Multi-Objective Optimization of a Multilayer Wire-on-Tube Condenser: Case Study R134a, R600a, and R513A

Abstract

This study presents the optimization of a multilayer wire-on-tube condenser exposed to forced convection, using the Optimized Multi-objective Particle Swarm Optimization (OMOPSO) algorithm. The maximization of the heat transfer and the minimization of the heat exchange area were defined as objective functions. In the optimization process, the variations of eight geometric parameters of the condenser were analyzed, and the Multi-objective Evolutionary Algorithm based on Decomposition (MOEAD), Non-dominated Sorting Genetic Algorithm-II (NSGAII), and OMOPSO algorithms were statistically explored. Furthermore, the condenser optimization analysis was extended to the use of alternative refrigerants to R134a such as R600a and R513A. Among the relevant results, it can be commented that the OMOPSO algorithm presented the best option from the statistical point of view compared to the other two algorithms. Thus, optimal designs for the wire-on-tube condenser were defined for three proposed study cases and for each refrigerant, providing an overview of compact designs. Likewise, the reduction of the condenser area was analyzed in more detail, presenting a maximum reduction of 15% for the use of R134a compared to for the current design. Finally, the crossflow condition was studied with respect to the current one, concluding in a greater heat transfer and a smaller heat exchange surface.

Keywords

• domestic refrigerator
• MOEAD
• NSGAII
• OMOPSO
• refrigerants