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 – 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 BGA’s chips of 85 C Minimize heat sink mass

Terminology 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

Geometry Parameterization – Casing Casing CAD parameterization – Exhaust Translation

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

Pipeline Mesh Operations – New in 8.02

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

Optimate+ Project Settings 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

Results – Design Iterations

Results – Objective and Performance History

Results – Top 40 Designs

Results – Parallel Plots

Results – Parallel Plots 100 Best Designs All Designs 50 Best Designs 25 Best Designs

Results – Optimum Design 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 – Temperature Isosurface

Results – Boundary Heat Flux

Results – Line Integral Convolution

Results – Line Integral Convolution

Results – Streamlines

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

Recognition 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

Questions?