An Experimental Assessment of Computational Fluid Dynamics Predictive Accuracy for Electronic Component Operational Temperature

Abstract

The flow modeling approaches employed in Computational Fluid Dynamics (CFD) codes dedicated to the thermal analysis of electronic equipment are generally not specific for the analysis of forced airflows over populated Printed Circuit Boards. This limitation has been previously highlighted [1], with component junction temperature prediction errors of up to 35% reported. This study evaluates the predictive capability of candidate turbulence models more suited to the analysis of electronic component heat transfer. Significant improvements in component junction temperature prediction accuracy are obtained, relative to a standard high-Reynolds number k-e model, which are attributed to better prediction of both board leading edge heat transfer and component thermal interaction. Such improvements would enable parametric analysis of product thermal performance to be undertaken with greater confidence in the thermal design process, and the generation of more accurate temperature boundary conditions for use in Physics-of-Failure based reliability prediction methods. The case is made for vendors of CFD codes dedicated to the thermal analysis of electronics to consider the adoption of eddy viscosity turbulence models more suited to board-level analysis.

Application of numerical analysis to the optimisation of electronic component reliability screening and assembly processes

“…[16,20]. The variation in accuracy with airflow velocity possibly reflects changes in the flow conditions, experimentally visualised in [13,23], to which the flow models display different sensitivity. Although not presented due to space constraints, excellent agreement was also obtained between measured and predicted component-PCB surface temperature profiles in free convection conditions, both in the span-wise and stream-wise airflow directions [13,24].…”

“…For the transient analyses, non-uniform temporal grids were applied having highest density in the time intervals where high rates of temperature change were experimentally recorded on the test assembly. These grids were constructed using time steps ranging from 3 ms to 5 s. The solutions obtained were verified to be both temporal and spatial grid independent [13].…”

“…As the component and board models are based on nominal material thermo-physical properties, prediction sensitivity to potential uncertainties in critical parameters was assessed by parametric analyses and found to be minimal, showing that the models were robust [13].…”

“…To avoid emissivity variations, the component and PCB surfaces were sprayed with a uniform layer of matt black paint having a uniform emissivity of 0.92 in the spectral range considered [13].…”

“…These measurements were made using an AGEMA infrared Thermovision 880 system operating in the 8-12 m spectral range, having a specified accuracy of ±2 • C or 2% and calibrated to ±1.4 • C [13].…”