Adaptive optimization decision system for plate-fin heat Exchangers: An integrated approach to enhancing efficiency and performance

作者：Na Sun, Shuai Zhang, Nan Li, Zijian Li, Meng He, Zhengchun Shen, Ke Wang, Xiaoyong Guo, Wen‐Quan Tao · 发表于：Case Studies in Thermal Engineering · 年份：2025 · DOI：10.1016/j.csite.2025.106619 · 被引用次数：3 · 研究领域：Heat Transfer and Optimization、Metaheuristic Optimization Algorithms Research、Advanced Multi-Objective Optimization Algorithms

Cross-flow Plate-Fin Heat Exchangers (PFHEs) are crucial in industries like new energy vehicles and data centers . This study presents a self-adaptive optimization framework to improve PFHE performance, addressing energy challenges and aiding industry progress. The framework includes four modules: problem formulation, global sensitivity analysis (GSA), optimization (single- and multi-objective), and decision-making. The GSA module uses the Sobol method to evaluate the impact of design variables on performance. The optimization module employs the Newton-Raphson-based optimizer (NRBO) and the multi-strategy improved grey wolf optimization algorithm (MIGWO). MIGWO features a dimension learning-based hunting strategy and variable scale learning factor, enhancing search capabilities. The decision-making module applies Entropy-TOPSIS and Entropy-VIKOR for selecting Pareto solutions , with customizable weights. Applied to a real cross-flow PFHE, the framework optimized seven key parameters identified by GSA. MIGWO outperformed previous studies in accuracy and efficiency, while NRBO achieved nearly equivalent results. Total Annual Cost was reduced by 86.36 % (NRBO) and 86.86 % (MIGWO), and heat exchanger area by 25.58 % (NRBO) and 26.28 % (MIGWO). Multi-objective optimization showed a 10–40 % decrease in TAC and a 0–5 % increase in effectiveness for the most economic-efficient scheme. This user-friendly framework provides a reliable design process, reducing uncertainties for inexperi...