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