Sustainability for Disaster Mitigation in Underground Engineering
A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Sustainable Engineering and Science".
Deadline for manuscript submissions: 31 August 2025 | Viewed by 1725
Special Issue Editors
Interests: digital rock and soil mechanics under extreme environments; nonlinear numerical methods for rock mass; monitoring simulation and digital twin technology for rock mass; disaster prevention and control methods for deep engineering; space rock mechanics and engineering
Interests: research on in situ microseismic/acoustic emission monitoring technology and analysis methods for the fracturing process of deep rock masses; study on the mechanisms and control technologies of fracturing disaster initiation processes in deep hard rock engineering
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Interests: rock and soil mechanics; deep underground excavations; tunnelling; environmental geotechnical engineering; mechanical modelling; microbial induced calcium carbonate precipitation (MICP); microstructure failure; analysis; machine learning; damage mechanics; weak interlayer zones
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The increasing scale and complexity of underground engineering projects have amplified the challenges associated with predicting and mitigating geological disasters, which pose significant risks to safety, economic stability, and environmental sustainability. As underground environments become more extreme—characterized by high stress, temperature, and pressure conditions—the demand for innovative solutions is more critical than ever. This Special Issue focuses on developing advanced systems for disaster prediction, early warning, and adaptive control in underground engineering, aiming to minimize the occurrence and impact of hazards such as engineering disasters, earthquakes, landslides, and collapses. By integrating novel technologies like artificial intelligence (AI), digital twins, and IoT-enabled sensor networks, these systems provide real-time monitoring, predictive modeling, and dynamic risk management solutions. These advancements not only enhance the safety and longevity of underground structures but also support sustainable practices by reducing environmental footprints, promoting efficient resource utilization, and ensuring the long-term stability of underground projects in harmony with surrounding ecosystems.
This Special Issue invites cutting-edge research and innovative technological applications related to disaster prediction, early warning, structural stability, and sustainable development in underground engineering. We encourage the submission of original research and review articles focusing on intelligent disaster prevention and control, stability analysis of underground structures, collaborative protection of resources and environments, as well as green materials and low-carbon construction technologies. Emphasis will be placed on how advanced tools such as AI, big data analytics, digital twin technology, and sensor networks can enhance disaster warning and response capabilities while promoting sustainable underground space development.
Topics of interest include, but are not limited to, the following:
- Advanced predictive modeling and early warning systems for geological hazards in underground engineering, utilizing geological surveys, sensor networks, and big data analytics.
- Research on the long-term stability of underground structures under extreme conditions (high stress, temperature, and pressure), employing digital geomechanics simulations for dynamic assessments.
- Collaborative protection of groundwater resources and geological environments, emphasizing sustainable practices to prevent over-exploitation and contamination during underground construction.
- Adaptive control technologies for managing underground geological hazards, investigating the dynamic response mechanisms of soils and rocks to external disturbances or sudden geological events.
- Strategies for reusing and restoring abandoned underground spaces, transforming them into functional facilities while mitigating ecological damage.
- Development of green materials and low-carbon construction techniques to minimize carbon emissions and environmental impact throughout the construction process.
- Dynamic repair and reinforcement strategies for underground structures post-disaster, ensuring rapid recovery and reducing the risk of secondary disasters.
- Risk assessment of geological hazards associated with underground energy storage, integrating storage technologies with geomechanical analysis to ensure safety and stability.
We welcome original research articles and reviews on the following areas (and related topics):
- Integration of AI and machine learning in disaster prediction and management systems for underground engineering.
- Real-time monitoring systems employing digital twin technology for effective hazard response in underground construction projects.
- Water-hydrology-mechanics coupled models for optimizing excavation techniques and wastewater treatment to promote sustainable coexistence with water resources.
- Use of intelligent materials and self-healing technologies to enhance the resilience of underground structures during and after disasters.
- Case studies demonstrating successful implementation of green engineering practices in underground construction and restoration projects.
- Evaluation of new materials for low-carbon construction that contribute to the sustainability of underground engineering.
We look forward to your contributions.
Dr. Zhaofeng Wang
Dr. Yaxun Xiao
Prof. Dr. Shuqian Duan
Guest Editors
Manuscript Submission Information
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Keywords
- underground engineering
- geological disasters
- digital technologies
- artificial intelligence
- sustainable development
- digital twins
- risk assessment
- real-time monitoring
- IoT (Internet of Things)
- machine learning
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