Multi-objective optimization for assisting the design of fixed-type packed bed reactors for chemical heat storage

Abstract

• Multi-objective optimization applied on packed bed reactor for chemical heat storage. • Simultaneous maximization of heat storage density, rate and exergy efficiency. • Optimal design of thickness, reaction condition and fabrication of composite material. • High thermal contact conductance is recommended when utilizing enhanced composites. • Limitations on the packed bed’s thickness for achieving high exergy efficiency. The enhancement of heat transfer in packed bed reactors is essential for the practical application of chemical heat storage technology. This work presents the first attempt to utilize a multi-objective optimization algorithm for the design of packed bed reactors comprising heat-transfer-enhanced materials as an alternative to the insertion of metallic fins. A numerical model for the simulation of heat transfer with chemical reaction in a flat packed bed reactor comprising a composite of Ca(OH) 2 (reagent) and a silicon-impregnated silicon carbide foam (thermal conductivity enhancer) is developed. The genetic algorithm applied to the model aims to optimize four design parameters: the effective thermal conductivity of the packed bed material, its thickness, the thermal contact conductance, and the heat supply temperature. As a result, it determines the optimal trade-off between heat storage density, average heat storage rate and exergy efficiency. Under the assumptions of the model, the Pareto solution indicates that the optimal foam porosity is the interval 70-80%, while the optimal thickness is the interval 20-70 mm. The analysis suggests the necessity to improve the thermal contact conductance in packed bed reactors and, for achieving higher exergy efficiency, thinner (modular) packed beds result better performing than thicker ones.