star-ccm+ / optimate -...
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STAR-CCM+ / Optimate Kynan Maley
Description
Process
Study examples
Token based licensing
Summary
Optimate
STAR-CCM+ add-on
Easy to use!
Panel to setup multiple STAR-CCM+ analyses
– Scriptless Automation
– Leverage STAR-CCM+ design space
Five available study types
– Design Exploration
– Design of Experiment
– Robustness
– Optimization
– Pareto Optimization
Setup is all done within STAR-CCM+ environment
Optimate performs the following
– Creates all necessary scripting
– Submits and monitors jobs
– Collects the simulation data
– Post-process the study
Optimate
Design Exploration
– Supplied inputs
– Test replication
Optimization
– Global and local design space exploration
– Identify important variables
– Pareto optimization
• Identify set of optimal designs
– Uses SHERPA algorithm
Design of Experiment
– Local design space exploration
– Response surface models
Robustness Analysis
– Characterize design due to input variation
– User supplies probability distribution
Study Types
3D-CAD Design Parameters
– Any scalar quantity
– Translation Components
Motions
– Rotation rate
– Translational velocity
Part Swapping
– CAD parts
Region Physics Values
– Volumetric heat source
Mesh Settings
– Base size
Field Functions
– User scalar field functions
Boundary Physics Values
– Velocity magnitude
– Mass flow rate
– Static temperature
– Static pressure
– Total temperature
– Total pressure
– Mach number
– Flow angles (modifies ‘wind’ CS)
– Mass fractions
– Wall roughness
– Turbulence scalars
– Thermal scalars
Currently Supported Variables
Problem
External aerodynamics
Imported CAD combined with 3D-CAD model
Goals
Investigate mirror placement effects on vehicle aerodynamics
Modify position of side view mirrors
Design Exploration Example
Design Exploration Example
Design Exploration Post-processing
Joint Common Missile
External Aerodynamics
Design Exploration
Pipe Flow
– Investigate blockage size on pressure drop
Blockage created in 3D-CAD
– Thickness
– Depth
Latin hypercube sampling
Ran 10 cases
Design of Experiment Example
Design of Experiment Example
Proprietary SHERPA / MO-SHERPA algorithm
Efficient
– Fewer evaluations required
– Rapid setup
– No iterating to find best method
– Solution first time more often
Easy to use:
– Simply define problem and number of evaluations
– No tuning
– No optimization expertise required
Robust
– Finds better solutions more often for broad classes of problems
Optimization Algorithm
Utilize power of MO-SHERPA algorithm
– Better solutions in fewer iterations
Electronics cooling
– Conjugate heat transfer
Pin configuration parameterized
– Spacing
– Height
– Diameter
– Taper
Optimization objectives
– Minimize pressure drop
– Minimize chip temperature
Ran 100 cases
Pareto Optimization Example
Pareto Optimization Example
Enables many concurrent jobs all derived from same parent sim file
STAR-CCM+/Optimate
– Design Exploration, Design of Experiment, Robustness modes
STAR-CCM+/Optimate+
– All modes (including Optimization and Pareto Optimization)
STAR-CCM+/Power Tokens
– Used only during run
– Counts as STAR-CCM+ Session or STAR-HPC
– ex. 100 tokens
• 1 concurrent job on 100 cpus, 10 concurrent jobs on 10 cpus, 100 concurrent jobs
on 1 cpu
Optimate Licensing
Knowledge Database
– support.cd-adapco.com
– Evaluation Mode Demonstration
– Pareto Optimization Mode Demonstration
Learn More
Optimate is a STAR-CCM+ add-on
Five available study types
– Design Exploration
– Design of Experiment
– Robustness
– Optimization
– Pareto Optimization
Optimate licensing scheme
– Designed to run lots of similar jobs
concurrently
Tutorial videos on Knowledge Base
Available now
Summary
Thank you