可再生能源与工程热物理

热声制冷机板叠性能指标数值计算与遗传算法优化

  • 金诚明 ,
  • 彭叶辉 ,
  • 刘德顺
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  • 1. 湖南科技大学机电工程学院 湘潭 411201;
    2. 湖南科技大学机械设备健康维护湖南省重点实验室 湘潭 411201;
    3. 湖南科技大学知识处理与网络化制造湖南省普通高等学校重点实验室 湘潭 411201
金诚明,男,1990年出生.主要研究方向为机械设计.E-mail:ex3558@163.com;彭叶辉,男,1976年出生,博士,副教授.主要研究方向为热声制冷机、计算流体力学.Email:pengyehui@hnust.edu.cn

收稿日期: 2016-11-05

  修回日期: 2017-04-15

  网络出版日期: 2017-10-20

基金资助

国家自然科学基金资助项目(51476052和51405157)。

Numerical Computation of the Coefficient of Performance and Optimal Design of the Stack in Thermoacoustic Refrigerators

  • JIN Chengming ,
  • PENG Yehui ,
  • LIU Deshun
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  • 1. School of Mechanical and Electrical Engineering, Hunan University of Science and Technology, Xiangtan 411201;
    2. Hunan Provincial Key Laboratory of Health Maintenance for Mechanical Equipment, Hunan University of Science and Technology, Xiangtan 411201;
    3. Hunan Province College Key Laboratory of Knowledge Processing and Networked Manufacturing, Hunan University of Science and Technology, Xiangtan 411201

Received date: 2016-11-05

  Revised date: 2017-04-15

  Online published: 2017-10-20

摘要

板叠是驻波热声热机的重要部件,直接影响热声热机的效率。针对驻波热声制冷机,构造了一个板叠性能指标的数值计算方法及其优化设计方法。分析基于短板叠近似理论的计算方法的局限,构造迭代数值方法同时求解制冷量、压力、体积流率、平均温度分布以及温度梯度等参数,从而计算出板叠性能指标;基于该迭代方法探讨了热声板叠长度、宽度、位置、阻塞率以及温差等与板叠性能指标之间的关系;以板叠长度、宽度、位置、阻塞率为优化设计变量,板叠性能指标为优化目标,利用遗传算法,对驻波热声制冷机板叠进行了优化设计。与基于短板叠近似理论的方法相比,由于考虑了更多的实际因素,该方法数值计算结果更为准确,优化设计结果更容易被接受。

本文引用格式

金诚明 , 彭叶辉 , 刘德顺 . 热声制冷机板叠性能指标数值计算与遗传算法优化[J]. 机械工程学报, 2017 , 53(20) : 145 -152 . DOI: 10.3901/JME.2017.20.145

Abstract

Stack is the most important component in the thermoacoustic engine for it directly affects the efficiency. For standing-wave thermoacoustic refrigerator, a numerical algorithm for the coefficient of performance of stack and an optimal design method of stack are presented, respectively. Considering the limits of the short-stack approximation method for stack, we an iterative algorithm for coefficient of performance of stack is constructed, by which the total power together with pressure, volume flow rate, average temperature function and gradient of temperature can be obtained at the same time. Based on the presented numerical method, the effects of length, width, position, block ratio and temperature difference on the coefficient of performance of stack are investigated. Then, choosing length, width, position and block ratio of stack as the design variables and coefficient of performance as the optimization objective, the thermoacoustic stack is optimized by using the genetic algorithm. Compared with the short-stack approximation method, the numerical method presented in the work is more accurate and the optimized results are more acceptable since some practical factors are taken in account.

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