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Optimal Design of an Air-to-Air Heat Exchanger with Cross-Corrugated Triangular Ducts by Using a Particle Swarm Optimization Algorithm

doi: 10.3390/app7060554
Optimal Design of an Air-to-Air Heat Exchanger with Cross-Corrugated Triangular Ducts by Using a Particle Swarm Optimization Algorithm
Air-to-air heat exchangers with cross-corrugated triangular ducts are widely used in various industrial fields to recover waste heat. The geometric parameters of the heat exchangers greatly affect the performance and total annual cost of these systems. In this study, the effectiveness-number of transfer units (ε-NTU) method was utilized to develop the thermal mathematical model, which was verified by comparing it with previous research. The configuration parameters of the heat exchanger were optimized in this study. The particle swarm optimization (PSO) algorithm was applied using both single and multi-objective algorithm. The colburn factor (j factor), friction factor (f factor), and comprehensive thermal hydraulic performance index (JF factor) were considered as objective functions to be optimized using a single objective and multi-objective algorithm. Then, the entropy generation rate and total annual cost were optimized by using a multi-objective PSO algorithm. In addition, to identify the influential geometric parameters, a global sensitivity analysis was performed. The sensitivity analysis showed that the apex angle θ, channel height H, and heat exchanger height Lh influenced the performance and annual total cost of these systems.
- Shanxi University China (People's Republic of)
- Shanxi University China (People's Republic of)
- Guilin University of Electronic Technology China (People's Republic of)
- Guilin University of Electronic Technology China (People's Republic of)
- Guilin University of Aerospace Technology China (People's Republic of)
cross-corrugated triangular ducts; air-to-air heat exchanger; particle swarm analysis (PSO); global sensitivity analysis
cross-corrugated triangular ducts; air-to-air heat exchanger; particle swarm analysis (PSO); global sensitivity analysis
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