Historically, thermal/fluid modeling began as a means of validating and sometimes correcting passively cooled designs that had been proposed by nonspecialists in heat transfer and fluid flow. As dissipation fluxes have risen, and as air cooling reaches the limits of its usefulness, involvement of thermal engineers is required earlier in the design process. Thermal engineers are now commonly responsible for sizing and selecting active cooling components such as fans and heat sinks, and increasingly single and two-phase coolant loops.
Meanwhile, heat transfer and fluid flow design analysis software has matured, growing both in ease of use and in phenomenological modeling prowess. Unfortunately, most software retains a focus on point-design simulations and needs to do a better job of helping thermal engineers not only evaluate designs, but also investigate alternatives and even automate the search for optimal designs.
This paper shows how readily available nonlinear programming (NLP) techniques can be successfully applied to automating design synthesis activities, allowing the thermal engineer to approach the problem from a higher level of automation. This paper briefly introduces NLP concepts, and then demonstrates their application both to a simplified fin (extended surface) as well as a more realistic case: a finned heat sink.