Design of ships in waves using CAESES and SHIPFLOW - FRIENDSHIP … · 2019. 10. 2. · Shape...
Transcript of Design of ships in waves using CAESES and SHIPFLOW - FRIENDSHIP … · 2019. 10. 2. · Shape...
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Design of ships in waves using CAESES and SHIPFLOW
presented byLeif Broberg FLOWTECH International
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Content
• Overview of the tools• Case study
• Optimizations• Cross-check
• Summary
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Overview of
SHIPFLOW and CAESES
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Integration of tools
Shape variationsOptimization methodsResource management
m a d e b y F R I E N D H S H I P S Y S T E M S
• Grid Generation• Flow simulations• Result processing
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The SHIPFLOW system
Flow solvers• BASIC
• XPAN potential flow solver. wave pattern, wave resistance, pressure, sinkage&trim
• XBOUND thin boundary layer method surface streamlines, friction drag, b.l. thickness
• Best suited for wave resistance optimizations
• RANS• XCHAP RANS equations solver
flow field, viscous resistance, self-propulsion, free-surface• Applied successfully to delivered power optimizations
• MOTIONS• time dependent potential flow solver• motions and added resistance in waves
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Optimization Strategy - Efficient choice of solvers
XPAN
• Wave resistance• forebody optimization
XCHAP
• Delivered power• aftbody optimization
MOTIONS
• Added resistance in waves • forebody optimization
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Case Study
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Case study provided for the NJTF optimization workshop 2018
• Particulars:• Loa(m) 322.5 m• Lpp(m) 314.6• B(m) 52.5• T(m) 18.1• Displacement (m3) 252045.4• Propeller diameter: 9.6m
• Conditions:• Vs=15kn
• Optimization target:• Resistance
• Constraints:• Lpp, ship width B, draught T remain unchanged;• Lcb (Lpp%) ≥ 3%• Displacement change less than 1500m3;
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Optimization Strategy
XPAN
• Wave resistance• forebody optimization
XCHAP
• Viscous resistance • aftbody optimization
MOTIONS
• Added resistance in waves • forebody optimization
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Added resistance in waves optimization
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Added resistance in waves optimization with MOTIONS
• Baseline analysis and target conditions• Transformation and design variables• Optimization process• Comparison of variants
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Added resistance in waves optimization with MOTIONS
• Baseline analysis
Target conditions
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Added resistance in waves optimization with MOTIONS
• Transformation and design variables
VARD Bow*
*) patented by VARD, Norway
Surface Delta Shift for fullness above DWL
Constant Loa
Constant Lpp
Transformations of stem and flare shape :- longitudinal position- vertical position- fullness
Surface Delta Shift for stem shape control
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Added resistance in waves variant comparison
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SHIPFLOW MOTIONS
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Added resistance in waves optimization with MOTIONS
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Averaged pressure distribution (over one wave period) - bow
optimizedbaseline
Lowered pressure
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Averaged pressure distribution (over one wave period) – stern
optimizedbaseline
No noticable difference
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Added resistance in waves: λ= 0.6Lpp
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Added resistance in waves variant comparison
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KCS results - comparison with experiments• experimental data taken
from Tokyo 2015 Workshop summary
• Average of FORCE, IIHR and OU measurements including standard deviation bars
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KVLCC2 results - comparison with experiments
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Optimization Strategy
XPAN
• Wave resistance• forebody optimization
XCHAP
• Viscous resistance • aftbody optimization
MOTIONS
• Added resistance in waves • forebody optimization
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Wave resistance optimization
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Transformation method – Delta Shift
Delta Curve
Control points,3 design variables
Vertical deformation of Delta curve results in longitudinal translation of stations
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Optimization history
N-M Simplex quickly finds the ”right” direction
1h
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Waterline shape – deviation and curvature
optimized
Waterline
baseline
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Forebody – Displacement correction
Surface Delta Shift
waterline
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Forebody – Displacement correction
waterline
Transverse deformation of Delta surface results in transverse station shape modification
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Optimization Strategy
XPAN
• Wave resistance• forebody optimization
XCHAP
• Viscous resistance • aftbody optimization
MOTIONS
• Added resistance in waves • forebody optimization
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Viscous resistance optimization
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Shape variations template (used previously for JBC)
Keel line profile
Skeg width
Bilge radius
Section fullness
1. Copy / Paste transformations to the new project2. Adjust for the new geometry
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Optimization method – NSGA2
Large population size and number of generations for more design variables
4 design variables
RT as an objective
Displacement constraint
For GA it is possible to run whole generation at once. After 8-10 generations the process is well converged. Total optimization time can be reduced to 6h.
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Optimization method – NSGA2
Baseline aftbody
Quickly visible results due to:- Well designed
transformation- Carefully
selected design space bounds
6h** - on a 10-node cluster
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Optimization Strategy
XPAN
• Wave resistance• forebody optimization
XCHAP
• Viscous resistance • aftbody optimization
MOTIONS
• Added resistance in waves • forebody optimization
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Cross-check of the variants with VOF
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Cross-check of the variants with VOF – resistance - RTm
-1.5% -1.5%
-4%
Optimized bow
Optimized bow +Optimized added resistance in waves (above free surface only)
Optimized bow +Optimized aftbody
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Cross-check of the variants with VOF – wave pattern
baseline
optimized
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Comments and suggestions
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Delivered Power - model scale calculations
Resistance
Delivered Power
Optimizing high Cb ships for resistance may lead to poor propulsive efficiency!
-4%
+1.5%
Hull optimized for minimum RTm
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Suggestion: Use PD not RT as your objective
Resistance
Delivered Power
Hull optimized for minimum RTm
Hull optimized directly for minimum Pdm
* - JBC optimization case
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Comments• Optimized hull form in 1 day!• CAESES and SHIPFLOW is an excellent environment for
hydrodynamic optimizations• Partially parametric modelling used in CAESES is flexible, easy to
apply and gives good results• SHIPFLOW MOTIONS is feasible to use for shape optimization for
minimum added resistance in waves• SHIPFLOW RANS aftbody optimization is possible thanks to very
fast solver• We must optimize full block coefficient hull forms for minimum
delivered power using self-propulsion computations.
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Thank You