Chevron plate heat exchanger optimization using efficient approximation-assisted multi-objective optimization techniques

Abstract

This article presents a comparison between different multi-objective optimization approaches that can be used to efficiently optimize the design of different thermal systems and components. Plate heat exchanger optimization is taken as case study to compare the different optimization techniques. The plate heat exchanger flow channel geometry is optimized to maximize the thermal-hydraulic performance of the heat exchanger. The thermal-hydrodynamic characteristics of single phase turbulent flow in chevron-type plate heat exchangers with sinusoidal-shaped corrugations have been analyzed using a commercially available computational fluid dynamics tool. The computational domain consists of a corrugation channel, and the simulations adopted the shear-stress transport κ-ω model as the turbulence model. The analysis of even a single design is computationally expensive, and hence, approximation techniques are used to speed up the optimization process. Exhaustive search, offline approximation-assisted optimization, and online approximation-assisted optimization are compared to optimize plate heat exchanger design. For both approximation techniques (offline and online), design optimization is performed using the multi-objective genetic algorithm based on metamodels that are built to represent the entire design space. In offline approximation, globally accurate metamodels are built, which requires adding samples in the entire design space. However in online approximation-assisted optimization, samples are added just to improve metamodel performance in the expected optimum region. Approximated optimum designs are verified using computationally expensive actual computational fluid dynamics simulations. Finally, a comparison between exhaustive search and offline/online approximation-assisted optimization is presented with guidelines to apply both approaches in the area of heat exchanger design optimization. The methods presented in this article are generic and can be applied to optimize different types of heat exchangers, electronic cooling devices, and other thermal system components.