Comparison of Shape Optimization Methods for Heat Exchanger Fins Using Computational Fluid Dynamics

Inverse design techniques are one way to leverage advances in 3D printing, artificial intelligence, and computational resources to achieve increased performance of heat exchangers. Two optimization tech-niques (genetic algorithm and particle swarm) and three geometry representations (binary level set, com-posite Bezier, and free form deformation) are used to increase the heat transfer and reduce the pressure drop of a heat exchanger fin. After running 210,810 OpenFOAM simulations, results indicate that a signif-icant performance increase of the fin can be realized in less than 48 hrs, allowing for such a process to be integrated in traditional design processes. The best design increased the performance of the objective function, compared to the baseline rectangular geometry by 75%. A custom distributed infrastructure was built, allowing for all methods to reach 95% of the final objective values in a little over 4 hrs, handling 1674 OpenFoam simulations per hour. Published by Elsevier Ltd.

Automated summary

Inverse design techniques utilize advances in 3D printing, artificial intelligence, and computational resources to improve the performance of heat exchangers. By using genetic algorithm and particle swarm optimization techniques, as well as three geometry representations, the heat transfer efficiency of a heat exchanger fin can be increased while reducing pressure drop. The results of over 210,810 OpenFOAM simulations show that significant performance improvements can be achieved in less than 48 hours, allowing for integration into traditional design processes. The best design increased the objective function's performance by 75% compared to the baseline rectangular geometry. Published by Elsevier Ltd.