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© 2018 Bai et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.

Abstract

In China’s northwest coal mining area, the excavation of shallow buried thick coal seams has caused serious damage to the phreatic water layer and induced deterioration of the ecological environment. Backfilling is a basic method of controlling the loss of groundwater and reducing surface subsidence. In order to reduce the porosity of the backfill material and control the compression ratio of the backfill body, the grain gradation of the local aeolian sand was studied based on the geological conditions of the shallow buried coal seam in the Yulin mining area, Shaanxi province. Subsequently, aeolian sand was selected as the backfilling aggregate, and tests were implemented. The optimum proportion and slurry concentration of the backfill material were then obtained. The engineering application shows that the strength and stability of the backfill body based on the close packing theory can satisfy the requirements of supporting the overlying strata, and the integrity of overburden strata is competent. The maximum accumulated surface subsidence was measured to be 38mm, indicating that the aeolian sand-based backfill material in shallow and thick underground coal seam mining is able to protect the eco-environment and control the geo-environmental hazards, which are critical for the sustainable development of the mining industry and economic growth.

Details

Title
The analysis and application of granular backfill material to reduce surface subsidence in China’s northwest coal mining area
Author
Bai, Erhu; ⨯ Wenbing Guo; Tan, Yi; Yang, Daming
First page
e0201112
Section
Research Article
Publication year
2018
Publication date
Jul 2018
Publisher
Public Library of Science
e-ISSN
19326203
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2074111827
Copyright
© 2018 Bai et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.