Geometry Optimization of an Electronics Cooling Case Aaron Godfrey, - - PowerPoint PPT Presentation

geometry optimization of an
SMART_READER_LITE
LIVE PREVIEW

Geometry Optimization of an Electronics Cooling Case Aaron Godfrey, - - PowerPoint PPT Presentation

Optimate+ Case Study: Flow and Geometry Optimization of an Electronics Cooling Case Aaron Godfrey, Application Engineer 03/20/2013 Outline Problem Description Geometry Parameterization Mesh Settings Results Problem Statement


slide-1
SLIDE 1

Optimate+ Case Study: Flow and Geometry Optimization of an Electronics Cooling Case

Aaron Godfrey, Application Engineer – 03/20/2013

slide-2
SLIDE 2

Problem Description Geometry Parameterization Mesh Settings Results

Outline

slide-3
SLIDE 3

Problem Statement – Electronics Cooling Optimization

Electronics equipment cooling (representative of customer projects) Each Ball Grid Array (BGA) to be fitted with one aluminum heat sink Maximum temperature on BGA chips of 85 C Minimize heat sink mass

BGA’s

slide-4
SLIDE 4

Optimate+ = STAR-CCM+ add-on available through user portal

– Creates all necessary scripting – Submits and monitors jobs – Collects the simulation data – Post-process the study

HEEDS = Software developed by our partner Red Cedar Technology that Optimate+ couples with

– Allows access to DOE, optimization, and post-processing capability

SHERPA = Adaptive global/local optimization algorithm from Red Cedar Technology

Terminology

slide-5
SLIDE 5

Geometry Parameterization – Casing

Casing CAD parameterization

– Exhaust Translation

slide-6
SLIDE 6

Geometry Parameterization – Heat Sinks

Heat sink CAD parameterization – Pin Height – Ellipse Major Radius – Ellipse Minor Radius – X Fill Percentage – Y Fill Percentage – Radii Ratio

slide-7
SLIDE 7

Pipeline Mesh Operations – New in 8.02

slide-8
SLIDE 8

Mesh

Polyhedral mesh with body fitted prism layers on all solid/fluid interfaces Conformal interfaces between all solid/solid, solid/fluid, and fluid/fluid contacts Mesh sizes ranged from 1.5M cells to 9M cells – this is entirely a function of heat sink design

slide-9
SLIDE 9

Optimization algorithm: SHERPA Objective Function: Min DeltaT, Min Mass with 3:1 weighting 183 Designs with 8 parallel runs on 8 cores each

– 64 cores for 4 days

Optimate+ Project Settings

slide-10
SLIDE 10

Results – Design Iterations

slide-11
SLIDE 11

Results – Objective and Performance History

slide-12
SLIDE 12

Results – Top 40 Designs

slide-13
SLIDE 13

Results – Parallel Plots

slide-14
SLIDE 14

Results – Parallel Plots

All Designs 100 Best Designs 50 Best Designs 25 Best Designs

slide-15
SLIDE 15

SHERPA identified Optimum:

– Exhaust Translation near minimum – Ellipse Major Radius at maximum – Ellipse Minor Radius at minimum – X Fill Percentage at maximum with some spread (expected) – Y Fill Percentage at minimum – Pin height at maximum – Radii Ratio towards maximum with significant spread

Results – Optimum Design

slide-16
SLIDE 16

Results – Temperature Isosurface

slide-17
SLIDE 17

Results – Boundary Heat Flux

slide-18
SLIDE 18

Results – Line Integral Convolution

slide-19
SLIDE 19

Results – Line Integral Convolution

slide-20
SLIDE 20

Results – Streamlines

slide-21
SLIDE 21

Possible Alternative Analysis

Complete multi-objective optimization using MO- SHERPA would allow for full resolution of Pareto front between two objectives Additional analysis of any of the three local optima found by SHERPA using the DOE capability inside Optimate+ could give more insight into trends and relationships Expanding design space where possible for parameters where the optimum value was at the min or max allowed

slide-22
SLIDE 22

Ruben Bons – CD-adapco, Electronics Sector Manager

Mike Dombroski – CD-adapco, Application Engineer and Developer of

Optimate(+) Matt Janeway – CD-adapco, Application Engineer Marcus Rademacher – Red Cedar Technology, Sr. Engineering Analyst

Recognition

slide-23
SLIDE 23

Questions?