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职称职务/POSITION

副教授/Associate   Professor

联
  系
  方
  式/CONTACT

Email

yuanyuanpu@cqu.edu.cn

联系地址/ADDRESS

重庆市沙坪坝区沙正街174号
  重庆大学A区资源与安全学院/ School of Resources and Safety Engineering

Chongqing   University, Shapingba district, Chongqing

研究方向/RESEARCH

 1、矿山动力灾害智能监测预警 Intelligent monitoring   and early-warning for mining

 2、矿山数字孪生   Digital twin applications in mining process

My research interests are centered on the areas of rock   signaling and mining dynamic disasters (slope failure, rock burst, gas   outburst, water inrush) prediction in both underground and surface mining   using massive field data combined with advanced machine learning methods. I   am also pursuing my research interests in the development of digital-twin   framework in smart mining safety.

个人简历/ PROFESSIONAL EXPERIENCE and EDUCATION

 2022.9~至今 重庆大学，资源与安全学院，副教授 Associate Professor, Chongqing University

2019.12~2022.9 重庆大学，资源与安全学院，讲师 Assistant Professor, Chongqing University

2019.9~2019.12 阿尔伯塔大学, 土木与环境工程学院，高级研究助理 Research   Assistant, University of Alberta

2016.8~2019.9阿尔伯塔大学, 土木与环境工程学院，博士 PhD in Mining Engineering, University of Alberta

 2013.9~2016.6 中国矿业大学，矿业工程学院，硕士 Master in Mining Engineering, China   University of Mining & Technology

 2009.9~2013.6 中国矿业大学，孙越崎学院，本科 Bachelor in Sun yueqi Honors College, China University of Mining   & Technology

代表性研究项目/ Projects

1、 国家自然科学基金面上项目“强采动诱发冲击地压演化信号学机制与灾害早期侦测”（主持）National Natural Science Foundation of China, “Evolutionary   signal mechanism of rock burst induced by strong mining and early detection   of disaster” (PI)

2、 国家自然科学基金青年项目“渗流-应力耦合作用下岩体裂隙时序演化规律及全波形空间定位机制”（主持）National Natural Science Foundation of China, “The temporal   evolution law and full waveform spatial locating mechanism of rock fractures   under hydro-mechanical coupling” (PI)

3、 中央高校基本业务费“岩石信号学及煤矿动力灾害智能预警”（主持）Fundamental Research Funds for the Central Universities, “Rock   signaling and intelligent pre-warning method for dynamic disasters in mining   engineering” (PI)

4、 国家重点研发计划“煤矿深部开采煤岩动力灾害防控技术研究”课题二“深部煤岩动力灾害危险性区域快速探测与评价技术”(2017YFC0804202) （主研）

5、 加拿大NSERC项目“Rock burst hazard evaluation   and prediction in Diavik diamond mine”（主研）

6、 重庆市科技计划项目“基于3S多源数据驱动和深度学习的滑坡预警关键技术研究与应用”（主研）

代表性获奖

1、2021年度重庆市科技进步一等奖“含瓦斯地层动力灾害智能监测-预警-防控一体化技术与应用”

2、2020年度重庆市科技进步一等奖“矿区滑坡灾害诱发机制及智能化监测预警技术与应用”

3、2020年度职业健康协会科技进步一等奖“煤与瓦斯突出危险层次化精准辨识方法与关键技术研究”

4、2024 International   Outstanding Young Scholar Award, International Committee on Mine Safety and   Engineering

代表性专利/软著

1、 蒲源源,陈结,杜俊生,等.基于贝叶斯方法的煤矿冲击地压危险性动静耦合评价方法[P]: CN113673119B

2、 陈结; 蒲源源; 杜俊生，等. 基于微震事件定量预测的煤矿冲击地压智能预警方法[P]: CN113723595B

3、 魏立科; 蒲源源; 王翀,等. 支架动态压力差指标实时确定与优化方法[P]: CN113761682B

代表性专著、教材

1、《数字矿山技术》，陈结，蒲源源 主编，清华大学出版社（2024）

代表性论文

1. Chen, J., Tong, J., Rui, Y., Cui, Y., Pu, Y.*, Du, J.,   & Apel, D. B. (2024). Step-path failure mechanism and stability analysis   of water-bearing rock slopes based on particle flow simulation. Theoretical   and Applied Fracture Mechanics, 131, 104370.

2. Pu, Y*., Chen, J., Jiang, D. et al. (2022). Improved Method   for Acoustic Emission Source Location in Rocks Without Prior Information.   Rock Mech Rock Eng 55, 5123–5137

3. Chen, J., Ye, Y., Pu, Y*., Xu, W., & Mengli, D. (2022).   Experimental study on uniaxial compression failure modes and acoustic   emission characteristics of fissured sandstone under water saturation.   Theoretical and Applied Fracture Mechanics, 119, 103359.

4. Chen, J., Zhu, C., Du, J., Pu, Y*., Pan, P., Bai, J., &   Qi, Q. (2022). A quantitative pre-warning for coal burst hazardous zones in a   deep coal mine based on the spatio-temporal forecast of microseismic events. Process   Safety and Environmental Protection, 159, 1105-1112.

5. Du, J., Chen, J., Pu, Y*., Jiang, D., Chen, L., &   Zhang, Y. (2021). Risk assessment of dynamic disasters in deep coal mines   based on multi-source, multi-parameter indexes, and engineering application.   Process Safety and Environmental Protection, 155, 575-586.

6. Pu, Y., Chen, J., & Apel, D. B. (2021). Deep and   confident prediction for a laboratory earthquake. Neural Computing and   Applications, 33(18), 11691-11701.

7. Pu, Y., Apel, D. B., Liu, V., & Mitri, H. (2019).   Machine learning methods for rockburst prediction-state-of-the-art review.   International Journal of Mining Science and Technology, 29(4), 565-570.

8. Pu, Y., Apel, D. B., Szmigiel, A., & Chen, J. (2019).   Image recognition of coal and coal gangue using a convolutional neural   network and transfer learning. Energies, 12(9), 1735.

9. Pu, Y., Apel, D. B., & Xu, H. (2019). Rockburst   prediction in kimberlite with unsupervised learning method and support vector   classifier. Tunnelling and Underground Space Technology, 90, 12-18.

10 尚雪义, 陈勇, 陈结, 陈林林,   & 蒲源源*.   (2024). 基于adaboost_lstm预测的矿山微震信号降噪方法及应用. 煤炭学报(1).

11 陈结,孟历德仁,崔义, & 蒲源源*. (2024).基于声光联合试验的预制双裂隙砂岩损伤演化特征研究[J/OL].岩石力学与工程学报,1-13

12 陈结,杜俊生,蒲源源*,等.冲击地压“双驱动”智能预警架构与工程应用[J].煤炭学报,2022,47(02):791-806.