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An experimental study of modified physical performance test of low-temperature epoxy grouting material for grouting joints with tenon and mortise

Author

Listed:
  • Huifeng Su

    (Shandong University of Science and Technology
    Shandong University of Science and Technology)

  • Renzhuang Li

    (Shandong University of Science and Technology)

  • Ming Yang

    (Beijing Urban Construction Design and Development Group Co. Limited)

Abstract

With the grouting material as focus, this study aims to guarantee that the joint with tenon and mortise constructing a metro station has the necessary waterproof performance, which shall not be poorer than the mechanical properties of the concrete with joints itself, and fine structural integrity. With groutability at low-temperature and available operational time as basis, low-temperature epoxy was selected as the grouting material for the joints. The silica powder of particular particle size and mass was added for modifying the physical performance of grouting material. A series of physical and mechanical tests were conducted in an attempt to achieve the optimal particle size and mix ratio provided that costs were reduced as practically as possible. Also, the flexural capacity of the joint filled with the above grouting material was demonstrated via the combined equal-proportion joint axial bend test.

Suggested Citation

  • Huifeng Su & Renzhuang Li & Ming Yang, 2021. "An experimental study of modified physical performance test of low-temperature epoxy grouting material for grouting joints with tenon and mortise," Journal of Intelligent Manufacturing, Springer, vol. 32(3), pages 667-677, March.
    • Handle: RePEc:spr:joinma:v:32:y:2021:i:3:d:10.1007_s10845-020-01664-0
    DOI: 10.1007/s10845-020-01664-0
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    References listed on IDEAS

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    1. Kumar Abhishek & V. Rakesh Kumar & Saurav Datta & Siba Sankar Mahapatra, 2017. "Parametric appraisal and optimization in machining of CFRP composites by using TLBO (teaching–learning based optimization algorithm)," Journal of Intelligent Manufacturing, Springer, vol. 28(8), pages 1769-1785, December.
    2. Jia-Bei Yu & Yang Yu & Lin-Na Wang & Ze Yuan & Xu Ji, 2016. "The knowledge modeling system of ready-mixed concrete enterprise and artificial intelligence with ANN-GA for manufacturing production," Journal of Intelligent Manufacturing, Springer, vol. 27(4), pages 905-914, August.
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