A new approach for global and multi-objective optimization of fin and tube heat exchanger

Abstract

Fin and tube heat exchangers (FTHEs) are widely used in buildings for various heating, ventilation, and air conditioning (HVAC) applications due to their efficiency and compact design. Optimizing the design of FTHEs for building applications can bring numerous advantages in terms of energy efficiency, performance, and overall cost-effectiveness. For this purpose, this paper introduces the Multi-Objective Set Trimming (MOST) algorithm, a robust and global optimization approach applied to the optimization of a fin and tube heat exchanger. The study compares the results obtained using MOST with the well-known semi-stochastic method, Multi-Objective Particle Swarm Optimization (MOPSO), and an exhaustive search, considering both computational time and convergence. The optimization focuses on two objectives: effectiveness and annual cost, considering eight design parameters related to heat exchanger geometry. Six different cases with varying mass flow rates on both the hot and cold sides are investigated. Results reveal that the Pareto optimal fronts achieved with MOPSO are entirely dominated by those obtained using MOST across all studied cases. Additionally, MOST improves the annual cost for the best economic solution by up to 10.69% compared to MOPSO, and effectiveness is enhanced by up to 1.95%. Notably, the computational time is significantly reduced with MOST, ranging from 49.36% to 97.49% compared to MOPSO across different cases. As a result, the implemented method provides highly effective tools for optimizing the FTHE, ensuring both fast convergence and efficient computational performance.