Abstract
A substantial number of the coal mines in China are in the geological condition of thick alluvium layer. Under these circumstances, it does not make sense to predict ground surface subsidence and other deformations by using conventional prediction models. This paper presents a novel ground surface subsidence prediction model for sub-critical mining in the geological condition of thick alluvium layer. The geological composition and mechanical properties of thick alluvium is regarded as a random medium, as are the uniformly distributed loads on rock mass; however, the overburden of the rock mass in the bending zone is looked upon as a hard stratum controlling the ground surface subsidence. The different subsidence and displacement mechanisms for the rock mass and the thick alluvium layer are respectively considered and described in this model, which indicates satisfactory performances in a practical prediction case.
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Zhanqiang CHANG received his Ph.D and Master’s degrees in Geodesy and Survey Engineering from China University of Mining Science and Technology (Beijing) respectively in 1990 and 2004. He received his Bachelor degree from Shandong Mining Institute in 1984. He is currently in School of Resources, Environment and Tourism, Capital Normal University of China. His research interests include ground subsidence prediction as well as monitoring ground subsidence by remote sensing technique. He has published more than 40 research papers in Chinese and international journals. In 2009, he worked in the Geotechnical Engineering Department of Civil Engineering, University of Minnesota, Duluth as a visiting scholar with Dr. Carlos Carranza-Torres.
Jingzhuang WANG received his Master’s degree from Donetsk University, the former Soviet Union in 1959. He is currently with the Institute of Earth Sciences and Mapping, China University of Mining and Technology (Beijing). He served as the deputy director of coal mining damage technology appraisal committee of China Coal Society. His research interests include mining subsidence and prevention, mining subsidence control theory and technology, and modern surveying technology and applications. He has published more than 300 research papers in Chinese and international journals.
Mi CHEN received her Ph.D in photogrammetry and remote sensing from Wuhan University, Wuhan, China, in 2006. She is currently a Lecturer with the School of Resources, Environment and Tourism, Capital Normal University. Her current research interests include regional land subsidence monitoring and InSAR technique applications.
Zurui AO received his Bachelor’s degree from Henan Polytechnic University in 2011. His research interests include the theory and application of remote sensing. He is currently in the Master’s degree program at the School of Resources, Environment and Tourism, Capital Normal University, China.
Qi YAO received his Bachelor’s degree from Capital Normal University in 2012. His research interests include land subsidence monitoring and forestry remote sensing. He will graduate from Capital Normal University in 2015 with his Master’s degree.
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Chang, Z., Wang, J., Chen, M. et al. A novel ground surface subsidence prediction model for sub-critical mining in the geological condition of a thick alluvium layer. Front. Earth Sci. 9, 330–341 (2015). https://doi.org/10.1007/s11707-014-0467-2
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DOI: https://doi.org/10.1007/s11707-014-0467-2