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journal article·2024-04-27Open access

Prediction of Delayed Surface Subsidence Based on the Improved Knothe-n Model

Jianhui Dong, Chengqian Tang, Xiao Liu, Yangdan Dong

Applied Sciences· Volume 14· Issue 9
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Source abstract

Abstract

The delayed surface subsidence caused by coal seam mining is a problem that cannot be ignored, while accurate prediction of the surface subsidence provides a guarantee of the safety and stability of the relevant areas. However, the traditional Knothe model has limitations in considering delayed surface subsidence. Because of this, the Knothe-n time function model is segmented and improved by using the data of the subsidence area obtained from a FLAC3D-based numerical model, and the maximum delayed surface subsidence in different periods is calculated. The analytical results are compared with the numerical results to validate the effectiveness of the improved segmented time function model in predicting delayed surface subsidence. The improved model is applied to predict the surface subsidence in the Yutianbao subsidence area. The root-mean-square error between the predicted and measured values for the maximum subsidence monitoring point is 1.12, and the root-mean-square error between the average predicted and measured values for the surface monitoring points is 0.37, which verifies the accuracy of the improved model. The prediction model provides a scientific basis for environmental protection and safety management after coal seam mining.
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Research context

OpenAlex topics: Rock Mechanics and Modeling · Synthetic Aperture Radar (SAR) Applications and Techniques · Dam Engineering and Safety

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Hubei Key Laboratory of Disaster Prevention and Mitigation, Three Gorges University, Yichang 443002, China

Engineering Research Center of Catastrophic Prophylaxis and Treatment of Road Traffic Safety of Ministry of Education, Changsha University of Science and Technology, Changsha 410114, China

School of Architecture and Civil Engineering, Chengdu University, Chengdu 610106, China

State Key Laboratory of Geohazard Prevention and Geoenvironment Protection, Chengdu University of Technology, Chengdu 610059, China

Funding

2021 Open Research Fund of Hubei Key Laboratory of Disaster Prevention and Mitigation, China Three Gorges University · Open Research Fund of Engineering Research Center of Catastrophic Prophylaxis and Treatment of Road and Traffic Safety of Ministry of Education, Changsha University of Science and Technology

References (23)

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