Deep Underground Science and Engineering最新文献

{"title":"Machine learning and Big Data in deep underground engineering","authors":"Asoke K. Nandi, Ru Zhang, Tao Zhao, Tao Lei","doi":"10.1002/dug2.70004","DOIUrl":"https://doi.org/10.1002/dug2.70004","url":null,"abstract":"<p>This special issue of <i>Deep Underground Science and Engineering</i> (DUSE) showcases pioneering research on the transformative role of machine learning (ML) and Big Data in deep underground engineering. Edited by guest editors Prof. Asoke Nandi (Brunel University of London, UK), Prof. Ru Zhang (Sichuan University, China), Prof. Tao Zhao (Chinese Academy of Sciences, China), and Prof. Tao Lei (Shaanxi University of Science and Technology, China), this issue highlights the innovative applications of ML technique in reshaping structural safety, tunneling operations, and geotechnical investigations.</p><p>As underground engineering challenges grow in complexity, ML and Big Data have become indispensable tools for improving prediction accuracy, optimizing operational efficiency, and ensuring the long-term safety and sustainability of infrastructure. By leveraging vast datasets, automating critical processes, and predicting complex engineering outcomes, these technologies are enabling smarter, more reliable engineering practices that drive both performance and resilience.</p><p>The contributions to this special issue illustrate the diverse and impactful applications of ML and Big Data in deep underground engineering. One article introduces ALSTNet, an advanced data-driven model that integrates long- and short-term time-series data using autoencoders to predict tunnel structural behaviors. When applied to strain monitoring data from the Nanjing Dinghuaimen tunnel, ALSTNet outperforms traditional models, offering promising potential for early disaster prevention in real-world engineering scenarios. Another study presents two robust ML models—Gene Expression Programming (GEP) and a Decision Tree-Support Vector Machine (DT-SVM) hybrid algorithm—to assess pillar stability in deep underground mines. Validated with 236 case histories, these models demonstrate exceptional accuracy and provide valuable tools for project managers to evaluate pillar stability during both the design and operational phases of mining projects. Yet another study demonstrates the use of fuzzy C-means clustering combined with ML models in Tunnel Boring Machine (TBM) operations. This innovative approach enhances prediction accuracy, providing more reliable insights for TBM tunneling processes and boosting efficiency in underground excavation projects.</p><p>Several other papers focus on optimizing monitoring systems for underground structures. One contribution presents a low-cost micro-electromechanical systems (MEMS) sensor designed to monitor tilt and acceleration in underground structures. Aided by ML algorithms, this sensor facilitates real-time monitoring and early warning capabilities, thereby significantly improving safety during underground construction. Another paper introduces a ML-based optimization model for underwater shield tunnels, showing how strategically placed monitoring points—such as at the spandrel and arch crown—can improve the accuracy of stress distribution","PeriodicalId":100363,"journal":{"name":"Deep Underground Science and Engineering","volume":"4 1","pages":"1-2"},"PeriodicalIF":0.0,"publicationDate":"2025-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/dug2.70004","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143602651","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Laboratory evaluation of a low-cost micro electro-mechanical systems sensor for inclination and acceleration monitoring","authors":"Antonis Paganis,&nbsp;Vassiliki N. Georgiannou,&nbsp;Xenofon Lignos,&nbsp;Reina El Dahr","doi":"10.1002/dug2.12135","DOIUrl":"https://doi.org/10.1002/dug2.12135","url":null,"abstract":"<p>In this study, the design and development of a sensor made of low-cost parts to monitor inclination and acceleration are presented. Α micro electro-mechanical systems, micro electro mechanical systems, sensor was housed in a robust enclosure and interfaced with a Raspberry Pi microcomputer with Internet connectivity into a proposed tilt and acceleration monitoring node. Online capabilities accessible by mobile phone such as real-time graph, early warning notification, and database logging were implemented using Python programming. The sensor response was calibrated for inherent bias and errors, and then tested thoroughly in the laboratory under static and dynamic loading conditions beside high-quality transducers. Satisfactory accuracy was achieved in real time using the Complementary Filter method, and it was further improved in LabVIEW using Kalman Filters with parameter tuning. A sensor interface with LabVIEW and a 600 MHz CPU microcontroller allowed real-time implementation of high-speed embedded filters, further optimizing sensor results. Kalman and embedded filtering results show agreement for the sensor, followed closely by the low-complexity complementary filter applied in real time. The sensor's dynamic response was also verified by shaking table tests, simulating past recorded seismic excitations or artificial vibrations, indicating negligible effect of external acceleration on measured tilt; sensor measurements were benchmarked using high-quality tilt and acceleration measuring transducers. A preliminary field evaluation shows robustness of the sensor to harsh weather conditions.</p>","PeriodicalId":100363,"journal":{"name":"Deep Underground Science and Engineering","volume":"4 1","pages":"46-54"},"PeriodicalIF":0.0,"publicationDate":"2024-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/dug2.12135","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143602528","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Two-year growth of Deep Underground Science and Engineering: A perspective","authors":"Jianguo Wang,&nbsp;Chunfai Leung,&nbsp;Heping Xie,&nbsp;Xiaozhao Li,&nbsp;Na Yue,&nbsp;Qingping Hou,&nbsp;Jihong Wang","doi":"10.1002/dug2.12139","DOIUrl":"https://doi.org/10.1002/dug2.12139","url":null,"abstract":"&lt;p&gt;&lt;i&gt;Deep Underground Science and Engineering&lt;/i&gt; (DUSE) launched its first issue in September 2022 as a quarterly journal. So far, it has published 106 articles with nine issues and online early view. The volume of received manuscripts increases by 50% each year and over 200 manuscripts were received by 28th of November 2024. In the early period, DUSE authorship came from five countries and now reaches 29 countries. DUSE articles have been downloaded over 97 000 times by readers from 170 countries/regions. It is indeed encouraging to note that DUSE has been admitted to different indices, including ESCI (August 2024), EI (March 2024), Scopus (July 2023), and DOAJ (May 2023). Its CiteScore in Scopus was 2.2 in 2023 and increased to 5.1 at the mid-November 2024. Its first impact factor from the Web of Science will be available in 2025. DUSE is growing to be a rapidly recognized international journal by readers in deep underground research and practice.&lt;/p&gt;&lt;p&gt;DUSE is making its best efforts to trace and shape a full-chain deep underground science and engineering through its six directions. &lt;i&gt;Direction 1&lt;/i&gt;: Exploration and extraction of geo-resources. The geo-resources refer to minerals, energy sources, and water. DUSE makes efforts to streamline research studies in geo-resources from the initial geological analysis of source location, geo-resource volume estimation, and hot sweat point identification. These processes involve geology, geophysics, rock mechanics, and related material science and technology. After the identification of geo-resources, the next step is to extract these geo-resources from (deep) ground. This step involves engineering science and technology, such as rock mechanics, hydraulic fracturing technology, blasting, and so on. The key outcome is the extraction of these identified geo-sources from the deep ground with technical feasibility and economic benefit. &lt;i&gt;Direction 2&lt;/i&gt;: Energy extraction and storage. Deep underground has abundant fuel matter, which was generated through long-term geological actions. Deep underground also has abundant space for the storage of energy and materials. This direction involves branches of engineering science, such as petroleum, engineering science and technology, material science, and environment science. &lt;i&gt;Direction 3&lt;/i&gt;: Underground infrastructures. This direction focuses on the excavation and utilization of underground spaces, such as cavern construction, tunneling, and other pore space use. &lt;i&gt;Direction 4&lt;/i&gt;: Geo-environments and waste geological disposal, which deals with the solutions to environmental problems in deep underground. The environmental problems have two types: The first one refers to the environmental problems induced by the exploitation of underground resources. The second one refers to the utilization of underground space (including pore space) to solve the environmental problems that are difficult to tackle on the ground surface, such as geological disposal of nuclea","PeriodicalId":100363,"journal":{"name":"Deep Underground Science and Engineering","volume":"3 4","pages":"383-384"},"PeriodicalIF":0.0,"publicationDate":"2024-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/dug2.12139","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143252587","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Acknowledgment of reviewers","authors":"","doi":"10.1002/dug2.12137","DOIUrl":"https://doi.org/10.1002/dug2.12137","url":null,"abstract":"&lt;p&gt;The Editors of &lt;i&gt;Deep Underground Science and Engineering&lt;/i&gt; (DUSE) wish to extend our deepest thanks to the following peer reviewers in 2024. We are grateful to their contributions of time and expertise to improve the quality of DUSE. We have made every effort to ensure that all ad hoc reviewers are correctly listed. Our apologies are given to those whose names were unwittingly misspelled or omitted.&lt;/p&gt;&lt;p&gt;Mahamuda Abu&lt;/p&gt;&lt;p&gt;Salaam Jansbaka Adams&lt;/p&gt;&lt;p&gt;Musab A. Q. Al-Janabi&lt;/p&gt;&lt;p&gt;Ni An&lt;/p&gt;&lt;p&gt;Matteo Antelmi&lt;/p&gt;&lt;p&gt;Gabriel de Alemar Barberes&lt;/p&gt;&lt;p&gt;Luca Basilone&lt;/p&gt;&lt;p&gt;Jianchao Cai&lt;/p&gt;&lt;p&gt;Jian Cao&lt;/p&gt;&lt;p&gt;Jie Cao&lt;/p&gt;&lt;p&gt;Shuai Cao&lt;/p&gt;&lt;p&gt;Zhiming Chao&lt;/p&gt;&lt;p&gt;Chaofan Chen&lt;/p&gt;&lt;p&gt;Jueliang Chen&lt;/p&gt;&lt;p&gt;Luwang Chen&lt;/p&gt;&lt;p&gt;Min Chen&lt;/p&gt;&lt;p&gt;Shi Chen&lt;/p&gt;&lt;p&gt;Yifan Chen&lt;/p&gt;&lt;p&gt;Yuedu Chen&lt;/p&gt;&lt;p&gt;Gang Cheng&lt;/p&gt;&lt;p&gt;Guanglei Cui&lt;/p&gt;&lt;p&gt;Xiaopu Cui&lt;/p&gt;&lt;p&gt;Chenxi Ding&lt;/p&gt;&lt;p&gt;Zhuo Dong&lt;/p&gt;&lt;p&gt;Xueming Du&lt;/p&gt;&lt;p&gt;Hongyu Duan&lt;/p&gt;&lt;p&gt;Hongyun Fan&lt;/p&gt;&lt;p&gt;Jinyang Fan&lt;/p&gt;&lt;p&gt;Ning Fan&lt;/p&gt;&lt;p&gt;Gan Feng&lt;/p&gt;&lt;p&gt;Aime Fournier&lt;/p&gt;&lt;p&gt;Jinwei Fu&lt;/p&gt;&lt;p&gt;Xiaolu Gan&lt;/p&gt;&lt;p&gt;Yanan Gao&lt;/p&gt;&lt;p&gt;Mehran Ghasabeh&lt;/p&gt;&lt;p&gt;Bin Gong&lt;/p&gt;&lt;p&gt;Fengqiang Gong&lt;/p&gt;&lt;p&gt;Qiuming Gong&lt;/p&gt;&lt;p&gt;Ankit Grag&lt;/p&gt;&lt;p&gt;Dogukan Guner&lt;/p&gt;&lt;p&gt;Weiyao Guo&lt;/p&gt;&lt;p&gt;Zhizheng Guo&lt;/p&gt;&lt;p&gt;H. Haeri&lt;/p&gt;&lt;p&gt;Jianyong Han&lt;/p&gt;&lt;p&gt;Sakuma Hiroshi&lt;/p&gt;&lt;p&gt;Hussein Hoteit&lt;/p&gt;&lt;p&gt;Zhengmeng Hou&lt;/p&gt;&lt;p&gt;Dawei Hu&lt;/p&gt;&lt;p&gt;Nan Hu&lt;/p&gt;&lt;p&gt;Xunjian Hu&lt;/p&gt;&lt;p&gt;Haiping Huang&lt;/p&gt;&lt;p&gt;Changbao Jiang&lt;/p&gt;&lt;p&gt;Wencheng Jin&lt;/p&gt;&lt;p&gt;Xiangsong Kong&lt;/p&gt;&lt;p&gt;Sunil Kumar&lt;/p&gt;&lt;p&gt;Guohui Lei&lt;/p&gt;&lt;p&gt;Bo Li&lt;/p&gt;&lt;p&gt;Genzhuang Li&lt;/p&gt;&lt;p&gt;Xiaofeng Li&lt;/p&gt;&lt;p&gt;Xing Li&lt;/p&gt;&lt;p&gt;Xudong Li&lt;/p&gt;&lt;p&gt;Yanghui Li&lt;/p&gt;&lt;p&gt;Yuwei Li&lt;/p&gt;&lt;p&gt;Zhiqiang Li&lt;/p&gt;&lt;p&gt;Wei Liang&lt;/p&gt;&lt;p&gt;Botao Lin&lt;/p&gt;&lt;p&gt;Hang Lin&lt;/p&gt;&lt;p&gt;Hejuan Liu&lt;/p&gt;&lt;p&gt;Jian Liu&lt;/p&gt;&lt;p&gt;Jianfeng Liu&lt;/p&gt;&lt;p&gt;Liyuan Liu&lt;/p&gt;&lt;p&gt;Mengxin Liu&lt;/p&gt;&lt;p&gt;Xuesheng Liu&lt;/p&gt;&lt;p&gt;A. J. (Tom) Van Loon&lt;/p&gt;&lt;p&gt;Shifeng Lu&lt;/p&gt;&lt;p&gt;Shouqing Lu&lt;/p&gt;&lt;p&gt;Yimin Lu&lt;/p&gt;&lt;p&gt;Zhao Lu&lt;/p&gt;&lt;p&gt;Zheng Lu&lt;/p&gt;&lt;p&gt;Hu Lv&lt;/p&gt;&lt;p&gt;Dongdong Ma&lt;/p&gt;&lt;p&gt;Ke Ma&lt;/p&gt;&lt;p&gt;Tianshou Ma&lt;/p&gt;&lt;p&gt;Satar Mahdevari&lt;/p&gt;&lt;p&gt;Mohamed Malki&lt;/p&gt;&lt;p&gt;Mohammad Mehrad&lt;/p&gt;&lt;p&gt;Pinqiang Mo&lt;/p&gt;&lt;p&gt;Mostafa Mollaali&lt;/p&gt;&lt;p&gt;Arun Narayanan Nair&lt;/p&gt;&lt;p&gt;Hongyang Ni&lt;/p&gt;&lt;p&gt;Fulong Ning&lt;/p&gt;&lt;p&gt;Qiang Ou&lt;/p&gt;&lt;p&gt;Dongjiang Pan&lt;/p&gt;&lt;p&gt;Deepak Patwa&lt;/p&gt;&lt;p&gt;J. K. Pearce&lt;/p&gt;&lt;p&gt;Huafu Pei&lt;/p&gt;&lt;p&gt;Chunde Piao&lt;/p&gt;&lt;p&gt;Chengzhi Qi&lt;/p&gt;&lt;p&gt;Dwarikanath Ratha&lt;/p&gt;&lt;p&gt;Bharat Rattan&lt;/p&gt;&lt;p&gt;Arshad Raza&lt;/p&gt;&lt;p&gt;Shengjie Rui&lt;/p&gt;&lt;p&gt;Zhenhua Rui&lt;/p&gt;&lt;p&gt;Ahmad Sakhaee Pour&lt;/p&gt;&lt;p&gt;Vahab Sarfarazi&lt;/p&gt;&lt;p&gt;Axel Schippers&lt;/p&gt;&lt;p&gt;Resmi Sebastian&lt;/p&gt;&lt;p&gt;Jianfu Shao&lt;/p&gt;&lt;p&gt;Zhushan Shao&lt;/p&gt;&lt;p&gt;Jihong Shi&lt;/p&gt;&lt;p&gt;Yue Shi&lt;/p&gt;&lt;p&gt;Dazhao Song&lt;/p&gt;&lt;p&gt;Yang Song&lt;/p&gt;&lt;p&gt;Zhanping Song&lt;/p&gt;&lt;p&gt;Mairaj Soomro&lt;/p&gt;&lt;p&gt;Alfred Strauss&lt;/p&gt;&lt;p&gt;Benyu Su&lt;/p&gt;&lt;p&gt;Shanjie Su&lt;/p&gt;&lt;p&gt;Wanghua Sui&lt;/p&gt;&lt;p&gt;Qiang Sun&lt;/p&gt;&lt;p&gt;Yuantian Sun&lt;/p&gt;&lt;p&gt;Xu Tao&lt;/p&gt;&lt;p&gt;Zhigang Tao&lt;/p&gt;&lt;p&gt;Francesco Tinti&lt;/p&gt;&lt;p&gt;Olli H. Tuovinen&lt;/p&gt;&lt;p&gt;Chunguang Wang&lt;/p&gt;&lt;p&gt;Daobing Wang&lt;/p&gt;&lt;p&gt;Fuyong Wang&lt;/p&gt;&lt;p&gt;Haiyang Wang&lt;/p&gt;&lt;p&gt;Huimin Wang&lt;/p&gt;&lt;p&gt;Jun Wang&lt;/p&gt;&lt;p&gt;Lu Wang&lt;/p&gt;&lt;p&gt;Luqi Wang&lt;/p&gt;&lt;p&gt;Mingquan Wang&lt;/p&gt;&lt;p&gt;Susheng Wang&lt;/p&gt;&lt;p&gt;Xiao Wang&lt;/p&gt;&lt;p&gt;Yukai Wang&lt;/p&gt;&lt;p&gt;Ming Wen&lt;/p&gt;&lt;p&gt;Tao Wen&lt;/p&gt;&lt;p&gt;Fei Wu&lt;/p&gt;&lt;p&gt;Huanyu Wu&lt;/p&gt;&lt;p&gt;Jinwen Wu&lt;/p&gt;&lt;p&gt;Saisai Wu&lt;/p&gt;&lt;p&gt;X","PeriodicalId":100363,"journal":{"name":"Deep Underground Science and Engineering","volume":"3 4","pages":"508-509"},"PeriodicalIF":0.0,"publicationDate":"2024-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/dug2.12137","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143248947","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A review of mechanical deformation and seepage mechanism of rock with filled joints","authors":"Lei Yue,&nbsp;Wei Li,&nbsp;Yu Liu,&nbsp;Shuncai Li,&nbsp;Jintao Wang","doi":"10.1002/dug2.12126","DOIUrl":"https://doi.org/10.1002/dug2.12126","url":null,"abstract":"<p>Various defects exist in natural rock masses, with filled joints being a vital factor complicating both the mechanical characteristics and seepage mechanisms of the rock mass. Filled jointed rocks usually show mechanical properties that are weaker than those of intact rocks but stronger than those of rocks with fractures. The shape of the rock, filling material, prefabricated fissure geometry, fissure roughness, fissure inclination angle, and other factors mainly influence the mechanical and seepage properties. This paper systematically reviews the research progress and findings on filled rock joints, focusing on three key aspects: mechanical properties, seepage properties, and flow properties under mechanical response. First, the study emphasizes the effects of prefabricated defects (shape, size, filling material, inclination angle, and other factors) on the mechanical properties of the rock. The fracture extension behavior of rock masses is revealed by the stress state of rocks with filled joints under uniaxial compression, using advanced auxiliary test techniques. Second, the seepage properties of rocks with filled joints are discussed and summarized through theoretical analysis, experimental research, and numerical simulations, focusing on organizing the seepage equations of these rocks. The study also considers the form of failure under stress–seepage coupling for both fully filled and partially filled fissured rocks. Finally, the limitations in the current research on the rock with filled joints are pointed out. It is emphasized that the specimens should more closely resemble real conditions, the analysis of mechanical indexes should be multi-parameterized, the construction of the seepage model should be refined, and the engineering coupling application should be multi-field–multiphase.</p>","PeriodicalId":100363,"journal":{"name":"Deep Underground Science and Engineering","volume":"3 4","pages":"439-466"},"PeriodicalIF":0.0,"publicationDate":"2024-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/dug2.12126","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143253292","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Applications of artificial intelligence in geothermal resource exploration: A review","authors":"Mahmoud AlGaiar,&nbsp;Mamdud Hossain,&nbsp;Andrei Petrovski,&nbsp;Aref Lashin,&nbsp;Nadimul Faisal","doi":"10.1002/dug2.12122","DOIUrl":"https://doi.org/10.1002/dug2.12122","url":null,"abstract":"<p>Artificial intelligence (AI) has become increasingly important in geothermal exploration, significantly improving the efficiency of resource identification. This review examines current AI applications, focusing on the algorithms used, the challenges addressed, and the opportunities created. In addition, the review highlights the growth of machine learning applications in geothermal exploration over the past decade, demonstrating how AI has improved the analysis of subsurface data to identify potential resources. AI techniques such as neural networks, support vector machines, and decision trees are used to estimate subsurface temperatures, predict rock and fluid properties, and identify optimal drilling locations. In particular, neural networks are the most widely used technique, further contributing to improved exploration efficiency. However, the widespread adoption of AI in geothermal exploration is hindered by challenges, such as data accessibility, data quality, and the need for tailored data science training for industry professionals. Furthermore, the review emphasizes the importance of data engineering methodologies, data scaling, and standardization to enable the development of accurate and generalizable AI models for geothermal exploration. It is concluded that the integration of AI into geothermal exploration holds great promise for accelerating the development of geothermal energy resources. By effectively addressing key challenges and leveraging AI technologies, the geothermal industry can unlock cost-effective and sustainable power generation opportunities.</p>","PeriodicalId":100363,"journal":{"name":"Deep Underground Science and Engineering","volume":"3 3","pages":"269-285"},"PeriodicalIF":0.0,"publicationDate":"2024-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/dug2.12122","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142233178","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The influence of the disturbing effect of roadways through faults on the faults' stability and slip characteristics","authors":"Shuaifeng Lu,&nbsp;Andrew Chan,&nbsp;Xiaolin Wang,&nbsp;Shanyong Wang,&nbsp;Zhijun Wan,&nbsp;Jingyi Cheng","doi":"10.1002/dug2.12119","DOIUrl":"https://doi.org/10.1002/dug2.12119","url":null,"abstract":"<p>In order to mitigate the risk of geological disasters induced by fault activation when roadways intersect reverse faults in coal mining, this paper uses a combination of mechanical models with PFC^2D software. A mechanical model is introduced to represent various fault angles, followed by a series of PFC^2D loading and unloading tests to validate the model and investigate fault instability and crack propagation under different excavation rates and angles. The results show that (1) the theoretical fault model, impacted by roadway advancing, shows a linear reduction in horizontal stress at a rate of −2.01 MPa/m, while vertical stress increases linearly at 4.02 MPa/m. (2) At field excavation speeds of 2.4, 4.8, 7.2, and 9.6 m/day, the vertical loading rates for the model are 2.23, 4.47, 6.70, and 8.93 Pa/s, respectively. (3) Roadway advancement primarily causes tensile-compressive failures in front of the roadway, with a decrease in tensile cracks as the stress rate increases. (4) An increase in the fault angle leads to denser cracking on the fault plane, with negligible cracking near the fault itself. The dominant crack orientation is approximately 90°, aligned with the vertical stress.</p>","PeriodicalId":100363,"journal":{"name":"Deep Underground Science and Engineering","volume":"3 4","pages":"399-412"},"PeriodicalIF":0.0,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/dug2.12119","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143248171","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Geothermal energy for sustainable and green energy supply in the future","authors":"Chunfai Leung,&nbsp;Jianguo Wang,&nbsp;Heping Xie,&nbsp;Xiaozhao Li","doi":"10.1002/dug2.12121","DOIUrl":"https://doi.org/10.1002/dug2.12121","url":null,"abstract":"&lt;p&gt;&lt;i&gt;Deep Underground Science and Engineering&lt;/i&gt; (DUSE) publishes this special issue on geothermal energy. The guest editors of this special issue are Prof. Ranjith Pathegama Gamage (Monash University, Australia), Prof. Zhongwei Huang (China University of Petroleum, Beijing, China), and Prof. Bing Bai (Institute of Rock and Soil Mechanics, Chinese Academy of Sciences, Wuhan, China). Geothermal energy is one sustainable and renewable energy and currently a hot research topic in research and development. Geothermal energy supply is one of the long-term efforts for carbon footprint reductions to tackle climate change issues. The development of geothermal energy includes exploration and extraction processes. This special issue is to highlight the challenges on the exploration and extraction of geothermal energy such as initial high cost and difficulties in heat extraction from deep underground. This special issue focuses on new geothermal extraction system, new theory, new technology, new application of latest techniques such as artificial intelligence, and potential environmental effects.&lt;/p&gt;&lt;p&gt;This special issue publishes 10 articles with authors from different countries. An article is contributed by Chinese researchers on the site investigation for geothermal potential evaluation. They propose an integrated geophysics technique by combining multiple geophysics techniques with a new data processing method and apply it to the site investigation of the geothermal potential in a county. A Finnish researcher publishes an article to highlight the challenges and precautionary measures to overcome the difficulties in deep borehole heat exchanges. An article by US researchers explores possible geothermal-mechanical alternations due to heat exchange and extraction in geothermal systems. This article certainly provides new insights into the geothermal energy research and practice. Researchers from Morocco present a status and prospects article on the development of geothermal energy in their country.&lt;/p&gt;&lt;p&gt;Several interesting articles on geothermal reservoirs appear in this issue. A joint multinational research effort by researchers from the United Kingdom, Belgium, China, and Indonesia reports the results of experiments on fluid-rock interaction for potential carbon storage in geothermal reservoirs. Their experimental results have provided some insightful findings on the subject matter. In addition, a group of researchers from China investigates the impact of well placement and flow rate on production efficiency in fractured geothermal reservoirs. Another group of Chinese researchers provides a state-of-the-art review on research and development for the thermal energy extraction from deep hot dry rock reservoirs. These three articles are certainly useful to researchers and engineers in geothermal energy fields.&lt;/p&gt;&lt;p&gt;An article by Chinese researchers reports the development of a thermal stress loading technique for mechanical tests on hot dry rock. Last b","PeriodicalId":100363,"journal":{"name":"Deep Underground Science and Engineering","volume":"3 3","pages":"255"},"PeriodicalIF":0.0,"publicationDate":"2024-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/dug2.12121","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142233162","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A state-of-the-art review on geothermal energy exploration in Morocco: Current status and prospects","authors":"Redouane Meryem,&nbsp;Khalis Hind,&nbsp;Haissen Faouziya,&nbsp;Sadki Othman,&nbsp;Berkat N. Eddine,&nbsp;Raji Mohammed","doi":"10.1002/dug2.12116","DOIUrl":"https://doi.org/10.1002/dug2.12116","url":null,"abstract":"<p>In the last few decades, addressing the global challenge of implementation of strategies for renewable energy and energy efficiency has become crucial. Morocco, since 2009, has made a steadfast commitment to sustainability, with a particular focus on advancing the development of renewable energy resources. A comprehensive strategy has been formulated, centering on utilizing the country's energy potential to drive progress in this vital sector. Morocco is considered a country with abundant thermal water, indicating deep reservoirs with significant hydrothermal potential. Geothermal zones were selected based on the abundance of hot springs where water temperatures were high and geothermal gradients were significant. The abundance and importance of hot springs, combined with recent volcanism and ongoing non-tectonic activity linked to alpine orogeny, strongly suggest that these regions are promising reservoirs for geothermal energy. This great potential also extends to neighboring countries. In northeast and south Morocco, the temperature of thermal water ranges from 26 to 54°C. This study serves as an inclusive review of the geothermal potentialities in Morocco.</p>","PeriodicalId":100363,"journal":{"name":"Deep Underground Science and Engineering","volume":"3 3","pages":"302-316"},"PeriodicalIF":0.0,"publicationDate":"2024-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/dug2.12116","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142233104","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Evaluation of underground hard rock mine pillar stability using gene expression programming and decision tree-support vector machine models","authors":"Mohammad H. Kadkhodaei,&nbsp;Ebrahim Ghasemi,&nbsp;Jian Zhou,&nbsp;Melika Zahraei","doi":"10.1002/dug2.12115","DOIUrl":"10.1002/dug2.12115","url":null,"abstract":"<p>Assessing the stability of pillars in underground mines (especially in deep underground mines) is a critical concern during both the design and the operational phases of a project. This study mainly focuses on developing two practical models to predict pillar stability status. For this purpose, two robust models were developed using a database including 236 case histories from seven underground hard rock mines, based on gene expression programming (GEP) and decision tree-support vector machine (DT-SVM) hybrid algorithms. The performance of the developed models was evaluated based on four common statistical criteria (sensitivity, specificity, Matthews correlation coefficient, and accuracy), receiver operating characteristic (ROC) curve, and testing data sets. The results showed that the GEP and DT-SVM models performed exceptionally well in assessing pillar stability, showing a high level of accuracy. The DT-SVM model, in particular, outperformed the GEP model (accuracy of 0.914, sensitivity of 0.842, specificity of 0.929, Matthews correlation coefficient of 0.767, and area under the ROC of 0.897 for the test data set). Furthermore, upon comparing the developed models with the previous ones, it was revealed that both models can effectively determine the condition of pillar stability with low uncertainty and acceptable accuracy. This suggests that these models could serve as dependable tools for project managers, aiding in the evaluation of pillar stability during the design and operational phases of mining projects, despite the inherent challenges in this domain.</p>","PeriodicalId":100363,"journal":{"name":"Deep Underground Science and Engineering","volume":"4 1","pages":"18-34"},"PeriodicalIF":0.0,"publicationDate":"2024-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/dug2.12115","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141810545","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}