Abstract
We provide an algorithm to optimizing the geometry of an array of heat sinks (fin height, fin spacing, etc.) in, e.g., a blade server, which is prohibitively long task using computational fluid dynamics (CFD). First, banks of CFD simulations are run to precompute dimensionless flow and thermal resistances (Poiseuille and conjugate Nusselt numbers) as a function of dimensionless heat sink geometry, thermophysical properties, and external parameters. These precomputed CFD results are embedded in Flow Network Models (FNMs) in the form of look-up tables. This preserves much of the accuracy of CFD and the speed of FNM. The FNMs are, in turn, embedded in a multivariable optimization algorithm (MVO). Our hybrid numerical algorithm is provided, and we exercise it for an example problem.
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