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Volume 59 Issue 5
Oct.  2024
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Journal of Southwest Jiaotong University  > 2024  >  59(5): 1167-1175.
WEI Xing, ZOU Jianhao, XIAO Lin, CHEN Yang, GU Xingyu. Digital Management of Crack Defects Information in Steel Truss Bridges Based on Building Information Modeling[J]. Journal of Southwest Jiaotong University, 2021, 56(3): 461-468, 492. doi: 10.3969/j.issn.0258-2724.20190507
Citation: JIA Demin, WANG Xiaoyan, WANG Peilun, YU Binbin, XU Yu, CHEN Xiumin, ZHAO Jianhui. Simulation Study of Influence of Structural Parameters on Entrainment Coefficient of Ejector Based on Response Surface Method[J]. Journal of Southwest Jiaotong University, 2024, 59(5): 1167-1175. doi: 10.3969/j.issn.0258-2724.20220232
shu

Simulation Study of Influence of Structural Parameters on Entrainment Coefficient of Ejector Based on Response Surface Method

doi: 10.3969/j.issn.0258-2724.20220232
  • 1.

    State Key Laboratory of Engine Reliability, Weichai Power Co., Ltd., Weifang 261001, China

  • 2.

    College of Power and Energy Engineering, Harbin Engineering University, Harbin 150001, China

  • Received Date: 19 Apr 2022
  • Rev Recd Date: 16 Jun 2022
    • Available Online: 18 Nov 2023
  • Publish Date: 13 Jul 2022
    Abstract

  • To analyze the significant influencing factors of the entrainment coefficient of the ejector, a two-dimensional numerical model of the compressible flow of the ejector with air as the working medium was established, and its calculation accuracy was validated by the experimental data. Meanwhile, the calculation matrix was designed by utilizing the D-optimal experimental design method. Based on the least-squares method, the response surface prediction model of the entrainment coefficient with a second-order form was constructed, and the significant parameters of the ejection coefficient and their interaction were simulated based on the constructed model. The research results show that the coincidence between the predicted and calculated values of the entrainment coefficients proves the accuracy of the response surface prediction model; the interaction between the length of the diffuser section, the mixing section length, the diameter of the mixing section, and the distance from the nozzle outlet to the inlet of the mixing section, the interaction between the mixing section diameter and mixing section length, and the interaction between the mixing section length and the diffusion angle of the diffuser section are the key factors affecting the entrainment coefficient because their P-values are less than 0.001. Meanwhile, the interaction of the diffusion angle of the diffuser section, the distance from the nozzle outlet to the inlet of the mixing section and the length of the diffuser section, and the interaction between the length of the mixing section and the distance from the nozzle outlet to the inlet of the mixing section have an important influence on the entrainment coefficient. Therefore, they are the main parameters affecting the entrainment coefficient. In addition, it is found that among the significant interaction of parameters, the significant factors affecting the entrainment coefficient will change with the value range of the two parameters with significant interaction.

     

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    • References(13)
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