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Optimization: Tools, Capabilities, Advantages, and Examples

Siemens Pioneer Siemens Pioneer
Siemens Pioneer

HEEDS

  • Stand alone optimization software
  • Advantages:
    • Proven to find better designs, faster in comparison to other standard optimization algorithms because MO-SHERPA uses a bend of these searching techniques simultaneously
    • MO-SHERPA takes the guess work out of choosing an algorithm and adjusting tuning parameters (SHERPA uses no tuning parameters)
    • Connects to Nastran, Ansys, Abaqus, LS--‐Dyna, ADAMS, MATLAB, NX, mainstream CAD tools, Excel, and in house codes.
    • Allows both discrete and continuous variables in the same problem, these can be independent or dependent on other quantities.
    • Requires no model simplification or surrogate models
    • Supports collaborative optimization
    • No black box optimization: users can inject intuition within the optimization cycles to enhance efficiency.
  • Study types:
    • Automated Design Evaluations
    • Design Sweeps
    • Design of Experiment (DOE)
    • Robustness Analysis
    • Optimization:
      • Single-objective (or linearly weighted multi-objective)
      • True multi-objective (Pareto Optimization)
    • This product provides users access to the SHERPA and MO-SHERPA search algorithms developed by Red Cedar Technology

Design manager

See:  file:///C:/Users/cd6inq/Downloads/STAR_CCM_Design_Manager_Spotlight_Customer_Presentation.pdf

 

Adjoint flow solver

  • Automatically included in STAR-CCM+ (no add on needed), uses adjoint solver (and mesh morphing if needed)
  • Focused on FINE TUNING OPTIMIZATION
  • Tutorial included in the user guide for three dimensional dual element wing, down force

 

Example: Heat Sink

This example shows how STAR-CCM+ can enable you to accurately and easily explore the design space for hundreds of heat sinks:

http://www.cd-adapco.com/webinar/heat-sink-optimization-using-simulation-entire-operating-range

 

Contents:

Setup of simple heat sink simulation in STAR-CCM+

15:40-21:30 (5 min 50 seconds)

 

Setup of heat sink optimization case

21:30-25:25 (4 min 55 seconds)

 

Optimization considered designs and results

25:25-33:00 (7 min 35 seconds)

 

Design sweep of heat sink with alternating number of fins

33:00-34:40 (1 min 40 seconds)

 

Results of electronics cooling with fan/vent positioning and heat sink configurations

34:40-35:40 (1 minute)

 

 

Example: Turbine Blade Cooling

Hole position and diameter is explored in a conjugate heat transfer simulation of a turbine blade to find the best performing blade (lift) that we can get under 650K.

https://www.youtube.com/watch?v=uQ10hqpjs4M

 

Results:

10000 cell mesh solves in 30 seconds on 2 cores.

60 design iterations were automatically tested.

2% increase in lift

4% reduction in maximum solid temperature

Removal of one cooling hole (reduces manufacturing cost and improves reliability)

 

This demonstration will show you:

-The STAR-CCM+ pipeline for automated simulation

-How to find the best family of designs with Optimate+

-Accurate heat transfer through conformal meshing