which itself depends on the temperature of the medium in the pipeline).

The above equation also represents the pipe-part of the DT-procedure of leak detection for shut-in pipe sections filled with a liquid and closed valves at both ends.

2.1.2.2. Acoustic velocity

The acoustic velocity2 is the speed at which pressure changes move through a pipeline. If one would consider a hydraulic profile of the pipeline online, one would see these pressure waves traveling at the acoustic velocity.

The acoustic velocity is approximately 1 km per second in liquid pipelines - in gas pipelines it is distinctly smaller. In the case of gases the acoustic velocity depends on the state of flow itself– in the case of liquids it is nearly constant.

2 c is the usual label in the case of gases or a in the case of liquids, respectively. The elasticity of the pipe wall is also included in a.

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( )

3

12p T

heat exchange friction heat ther modynamic

vT T q p pc v K vt x A D t x

∂ ∂ λ ∂ ∂ ρ ⋅ ⋅ + = + ⋅ρ ⋅ + + ⋅ + ∂ ∂ ∂ ∂

(5)

This reformulation illustrates the correlation between temperature and pressure profiles which is essential for gas pipelines.

2.1.2. Further equations

2.1.2.1. Cross section

( )1 1 2 RR

dA D ² dp dTA s E

− ν= ⋅ + + ν ⋅ ⋅β ⋅ (6)

The flow cross section in a pipeline changes with the pressure which the pipeline is subjected to (and with the temperature of the pipe wall which itself depends on the temperature of the medium in the pipeline).

The above equation also represents the pipe-part of the DT-procedure of leak detection for shut-in pipe sections filled with a liquid and closed valves at both ends.

2.1.2.2. Acoustic velocity

The acoustic velocity2 is the speed at which pressure changes move through a pipeline. If one would consider a hydraulic profile of the pipeline online, one would see these pressure waves traveling at the acoustic velocity.

The acoustic velocity is approximately 1 km per second in liquid pipelines - in gas pipelines it is distinctly smaller. In the case of gases the acoustic velocity depends on the state of flow itself– in the case of liquids it is nearly constant.

2 c is the usual label in the case of gases or a in the case of liquids, respectively. The elasticity of the pipe wall is also included in a.

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The above equation also represents the pipe-part of the DT-procedure of leak detection for shut-inpipesectionsfilledwithaliquidandclosedvalvesatbothends.

2.1.2.2. Acoustic velocity

The acoustic velocity1 is the speed at which pressure changes move through a pipeline. If onewouldconsiderahydraulicprofileofthepipelineonline,onewouldseethesepressurewaves traveling at the acoustic velocity.

The acoustic velocity is approximately 1 km per second in liquid pipelines - in gas pipelines it is distinctly smaller. In the case of gases the acoustic velocity depends on the state of flowitself–inthecaseofliquidsitisnearlyconstant.

Figure 1: Acoustic velocity calculated by the PipelineCockpit simulation

2.1.2.3 Thermal equation of state

Figure 2: Equation of state calculated by the PipelineCockpit simulation

1 c is the usual label in the case of gases or in the case of liquids, respectively. The elasticity of the pipe wall is also included in a.

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liquids gases

( )

2barotropc

F

barotropF

R

E

aD 1 ²E1

E s

ρ=⋅ − ν

+

Ns

p pc k K R T kυ υ ∂= = ⋅ = ⋅ ⋅ ⋅ ∂ρ ρ

Figure 1: Acoustic velocity calculated by the PipelineCockpit simulation

2.1.2.3. Thermal equation of state

liquids gases

( )

( ) ( ){ }

NN

N

N N N N

p pp,T 1E

exp T T 1 0,8 T T

−ρ = ρ ⋅ + ⋅

−α ⋅ − ⋅ + ⋅ α ⋅ −

( )

( )1

NN

N N

NZ

Z R

m m

Tpp,TK p,T T p

pZ R T

ρ ⋅ρ = ⋅⋅

=ρ ⋅ ⋅

API-formulas for the pressure and temperature dependence of the density of raw oil, kerosine and products (gasoline, diesel, etc.).

BWR-formula for the equation of state of real gases.

Figure 2: Equation of state calculated by the PipelineCockpit simulation

2.1.2.4. Quasi-steady friction

The λ-coefficient is calculated in dependence on the flow type (laminar or turbulent), which is determined by the REYNOLDS-number. In the turbulent regime, the λ-coefficient is calculated either iteratively using the COLEBROOK-WHITE equation or according to NIKURADSE. The friction coefficient is adjusted to the flow type during the calculation. Quasi-steady friction slightly „underestimates“ the damping effect of the friction on the attenuation of the amplitudes of the pressure waves. Therefore, vibrations attenuate slightly faster in reality than in the simulation.

2.1.3. Flow processes in pipelines

Equations (1) and (2) represent a set of partial differential equations with the independent variables position x, time t and the dependent variables density ρ, velocity v, pressure p and cross section A. Consequently, there are 2 equations for 4 unknowns. The redundant unknowns are eliminated by introducing the acoustic velocity and using the thermal equation of state. Actemium Cegelec GmbH Viewstar™ - Product-Catalog

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liquids gases

( )

2barotropc

F

barotropF

R

E

aD 1 ²E1

E s

ρ=⋅ − ν

+

Ns

p pc k K R T kυ υ ∂= = ⋅ = ⋅ ⋅ ⋅ ∂ρ ρ

Figure 1: Acoustic velocity calculated by the PipelineCockpit simulation

2.1.2.3. Thermal equation of state

liquids gases

( )

( ) ( ){ }

NN

N

N N N N

p pp,T 1E

exp T T 1 0,8 T T

−ρ = ρ ⋅ + ⋅

−α ⋅ − ⋅ + ⋅ α ⋅ −

( )

( )1

NN

N N

NZ

Z R

m m

Tpp,TK p,T T p

pZ R T

ρ ⋅ρ = ⋅⋅

=ρ ⋅ ⋅

API-formulas for the pressure and temperature dependence of the density of raw oil, kerosine and products (gasoline, diesel, etc.).

BWR-formula for the equation of state of real gases.

Figure 2: Equation of state calculated by the PipelineCockpit simulation

2.1.2.4. Quasi-steady friction

The λ-coefficient is calculated in dependence on the flow type (laminar or turbulent), which is determined by the REYNOLDS-number. In the turbulent regime, the λ-coefficient is calculated either iteratively using the COLEBROOK-WHITE equation or according to NIKURADSE. The friction coefficient is adjusted to the flow type during the calculation. Quasi-steady friction slightly „underestimates“ the damping effect of the friction on the attenuation of the amplitudes of the pressure waves. Therefore, vibrations attenuate slightly faster in reality than in the simulation.

2.1.3. Flow processes in pipelines

Equations (1) and (2) represent a set of partial differential equations with the independent variables position x, time t and the dependent variables density ρ, velocity v, pressure p and cross section A. Consequently, there are 2 equations for 4 unknowns. The redundant unknowns are eliminated by introducing the acoustic velocity and using the thermal equation of state.

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2.1.2.4. Quasi-steady friction

The λ-coefficientiscalculatedindependenceontheflowtype(laminarorturbulent),whichis determined by the REYNOLDS-number. In the turbulent regime, the λ-coefficientiscalculated either iteratively using the COLEBROOK-WHITE equation or according to NI-KURADSE.Thefrictioncoefficientisadjustedtotheflowtypeduringthecalculation.Qua-si-steadyfrictionslightly„underestimates“thedampingeffectofthefrictionontheattenu-ation of the amplitudes of the pressure waves. Therefore, vibrations attenuate slightly faster in reality than in the simulation.

2.1.2.5. Flow processes in pipelines

Equations(1)and(2)representasetofpartialdifferentialequationswiththeindepend-ent variables position x, time t and the dependent variables density p, velocity v, pressure p and cross section A. Consequently, there are 2 equations for 4 unknowns. The redundant unknowns are eliminated by introducing the acoustic velocity and using the thermal equa-tion of state.

Aftersomemanipulations,thefollowingdifferentialequationsresult:

Figure 3: Differential equations solved by the PipelineCockpit simulation

F (1st row) denotes liquids and G (2nd row) denotes gases.

In the case of liquids, these equations are termed as water hammer equations. In the case of gases, the term „long-pipe“ model has been introduced.

One of the central features of dynamic processes in pipeline systems is the possible im-balancebetweenincomingandoutgoingmassflow:Aliquidpipelinecanbe„expanded“:mass streams in – but not out. The pressure in the pipe increases correspondingly. A gas pipeline can supply exit points with gas without receiving gas from the presupplier: The

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After some manipulations, the following differential equations result:

equation of continuity equation of motion 2

0p a mt A x

∂ ∂+ =∂ ∂

1 02

m pA A gsin m mt x DA

∂ ∂ λ+ + ρ α + =∂ ∂ ρ

2

0p c mt A x

∂ ∂+ =∂ ∂

02

N

N

K R Tm p pA A gsin m mt x K R T p DA

⋅ ⋅∂ ∂ λ+ + α + =∂ ∂ ⋅ ⋅

Figure 3: Differential equations solved by the PipelineCockpit simulation

F (1st row) denotes liquids and G (2nd row) denotes gases.

In the case of liquids, these equations are termed as water hammer equations. In the case of gases, the term „long-pipe“ model has been introduced.

One of the central features of dynamic processes in pipeline systems is the possible imbalance between incoming and outgoing mass flow: A liquid pipeline can be „expanded “: mass streams in – but not out. The pressure in the pipe increases correspondingly. A gas pipeline can supply exit points with gas without receiving gas from the presupplier: The pressure in the pipeline decreases correspondingly.

If pumps or compressors change their rotation speed, if control valves regulate, if shut-in valves leave or reach borderline positions, if leakages occur suddenly, if the process is unsteady: pressure waves travel through the pipeline. Every change in flow is connected with such a change in pressure.

A PipelineCockpit simulation entity is able to map the physics of the aforementioned relations realistically.

In order to solve the equations shown in Figure 3, the PipelineCockpit computation engine uses the method of characteristics as well as the finite difference method.

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pressure in the pipeline decreases correspondingly. If pumps or compressors change their rotation speed, if control valves regulate, if shut-in valves leave or reach borderline posi-tions, if leakages occur suddenly, if the process is unsteady: pressure waves travel through thepipeline.Everychangeinflowisconnectedwithsuchachangeinpressure.

A PipelineCockpit simulation entity is able to map the physics of the aforementioned rela-tions realistically.

In order to solve the equations shown in Figure 3, the PipelineCockpit computation engine usesthemethodofcharacteristicsaswellasthefinitedifferencemethod.

2.2. Flow processes in systems

Inapipelinesystem,flowpathscanbranchormergearbitrarily.Apartfrompipelinestherearepumps/compressors,controlvalves,safetyarmatures,shut-invalves,backflowpreven-ter, containers and reservoir, heating and cooling elements, bends and generally elements alongtheflowpath.

The hydraulic model of the PipelineCockpits consists of all elementsandflowpathsinthehydraulicinterplay!

Thedifferentialequations,whichasingleelementofthehydraulicmodelissubjectedto,are, to this end, coupled by algebraic constraints.

The most important one of these algebraic constraints is the mass balance at the nodes: The sign-consistentsummationofallmassflowsmustequal0ateverynode1.

Example:Onthedischargesideofthecompressorthemassflowofthecompressorsplitsintothemassflowofthebypassandthemassflowofthecoolingelement(cf.figurebelow).

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Figure 4: Algebraic constraints accounted for by the PipelineCockpit simulation

Systems of equations consisting of differential equations and algebraic constraints are termed as DAEs4 in mathematics.

Using the equation of continuity at every node one gets a system of equations for pressure and flows in the whole facility. The system of equations has the following structure:

4 Differential Algebraic Equations

Figure 4: Algebraic constraints accounted for by the PipelineCockpit simulation

Systemsofequationsconsistingofdifferentialequationsandalgebraicconstraintsaretermed as DAEs1 in mathematics.

Using the equation of continuity at every node one gets a system of equations for pressure andflowsinthewholefacility.Thesystemofequationshasthefollowingstructure:

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1 111 12 1

221 22

1

00

00 0 0 1

,eN

iii

j

N NNN

p mr r ... ... ... rpr r ... ... ... ......... ... ... ... ... ... ...p... ... ... r ... ...

... ... ... p... ... ... ... ... ... ... ...r ... ... ... ... ... r p

=

11

2 22

0 0

xt j j

,ext j j

i,ext ij ji

j

NN,ext Nj j

r psm r ps... ......m r psp

...... ...sm r p

− −

ik ik i i ik

ik ik k k ik

r r p m sr r p m s

− = − − −

ik i k ikr (p p ) m s− = −

Figure 5: System of equations solved by the PipelineCockpit simulation

The system of equations can consist of several 10-thousand nodes5 (=rows=columns) for large facilities. It is sparse – i.e., only very few elements of the N2-sized matrix (corresponding to N nodes) are non-zero.

The simulation has to solve this system of equations eventually several times for the calculation of each single time step due to the non-linearity of the basic equations.

The PipelineCockpit uses the so-called Pardiso technique in order to solve the system of equations.

The calculation of a subsequent time step based on the known state in the old time step is generally much faster than the calculation of an unknown initial state (i.e., a steady calculation).

The equations (cf. Figure 3) which the PipelineCockpit solves for the steady calculation are derived by discarding the partial derivatives with respect to time.

If the PipelineCockpit computation engine is not able to solve the system of equations, i.e., it is not able to calculate the initial condition or the subsequent time step, the simulation entity gives an error message and terminates.

5 internal nodes of long pipes are not accounted for

Figure 5: System of equations solved by the PipelineCockpit simulation

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The system of equations can consist of several 10-thousand nodes1 (=rows=columns) for large facilities. It is sparse – i.e., only very few elements of the N2-sized matrix (correspond-ing to N nodes) are non-zero.

The simulation has to solve this system of equations eventually several times for the calcu-lation of each single time step due to the non-linearity of the basic equations.

The PipelineCockpit uses the so-called Pardiso technique in order to solve the system of equations.

The calculation of a subsequent time step based on the known state in the old time step is generally much faster than the calculation of an unknown initial state (i.e., a steady calcula-tion).

The equations (cf. Figure 3) which the PipelineCockpit solves for the steady calculation are derived by discarding the partial derivatives with respect to time.

If the PipelineCockpit computation engine is not able to solve the system of equations, i.e., it is not able to calculate the initial condition or the subsequent time step, the simulation entity gives an error message and terminates.

2.3. Units as well as spatial and temporal discretization

Figure 6: Units and discretization used by the PipelineCockpit simulation

Units:

The simulation works internally with Pa absolute pressure for pressure p and kg/s for mass flowm(theflowortheexternalremoval).

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2.3. Units as well as spatial and temporal discretization

Figure 6: Units and discretization used by the PipelineCockpit simulation

Units:

The simulation works internally with Pa absolute pressure for pressure p and kg/s for mass flow m (the flow or the external removal).

Modeling input for boundary conditions may be entered in different units (beyond Pa and kg/s); they are converted by the simulation. The same holds for the output of results.

The unit conversion relations corresponding to the geodetic height z of a node, the pressure height at a node and the energy height H at a node are shown in the left part of Figure 6 for a steady operating state (the energy curve is shown without velocity height; the latter can usually be neglected for pipelines).

The steady energy curve is declined in the direction of the flow. The steady energy loss (red) results from quasi-steady friction (see 2.1.2.4). In the case of liquids, the energy curve exhibits a knee at the batch boundary and the pressure curve a jump.

Discretization:

The simulation provides – if required – also results at internal nodes of pipes in correspondence to the spatial discretization. The number of internal nodes may be larger than the number N of nodes in Figure 5.

The raw-data records for pipes usually contain an internal node whereever a GIS-break point and/or a pipe geodesic height point exists (break points and geodesic height points are not shown in the left part of Figure 6). At the start, the simulation sets up an equidistant spatial grid along the pipeline whose resolution xΔ is coupled

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2.3. Units as well as spatial and temporal discretization

Figure 6: Units and discretization used by the PipelineCockpit simulation

Units:

The simulation works internally with Pa absolute pressure for pressure p and kg/s for mass flow m (the flow or the external removal).

Modeling input for boundary conditions may be entered in different units (beyond Pa and kg/s); they are converted by the simulation. The same holds for the output of results.

The unit conversion relations corresponding to the geodetic height z of a node, the pressure height at a node and the energy height H at a node are shown in the left part of Figure 6 for a steady operating state (the energy curve is shown without velocity height; the latter can usually be neglected for pipelines).

The steady energy curve is declined in the direction of the flow. The steady energy loss (red) results from quasi-steady friction (see 2.1.2.4). In the case of liquids, the energy curve exhibits a knee at the batch boundary and the pressure curve a jump.

Discretization:

The simulation provides – if required – also results at internal nodes of pipes in correspondence to the spatial discretization. The number of internal nodes may be larger than the number N of nodes in Figure 5.

The raw-data records for pipes usually contain an internal node whereever a GIS-break point and/or a pipe geodesic height point exists (break points and geodesic height points are not shown in the left part of Figure 6). At the start, the simulation sets up an equidistant spatial grid along the pipeline whose resolution xΔ is coupled

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Modelinginputforboundaryconditionsmaybeenteredindifferentunits(beyondPaandkg/s); they are converted by the simulation. The same holds for the output of results.

The unit conversion relations corresponding to the geodetic height z of a node, the pres-sure height at a node and the energy height H at a node are shown in the left part of Fig-ure 6 for a steady operating state (the energy curve is shown without velocity height; the latter can usually be neglected for pipelines).

Thesteadyenergycurveisdeclinedinthedirectionoftheflow.Thesteadyenergyloss(red) results from quasi-steady friction (see Quasi-steady friction). In the case of liquids, the energy curve exhibits a knee at the batch boundary and the pressure curve a jump.

Discretization:

The simulation provides – if required – also results at internal nodes of pipes in corre-spondence to the spatial discretization. The number of internal nodes may be larger than the number N of nodes in Figure 5.

The raw-data records for pipes usually contain an internal node whereever a GIS-break point and/or a pipe geodesic height point exists (break points and geodesic height points are not shown in the left part of Figure 6). At the start, the simulation sets up an equidis-tantspatialgridalongthepipelinewhoseresolution∂xiscoupledtothetemporalresolu-tion∂tfordynamicalcalculations(calculationsaccordingtoFigure3):Inordertoresolvepressurewavesinapipespatially(e.g.inahydraulicprofile),thetimestephastobecom-parably short: a 1 second time step already means a 1 km spatial step in the case of liquid pipelines.

2.4. Mixing and transport processes - tracking

The PipelineCockpit simulation is able to calculate mixing and transport processes.

Quality tracking (or batch tracking in the case of liquid pipelines) or the forecast of gas quality at exit points (or the batch arrival at destination tanks in the case of liquid pipelines) are usually the aims of this kind of calculation.

Specifying the quantity to be tracked (temperature, norm density, gas component or gas qualityparameterlikethecalorificvalue)atallsourcesisnecessaryfortrackingcalculations.

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TrackingcalculationsarepossibleafterthecalculationoftheflowfieldisdoneaccordingtoChapter.Afterthis,thesimulationcantransportthepropertyatflowvelocitythroughthepipeline network by means of a post-processing1 calculation.

2.4.1. Mixing processes

The correct calculation of the mixing is prerequisite for the correct transport of the mixing resultinflowdirection.

Mixingprocessesoccuratmergersonly.Temperatures(offluidsandgases)aswellasgascompositions2 mix.

The technique to deal with the system of equations for mixing calculations used by the PipelineCockpit is independent of the property (temperature, norm density, gas compo-nentorgasqualityparameterlikethecalorificvalue).Thealgebraicrelationformixingtobe solved is analogous to the respective one for conservation of mass. On the element lev-el the relation reads (here exemplarily given for the temperature):

1Usuallythereisnoinsignificantinteractionbetweenadvectivetransportbasedonhydraulicandthehydraulicitself.However,thereareexceptionswherearelevantorsignificantinteractionexists.2Theoperatorofaliquidpipelinehasusuallynointerestinthemixingofdifferentproducts.

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( ) = > − ⋅ ⋅ ⋅

= +

i

p,k p,k p,kk

k i

with

0 0 0Tm 0

m c A m c m c BT

T AT B (7)

2.4.2. Temperature transport

The property temperature plays a special role in the transport process. On the one hand, heat exchange with the environment is possible for fluids and gases according to equation (4) (usually connected with a decrease in temperature). This is not possible for the transport of so-called conservative properties like norm density, gas component or gas quality parameter like the calorific value. From a calculation point of view, the PipelineCockpit uses an operator split approach for temperature transport: First, the partial differential equation for transport (advection), and second, using a different numerical scheme, for heat exchange (diffusion), are solved.

Special role of temperature transport: On the other hand for gases pressure and temperature profiles correlate – see (5).. In this way, the transport affects its own transport velocity to some degree. In calculating gas flow, an interaction loop between the system of equations from Chapter 2.2 / 2.1.3 and the transport calculation as outlined above and (5) arises. In the transport of changes in temperature or norm density in liquid pipelines, an interaction with the hydraulICS exits (equations (1) to (5) hold) – this dependence, however, is rather weak compared to gases.

2.4.3. Transport processes in pipelines

All properties (…) have the so-called advective transport with the flow velocity v in common:

( ) ( )0

... ...v

t x∂ ∂

+ =∂ ∂ (8)

In order to solve equations of type (8), the PipelineCockpit computation engine uses a finite volume method as well as analytical methods. As already mentioned in the case of pressure waves, the simulation can provide results at internal nodes for the transported properties.

The equations which the PipelineCockpit computation engine solves for steady calculations are derived from equation (8) by discarding the partial derivatives with respect to time. The distribution of the property in the pipeline system, which is calculated by the simulation as initial condition upon restart, can be basically different from the current real distribution. This drawback can be circumvented by a restart

2.4.2. Temperature transport

The property temperature plays a special role in the transport process. On the one hand, heatexchangewiththeenvironmentispossibleforfluidsandgasesaccordingtoequa-tion Fehler: Referenz nicht gefunden (usually connected with a decrease in temperature). This is not possible for the transport of so-called conservative properties like norm density, gascomponentorgasqualityparameterlikethecalorificvalue.Fromacalculationpointofview, the PipelineCockpit uses an operator split approach for temperature transport: First, thepartialdifferentialequationfortransport(advection),andsecond,usingadifferentnu-mericalscheme,forheatexchange(diffusion),aresolved.

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Special role of temperature transport: On the other hand for gases pressure and tempera-tureprofilescorrelate–see(5).Inthisway,thetransportaffectsitsowntransportvelocitytosomedegree.Incalculatinggasflow,aninteractionloopbetweenthesystemofequa-tions from Chapter 2.2 / 2.1.3. and the transport calculation as outlined above and (5) aris-es. In the transport of changes in temperature or norm density in liquid pipelines, an inter-action with the hydraulICS exits (equations (1) to (5) hold) – this dependence, however, is rather weak compared to gases.

2.4.3. Transport processes in pipelines

Allproperties(…)havetheso-calledadvectivetransportwiththeflowvelocityvincommon:

Inordertosolveequationsoftype(1),thePipelineCockpitcomputationengineusesafinitevolume method as well as analytical methods. As already mentioned in the case of pressure waves, the simulation can provide results at internal nodes for the transported properties.

The equations which the PipelineCockpit computation engine solves for steady calculations are derived from equation (1) by discarding the partial derivatives with respect to time. The distribution of the property in the pipeline system, which is calculated by the simulation as initialconditionuponrestart,canbebasicallydifferentfromthecurrentrealdistribution.This drawback can be circumvented by a restart with history record (measured values from archive). An online simulation always has the current property distribution, as it solves the differentialequationsinreal-timepermanently.Propagationprocesses(e.g.thegasfromasupplierstationjuststartedpropagatessuccessivelythroughthepipelinesystematflowvelocity) are transport processes. Transport or propagation processes of properties (…) are unsteadyprocessesevolvingatflowvelocityinthesamewayaschangesinpressure/floware unsteady processes. The latter, however, spread at acoustic velocity and might be re-flectedpartlyatboundariesofthemodeldependingonthetypeofboundarycondition.Incontrast, the properties (…) leave the model‘s boundaries at valleys simply and „quietly“.

Initial conditions or steady snap shots of transport or propagation processes are ranges of influence.Correspondingly,onemayraisethequestion,whereandtowhichextentanothersupplierstationpushesbackbeforeandafteritsstartconcerningtherangeofinfluence.Thecalculationresult„fluidage“3 belongs to the transport process methodologically as well.

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( ) = > − ⋅ ⋅ ⋅

= +

i

p,k p,k p,kk

k i

with

0 0 0Tm 0

m c A m c m c BT

T AT B (7)

2.4.2. Temperature transport

The property temperature plays a special role in the transport process. On the one hand, heat exchange with the environment is possible for fluids and gases according to equation (4) (usually connected with a decrease in temperature). This is not possible for the transport of so-called conservative properties like norm density, gas component or gas quality parameter like the calorific value. From a calculation point of view, the PipelineCockpit uses an operator split approach for temperature transport: First, the partial differential equation for transport (advection), and second, using a different numerical scheme, for heat exchange (diffusion), are solved.

Special role of temperature transport: On the other hand for gases pressure and temperature profiles correlate – see (5).. In this way, the transport affects its own transport velocity to some degree. In calculating gas flow, an interaction loop between the system of equations from Chapter 2.2 / 2.1.3 and the transport calculation as outlined above and (5) arises. In the transport of changes in temperature or norm density in liquid pipelines, an interaction with the hydraulICS exits (equations (1) to (5) hold) – this dependence, however, is rather weak compared to gases.

2.4.3. Transport processes in pipelines

All properties (…) have the so-called advective transport with the flow velocity v in common:

( ) ( )0

... ...v

t x∂ ∂

+ =∂ ∂ (8)

In order to solve equations of type (8), the PipelineCockpit computation engine uses a finite volume method as well as analytical methods. As already mentioned in the case of pressure waves, the simulation can provide results at internal nodes for the transported properties.

The equations which the PipelineCockpit computation engine solves for steady calculations are derived from equation (8) by discarding the partial derivatives with respect to time. The distribution of the property in the pipeline system, which is calculated by the simulation as initial condition upon restart, can be basically different from the current real distribution. This drawback can be circumvented by a restart

3 This is usually not relevant for gas and oil pipelines. Possibly of interest in the case of water pipelines: water age is a quality property in drinking water supply.

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2.5. Thermodynamic properties of real gases

In addition to the BWR formula for the equation of state (see Chapter Fehler: 2.1.2.3) the PipelineCockpit simulation is based on the fundamental relations for real gases outlined in the following.

2.5.1. Enthalpy und entropy

Differentials:

Integrals:

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2.5. Thermodynamic properties of real gases

In addition to the BWR formula for the equation of state (see Chapter 2.1.2.3) the PipelineCockpit simulation is based on the fundamental relations for real gases outlined in the following.

2.5.1. Enthalpy und entropy

Differentials:

∂ ∂ ∂υ = + = + υ − ∂ ∂ ∂ p

p pT

h hdh dT dp c dT T dpT p T

(9)

υ ∂υ = + = − ∂ p

p

c1ds dh dp dT dpT T T T

(10)

Integrals:

∂υ − = = + υ − ∂ 0

0 0 0 0

(p,T) pT

0 0 p p Tp(p ,T ) T p

h(p,T) h(p ,T ) dh c dT T dpT

(11)

∂υ − = = − ∂ 0

0 0 0 0

(p,T) pTp

0 0 p Tp(p ,T ) T p

cs(p,T) s(p ,T ) ds dT dp

T T (12)

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2.5. Thermodynamic properties of real gases

In addition to the BWR formula for the equation of state (see Chapter 2.1.2.3) the PipelineCockpit simulation is based on the fundamental relations for real gases outlined in the following.

2.5.1. Enthalpy und entropy

Differentials:

∂ ∂ ∂υ = + = + υ − ∂ ∂ ∂ p

p pT

h hdh dT dp c dT T dpT p T

(9)

υ ∂υ = + = − ∂ p

p

c1ds dh dp dT dpT T T T

(10)

Integrals:

∂υ − = = + υ − ∂ 0

0 0 0 0

(p,T) pT

0 0 p p Tp(p ,T ) T p

h(p,T) h(p ,T ) dh c dT T dpT

(11)

∂υ − = = − ∂ 0

0 0 0 0

(p,T) pTp

0 0 p Tp(p ,T ) T p

cs(p,T) s(p ,T ) ds dT dp

T T (12)

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Figure 7: h-s diagram for natural gas calculated by the PipelineCockpit simulation.

2.5.2. Specific heat

∂ = ∂ p

p

hcT (13)

υυ υ υ

∂ ∂ ∂ = = − υ ∂ ∂ ∂

u h pcT T T

(14)

υ+− = ⋅ ⋅−

2T

pp

(1 K )c c Z R(1 K ) (15)

ρ

∂ ∂ ∂ = = − + ∂ ρ ∂ ∂ρ

∂= = − ∂ ρ ∂ ∂ρ

mT

p m

m T

pmT

m T

pTlnZ TK 1

lnT p

lnZ p 1K 1lnp p

(16)

Figure 1: h-s diagram for natural gas calculated by the PipelineCockpit simulation.

2.5.2. Specific heat

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Figure 7: h-s diagram for natural gas calculated by the PipelineCockpit simulation.

2.5.2. Specific heat

∂ = ∂ p

p

hcT (13)

υυ υ υ

∂ ∂ ∂ = = − υ ∂ ∂ ∂

u h pcT T T

(14)

υ+− = ⋅ ⋅−

2T

pp

(1 K )c c Z R(1 K ) (15)

ρ

∂ ∂ ∂ = = − + ∂ ρ ∂ ∂ρ

∂= = − ∂ ρ ∂ ∂ρ

mT

p m

m T

pmT

m T

pTlnZ TK 1

lnT p

lnZ p 1K 1lnp p

(16)

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2.5.3. Polytropic and isentropic exponents

Inordertoproperlydefineisentropicandpolytropicheads,itisnecessarytodefinethepolytropic and isentropic exponents. There are, however, two generally non-equivalent definitionsofthepolytropicprocessintheliterature,whichisimportantfortheactualin-put of a characteristic map. The PipelineCockpit simulation is based on a polytropic process definedasthechangeofstateforconstantpolytropicefficiency:

The thermodynamic processes in p--formulation read

Using

leads to

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2.5.3. Polytropic and isentropic exponents

In order to properly define isentropic and polytropic heads, it is necessary to define the polytropic and isentropic exponents. There are, however, two generally non-equivalent definitions of the polytropic process in the literature, which is important for the actual input of a characteristic map. The PipelineCockpit simulation is based on a polytropic process defined as the change of state for constant polytropic efficiency:

υ ⋅η = =pdp const

dh (17)

The thermodynamic processes in p-υ-formulation read

κ

⋅ υ =⋅ υ =

np konstp konst

(18)

Using

η

υ ∂ = − ∂υ

υ ∂ κ = − ∂υ

p

s

pnp

pp

(19)

leads to

=− − + + + −

η

κ =− − +

p

2p p T T

p

p2

p p T

cn 1c (1 K ) ZR(1 K ) ZR(1 K )(1 )

cc (1 K ) ZR(1 K )

(20)

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2.5.3. Polytropic and isentropic exponents

In order to properly define isentropic and polytropic heads, it is necessary to define the polytropic and isentropic exponents. There are, however, two generally non-equivalent definitions of the polytropic process in the literature, which is important for the actual input of a characteristic map. The PipelineCockpit simulation is based on a polytropic process defined as the change of state for constant polytropic efficiency:

υ ⋅η = =pdp const

dh (17)

The thermodynamic processes in p-υ-formulation read

κ

⋅ υ =⋅ υ =

np konstp konst

(18)

Using

η

υ ∂ = − ∂υ

υ ∂ κ = − ∂υ

p

s

pnp

pp

(19)

leads to

=− − + + + −

η

κ =− − +

p

2p p T T

p

p2

p p T

cn 1c (1 K ) ZR(1 K ) ZR(1 K )(1 )

cc (1 K ) ZR(1 K )

(20)

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2.5.3. Polytropic and isentropic exponents

In order to properly define isentropic and polytropic heads, it is necessary to define the polytropic and isentropic exponents. There are, however, two generally non-equivalent definitions of the polytropic process in the literature, which is important for the actual input of a characteristic map. The PipelineCockpit simulation is based on a polytropic process defined as the change of state for constant polytropic efficiency:

υ ⋅η = =pdp const

dh (17)

The thermodynamic processes in p-υ-formulation read

κ

⋅ υ =⋅ υ =

np konstp konst

(18)

Using

η

υ ∂ = − ∂υ

υ ∂ κ = − ∂υ

p

s

pnp

pp

(19)

leads to

=− − + + + −

η

κ =− − +

p

2p p T T

p

p2

p p T

cn 1c (1 K ) ZR(1 K ) ZR(1 K )(1 )

cc (1 K ) ZR(1 K )

(20)

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2.5.3. Polytropic and isentropic exponents

In order to properly define isentropic and polytropic heads, it is necessary to define the polytropic and isentropic exponents. There are, however, two generally non-equivalent definitions of the polytropic process in the literature, which is important for the actual input of a characteristic map. The PipelineCockpit simulation is based on a polytropic process defined as the change of state for constant polytropic efficiency:

υ ⋅η = =pdp const

dh (17)

The thermodynamic processes in p-υ-formulation read

κ

⋅ υ =⋅ υ =

np konstp konst

(18)

Using

η

υ ∂ = − ∂υ

υ ∂ κ = − ∂υ

p

s

pnp

pp

(19)

leads to

=− − + + + −

η

κ =− − +

p

2p p T T

p

p2

p p T

cn 1c (1 K ) ZR(1 K ) ZR(1 K )(1 )

cc (1 K ) ZR(1 K )

(20)

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2.5.4. Isentropic and polytropic head

Thespecificworkforcompressionyisdefinedas

In practice, detailed knowledge about the change of state (the path between states 1 and 2) is necessary in order to evaluate this integral. This path-dependency is due to the fact, thatthespecificworkisnotanexactdifferentialincontrasttoenthalpyorentropy!Forthepolytropicandisentropicprocessesthespecificworksread

2.6. Selected equipment components

In the following, the PipelineCockpit simulation is explained for selected element types. The compressor and gas pressure regulator are outlined as the most important basic func-tions (increase pressure increaseflowanddecreasepressuredecreaseflow).Themethodologyiscompletelyanalogoustothecaseoffluids(pumpsandpressureregula-tors) as addressed shortly.

Fromafluidmechanicspointofview,theprocessesofcompressionandpressureregula-tionforrealgasesaremuchmoreintricatethanforfluidsduetotheirdistinctthermody-namicnature.Thisstatementholdsforthepipeflowaswell:Theinteractionofpressureandtemperatureprofiles–presentincaseofgaspipelinesonly–hasalreadybeenmen-tioned in Chapter 2.4.2.

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2.5.4. Isentropic and polytropic head

The specific work for compression y is defined as

= υ ⋅2

121

y dp (21)

In practice, detailed knowledge about the change of state (the path between states 1 and 2) is necessary in order to evaluate this integral. This path-dependency is due to the fact, that the specific work is not an exact differential in contrast to enthalpy or entropy! For the polytropic and isentropic processes the specific works read

κκ−

≡ = − − κ ≡ = − κ −

nn 1

2p p,12 1 1

1

12

s s,12 1 11

pny y Z RT 1n 1 p

py y Z RT 11 p

(22)

2.6. Selected equipment components

In the following, the PipelineCockpit simulation is explained for selected element types. The compressor and gas pressure regulator are outlined as the most important basic functions (increase pressure increase flow and decrease pressure decrease flow). The methodology is completely analogous to the case of fluids (pumps and pressure regulators) as addressed shortly.

From a fluid mechanics point of view, the processes of compression and pressure regulation for real gases are much more intricate than for fluids due to their distinct thermodynamic nature. This statement holds for the pipe flow as well: The interaction of pressure and temperature profiles – present in case of gas pipelines only – has already been mentioned in Chapter 2.4.2.

2.6.1. Compressor and characteristic map

The starting point for compression and pressure regulation processes for fluids and gases is the first law of thermodynamics: Actemium Cegelec GmbH Viewstar™ - Product-Catalog

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2.5.4. Isentropic and polytropic head

The specific work for compression y is defined as

= υ ⋅2

121

y dp (21)

In practice, detailed knowledge about the change of state (the path between states 1 and 2) is necessary in order to evaluate this integral. This path-dependency is due to the fact, that the specific work is not an exact differential in contrast to enthalpy or entropy! For the polytropic and isentropic processes the specific works read

κκ−

≡ = − − κ ≡ = − κ −

nn 1

2p p,12 1 1

1

12

s s,12 1 11

pny y Z RT 1n 1 p

py y Z RT 11 p

(22)

2.6. Selected equipment components

In the following, the PipelineCockpit simulation is explained for selected element types. The compressor and gas pressure regulator are outlined as the most important basic functions (increase pressure increase flow and decrease pressure decrease flow). The methodology is completely analogous to the case of fluids (pumps and pressure regulators) as addressed shortly.

From a fluid mechanics point of view, the processes of compression and pressure regulation for real gases are much more intricate than for fluids due to their distinct thermodynamic nature. This statement holds for the pipe flow as well: The interaction of pressure and temperature profiles – present in case of gas pipelines only – has already been mentioned in Chapter 2.4.2.

2.6.1. Compressor and characteristic map

The starting point for compression and pressure regulation processes for fluids and gases is the first law of thermodynamics:

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2.6.1 Compressor and characteristic map

Thestartingpointforcompressionandpressureregulationprocessesforfluidsandgasesisthefirstlawofthermodynamics:

It states: The heat q12 and the technical work w12 transferred to the system induce changes in enthalpy, kinetic and potential energy. The term also includes the irreversibly dissipated energy1.Thekineticenergyisgenerallynegligiblefortechnicalflows.Inthecaseofcom-pressors/pumps(andpressureregulators)theeffectofheightdifferencesbetweensuctionand discharge nozzles can be neglected in general. For the adiabatic process (no trans-ferred heat) this leads to:

The energy balances for compressor and pump are quite similar:

Pump

Compressor

The „polytropic head“ ypofacompressorcorrespondstothe„head“ΔHofthepump.

Pisthepowertransferredtotheflowandηitscorrespondingefficiency.Onehastodistin-guishthisfromtheengineordrivepoweranditscorrespondingefficiency.Thesequanti-ties are calculated concurrently by the PipelineCockpit simulation. Usually, compressors are driven by a gas turbine, where a small part of the transported combustible gas is used to run this turbine (fuel gas consumption). The PipelineCockpit simulation provides the calcu-lation of the fuel gas consumption.

ThequantitiesP,ηandΔH(pump)orP,ηandyp (compressor) are generally given by the manufacturer as characteristic maps measured at the test facility in dependence on norm volumeflowanddifferentrotationfrequencies.Inthecaseofapump,knowledgeofa

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−+ = − + + −2 22 1

12 t12 2 1 2 1v vq w h h g(z z )

2 (23)

It states: The heat 12q and the technical work t12w transferred to the system induce

changes in enthalpy, kinetic and potential energy. The term t12w also includes the irreversibly dissipated energy9. The kinetic energy is generally negligible for technical flows. In the case of compressors/pumps (and pressure regulators) the effect of height differences between suction and discharge nozzles can be neglected in general. For the adiabatic process (no transferred heat) this leads to:

= + = −t12 12 12 2 1w y j h h (24)

The energy balances for compressor and pump are quite similar:

Pump

Δ= =⋅ η

t12w P H in [m]g g m

(25)

Compressor

= =⋅ ⋅η

pt12 yw P in [m]g g m g

(26)

The „polytropic head“ py of a compressor corresponds to the „head“ ΔH of the pump.

P is the power transferred to the flow and η its corresponding efficiency. One has to distinguish this from the engine or drive power and its corresponding efficiency. These quantities are calculated concurrently by the PipelineCockpit simulation. Usually, compressors are driven by a gas turbine, where a small part of the transported combustible gas is used to run this turbine (fuel gas consumption). The PipelineCockpit simulation provides the calculation of the fuel gas consumption.

The quantities P , η and ΔH (pump) or P , η and py (compressor) are generally

given by the manufacturer as characteristic maps measured at the test facility in dependence on norm volume flow and different rotation frequencies. In the case of a pump, knowledge of a characteristic curve for one rotation speed is sufficient to determine the characteristic curves for different rotation speeds using similarity laws. In the case of a compressor these similarity laws are not applicable, i.e., characteristic curves for several rotation speeds are needed.

9 In the case of steady pipe flows, the energy dissipation refers to the pressure loss due to 2.1.2.4 which produces irreversible friction heat. Equation (8) is also referred to as BERNOULLI equation in connection with steady pipe flows.

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−+ = − + + −2 22 1

12 t12 2 1 2 1v vq w h h g(z z )

2 (23)

It states: The heat 12q and the technical work t12w transferred to the system induce

changes in enthalpy, kinetic and potential energy. The term t12w also includes the irreversibly dissipated energy9. The kinetic energy is generally negligible for technical flows. In the case of compressors/pumps (and pressure regulators) the effect of height differences between suction and discharge nozzles can be neglected in general. For the adiabatic process (no transferred heat) this leads to:

= + = −t12 12 12 2 1w y j h h (24)

The energy balances for compressor and pump are quite similar:

Pump

Δ= =⋅ η

t12w P H in [m]g g m

(25)

Compressor

= =⋅ ⋅η

pt12 yw P in [m]g g m g

(26)

The „polytropic head“ py of a compressor corresponds to the „head“ ΔH of the pump.

P is the power transferred to the flow and η its corresponding efficiency. One has to distinguish this from the engine or drive power and its corresponding efficiency. These quantities are calculated concurrently by the PipelineCockpit simulation. Usually, compressors are driven by a gas turbine, where a small part of the transported combustible gas is used to run this turbine (fuel gas consumption). The PipelineCockpit simulation provides the calculation of the fuel gas consumption.

The quantities P , η and ΔH (pump) or P , η and py (compressor) are generally

given by the manufacturer as characteristic maps measured at the test facility in dependence on norm volume flow and different rotation frequencies. In the case of a pump, knowledge of a characteristic curve for one rotation speed is sufficient to determine the characteristic curves for different rotation speeds using similarity laws. In the case of a compressor these similarity laws are not applicable, i.e., characteristic curves for several rotation speeds are needed.

9 In the case of steady pipe flows, the energy dissipation refers to the pressure loss due to 2.1.2.4 which produces irreversible friction heat. Equation (8) is also referred to as BERNOULLI equation in connection with steady pipe flows.

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−+ = − + + −2 22 1

12 t12 2 1 2 1v vq w h h g(z z )

2 (23)

It states: The heat 12q and the technical work t12w transferred to the system induce

changes in enthalpy, kinetic and potential energy. The term t12w also includes the irreversibly dissipated energy9. The kinetic energy is generally negligible for technical flows. In the case of compressors/pumps (and pressure regulators) the effect of height differences between suction and discharge nozzles can be neglected in general. For the adiabatic process (no transferred heat) this leads to:

= + = −t12 12 12 2 1w y j h h (24)

The energy balances for compressor and pump are quite similar:

Pump

Δ= =⋅ η

t12w P H in [m]g g m

(25)

Compressor

= =⋅ ⋅η

pt12 yw P in [m]g g m g

(26)

The „polytropic head“ py of a compressor corresponds to the „head“ ΔH of the pump.

P is the power transferred to the flow and η its corresponding efficiency. One has to distinguish this from the engine or drive power and its corresponding efficiency. These quantities are calculated concurrently by the PipelineCockpit simulation. Usually, compressors are driven by a gas turbine, where a small part of the transported combustible gas is used to run this turbine (fuel gas consumption). The PipelineCockpit simulation provides the calculation of the fuel gas consumption.

The quantities P , η and ΔH (pump) or P , η and py (compressor) are generally

given by the manufacturer as characteristic maps measured at the test facility in dependence on norm volume flow and different rotation frequencies. In the case of a pump, knowledge of a characteristic curve for one rotation speed is sufficient to determine the characteristic curves for different rotation speeds using similarity laws. In the case of a compressor these similarity laws are not applicable, i.e., characteristic curves for several rotation speeds are needed.

9 In the case of steady pipe flows, the energy dissipation refers to the pressure loss due to 2.1.2.4 which produces irreversible friction heat. Equation (8) is also referred to as BERNOULLI equation in connection with steady pipe flows. Actemium Cegelec GmbH

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−+ = − + + −2 22 1

12 t12 2 1 2 1v vq w h h g(z z )

2 (23)

It states: The heat 12q and the technical work t12w transferred to the system induce

changes in enthalpy, kinetic and potential energy. The term t12w also includes the irreversibly dissipated energy9. The kinetic energy is generally negligible for technical flows. In the case of compressors/pumps (and pressure regulators) the effect of height differences between suction and discharge nozzles can be neglected in general. For the adiabatic process (no transferred heat) this leads to:

= + = −t12 12 12 2 1w y j h h (24)

The energy balances for compressor and pump are quite similar:

Pump

Δ= =⋅ η

t12w P H in [m]g g m

(25)

Compressor

= =⋅ ⋅η

pt12 yw P in [m]g g m g

(26)

The „polytropic head“ py of a compressor corresponds to the „head“ ΔH of the pump.

P is the power transferred to the flow and η its corresponding efficiency. One has to distinguish this from the engine or drive power and its corresponding efficiency. These quantities are calculated concurrently by the PipelineCockpit simulation. Usually, compressors are driven by a gas turbine, where a small part of the transported combustible gas is used to run this turbine (fuel gas consumption). The PipelineCockpit simulation provides the calculation of the fuel gas consumption.

The quantities P , η and ΔH (pump) or P , η and py (compressor) are generally

given by the manufacturer as characteristic maps measured at the test facility in dependence on norm volume flow and different rotation frequencies. In the case of a pump, knowledge of a characteristic curve for one rotation speed is sufficient to determine the characteristic curves for different rotation speeds using similarity laws. In the case of a compressor these similarity laws are not applicable, i.e., characteristic curves for several rotation speeds are needed.

9 In the case of steady pipe flows, the energy dissipation refers to the pressure loss due to 2.1.2.4 which produces irreversible friction heat. Equation (8) is also referred to as BERNOULLI equation in connection with steady pipe flows.

3Inthecaseofsteadypipeflows,theenergydissipationreferstothepressurelossdueto2.1.2.4whichproduc-es irreversible friction heat. Equation (8) is also referred to as BERNOULLI equation in connection with steady pipeflows.

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Figure 8: Characteristic compressor map used by the PipelineCockpit simulation which is supplied to the hydraulic model while modeling

The starting point of a thermodynamic-hydraulic simulation of a compressor is the characteristic compressor map given by the manufacturer for one gas composition and one set of suction conditions ( 1 1T ,p ). The characteristic map relates

thermodynamic quantities (discharge pressure 2p , polytropic head py , polytropic

efficiency ηp ) and „hydraulic“ quantities (power P , norm volume flow NQ , rotation

speed N ). An example of such a characteristic map is shown in Figure 8.

characteristic curve for onerotationspeedissufficienttodeterminethecharacteristiccurvesfordifferentrotationspeedsusingsimilaritylaws.Inthecaseofacompressorthesesimilarity laws are not applicable, i.e., characteristic curves for several rotation speeds are needed.

Figure 1: Characteristic compressor map used by the PipelineCockpit simulation which is supplied to the hydraulic model while modeling

The starting point of a thermodynamic-hydraulic simulation of a compressor is the charac-teristic compressor map given by the manufacturer for one gas composition and one set of suction conditions (T1,p1). The characteristic map relates thermodynamic quantities (dis-charge pressure p2, polytropic head yp,polytropicefficiencyηp) and „hydraulic“ quantities (powerP,normvolumeflowQn, rotation speed N). An example of such a characteristic map is shown in Figure 8.

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Figure 2: Characteristic compressor map calculated by the PipelineCockpit simulation where the blue curve in-dicates a characteristic curve for a fixed rotation speed. The PipelineCockpit simulation calculates the operating point of the compressor (green cross in Figure 2) in the characteristic map.

The compressor integrates itself into the system of equations of the facility accord-ing to Figure 5 (i.e., the operating point of the compressor is the intersection point of the characteristiccompressorcurveandthecharacteristicfacilitycurve)!

ThecompressorcanoperatewithdifferentmodesinthePipelineCockpitsimulation.Iftherotationspeedisfixed,thesimulationleadstotheoperatingpointonthebluecurve.Ifthefloworthepressureincreasearefixed,thePipelineCockpitSimulationcalculatesarota-tion speed. If the compressor is not able to provide the desired value, it either1 ends up in a borderline position (min. or max. rotation speed or surge or choke limit) in the simulation or an operating point outside the operating regime is calculated and the invalid state of the result is indicated by a corresponding warning.

2.6.2. Pressure regulator and characteristic curve

The starting point of a thermodynamic-hydraulic simulation of a pressure regulator is the

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Figure 9: Characteristic compressor map calculated by the PipelineCockpit simulation where the blue curve indicates a characteristic curve for a fixed rotation speed. The PipelineCockpit simulation calculates the operating point of the compressor (green cross in Figure 9) in the characteristic map.

The compressor integrates itself into the system of equations of the facility according to Figure 5 (i.e., the operating point of the compressor is the intersection point of the characteristic compressor curve and the characteristic facility curve)!

The compressor can operate with different modes in the PipelineCockpit simulation. If the rotation speed is fixed, the simulation leads to the operating point on the blue curve. If the flow or the pressure increase are fixed, the PipelineCockpit Simulation calculates a rotation speed. If the compressor is not able to provide the desired value, it either10 ends up in a borderline position (min. or max. rotation speed or surge or choke limit) in the simulation or an operating point outside the operating regime is calculated and the invalid state of the result is indicated by a corresponding warning.

10 The compressor accounts for restrictions in the language use of the simulation. Accounting for the restrictions On/Off is an adjustment property of the compressor in the simulation.

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characteristic curve given by the manufacturer. The characteristic curves of pressure regula-torsareusuallygiveninthisform:valvecoefficient()independenceonvalvestroke.

Figure 3: Characteristic curve of a pressure regulator used by the PipelineCockpit simulation which is supplied to the hydraulic model while modeling

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2.6.2. Pressure regulator and characteristic curve

The starting point of a thermodynamic-hydraulic simulation of a pressure regulator is the characteristic curve given by the manufacturer. The characteristic curves of pressure regulators are usually given in this form: valve coefficient K ( G V VK ,K ,C ) in dependence on valve stroke φ .

Figure 10: Characteristic curve of a pressure regulator used by the PipelineCockpit simulation which is supplied to the hydraulic model while modeling

In practice, different versions of the valve coefficient are in use:

GK : defined for natural gas at reference conditions ( = ° = =1 1 2T 15 C,p 2bar,p 1bar )

VK : defined for water at reference conditions ( = − ° Δ =1T 5 40 C, p 1bar )

VC : analogous to VK , but using non-metric units

which are convertible according to their definitions.

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2.6.2. Pressure regulator and characteristic curve

The starting point of a thermodynamic-hydraulic simulation of a pressure regulator is the characteristic curve given by the manufacturer. The characteristic curves of pressure regulators are usually given in this form: valve coefficient K ( G V VK ,K ,C ) in dependence on valve stroke φ .

Figure 10: Characteristic curve of a pressure regulator used by the PipelineCockpit simulation which is supplied to the hydraulic model while modeling

In practice, different versions of the valve coefficient are in use:

GK : defined for natural gas at reference conditions ( = ° = =1 1 2T 15 C,p 2bar,p 1bar )

VK : defined for water at reference conditions ( = − ° Δ =1T 5 40 C, p 1bar )

VC : analogous to VK , but using non-metric units

which are convertible according to their definitions.

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Using the characteristic curve for the valve coefficient (here GK ) the norm volume flow relates to the valve stroke as follows:

κ−κ κ

φγ= ⋅ γ φ

κγ = ⋅ − ρ κ −

N Gref 100

1 1

2 21

N 1 1 1 1

Q K

p p1 2 1 p 11Z RT p p

(27)

Here, γref is the corresponding value for the definition conditions of the GK -value.

The methodology of pressure regulation is analogous for fluids and gases. Using the loss coefficient, the pressure loss along the pressure regulator reads

Δ = ρς2vp

2 (28)

The loss coefficient, however, does not depend on the thermodynamic- boundary conditions but on the valve stroke only:

( )4

100 2V

100

100 d16

K

⋅ φς = ⋅ φ φ φ

(29)

In the case of gas flows, the PipelineCockpit simulation relates the loss coefficient to the final state of isentropic relaxation:

Δς =ρ2s 2

2s 2s

2 pv

(30)

Isenthalpic pressure regulation in the −h s -diagram ( →1 2 ) with fictitious sub-processes:

Isentropic relaxation ( →1 2s ) and isobaric warming ( →2s 2 ):

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Figure 11: Pressure regulation process calculated by the PipelineCockpit simulation.

For comparison: The simulation calculates the adiabatic compression ( →1 2 ) t in −h s -diagram with

fictitious sub-processes: Isentropic ( →1 2s ) and polytropic process ( →1 2p):

Figure 12: Compression process calculated by the PipelineCockpit simulation

The pressure regulator integrates itself into the system of equations of the facility according to Figure 5 (i.e., the flow at a given valve stroke results from the operating state of the facility)!

Figure 11: Pressure regulation process calculated by the PipelineCockpit simulation.

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Figure 11: Pressure regulation process calculated by the PipelineCockpit simulation.

For comparison: The simulation calculates the adiabatic compression ( →1 2 ) t in −h s -diagram with

fictitious sub-processes: Isentropic ( →1 2s ) and polytropic process ( →1 2p):

Figure 12: Compression process calculated by the PipelineCockpit simulation

The pressure regulator integrates itself into the system of equations of the facility according to Figure 5 (i.e., the flow at a given valve stroke results from the operating state of the facility)!

Figure 5: Compression process calculated by the PipelineCockpit simulation

The pressure regulator integrates itself into the system of equations of the facility ac-cording to Figure5(i.e.,theflowatagivenvalvestrokeresultsfromtheoperatingstateofthefacility)!

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TheregulatorcanoperatewithdifferentmodesinthePipelineCockpitsimulation:massregulator,pressureregulator(downstreampressure,upstreampressure,differencepres-sure). The simulation calculates this valve stroke. The regulator ends up in a borderline po-sition (Open and Closed) if it is not able to provide the desired value. In this case the bor-der state of the result is indicated by a warning.

The operating mode “valve stroke” of the regulator is analogous to the operating mode “rotation speed” of the compressor. In contrast to the compressor, in the case of the reg-ulator there is no adjustment possibility in the simulation, which allows the regulator to leave its restrictions (the regulator is not able to be set beyond completely open or com-pletely closed – in the case of the compressor it might be of particular interest which inva-lid (in reality non-accessible) operating point deviates from an infeasible operating idea).

2.7. Model Quality

This chapter presents the model quality that is reachable with the PipelineCockpit simula-tionwiththeexampleofstartingafluidpipeline(kerosene).

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2.7. Model Quality

This chapter presents the model quality that is reachable with the PipelineCockpit simulation with the example of starting a fluid pipeline (kerosene).

Figure 13: PipelineCockpit simulation process model – starting up a fluid pipeline (kerosine)

The pipeline under consideration has a length of 110 km. Its hydraulic profile is shown in figure 14. We consider the quality of the simulation from shut-in conditions (red line) until a new stationary state is reached (green line).

The pump groups at the left side and in the middle are started which a small time delay. The control valve on the right side is opened successively.

The characteristic curves for these pumps and valves have been the entered in the hydraulic model used by the PipelineCockpit simulation. The pipe data are imported from the so called “pipe book” or GIS, respectively. After this, the simulation is driven by measured speeds of the pumps and measured positions of the valves.

Figure 13: PipelineCockpit simulation process model – starting up a fluid pipeline (kerosine)

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Thepipelineunderconsiderationhasalengthof110km.Itshydraulicprofileisshowninfigure14.Weconsiderthequalityofthesimulationfromshut-inconditions(redline)untila new stationary state is reached (green line).

The pump groups at the left side and in the middle are started which a small time delay. The control valve on the right side is opened successively.

The characteristic curves for these pumps and valves have been the entered in the hydrau-lic model used by the PipelineCockpit simulation. The pipe data are imported from the so called “pipe book” or GIS, respectively. After this, the simulation is driven by measured speeds of the pumps and measured positions of the valves.

Thecomputedpressurevaluesandflowvaluescanbecomparedwiththemeasuredvalues.The results are presented in Figure 15.

Figure 15: PipelineCockpit simulation result – starting up fluid pipeline (kerosine)

Evaluation of the model quality:

The agreement is good – in some parts very good.

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The computed pressure values and flow values can be compared with the measured values. The results are presented in Figure 15.

Figure 15: PipelineCockpit simulation result – starting up fluid pipeline (kerosine)

Evaluation of the model quality:

The agreement is good – in some parts very good.

Usefulness of the model quality:

Using a simulation instance of the PipelineCockpit one can train operators in starting up a pipeline close to reality. Even trainers would hardly be able to detect the differences between the simulation and reality during the training session.

Using a What If instance of the PipelineCockpit simulation operators can test the pipeline’s reaction to their new start-up concepts in the style of an ad-hoc training rather than applying them directly in reality. They might expect that good results in

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Usefulness of the model quality:

Using a simulation instance of the PipelineCockpit one can train operators in starting up apipelineclosetoreality.Eventrainerswouldhardlybeabletodetectthedifferencesbe-tween the simulation and reality during the training session.

Using a What If instance of the PipelineCockpit simulation operators can test the pipeline’s reaction to their new start-up concepts in the style of an ad-hoc training rather than apply-ing them directly in reality. They might expect that good results in the simulation will lead to good results in the reality and vice versa. The chief operator can do this in the same way if he intends to verify and improve start-up concepts.

A Look Ahead instance that shall predict the arrival of a batch at destination tanks would simulatethearrivaltimeinagoodwaydrivenbypumpon/offdecisionsbecausethemod-elcanreproducethestationaryflowratedependinguponthenumberofpumpsrunningvery well.

Not least, excellent performance characteristics would result on the basis of the mod-el quality achieved in leak detection. We consider a leak which arises during the dynamic start-up process.

Figure 16: PipelineCockpit Leak detection in a liquid pipeline (kerosine)

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the simulation will lead to good results in the reality and vice versa. The chief operator can do this in the same way if he intends to verify and improve start-up concepts.

A Look Ahead instance that shall predict the arrival of a batch at destination tanks would simulate the arrival time in a good way driven by pump on/off decisions because the model can reproduce the stationary flow rate depending upon the number of pumps running very well.

Not least, excellent performance characteristics would result on the basis of the model quality achieved in leak detection. We consider a leak which arises during the dynamic start-up process.

Figure 16: PipelineCockpit Leak detection in a liquid pipeline (kerosine)

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The start-up process begins after 100 seconds in each case in Figure 16.

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The start-up process begins after 100 seconds in each case in

Figure 16.

Left: No leakage.

Due to high model quality error indicators of the leak detection would hardly respond. In the case of a perfect process model and (perfect measurement readings) the error indicators would not respond at all. Due to high model quality the detection limit for leak detection in transient operational states is less than 1% of the stationary feed rate. If the model quality was worse error indicators would respond even if there is no leak. In consequence, one would be faced with high detection limits, deactivation during the transient phases or even false alarms.

Right: Leakage:

During the drive up process a leak of 4 m3/h arises which corresponds to 1.6% of the feed rate. Due to the high model quality error indicators respond quickly and precisely. Even the leakage location signal responds quickly and precisely. The leak detection system recognizes the small leak in the transient phase safely, quickly and precisely.

Left: No leakage.

Due to high model quality error indicators of the leak detection would hardly respond. In the case of a perfect process model and (perfect measurement readings) the error indica-tors would not respond at all. Due to high model quality the detection limit for leak detec-tion in transient operational states is less than 1% of the stationary feed rate. If the model quality was worse error indicators would respond even if there is no leak. In consequence, one would be faced with high detection limits, deactivation during the transient phases or even false alarms.

Right: Leakage:

During the drive up process a leak of 4 m3/h arises which corresponds to 1.6% of the feed rate. Due to the high model quality error indicators respond quickly and precisely. Even the leakage location signal responds quickly and precisely. The leak detection system recogniz-es the small leak in the transient phase safely, quickly and precisely.

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2.8. Simulation instances

PipelineCockpitsimulationsareusefultooperatesystemssafely,efficientlyandatoptimalcosts.

Thereforeoneorseveralsimulationinstancescanbeconfigured,suppliedwithdataandstarted. Data are measurement readings, nominal values (i.a. set points), messages (i.a. op-erating modes) and forecast values (i.a. for demands or planned operation of pumps/com-pressors).

For each instance the process model used is the same. The simulation instance calculates theprocessmodelaccordingtothemodelconfigurationandthedatadescribedabove.

A periodic forecast of a gas pipeline system (a continuous Look Ahead calculation initiat-ed every hour to calculate the next 24 hours) requires the prognostic demand value of all demand nodes and the time plans of the compressors. The Look Ahead instance computes theflowandtransportstateforthenext24hourspermanently.Ifthecompressorsareop-eratedaccordingtofixedrules,theserulescanbeincorporatedintheprocessmodel(byusing the signal model part of the process model; the signal model is explained below) -- regardless of whether these rules are automated in the real system or are merely recom-mendations or ideas concerning the mode of operation. Correspondingly, the Look Ahead instance requires the availability of compressors rather than the compressor operation as time series. The Look Ahead instance itself decides about compressor operation according totheconfigurationdoneinthesignalmodel.

Let’sassumethattherulesareautomatedintherealsystem.Modifiedcompressoroper-ation rule shall be checked for security, performance and costs. For this purpose, simply a secondLookAheadinstanceisstarted(withthemodifiedcompressorrules)withthesamedata(i.e.thesamedemandforecast).Thedifferencesbetweenthe2LookAheadinstancesarerecordedandanalyzedbythechiefoperatorusingthePipelineCockpit.Ifthemodifiedcompressoroperationrulesfulfilsallexpectations,itisautomatedtoafullextentinthereal system.

Let’s assume that the prognosed (forecasted) value of an important demand node is of lowquality.TwoLookAheadinstancesarestartedwiththesameconfiguration(i.e.accord-ingtothesamerules)butdifferentdata:onewiththeminimallyandanotheronewiththemaximally predicted value. The results are analyzed online - the resulting possible corridor offlowandtransportstatesisavailabletotheoperator.

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Let’s assume that the operator wants to verify his next switching operation (before actually applying the switching operation to the facility). For this purpose simply a training instance is started with an initial operating state identically to the actual operating statebased on the same state as the Look Ahead instances mentioned before. The training instance will run with a high resolution in time (1 second - the Look Ahead instances mentioned before have a time resolution of 3 minutes or higher). The operator will see the system’s reaction of his switching operation in the style of a training simulator.

Up to this point, examples of simulation instances have been outlined. In the following the principles of the signal model are presented.

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Let’s assume that the operator wants to verify his next switching operation (before actually applying the switching operation to the facility). For this purpose simply a training instance is started with an initial operating state identically to the actual operating statebased on the same state as the Look Ahead instances mentioned before. The training instance will run with a high resolution in time (1 second - the Look Ahead instances mentioned before have a time resolution of 3 minutes or higher). The operator will see the system’s reaction of his switching operation in the style of a training simulator.

Up to this point, examples of simulation instances have been outlined. In the following the principles of the signal model are presented.

Compressor made controllable from the “outside” by the signal model.

Example of an element of the signal model.

Desired value generator; the desired value can be set from the “outside”; e.g. by OPC.

Hydraulic Process model+

signal model

Figure 17: PipelineCockpit Simulation – hydraulic model controlled by signal model „from the outside“

The process model consists of two parts: the hydraulic model and the signal model. The interplay between hydraulic model and signal model is explained below.

The compressor in Figure 17 is intended to be controlled. Assume the compressor has two operating modes in reality: speed and flow. If the compressor is off, one of both operating modes is active and has nominal value (set point) 0. The signal model part of the process model will drive the compressor according to reality. This procedure is

Figure 17: PipelineCockpit Simulation – hydraulic model controlled by signal model „from the outside“

The process model consists of two parts: the hydraulic model and the signal model. The in-terplay between hydraulic model and signal model is explained below.

The compressor in Figure 17 is intended to be controlled. Assume the compressor has two operatingmodesinreality:speedandflow.Ifthecompressorisoff,oneofbothoperating

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modes is active and has nominal value (set point) 0. The signal model part of the process model will drive the compressor according to reality. This procedure is shown in Figure 1: at the lower left light blue box, the signal model writes permanently the actual nomi-nal values (set points) to the corresponding operating modes. This is done independent of whether the compressor actually uses one of the operating modes or not. At the right mid-dleofthisfigurethesignalmodelswitchestheoperatingmodewhenthecorrespondingmessage is true. The operator himself (or the SCADA system) has to take care that both op-erating modes are not active at same time. The hydraulic model uses operating mode and set point. This control technique requires two nominal values (set points) and two messag-es (for the two operational modes). The process model reacts to these four channels “from the outside” permanently. Let’s assume that this control technique belongs only to the What If simulation and in other circumstances other techniques shall be applied in the pro-cessmodel.Inthatcase,thewholeWhatIftechniquecanbeswitchedonoroffbyafifthchannel(message)(atthetopleftofthefigure).Withsuchaprinciplevariousoperatingconcepts can be modeled and activated or deactivated. The elements of the signal model can be edited by the model editor in the same way as the elements of the hydraulic model.

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2.9. Nomenclature (Englisch) / Nomenklatur (German)

2.9.1. Greek Letters / Griechische Buchstaben

Symbol Einheit

/ Unit

Bedeutung

/ Meaning

( )...~

∂∂

partielle Ableitung von ( )... nach ~

/ partial derivative from ( )... after ~

( )2

2 ...~

∂∂

zweifache partielle Ableitung von ( )... nach ~

/ partial derivative from ( )... after ~ twice

α 2

WK m⋅

Wärmeübergangskoeffizient Fluid/Rohrwandung-innen

/ heat transfer coefficient fluid-pipe

pα 1K

isobarer Volumenausdehnungskoeffizient

/ isobaric volume expansion coefficient

Tp

p p

1 K1 1T T T

+∂ρ ∂υ α = − = = ρ ∂ υ ∂

Rβ 1K

linearer Volumenausdehnungskoeffizient des Rohrwandungsmaterials

η - Prozesswirkungsgrad / efficiency

ηp - Polytroper Wirkungsgrad / polytropic efficiency

ηs - Isentroper Wirkungsgrad / isentropic efficiency

κ - Isentropenexponent / isentropic exponent

2.9. Nomenclature (Englisch) / Nomenklatur (German)

2.9.1. Greek Letters / Griechische Buchstaben

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TF

1E

κ = 1Pa

isotherme Kompressibilität

/ isothermal compressibility

pT T

F T T

1 K1 1 1E p p p

− ∂ρ ∂υκ = β = = = − = ρ ∂ υ ∂

λ - Reibungsbeiwert

/ friction coefficient

HCλ WK m⋅

Wärmeleitfähigkeit des Fluides

/ thermal conductivity fluid

iHCλ W

K m⋅ Wärmeleitfähigkeit (der i-ten Komponente einer aus

mehreren Komponenten bestehenden Rohrwandung)

/ thermal conductivity (of pipe wall component i)

ρ 3

kgm

Dichte / density

ρN Normdichte / norm density

ρρ =mmM

3

kmolm

Molare Dichte / molar density

1υ =ρ

3m

kg Spezifisches Volumen / specific volume

ν - Querdehnungszahl des Rohrwandungsmaterials

2.9.2. Latin Letters / Lateinische Buchstaben u. Abkürzungen

Symbol Einheit

/ Unit

Bedeutung

/ Meaning

HC

p

ac

λ=ρ ⋅

2m

s

Temperaturleitfähigkeit

/ thermal diffusivity

3

kgm

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a ms

kombinierte Fluid-Rohrwandungs-Schallgeschwindigkeit

/ combined fluid pipewall wave speed

( )

F

b

F

p W

E

a

D 1 ²c Ec E s

μ

υ

ρ=

⋅ − μ+

barotropa ms

kombinierte Fluid-Rohrwandungs-Schallgeschwindigkeit für eine barotrope Flüssigkeit

/ combined fluid pipewall wave speed (barotropic liquid)

( )

F

barotrop b

F

W

E

a

D 1 ²E1E s

μ

ρ=

⋅ − μ+

A 2m durchflossene Querschnittfläche / cross sectional pipe area

s

pc kυ ∂= = ∂ρ

ms

isentrope Schallgeschwindigkeit

/ isentropic wave speed

pc ,cυ Jkg K⋅

spezifische Wärmekapazität bei konstantem Druck, Volumen / specific heat capacities at constant pressure, volume

( )d ...dt

substantielle Ableitung von ( )... nach

der Zeit

/ substantial derivative from ( )... after

time

D,d m Hydraulischer Durchmesser (Rohrinnendurchmesser)

/ hydraulic diameter (inner pipe

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TF

1E

κ = 1Pa

isotherme Kompressibilität

/ isothermal compressibility

pT T

F T T

1 K1 1 1E p p p

− ∂ρ ∂υκ = β = = = − = ρ ∂ υ ∂

λ - Reibungsbeiwert

/ friction coefficient

HCλ WK m⋅

Wärmeleitfähigkeit des Fluides

/ thermal conductivity fluid

iHCλ W

K m⋅ Wärmeleitfähigkeit (der i-ten Komponente einer aus

mehreren Komponenten bestehenden Rohrwandung)

/ thermal conductivity (of pipe wall component i)

ρ 3

kgm

Dichte / density

ρN Normdichte / norm density

ρρ =mmM

3

kmolm

Molare Dichte / molar density

1υ =ρ

3m

kg Spezifisches Volumen / specific volume

ν - Querdehnungszahl des Rohrwandungsmaterials

2.9.2. Latin Letters / Lateinische Buchstaben u. Abkürzungen

Symbol Einheit

/ Unit

Bedeutung

/ Meaning

HC

p

ac

λ=ρ ⋅

2m

s

Temperaturleitfähigkeit

/ thermal diffusivity

3

kgm

2.9.2. Latin Letters / Lateinische Buchstaben u. Abkürzungen

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a ms

kombinierte Fluid-Rohrwandungs-Schallgeschwindigkeit

/ combined fluid pipewall wave speed

( )

F

b

F

p W

E

a

D 1 ²c Ec E s

μ

υ

ρ=

⋅ − μ+

barotropa ms

kombinierte Fluid-Rohrwandungs-Schallgeschwindigkeit für eine barotrope Flüssigkeit

/ combined fluid pipewall wave speed (barotropic liquid)

( )

F

barotrop b

F

W

E

a

D 1 ²E1E s

μ

ρ=

⋅ − μ+

A 2m durchflossene Querschnittfläche / cross sectional pipe area

s

pc kυ ∂= = ∂ρ

ms

isentrope Schallgeschwindigkeit

/ isentropic wave speed

pc ,cυ Jkg K⋅

spezifische Wärmekapazität bei konstantem Druck, Volumen / specific heat capacities at constant pressure, volume

( )d ...dt

substantielle Ableitung von ( )... nach

der Zeit

/ substantial derivative from ( )... after

time

D,d m Hydraulischer Durchmesser (Rohrinnendurchmesser)

/ hydraulic diameter (inner pipe

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a ms

kombinierte Fluid-Rohrwandungs-Schallgeschwindigkeit

/ combined fluid pipewall wave speed

( )

F

b

F

p W

E

a

D 1 ²c Ec E s

μ

υ

ρ=

⋅ − μ+

barotropa ms

kombinierte Fluid-Rohrwandungs-Schallgeschwindigkeit für eine barotrope Flüssigkeit

/ combined fluid pipewall wave speed (barotropic liquid)

( )

F

barotrop b

F

W

E

a

D 1 ²E1E s

μ

ρ=

⋅ − μ+

A 2m durchflossene Querschnittfläche / cross sectional pipe area

s

pc kυ ∂= = ∂ρ

ms

isentrope Schallgeschwindigkeit

/ isentropic wave speed

pc ,cυ Jkg K⋅

spezifische Wärmekapazität bei konstantem Druck, Volumen / specific heat capacities at constant pressure, volume

( )d ...dt

substantielle Ableitung von ( )... nach

der Zeit

/ substantial derivative from ( )... after

time

D,d m Hydraulischer Durchmesser (Rohrinnendurchmesser)

/ hydraulic diameter (inner pipe

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diameter)

iD m Innendurchmesser (der i-ten Komponente einer aus mehreren Komponenten bestehenden Rohrwandung)

/ inner diameter (of pipe wall component i)

i 1D+ m Außendurchmesser (der i-ten Komponente einer aus mehreren Komponenten bestehenden Rohrwandung)

/ outer diameter (of pipe wall component i)

sD m S „Surrounding“

Außendurchmesser (der letzten Komponente einer aus mehreren Komponenten bestehenden Rohrwandung)

/ outer diameter (of the last pipe wall component)

FE Pa Elastizitätsmodul des Fluides

FT

1E =κ

RE Pa Elastizitätsmodul des Rohrwandungsmaterials

g 2

ms

Erdbeschleunigung / gravitational acceleration

h Jkg

spezifische Enthalpie / specific enthalpy

rh - Invariante polytrope Referenzarbeit / dimensionless polytropic head

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diameter)

iD m Innendurchmesser (der i-ten Komponente einer aus mehreren Komponenten bestehenden Rohrwandung)

/ inner diameter (of pipe wall component i)

i 1D+ m Außendurchmesser (der i-ten Komponente einer aus mehreren Komponenten bestehenden Rohrwandung)

/ outer diameter (of pipe wall component i)

sD m S „Surrounding“

Außendurchmesser (der letzten Komponente einer aus mehreren Komponenten bestehenden Rohrwandung)

/ outer diameter (of the last pipe wall component)

FE Pa Elastizitätsmodul des Fluides

FT

1E =κ

RE Pa Elastizitätsmodul des Rohrwandungsmaterials

g 2

ms

Erdbeschleunigung / gravitational acceleration

h Jkg

spezifische Enthalpie / specific enthalpy

rh - Invariante polytrope Referenzarbeit / dimensionless polytropic head

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j Jkg

spezifische dissipative Wärme / specific dissipative heat

p TK ,K - Kompressibilitätszahlen bezüglich Druck- und Temperaturänderung / compressibility factors for pressure and temperature change

'Dk W

K m⋅ Wärmedurchgangskoeffizient (auf hydr.

Umfang bezogen)

/ heat transfer coefficient

' ''D D

U

k k D=

= ⋅ π ⋅

''Dk

2

WK m⋅

Wärmedurchgangskoeffizient (auf D bezogen)

/ heat transfer coefficient

''D N

i 1i

i 1 HC iWärmeübergang Wärmeleitung Wärm/ transition /conduction / transfluid pipe pipe s

1kD1 D 1 Dln

2 D D+

=

− −

=+ +

α λ

mM kgkmol

molare Masse / molar mass

m v A Q= ρ ⋅ ⋅ = ρ ⋅

kgs

Massenstrom / mass flow rate

N Index für Normzustand / index of norm state

(TN = 0°C , pN = 101.325 kPa)

n - Polytropenexponent / polytropic exponent

N 1min

Drehzahl / rotations per minute

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j Jkg

spezifische dissipative Wärme / specific dissipative heat

p TK ,K - Kompressibilitätszahlen bezüglich Druck- und Temperaturänderung / compressibility factors for pressure and temperature change

'Dk W

K m⋅ Wärmedurchgangskoeffizient (auf hydr.

Umfang bezogen)

/ heat transfer coefficient

' ''D D

U

k k D=

= ⋅ π ⋅

''Dk

2

WK m⋅

Wärmedurchgangskoeffizient (auf D bezogen)

/ heat transfer coefficient

''D N

i 1i

i 1 HC iWärmeübergang Wärmeleitung Wärm/ transition /conduction / transfluid pipe pipe s

1kD1 D 1 Dln

2 D D+

=

− −

=+ +

α λ

mM kgkmol

molare Masse / molar mass

m v A Q= ρ ⋅ ⋅ = ρ ⋅

kgs

Massenstrom / mass flow rate

N Index für Normzustand / index of norm state

(TN = 0°C , pN = 101.325 kPa)

n - Polytropenexponent / polytropic exponent

N 1min

Drehzahl / rotations per minute

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eN 1m

Invariante Drehzahl / rotations per minute (invariant)

p =

⋅ 2

kgPam s

Druck / pressure

P m Invariante Leistung / invariant power

P ⋅= 3

kg mWs

Leistung / power

q Jkg

Spezische Wärme / specific heat

q - Invarianter Volumenstrom / invariant volumetric flow

Q v A= ⋅ 3ms

Volumenstrom/ volume flow rate

NQ 3ms

Normvolumenstrom/ norm volume flow rate

m

m

RRM

= ⋅

Jkg K

spezifische Gaskonstante / specific gas constant

mR ⋅

Jkmol K

molare universelle Gaskonstante / molar universal gas constant

s ⋅

Jkg K

spezifische Entropie / specific entropy

s m Rohrwanddicke

/ pipe wall thickness

T K Temperatur / temperature

cT K (pseudo-) kritische Temperatur / (pseudo-) critical temperature

t s Zeit / time

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eN 1m

Invariante Drehzahl / rotations per minute (invariant)

p =

⋅ 2

kgPam s

Druck / pressure

P m Invariante Leistung / invariant power

P ⋅= 3

kg mWs

Leistung / power

q Jkg

Spezische Wärme / specific heat

q - Invarianter Volumenstrom / invariant volumetric flow

Q v A= ⋅ 3ms

Volumenstrom/ volume flow rate

NQ 3ms

Normvolumenstrom/ norm volume flow rate

m

m

RRM

= ⋅

Jkg K

spezifische Gaskonstante / specific gas constant

mR ⋅

Jkmol K

molare universelle Gaskonstante / molar universal gas constant

s ⋅

Jkg K

spezifische Entropie / specific entropy

s m Rohrwanddicke

/ pipe wall thickness

T K Temperatur / temperature

cT K (pseudo-) kritische Temperatur / (pseudo-) critical temperature

t s Zeit / time

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u Jkg

spezifische thermische Energie / specific thermal energy

U D= π ⋅ m Hydraulischer Umfang (Innenumfang)

/ perimeter

v ms

Strömungsgeschwindigkeit (querschnittsgemittelt)

/ flow velocity (cross section averaged)

tw Jkg

spezifische technische Arbeit / specific technical work

y Jkg

Spezifische Verdichtungsarbeit / specific compression work

p sy ,y Jkg

Spezifische polytrope und isentrope Verdichtungsarbeit / specific polytropic and isentropic compression work

z m Höhe / altitude

Z - Realgasfaktor / compressibility factor

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2.10 Table of figures

fehlt leider im WORD bzw. hat sich im PDF “zerschossen”

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Chapter II:Viewstar ICS TAS

3.1. Introduction

Viewstar ICS TAS is an integrated automation system for loading facilities.

The abbreviation TAS stands for Terminal Automation System.

ICS TAS is a technology package for the Viewstar ICS communication system.

The Viewstar ICS communication system provides comprehensive SCADA functionalities as well as various other technology packages which will not be addressed in detail within the scope of this document.

Further details about Viewstar ICS can be found in the relevant descriptions.

3.2. Fields of Application

TheICSTASproductisaflexiblydesignedsystemforloadingfacilitiesinthemineraloiland chemical industries.

The handling processes (storage and removal from storage) required for petroleum / liquid chemical products are carried out by means of trucks, railway vehicles and ships.

Awiderangeoffield,measuringandcommunicationfunctionsarerequiredinordertoau-tomate these processes.

The ICS TAS system contains special function modules in order to realise these complex tasks.

The ICS TAS system is designed for the following applications:

• Tank depots

• Loading and unloading facilities

• Product distribution systems

• Product and/or access control

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3.2.1. System Structure

The system is divided into the following parts:

ICS TAS

Based on Viewstar ICS, ICS TAS provides the SCADA part for the display and control of the loading and unloading processes, tank depot equipment and the administrative manage-ment, as well as the event/incident and alarm management and archiving.

AdminNET

This provides the administrative management of the loading data.

It is the interface between the commercial data and the loading control and provides com-prehensive functions for this, including delivery notes, partner and customer data, driver / conductor / skipper and vehicle / vessel data, product data, tank data maintenance, key data, product import/export data, inventory and stock, quotas, MPKS and IFlexx data records.

DrustaNET

It is a PC-based system approved by the PTB (PTB=Physikalisch Technische Bundesanstalt [Germany’snationalmetrologyinstituteprovidingscientificandtechnicalservices])andisused for the secure storage of custody transfer original document data as well as non-cus-tody transfer project data.

Optionally, an original document printer can be connected.

ProconNET

Asanautomationunit,theProConNetprocesscontrolleroffersallfunctionsrequiredtocontrol and regulate the loading-related functions such as TTF (tanker truck, fuel), railway tank wagons, ship loading / unloading, pump control, additivation etc.

FlcNET

TheFlcNETisaMID-compliantflowcomputerforcalibratablevolumemeasurement.(MID= European Measuring Instruments Directive)

It has a modular structure and has been designed for a maximum of 16 measuring points.

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FlcNET

The FlcNET is a MID-compliant flow computer for calibratable volume measurement. (MID = European Measuring Instruments Directive)

It has a modular structure and has been designed for a maximum of 16 measuring points.

3.2.2 Typical Tank Depot Configuration

The following figure shows a typical facility configuration of a tank depot with different components of the TAS system.

Figure 18: Configuration

3.2.2. Typical Tank Depot Configuration

Thefollowingfigureshowsatypicalfacilityconfigurationofatankdepotwithdifferentcomponents of the TAS system.

Figure 18: Configuration

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German EnglishViewstar ICS TAS Viewstar ICS TAS

AdminNET AdminNET

DustraNET DustraNET

Redundanter Server Redundant server

Alarme / Ereignisse Alarms / events/incidents

Operator Station 1 Operator station 1

Operator Station n Operator station n

Urbeleg PC Original document PC

Berichte Reports

Versanddokumente- Drucker an Ausfahrt

Shipping document printer at exit

ProconNET ProconNET

FlcNET FlcNET

LAN LAN

Eichwerte Aktuelle Werte

Calibration values Current values

Ex-Barrieren Ex barriers

Remote-I/O-terminals Remote I/O terminals

ID-Terminals Ein-/Ausfahrt

ID terminals entry / exit

ID Terminal ID terminal

Explosionszone Explosion zone

z.B. Verladebühnen e.g. loading platforms

Produkt-Pumpen Product pumps

Gravimetrische Verladung Bitumen / LPG

Gravimetric loading Bitumen / LPG

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3.3. Function Modules

The function modules integrated into Viewstar ICS TAS cover the following areas:

• Administrative Management AdminNET

• Tank Depot Management / Control

3.3.1. Administrative Data Management AdminNET

The AdminNET module contains the functionalities to manage:

• Delivery notes

• Partner and customer data

• Driver / conductor / skipper and vehicle / vessel data

• Product data

• Tank data maintenance

• Key data

• Product import/export data

• Inventory and stock

• Quotas

• MPKS and IFlexx data records (XML)

• Reporting

Themanagementofadministrativemasterdata,suchasproductandtypedefinitions,quo-tas, stock, business partners, additives, addresses, driver / conductor / skipper and vehicle / vessel data, customer addresses etc. are stored in a relational database.

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The user dialogues are running on the operator stations.

In addition to the administrative master data maintenance dialogues, the range of func-tions also includes dialogues for the management of operating data, such as the handling of products (storage and removal from storage) via the pipeline, tank wagons, ships as well as dialogues for tank data management.

Reporting includes standard reports such as:

• Quantities of handled products (stored and removed from storage) per day and month

• Dosing protocol

• Product stock

• Product disposition

• Product movements

• Consignment note

• Loading instructions and many more

The available functions and reports can be adjusted and supplemented in a project-specif-ic manner.

3.3.2. Tank Depot Management / Control

The tank depot control module contains functions for

• Access control at entries and exits to the tank depot

• Operating mode management

• TrafficcontrolforTTF

• Management and control of loading and unloading data

• Monitoring of vehicles on loading positions

• Tankfieldmanagement

• Pump control

• Control and monitoring of secondary facilities

• Event/incident and alarm monitoring

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• Reporting

• Certifiedcustodytransferdataacquisitionandbalancingoftheloadedproducts

• Balancing of product handling (storage and removal from storage)

• Original document entry via PC, based on national and OIML calibration standards

3.4. Example Screenshots of the SCADA System Graphics

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3.4 Example Screenshots of the SCADA System Graphics

Figure 19: Overview screen of TTF loading platforms

Figure 19: Overview screen of TTF loading platforms

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Figure 20: Pipeline with control panel

Figure 20: Overview screen of TTF loading platforms

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Actemium Cegelec GmbH Colmarer Straße 5 60528 Frankfurt am Main/Germany [email protected]


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