Optimized Ship Design Using HEEDS & STAR-CCM+ · PDF fileOptimized Ship Design Using HEEDS &...

Optimized Ship Design Using

HEEDS & STAR-CCM+

Damian Tatum – Downey Engineering

Darren Preston - Downey Engineering

Timothy Yen – CD-adapco

Nate Chase – Red Cedar Technology

Cargo ship design requires a challenging balancing act between construction costs

and operational efficiency. Naval architects strive to minimize hull drag while

maximizing propulsive efficiency with limits on cavitation, erosion, and up-front material

costs. In this current study, we leveraged recent advances in simulation-based design,

multidisciplinary design exploration, and scalable computation to automate the

identification of new and efficient cargo ship designs.

The commercial HEEDS multidisciplinary design exploration software was used to

automatically drive hull form geometry changes and hydrostatic performance

evaluation in the MultiSurf software followed by a drag and propulsive power

assessment in the STAR-CCM+ computational fluid dynamics (CFD) software. Design

variables included basic hull parameters such as length and width, bulb geometry,

skeg geometry, and propeller design features. Hybrid, adaptive design search

techniques were utilized to identify designs that yielded considerable reductions in

drag along with increases in propulsive power, directly translating into reduced fuel and

operational costs.

This study demonstrates considerable advantages over traditional ship design

methodologies and opens up new avenues to leverage inexpensive high-performance

computing resources to wring out higher performance and lower cost designs.

Abstract

This project utilized the same methodology and framework as a

proprietary project performed for a similar vessel with a more diverse

operational profile.

The vessel design considered was an alternative single-skeg, twin screw

design for aforementioned project.

The process deployed throughout this project is applicable to any design.

The vessel chosen here is for demonstration purposes only.

Background

Ship efficiency and emissions regulations (EEDI) are gradually increasing

the need for more holistic design approaches

– Fuel efficiency devices provide marginal improvements to existing designs

– De-rating of engines and simply reducing speed can only take

owners/operators so far

Vessels with varied operational profiles require trade-off analyses that

make a test regime exponentially more difficult.

It’s very hard to know how subtle changes in hull form can effect overall

performance, operational expenses and acquisition costs

– Any wisdom is very general

Motivation

Bulbous bow, and twin screw, skeg stern configurations are used to

improve efficiencies

Advantages:

– Reduces wave-making resistance (bulbous bow)

– Provides propeller and maneuverability redundancy

– Improves flow into the propellers and directional stability

Disadvantages:

– Traditional classical rules and standard practices do not lend themselves

alone to determine tradeoffs and balancing of configurations for these types of

designs

– Advanced methodologies will be required to effectively improve efficiencies

Overall Objective

To explore the fuel-consumption performance of a parametrically variable

hull design running as a self-propelled vessel in calm water with realistic

operational constraints

– The design geometry is constrained in maximum global dimensions to legacy

PANAMAX

– Mass displacement (Δ) is a function of dimensions and cargo deadweight

– Minimum intact stability (GM) requirements and hydrostatic trim allowances

Implicitly Explored Design Features:

– Wave-making resistance attenuation with bulbous bows, entry angle, stern

shaping, shoulder shaping.

– Propeller design exploration (B-Series)

– Propeller, hull, shafting, and rudder interactions

Specific Objective

The goal is to find a family of optimal hull designs and propeller

parameters that minimize fuel consumption rates for the following

mission:

– 28,000 DWT Medium Range bulk carrier

– Twin screws

– Single skeg

– Constrained to legacy PANAMAX dimensions

– Installed two medium speed diesels

– In the follow operating conditions:

• Full Load: 28,000 DWT

• Ballast Load: 70% Heavy Condition (19,600 MT)

Performance considerations:

– Trim requirements

– Intact initial stability requirements (GMT)

– Available installed power and reduction gearing efficiencies

Problem Particulars

Design Exploration Studies leveraging modern simulation tools:

– Hull Modeling Software – MultiSurf by AeroHydro

– Hydrostatic Calculations – MultiSurf by AeroHydro

– Computational Fluid Dynamics – STAR-CCM+ by CD-adapco

– Pareto Optimization – HEEDS by CD-adapco

– Scalable Computation – High Performance Computing Cluster

Solution: Drive Product Innovation with CAE

Solution: Drive Product Innovation with CAE

2. Process Automation

3. Scalable Computation

4. Efficient Exploration 5. Sensitivity & Robustness

1. Validated CAE Models

m cores per node

n nodes

MultiSurf

Hull Modeling & Hydrostatics

STAR-CCM+

CFD Analysis

A parameterized hull model was developed in MultiSurf/Hydro 8.7,

developed by AeroHydro

– MultiSurf is a software suite used for the parametric design of 3D complex

objects involving freeform curves and surfaces, specializing in ship hull design

– Entire model is updated whenever underlying points, lines, or surfaces are

updated, and fairing tools allow surfaces to be faired and refined with

geometry updates

– Surfaces composing the hull body are durably joined, allowing subsequent

analysis packages to treat the generated hull as a “meshable” solid

1 - Validated CAE Models – MultiSurf

MultiSurf Hydro outputs of interest:

– Trim Overall (must be between -0.15 m and 1 m at Heavy load for a valid

design)

– GMT (must be greater than 0.3 m under both load conditions for a valid

design)

– Maximum Draft (must be less than 12 m under Heavy load to meet PANAMAX

requirements)

MultiSurf Hull Parametric Model outputs of interest:

– LCG (from both load conditions)

– VCG (from both load conditions) (constant)

– Center of flotation (ZCF)

– Hull Length

– Propeller outside diameter

– Propeller location (coordinates)

– Displacement weight

1 - Validated CAE Models – MultiSurf

For this study, full scale design simulations were conducted on a

longitudinally-symmetric half-domain using CFD analysis performed using

STAR-CCM+ v9.06.11

Roll and yaw variations were not considered, consistent with an

assumption that the hull should be optimized for even-keel, straight-

ahead navigation

Water conditions were assumed to be seawater (1025 kg/m3)

1 - Validated CAE Models – STAR-CCM+

Wrapper was used to seal co-planar hull surfaces and dynamically positioned and sized appendages

(skeg, rudder, shafting)

Surface meshing was accomplished using a local surface resolution size of 0.75 m globally with

refinement around curvature and appendages

Volumetric meshing involved an orthogonal 3D mesh that subdivides elements in the bow wave and wake

regions as well as the free surface, using the Trimmer mesher

Boundary layer was captured using the STAR-CCM+ prism layer mesher with an initial skin cell thickness

of 0.6 mm to properly capture near-wall viscous effects.

Model mesh sizes ranged between 2.5-3 million cells


Two load cases considered:

– Heavy load (28,000 ton deadweight): 16.5 knots

– Ballast condition (19,600 ton deadweight): 12.5 knots


Heavy Load:

16.5 knots at 28,000 ton deadweight

Ballast Load:

12.5 knots at 19,600 ton deadweight

Each design was evaluated by a self-propulsion simulation at the specified displacement and speed. The

propeller was free to turn at any RPM to produce the thrust to counteract the overall drag.

2nd

order segregated flow implicit unsteady solver was utilized with a fixed time step size tailored to the

length of the ship and it’s speed to provide a suitable Courant number

Turbulence was treated with the Reynolds-averaged Navier-Stokes (RANS) realizable K-epsilon turbulence

model with two-layer all-y+ wall treatment

Free surface of the water was treated using the volume of fluid (VoF) model

The vessel was treated as a dynamic fluid body interaction entity (DFBI) and placed in a global reference

frame, initialized at the desired run speed. The ship was free to trim and heave.

The propeller effects, pressure gradient and swirl, were accomplished using the Virtual Propeller model

based on open-water curves computed by published polynomials for B-Series (Bernitsas, 1981, U. of

Michigan)

1 - Validated CAE Models

Self-propelled tests were conducted using a propulsion element using the

Star CCM+ virtual disk model

– Marks all cells in a volume of space occupied by the propeller.

– Imparts torque and axial force to the fluid in those cells as if the propeller were

acting on them, accounting for the upstream and downstream flow conditions as a

propeller would.

– Requires the input of a propeller open water performance curves

– The propeller properties, such as diameter, blade count, and pitch ratio were input

into the STAR-CCM+ model and appropriate propeller curves generated for each

load condition

– STAR-CCM+ was able to choose the operating point based on the necessary

thrust and the measured velocity of advance of the propeller. The thrust of the

propeller was feathered to maintain the speed being investigated, and the program

automatically adjusted the propeller RPM on the fly.


3,200 timesteps performed

Resistance computed as the sum of the viscous and pressure forces acting

on all elements in the –x direction. Forces were averaged over the time history

once it stabilized

1 - Validated CAE Models

Heave:

Trim:

2 – Process Automation

MultiSurf


STAR-CCM+

CFD Analysis

MultiSurf


Hull Design Parameters

An MS Excel interface is used by HEEDS to drive the parameterized MultiSurf model using

the VBA API available within MultiSurf

The Excel file specifies variable values for a given design and calculates the applied weight

based upon the load case and beam and length characteristics

The VBA script is contained within a Macro in Excel which does the following steps:

– Initiates MultiSurf in the background

– Opens the baseline MultiSurf model

– Modifies the applied weight

– Reads in from the Excel worksheet the variable values and updates the hull shape accordingly

– Saves a new MultiSurf database for reference

– Exports an IGES file for STAR-CCM+ usage

– Executes Hydro

– Writes Hydro calculation results to a text file

– Writes outputs to text file for STAR-CCM+ usage

• Propeller coordinates

• Propeller outside diameter

• LCG

• VCG

• Length

• Displacement Weight



MultiSurf


STAR-CCM+

CFD Analysis

MultiSurf


MultiSurf


Hydrostatics Results File

Geometry IGES file Hull Design Parameters


MultiSurf


STAR-CCM+

CFD Analysis Hydrostatics Results File

MultiSurf



Geometry IGES file




STAR-CCM+

CFD Analysis

MultiSurf


STAR-CCM+



STAR-CCM+ is driven through a java script that reads in design

conditions from a text file along with the given hull geometry

– The hull geometry is passed by HEDS from MultiSurf in the form of an IGES

file

– The values for propeller coordinates, propeller outside diameter, LCG, VCG,

ZCF, Displacement Weight, and Length are passed from MultiSurf to STAR-

CCM+ by HEEDS for both load conditions through the design condition file

– Values for other variables dictating propulsion characteristics are supplied by

HEEDS to STAR-CCM+ through the design condition file

• Propeller number of blades

• Propeller pitch ratio

• Propeller blade area ratio

• Propeller handedness (left or right)


After the conditions and geometry are read-into STAR-CCM+ the propeller

performance curves are extrapolated and the simulations conducted :

– Heavy load (28,000 MT deadweight) @ 16.5 knots

– Ballast condition (19,600 MT deadweight) @ 12.5 knots

At the conclusion of the simulations, relevant outputs are written to a results text file

and the data stored by HEEDS for the design for both load cases

– Draft

– Displacement

– Speed

– Drag

– Effective Power

– Delivered Power

– Trim

– Heave

– RPM

Fuel rate is calculated for each load case by HEEDS utilizing the delivered power in its

calculations



STAR-CCM+

CFD Analysis

Hydrodynamic Results Geometry IGES file


Propulsive Design Parameters


STAR-CCM+

CFD Analysis

Hydrodynamic Results

MultiSurf


STAR-CCM+


Geometry IGES file Hydrodynamic Results


Geometry IGES file


Propulsive Design Parameters Propulsive Design Parameters


MultiSurf


STAR-CCM+


Geometry IGES file Hydrodynamic Results



HEEDS and Multi-Surf were performed using a single core of a 64-bit

Windows HP PC with an Intel Xeon 2.8GHz processor with 12 GB of RAM

– Average MultiSurf Simulation Time for Heavy Load case: 3 mins

– Average MultiSurf Simulation Time for Ballast Load case: 2 mins

STAR-CCM+ was run on 84-cores of a High Performance Compute

Cluster (HPC)

– Average STAR-CCM+ Simulation Time: 5.5 hours

3 – Scalable Computation

12 cores per node

7 nodes

HEEDS MDO has a robust, efficient, easy to use optimization search

technology called SHERPA

– One input parameter

• Number of Evaluations (budget)

• No tuning required

– Hybrid

• Blend of search strategies used simultaneously

• Global and local search performed together

• Leverages the best of all methods

– Adaptive

• Adapts itself to the design space

• Efficiently searches simple and very complicated spaces

• Very cost effective for complex problems

4 – Efficient Exploration

A dual stage approach was taken to optimize the bulk carrier (and

proprietary vessel for which this project was based)

Design Exploration Study 1: Optimization for Hydrostatics Only



MultiSurf



Geometry IGES file

A dual stage approach was taken to optimize the bulk carrier (and

proprietary vessel for which this project was based)

Design Exploration Study 2: Optimization for Hydrostatics and

Hydrodynamics

– Start with good hydrostatic design concepts from Design Exploration Study 1

to speed up the search process



Design Exploration Study 2: Optimization for Hydrostatics and Hydrodynamics

High Performing Design Concepts from Hydrostatics

Design Exploration Study 1: Optimization for

Hydrostatics Only

Variables: BEAM

14.75 m 16.155 m


Hydrostatics Only

Variables: STATION_10_X

210.85 m 294.13 m


Hydrostatics Only


20 m 172m

NOTE: Here STATION_4_X is set to 20 m


Hydrostatics Only


20 m 131.58m

NOTE: Here STATION_5_X is set to 172 m NOTE: STATION_4_X is designed semi-independently such that it is always < STATION_5_X


Hydrostatics Only

Variables: BULB_WIDTH

2.5 m 5 m


Hydrostatics Only

Variables: BULB_HEIGHT

BULB_0_Z (m) 8.5 m


Hydrostatics Only

23 High Performing Hydrostatic Design Concepts Identified


Hydrostatics & Hydrodynamics

Objectives (Pareto Optimization/Trade-off Study):

– Minimize: Fuel Rate (kg/hr) for Heavy Condition

– Minimize: Fuel Rate (kg/hr) for Ballast Condition

Constraints:

– Maximum Draft (Full load case) < 12 m

– -0.15 m < Trim Overall (Full load case) < 1 m

– GMT (Full load case) > 0.3

– GMT (Ballast condition) > 0.3

– Propeller RPM (Heavy load case) <110

– Propeller RPM (Ballast condition) <110

By Varying:

– Same 19 geometric variables as with previous optimization

– PROPELLER_#_OF_BLADES= 4 or 5

– 0.5 < PROPELLER_PITCH_RATIO < 1.4

– 0.3 <PROPELLER_BLADE_AREA_RATIO < 0.77

– PROPELLER_HANDEDNESS = RIGHT OR LEFT (+1 or -1)


Hydrostatics & Hydrodynamics

Baseline Design:

– Fuel Rate (1) Heavy Condition = 1377.8

– Fuel Rate (2) Ballast Condition = 830.42

– Maximum Draft (Heavy load case) = 11.44 m (meets design criteria)

– Trim Overall (Heavy load case) = -1.37 m (DOES NOT MEET DESIGN CRITERIA)

– GMT (Heavy load case) = 3.397 m (meets design criteria)

– GMT (Ballast condition) = 4.063 m (meets design criteria)

– RPM (1) Heavy Condition = 110.88 (DOES NOT MEET DESIGN CRITERIA)

– RPM (2) Ballast Condition = 90.64 (meets design criteria)

23 good hydrostatic concepts identified from Design Exploration Study 1

are used to “kick start” Design Exploration Study 2

120 Pareto optimization evaluations performed using SHERPA


Hydrostatics and Hydrodynamics


Design Exploration Study 2: Optimization for Hydrostatics and Hydrodynamics

High Performing Design Concepts from Hydrostatics

Feasible

Infeasible

Design Exploration Study 2

MultiSurf

Hydrodynamic Results

Geometry IGES file


SHERPA



STAR-CCM+



Feasible

Infeasible

Baseline

Injected

Baseline Injected



Feasible

Infeasible

Baseline

Injected

Pareto Optimal Solutions (Family of Ship Designs)







21 % reduction in Heavy load case fuel consumption

7% reduction in Ballast load case fuel consumption














1 % increase in Heavy load case fuel consumption





2 % increase in Heavy load case fuel consumption




Responses:

Variables:

Variables:

Feasible Infeasible Pareto Set



Responses:

Variables:

Variables:




Responses:

Variables:

Variables:












The Effect of Drag

Band in fuel rates for a given drag observed

Family of designs are on lower fuel rates of ballast condition band but not

necessarily on the heavy condition band due to the tradeoffs between the

two

Feasible

Pareto

The Effect of Propulsive Efficiency

Propulsion also affects drag

Feasible

Pareto



Feasible

Pareto



Feasible

Pareto



Feasible

Pareto

The Pareto front identifies high performing design candidates applicable for

a trade-off analysis. Specific operating conditions determine the actual best

design.

The case study will make the following operating conditions and fuel

situations.

– 60% of the time at sea (219 days)

– 60% at Full Displacement & 40% at Ballast Displacement when at sea

• 30% of operating time in Sulphur Emissions Control Areas (ECA)

– 0.1% Suphur, Marine Gas Oil (LSMGO) @ $550USD/MT

• Operations in ECA

– 3.8% Sulphur, 180 cSt, Intermediate Fuel Oil (IFO180) @ $350USD/MT

Case Study

Design Fuel Consumption [kg/hr]

Ratio Total Annual Consumption

[MT]

Annual Bunkering

Cost Savings

Full Load Ballast

Baseline 1377.8 830.4 1.7 6090.9 $2,497,265 - - -

101 1087.9 773.4 1.4 5056.8 $2,073,290 $423,975

46 1147.8 756.7 1.5 5210.7 $2,136,373 $360,892

118 1237.6 739.1 1.7 5456.8 $2,237,273 $259,992

117 1391.3 721.2 1.9 5903.9 $2,420,583 $76,682

86 1409.3 681.5 2.1 5877.0 $2,409,573 $87,692

Case Study

Minimizing Full Load consumption rate appears to have the greatest

effect on the annual bunkering cost

– Best design reduces consumption by 1e6 kg of fuel oil

Fully automated design optimization of a medium range bulk carrier was

done to find Pareto front to allow for trade-off studies for various operating

conditions

– Optimization implicitly balanced hull particulars, bow & stern shaping and

propeller matching.

– HEEDS efficiently explored design concepts that may have been overlooked in

a manually specified parametric sweep

Summary

Acknowledgements

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