- Title
- Experimental and practical investigation of reinforcement mechanism on permeable polymer in loose area of drainage pipeline
- Creator
- Du, Xueming; Fang, Hongyuan; Liu, Kang; Li, Bin; Wang, Niannian; Zhang, Chao; Wang, Shanyong
- Relation
- Tunnelling and Underground Space Technology Vol. 140, Issue October 2023, no. 105250
- Publisher Link
- http://dx.doi.org/10.1016/j.tust.2023.105250
- Publisher
- Elsevier
- Resource Type
- journal article
- Date
- 2023
- Description
- Permeation grouting is one of the important methods of anti-seepage reinforcement when the drainage pipes crosses loose diseases caused by leakage. With the development of grouting materials, permeable polymer slurry is widely used in engineering practice. Due to its low viscosity, fast reaction and micro-expansion, the diffusion and reinforcement law of slurry in loose area of drainage pipeline is more complex. To better understand the effects of water head pressure, grouting pressure, sand particle size and clay content on the anti-seepage and reinforcement effect of permeable polymer grouting in loose area of drainage pipeline, several types of tests, including permeability and uniaxial compressive strength tests, were performed. Then, based on the model test results, a BP neural network prediction model for the anti-seepage reinforcement effect of permeable polymer grouting in loose area of drainage pipeline is constructed, and the research results are applied to the treatment project of loose area of drainage pipeline for verification. The results show that: 1) after grouting, the order of magnitude of permeability coefficient of the consolidated body is reduced to 10-7cm/s, the anti-seepage performance of the sand layer is greatly improved, and the grouting pressure is the main controlling factor affecting the anti-seepage performance of the consolidated body. 2) The compressive strength of the consolidated body is obvious different under different working conditions. The water head pressure is the main controlling factor affecting the strength of the consolidated body. 3) Due to the limitation of test conditions, the relative error between the predicted value of BP neural network model and the actual value is about 20%, which can meet the general prediction needs.
- Subject
- loose area of drainage pipeline; permeable polymer; permeation grouting; anti-seepage reinforcement; BP neural network
- Identifier
- http://hdl.handle.net/1959.13/1489730
- Identifier
- uon:52756
- Identifier
- ISSN:0886-7798
- Language
- eng
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