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Optimization of Liquid−Liquid Mixing in a Novel Mixer Based on Hybrid SVR-DE Model

Author

Listed:
  • Hao Wang

    (College of Metrology & Measurement Engineering, China Jiliang University, Hangzhou 310018, China)

  • Peijian Zhou

    (College of Metrology & Measurement Engineering, China Jiliang University, Hangzhou 310018, China
    Zhejiang Engineering Research Center of Smart Fluid Equipment & Measurement and Control Technology, Hangzhou 310018, China)

  • Ting Chen

    (School of Optical Information and Energy Engineering, Wuhan Institute of Technology, Wuhan 430205, China)

  • Jiegang Mou

    (College of Metrology & Measurement Engineering, China Jiliang University, Hangzhou 310018, China
    Zhejiang Engineering Research Center of Smart Fluid Equipment & Measurement and Control Technology, Hangzhou 310018, China)

  • Jiayi Cui

    (College of Metrology & Measurement Engineering, China Jiliang University, Hangzhou 310018, China)

  • Huiming Zhang

    (Dezhou Keyuan Water Supplying Engineering Development Co., Ltd., Dezhou 253000, China)

Abstract

To solve the problem of evenly mixing flocculant and sewage, a new type of two-chamber mechanical pipe mixer was numerically calculated and its working principle was studied by means of the internal flow field. The single factor numerical simulation and analysis of some of the structural parameters in the mixer were carried out to determine the influence of different parameters on the results. Latin hypercube sampling was used to design 100 sets of test tables for the four variables of the branch pipe diameter, sewage flow rate, the installation height of the impeller, and the angle of the deflector. The results were optimized using the SVR-DE algorithm. After optimization, the variation coefficient of export flocculant mixing uniformity was 16.02%, which was increased by 74.94% compared with the initial 63.921%. The power consumption of the impeller was reduced by 8.30%. The concentration curves of the flocculant at different positions of the outlet tube could quickly converge to the target value.

Suggested Citation

  • Hao Wang & Peijian Zhou & Ting Chen & Jiegang Mou & Jiayi Cui & Huiming Zhang, 2023. "Optimization of Liquid−Liquid Mixing in a Novel Mixer Based on Hybrid SVR-DE Model," Energies, MDPI, vol. 16(4), pages 1-17, February.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:4:p:1808-:d:1065488
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    References listed on IDEAS

    as
    1. Lei Wang & Jiayi Cui & Lingfeng Shu & Denghui Jiang & Chun Xiang & Linwei Li & Peijian Zhou, 2022. "Research on the Vortex Rope Control Techniques in Draft Tube of Francis Turbines," Energies, MDPI, vol. 15(24), pages 1-27, December.
    2. Huican Luo & Peijian Zhou & Lingfeng Shu & Jiegang Mou & Haisheng Zheng & Chenglong Jiang & Yantian Wang, 2022. "Energy Performance Curves Prediction of Centrifugal Pumps Based on Constrained PSO-SVR Model," Energies, MDPI, vol. 15(9), pages 1-19, May.
    3. Fei Tian & Erfeng Zhang & Chen Yang & Weidong Shi & Yonghua Chen, 2022. "Research on the Characteristics of the Solid–Liquid Two-Phase Flow Field of a Submersible Mixer Based on CFD-DEM," Energies, MDPI, vol. 15(16), pages 1-20, August.
    4. Huang, Renfang & Zhang, Zhen & Zhang, Wei & Mou, Jiegang & Zhou, Peijian & Wang, Yiwei, 2020. "Energy performance prediction of the centrifugal pumps by using a hybrid neural network," Energy, Elsevier, vol. 213(C).
    Full references (including those not matched with items on IDEAS)

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