Optimization of the Design Parameter for Standing Wave Thermoacoustic Refrigerator using Genetic Algorithm

International Conference on Sustainable Energy and Green Technology 2018

能源学;生态环境科学

Yuan Ong, Jing^1 ; Jin King, Yeong^1 ; Huat Saw, Lip^1 ; Keng Theng, Kai^1

Lee Kong Chian Faculty of Engineering and Science, UTAR, Kajang

43000, Malaysia^1

关键词: Design parameters;    Gas thermal penetrations;    Harmful chemicals;    Multi-objective genetic algorithm;    No-load conditions;    Normalized parameters;    Thermoacoustic refrigerators;    Vapor compression refrigeration system;   

Others  :  https://iopscience.iop.org/article/10.1088/1755-1315/268/1/012021/pdf
DOI  :  10.1088/1755-1315/268/1/012021

学科分类：环境科学（综合）

来源: IOP

【 摘 要 】

Standing wave thermoacoustic refrigerator has a potential of replacing conventional vapor compression refrigeration system due to several factors. Firstly, this green technology does not contain any harmful chemicals or ozone depletion refrigerant. In fact, it uses the sound wave to generate the cooling effect. Thus, it is friendly to the environment. Besides, this technology is affordable, lightweight and easy to be constructed too. However, it has a low coefficient of performance compared to conventional refrigerator with the same cooling capacity. Recently, there is no noticeable breakthrough in the research of this technology. In this study, genetic algorithm is used to optimize the design parameters of the standing wave thermoacoustic refrigerator system to achieve the highest coefficient of performance. Multi-Objective Genetic Algorithm is used to provide the performance trend of a standing wave thermoacoustic refrigerator system. There are five normalized parameters which will undergo optimization using genetic algorithm, namely normalized stack length, normalized stack center position, blockage ratio, drive ratio and normalized gas thermal penetration depth. The results show that the highest COP that can be achieved by a thermoacoustic refrigerator system (working gas = air, temperature = 300 K and pressure = 1 atm) is 4.8904. The coefficient of performance is about 120.3 % higher than the previously published data. A standing wave thermoacoustic refrigerator prototype is built based on the optimized results obtained from genetic algorithm, whereby the system is operating under no load condition. It is found that the experimental results agree well with the optimization results.