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Determining safety distance in process design
On 9 July 1976, one kilogram of 2,3,7,8 tetrachlorodibenzo-dioxin (TCDD) was released
through a rupture disk at the ICMESA plant in Seveso, Italy. That was not only the day when the
hazard of a toxic cloud potentially spreading over the whole commu-nity, but it was also the beginning of a huge change in the regulatory and methodological approach to process safety. Seveso Directives I (1982), II (1997) and III (2012) have introduced the concept of risk in the industry and have addressed the quantitative risk assessment (QRA) approach for siting of potentially hazardous installations.
Previously, a prescriptive approach was the general method used to manage safety and occupa-tional aspects of the industrial world. The methodological change
the safety and occupational health laws of the European Union. Through New Approach and Global Approach, the European Commission in 2000 also introduced individual responsibility for the site owner to provably certify the acceptability of risk. In the industrial sectors poten-tially affected by major hazards, such as the oil and gas and petro-chemical/chemical industries, this process has been implemented rela-tively more quickly than in others, due to the industries’ cultural back-ground and their high potential hazards. The need to minimise risk and a progressively growing consciousness about “friendly safety” (Kletz, 2010) have led to the adoption of techniques and meth-odologies which are capable of
Safety distance determination is a key design issue that may have a dramatic
impact on a refinery construction project
RENATO BENINTENDI, ANGELA DEISY RODRIGUEZ GUIO and SAMUEL MARSH
Amec Foster Wheeler
reducing post-incident measures and able to develop increasingly sustainable approaches because of their inherent low hazard and potential for harm. The key concept of ‘inherent safety’, which had been introduced several years earlier (Kletz, 2010) is “the limitation of effects by changing designs or reac-tion conditions rather than by adding protective equipment that may fail or be neglected”.
QRA studies in the industry have traditionally been implemented as separate, stand-alone tasks, often not synchronised with design devel-opment. A possible outcome of this for the design team is to be delayed while implementing suitable design and layout changes, which gener-
protective measures, a non-harmo-
impact on project cost and, last but not least, an ineffective achievement of safety targets. This is often the case with plant/equipment siting. The traditional approach consists essentially of the adoption of prescriptive distances, which may in fact be unsafe, or which may lead to the available space being used in a less than optimised manner. Amec Foster Wheeler’s experience includes a long project execution history, throughout which the necessity to develop risk-based,
safety distances between plant units, between main equipment and occupied areas, has increased in importance. This article describes this evolution and presents a state-of-the-art, quantitative risk assessment approach to safety distance determination.
Background of the methodology of the separation distance assignment Early guidance about safety distances was given by Armistead (1952), Backurst and Harker (1973), and Anderson (1982). In 1976, the Dow Chemical company included safety distances in its Fire and Explosion Index (FEI) Guide. Developed in the 1980s, the Mond Fire Explosion and Toxicity Index method is an extension of the origi-nal Dow Index method. Exxon (1998) issued some safety design
-tive values for layout spacing. Similar separation distance tables have been given by Mecklenburgh (1985) and Industrial Risk Insurers. Mecklenburgh also carried out a categorisation of the most important hazardous scenarios to be used in support of plant layout.
Prescriptive separation distances for small and large tanks containing
the Health and Safety Executive in 1998 and, for LPG, in 2013. The US Center for Chemical Process Safety (CCPS) (2003) has provided typical separation distances between vari-ous elements in open-air process facilities. These tables are based on historical and current data from
and insurance sectors. The data were developed based on experi-ence and engineering judgment and, as clearly stated in the CCPS textbook, not always on calculations.
On the other hand, risk- and consequence-based methods have increased in importance and this has
and standards. In 1996, the
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The FEATHER model
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Determination of Safety Distances
Risk Management Program Guidance for Offsite Consequence Analysis
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et al
Safety distance as part of inherently safer design
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Chemical Hazard Engineering Guidelines -
-Process
Plants: A Handbook for Inherently Safer Design
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Safety distance
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34 PTQ Q1 2015 www.eptq.com
Amec Foster Wheeler aimed at auto-matically identifying the hazard scenarios and providing frequency and safety distances, along with iso-contour diagrams. Safety
from the release or blasting (BLEVE) -
mable, heat-radiation, overpressure endpoint. This software has been programmed in Microsoft Visual Basic and incorporates API’s physi-cal-chemical database and
-trated in Figure 1, where the light
the output data or intermediate data automatically calculated or uploaded by the software.
Chemical substances
octane, crude oil, hydrogen, carbon
along with the corresponding hazard scenarios.
Flow models
are calculated according to adiaba-
liquid state at the outlet because the Fauske and Epstein critical length (1988) for phase transition is not
-lated through Torricelli’s formula.
Figure 1 Flow chart of FEATHER software
(LEL, ERPG, combustion, heat...)
Design case
Plant units/modules
Main equipment/piping
Substance(s) selection
Process data
Data collection
Substances and equipment data
Process and layout data
Hazardous properties
Hazard intrinsic scenario
Field hazard process scenario
Ignition sources
Jet fire Near/medium/far-field flow(flame length, heat, radiation) (light/heavy gases)
(yes/no)
Specific data requirements(particular endpoints)
(thermodynamic, toxic)
Hazardous material identity
Main process data
Equipment/pipe selection
Module(s) congestion data
Programme substances properties database
Flammability, toxicity
Multiple hazard data(flammability and toxicity)
Failure data(hole size, failure rates...)
Outflow model BLEVE
LPG
Carbon dioxide
Ammonia
One phase
Two phase
Diked/unidiked pool fire
Frequency
Safety distance
Vaporisation flow
Congested-space blast Flash fire Toxic cloud Open-space blast
Frequency Safety distance
www.eptq.com PTQ Q1 2015 35
(module and units) has been modelled according to the method provided by Puttock. The user is requested to provide geometrical and congestion data. The software
35
45
40
30
25
20
15
10
5
10 20 30 40 50 60
FEATHER
PHAST
Figure 2 Propane jet fire; comparison of FEATHER vs PHAST
300
350
250
200
150
100
50
Radia
tive s
afe
ty d
ista
nce, m
0
0 20000 40000 60000 80000 100000
FEATHER
PHAST
Figure 3 Heptane pool fire; comparison of FEATHER vs PHAST
Figure 4 Fireball; comparison of FEATHER vs PHAST
120
200
180
160
140
100
80
60
40
20
0
FEATHER
PHAST
0 100 200 300
DispersionDispersion modelling has been approached by tuning a blending of sequential models, taking into account the initial jet momentum/
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(Britter and McQuaid, 1988), and the
Wind and Pasquill weather catego-ries data are selected by the user.
Pool evaporation and strippingMacKay and Matsugu’s (1987) formula has been adopted because of its validation against experi-ments. For crude oil, gasolines, diesels and kerosenes, the Reid vapour pressure can be used to estimate the mass of vapour evapo-rating from the liquid. It has been assumed that all of the toxic gas is stripped from the liquid in order to be conservative. Once this mass of toxic vapour is known, dispersion models have been applied.
Hazard scenariosHazard scenarios are automatically
the characteristics of the substances.
Pool fire
have been modelled. The evapora-tion effect has been considered according to the methodology outlined above. The TNO (2005) model has been adopted.
Jet fire
Flame dimensions and the radiative
according to TNO (2005). A light or
Flash fire and toxic release
considering the distance to substance lower explosive limits. This is conservative and reasonable. Therefore, toxic release has been modelled in the same way, just
Open space explosion
The TNT method has been selected for modelling open space explo-sion. Despite the claimed poor accuracy stated in the literature,
comparison with DNV PHAST has shown very good results.
Congested space explosion
Explosion in congested space
36 PTQ Q1 2015 www.eptq.com
and Related Industries, John G Simmonds & Co,
Inc., New York, 1952.
2 Anderson F V, Plant Layout In: Kirk R E,
Othmer D F, 1982, op. cit., vol. 18, 23.
3 Backhurst J R, Harker J H, Process plant
design, American Elsevier, New York, 1973.
4 Benintendi R, Turbulent jet modelling for
hazardous area classification, Journal of Loss
Prevention in the Process Industries, 2010, vol
23, issue 3, 373–378.
5 Britter R E, McQuaid J, Workbook on the
Dispersion of Dense Gases, HSE Contract
Research Report No. 1.7, 1988.
6 Cox A W, Lees F P, Ang M L, Classification of
Hazardous Locations, IChemE, 1993.
7 Crowl D, Louvar J, Chemical process safety
- Fundamentals with applications, New Jersey,
Prentice Hall PTR, 2002.
8 Fauske H K, Epstein M, Source term
considerations in connection with chemical
accidents and vapour cloud modelling, Journal
of Loss Prevention in the Process Industries, vol
1, April1988.
9 Ivings M J, Clarke S, Gant S E, Fletcher B,
Heather A, Pocock D J, Pritchard D K, Santon R,
Saunders C J, Area Classification for secondary
releases from low pressure natural gas
systems, Health and Safety Executive Research
Report RR630, 2008.
10 Kletz T, Amyotte P, Process Plants: A
Handbook for Inherently Safer Design, CRC
Press Taylor & Francis Group, 2010.
11 Kawamura P I, MacKay D, The Evaporation
of volatile liquids, J. of Hazardous Materials,
1987, 15, 365-376.
12 Kletz T, Amyotte P, Process plants: A
Handbook for Inherently Safer Design, 2nd ed,
CRC Press Taylor & Francis Group, 2010.
13 Marsh S, Guidelines for the determination
of safety distances with respect to fire,
explosion and toxic hazards, Foster Wheeler,
2013.
14 Mecklenburgh J C, Process Plant Layout,
John Wiley & Sons, New York, 1985.
15 TNO, Method for the Calculation of Physical
Effects (Yellow Book), Ed: van den Bosch C J H,
Weterings R A P M, 2005.
Renato Benintendi is Principal Consultant,
Loss Prevention with Amec Foster Wheeler,
Reading, UK. He holds an advanced degree in
chemical engineering from the University of
Naples, Italy, as well as a master’s degree in
environmental and safety engineering.
Angela D Rodriguez Guio is a Senior Process
Safety Engineer. She holds a bachelor’s degree
in chemical engineering from Universidad
Nacional de Colombia, a postgraduate degree
in occupational health and safety from
the Universidad Distrital Francisco Jose de
Caldas and an MSc in process safety and loss
prevention from the University of Sheffield, UK.
Samuel Marsh is a Process Engineer with Amec
Foster Wheeler. He holds a master’s degree in
chemical engineering from the University of
Manchester, UK.
very good within the sensitivity analysis results. The software is not intended to replace validated soft-ware adopted in QRA and consequence assessment studies. Nevertheless, it can be considered a
-tion of initial equipment spacing.
ConclusionAmec Foster Wheeler is implement-ing a risk-based approach to safety distance determination early in the design of process plant. Spacing of equipment and separation distance
has been traditionally approached by means of prescriptive distances,
risk-based methodology has been used and software has been devel-oped, which includes and integrates validated models and provides satisfactory predictive results in terms of frequency and safety distances. The method is considered a step forward in the implementa-tion of inherently safer design.
Based on a paper presented at the IChemE
HAZARDS 24 Conference, Edinburgh, 7-9 May
2014.
Further reading
1 Armistead G, Safety in Petroleum Refining
automatically calculates whether a
module/unit and assumes that
reasonable and conservative hypothesis.
BLEVE
BLEVE has been modelled accord-ing to the method provided by CCPS.
Accuracy and validityFEATHER works according to the
Typically, a frequency of 10-4/yr is
which can be changed. Accordingly, a dual option has been imple-mented, which allows for the provision of the iso-contours for the
of the possible incidents. The soft-
with DNV PHAST results. Some
Figures 2, 3 and 4, and in Tables 1 and 2, showing the calculation of distances to acceptable radiation
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masses. The comparability is also
Distance from Pipe rack Assumed operating Distance Distance pressure bar, g FEATHER, m tables, mTo Heat exchanger 10To Columns, accumulators, drums 10To Rundown tanks 20 90 (jet fire) 100To Moderate hazard reactors 150 ÷ 300 (fireball) 10To Intermediate hazard reactors 15To High hazard reactors 25
Comparison of FEATHER distances (to 8 kw/m2) with tabulated (prescriptive) distances: jet fire and fireball
Table 1
Distance from Intermediate Assumed Distance Distance hazard pumps substance FEATHER, m tables, mTo Columns, accumulators, drums 10To Pipe racks 10To Heat exchangers Heptane 15÷35 15To Moderate hazard reactors 10To Intermediate hazard reactors 10To High hazard reactors 10
Comparison of FEATHER distances (to 8 kw/m2) with tabulated (prescriptive) distances: pool fire
Table 2