<p>The Stirling heat engine is known to be an efficient external heat engine in converting thermal energy to work as well as operating as a heat pump. This two-way energy transfer may provide an advantage in converting excess wind and solar energy into heat and then utilizing the same apparatus to retrieve the stored thermal energy and convert it to available power. Although this approach of thermal energy storage may not be optimal in terms of efficiency, it takes advantage of excess energy that may be otherwise discarded. This study investigates the use of automatic topology optimization approaches to increase the performance of Stirling Engines as heat engines and heat pumps. The theoretical limit of the Stirling Engine is known to approach the Carnot efficiency, the best possible efficiency. However, this efficiency is not possible in practical applications. With the development of 3D printing methods for metals and adjoint CFD topology optimization solvers there exist a new design paradigm to develop the best performing shape regarding the conjugate heat transfer from this engine. This study investigates the use of topology optimization within a commercial software ANSYS via the adjoint solver and Fluent CFD components to develop the most efficient shapes for heat transfer at the cold and hot reservoirs. These preliminary heat sink shapes are then modified to take into account practical manufacturing available in metal 3D printing. In particular, the study utilizes a computational fluid dynamic model along with an adjoint solver to couple the solid heat sink shape to the complex fluid convection. The results of the adjoint method are compared to parametric optimization based on governing equations. The results indicate the unique shape from topology optimization for improving the natural convection is better for the adjoint method than the parametric optimization because the parametric optimization is limited to traditional manufacturing for heat sinks. The simulations were performed for sensible heat transfer of thermal energy from a liquid (water) thermal reservoir to a gas (air) reservoir. Air is also utilized as the working fluid in the Stirling engine and is also modeled by the computational fluid dynamic simulation utilizing a moving mesh method.</p>

Adjoint Optimization of Heat Transfer Within a Stirling Engine

Paper Proceedings: https://asmedigitalcollection.asme.org/POWER/POWER2021/volume/85109

ASME 2021 Power Conference (POWER2021)

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