机械工程

基于多种湍流模型的电解加工温度多场耦合仿真

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  • 1.合肥工业大学 机械工程学院,安徽 合肥 230009; 2.皖西学院 机械与车辆工程学院,安徽 六安 237000
陈远龙(1964-),男,教授,博士生导师,主要从事特种加工工艺及装备研究。

收稿日期: 2021-04-16

  修回日期: 2021-06-23

  网络出版日期: 2021-08-27

基金资助

国家自然科学基金资助项目(51775161;51775158);安徽省自然科学基金资助项目(2008085QE278)

Multiphysics Coupling Simulation of ECM Temperature Based on Different Turbulence Models

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  • 1.School of Mechanical Engineering, Hefei University of Technology, Hefei 230009, Anhui, China;
    2.School of Mechanical and Automotive Engineering, West Anhui University, Luan 237000, Anhui, China
陈远龙(1964-),男,教授,博士生导师,主要从事特种加工工艺及装备研究。

Received date: 2021-04-16

  Revised date: 2021-06-23

  Online published: 2021-08-27

Supported by

Supported by the National Natural Science Foundation of China(51775161,51775158)and the Natural Science Foundation of Anhui Province(2008085QE278)

摘要

针对型面电解加工过程中的间隙温度分布难以预测和测量的问题,建立型面二维电解加工温度多物理场耦合仿真模型,分别基于SA、k-ε、k-ω、SST和低雷诺数k-ε等湍流模型求解加工间隙流场分布,耦合电场、流场和温度场求解间隙温度场分布,并将计算值与试验值进行对比。结果表明,求解近壁区流速时采用低雷诺数壁处理比采用壁函数处理的精度高,间隙温升能在较短时间内达到准稳态,基于SST、低雷诺数k-ε模型的间隙温度仿真值非常接近,其耦合气泡的温度多场耦合模型仿真值与试验值更为接近。

本文引用格式

陈远龙, 林华, 陈培譞, 等 . 基于多种湍流模型的电解加工温度多场耦合仿真[J]. 华南理工大学学报(自然科学版), 2022 , 50(3) : 88 -94,126 . DOI: 10.12141/j.issn.1000-565X.210219

Abstract

In view of the difficulties in the prediction and measurement of machining gap temperature distribution in the process of electrochemical machining (ECM), this paper established and analyzed a temperature multiphy-sics coupling model for profile ECM. The turbulence models of SA, k-ε, k-ω, SST and low-Reynolds-number k-ω were used to calculate the flow field distribution, and the temperature distribution was obtained by coupling electrical field, flow field and temperature field. The simulated value was compared with the experimental value. Results show that the near-wall region flow field solution accuracy of the low-Reynolds-number wall treatment is higher than that of the wall-function and the temperature in the ECM gap can reach a quasi-stable state in a relatively short time. The calculated temperature values based on SST and low-Reynolds-number k-ω models are very close to each other, and the simulated temperature values of the model coupled with the bubble rate are closer to the experimental values.
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