Multi-objective optimization-based design of fin parameters for waste heat recovery equipment

With the intensifying global energy crisis and heightened environmental awareness, developing green industry has become a significant trend. As a critical component for heat exchange, optimizing the structure of heat exchangers holds substantial importance for recovering waste heat from chemical industry exhaust gases and advancing green industrial development. This study proposes a multi-objective optimization algorithm-based parameter optimization method targeting critical structures in large-scale chemical waste gas heat recovery equipment. By integrating numerical simulation with multi-objective genetic algorithms, it systematically analyzes the influence patterns of fin interval, thickness, and height on heat transfer performance and economic costs, establishing corresponding response models. Optimization results demonstrate that under varying target weightings, a Pareto optimal solution set balancing heat transfer efficiency and economic benefits can be obtained. Simulation validation demonstrates that the optimized fin parameter combination reduces material cost per unit by 9.91% while lowering exhaust gas outlet temperature by 5.02 °C, significantly enhancing the equipment's overall performance. This study provides theoretical foundations and decision support for engineering selection of fin parameters in waste heat recovery equipment, offering strong practicality and applicability.