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2024
5
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矿山工程技术其他学科
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Dongqiao Liu
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CNPC Key Laboratory of Oil &Gas Reservoir Stimulation, Langfang, 065007, China
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School of Electrical and Information Engineering, Beijing University of Civil Engineering and Architecture, Beijing, 100044, China
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Advanced Materials Additive Manufacturing Innovation Research Center, Hangzhou City University, 310015, China
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Beijing Key Laboratory of Intelligent Processing for Building Big Data, Beijing University of Civil Engineering and Architecture, Beijing, 100044, China
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Center for Hyper-gravity Experimental and Interdisciplinary Research, Zhejiang University, Hangzhou, 310058, China
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Department of Civil Engineering, Hangzhou City University, Hangzhou, 310015, China
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Department of Earth Sciences, University of Florence, Firenze 50121, Italy
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Department of Geotechnical Engineering, College of Civil Engineering, Tongji University, Shanghai, 200092, China
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Department of Petroleum Engineering, Montanuniversit€at Leoben, Leoben, Leoben, 8700, Austria
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Engineering Research Center of Green and Intelligent Mining for Thick Coal Seam, Ministry of Education, Beijing 100083, China
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Institute for Deep Underground Science and Engineering, China University of Mining and Technology, Beijing, 100083, China
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Key Laboratory of Geotechnical & Underground Engineering of Ministry of Education, Tongji University, Shanghai, 200092, China
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Key Laboratory of Safe Construction and Intelligent Maintenance for Urban Shield Tunnels of Zhejiang Province, Hangzhou, 310015, China
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State Key Laboratory for Geomechanics and Deep Underground Engineering, China University of Mining and Technology, Beijing, 100083, China
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1. ChinaXiv:202407.00099
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Two-phase flow thermo-hydro-mechanical modeling for a water flooding field case
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2. ChinaXiv:202407.00100
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Rockburst prediction using artificial intelligence techniques: A review
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3. ChinaXiv:202407.00101
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Hyper-gravity experiment of solute transport in fractured rock and evaluation method for long-term barrier performance
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Experimental investigation on acoustic emission precursor of rockburst based on unsupervised machine learning method
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5. ChinaXiv:202407.00102
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Compaction and seepage characteristics of broken coal and rock masses in coal mining: A review in laboratory tests
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