Thermal-economic optimization design of shell and tube heat exchanger using an improved sparrow search algorithm

Abstract

Optimal design of heat exchangers is challenging, since complex non-linear relationship exists among the various design parameters. This study aims to construct a full-dimensional thermal-economic model for shell-and-tube heat exchanger using two commonly (i.e., Kern and Bell-Delaware) methods based on Logarithmic-Mean-Temperature-Difference (LMTD) or ε-Number-of-Transfer-Units (ε-NTU) method and proposes a novel solving mechanism based on improved sparrow search algorithm to achieve thermal-economic optimization design of heat exchanger. The improved method organically combines nonlinear gradient descent weight factor, elite reverse strategy, selection-mutation operator to maintain population diversity, enhance convergence speed and avoid being stuck in local optima. Firstly, the constructed model’s accuracy is verified by numerical analysis. Then, the improved sparrow search algorithm is applied to four examples after algorithm parameter tuning, and the results show that the area decreases by 15.62%∼49.30% and total annual cost is reduced by 27.93% compared to the literature. It can also identify feasible solutions at a lower total cost than the metaheuristic method, with reductions of 7.56%∼59.42%(Kern) and 6.26%∼60.19%(Bell-Delaware). Moreover, a multi-objective optimization algorithm is obtained by adding fast non-dominated sorting mechanism and archival gene pool, and the superiority is verified by standard test functions. Finally, a multi-objective optimization scheme with the higher effectiveness-economic benefit is conducted to achieve cost-effectiveness tradeoff for two real-world cases. The results show that total cost of the most economic-efficient scheme decreases by 53.73% and effectiveness increases by 2.33%, while the runtime decreases by 35%. Furthermore, sensitivity analysis of effectiveness and total cost varying with crucial variables is performed and discussed.