Scholarlink

<p>This book provides an integrated view of underground and geotechnical engineering, combining experimental, numerical, and field studies on rock mechanics, tunnel design, mining hazards, slope stability, and subsurface storage. Studies on brittle and sedimentary rocks under thermal, dynamic, and stress conditions reveal dilation, anisotropy, and fracture processes, supported by simulations of rockburst risk, EDZs, and stress redistribution. Case studies from Indian hydroelectric and mining projects showcase site-specific designs, reinforced soil technologies, and hazard mitigation in Himalayan strata. Topics include CO₂/hydrogen storage in lined caverns, hydrogeological confinement, and seepage control. Monitoring and safety are enhanced by infrared thermography, acoustic emission, and blast vibration analysis. AI-driven modeling for discontinuity mapping, stress prediction, and support optimization underscores the growing role of data-driven intelligence in resilient underground infrastructure.&#xa0;</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Advances in Rock Mechanics—Infrastructure Development, Volume 4

  • 会议论文集

  • 发表日期：

    2026年

查看全文

摘要

This book provides an integrated view of underground and geotechnical engineering, combining experimental, numerical, and field studies on rock mechanics, tunnel design, mining hazards, slope stability, and subsurface storage. Studies on brittle and sedimentary rocks under thermal, dynamic, and stress conditions reveal dilation, anisotropy, and fracture processes, supported by simulations of rockburst risk, EDZs, and stress redistribution. Case studies from Indian hydroelectric and mining projects showcase site-specific designs, reinforced soil technologies, and hazard mitigation in Himalayan strata. Topics include CO₂/hydrogen storage in lined caverns, hydrogeological confinement, and seepage control. Monitoring and safety are enhanced by infrared thermography, acoustic emission, and blast vibration analysis. AI-driven modeling for discontinuity mapping, stress prediction, and support optimization underscores the growing role of data-driven intelligence in resilient underground infrastructure.