Investigation of Data Mining Method for Thermal-Fluid Simu-Lation Results Based on Pressure Difference Between Front and Back Sides Using Medial-Surface and Its Application to Thermal Design Problems

Abstract

A data mining method is proposed for extracting feature regions and for suggesting design candidates from large-scale Computational Fluid Dynamics (CFD) results. The detected regions in this method are the regions where the pressure difference between the front and back sides is large. We introduce a medial-surface used in the structural analysis for the thin parts as an evaluation surface in order to apply complicated geometries, which have curved surfaces, holes, ribs, and steps. We applied this method to the laser diode (LD) cooling problem in optical disc drives, and the following results were obtained. (1) Three featureregions are extracted from the CFD results. (2) Two of three regions were effective and were consistent with the actual product design.