岩爆柔性防护网力学机理及其智能设计方法研究

Rockburst hazard encountered in underground excavation poses a significant threat to construction facilities and human lives, and its prediction and prevention was always a topic of interest in research and engineering field. The generating process of rockburst has a complex mechanical mechanism, with large uncertainties in its intensity, occurrence time and position. Thus, how to prevent the rockburst and to protect construction facilities and human lives are still open questions; in particular, quantitative assessment of rockburst intensity and exploration of new protection method are significant technical problems that need to be solved urgently in tunnel and underground constructions. This study employs a variety of research methods, such as data collection, in-site investigation, theoretical analysis, physical experiment, numerical modeling and in-site test, to investigate the sizes and velocities of ejected rocks under different geological conditions, and to build a fast and intelligent rock kinetic energy prediction model that considers major control factors. Based on this, we will construct an energy absorption safety netting system, analyze its protection mechanism and dynamic mechanical mechanism. Then, an artificial intelligent deep learning method will be adapted to construct a dynamic design method based on the rock kinetic energy; and this method will be validated and optimized according to in-site test data. Results of this study can fulfill the current insufficient in quantitative assessment of rockburst intensity, provide new energy absorption safety netting system to rockburst protection; and also can provide theoretical and technical supports to underground space construction safety improvement.

地下工程中的岩爆灾害对施工安全构成重大威胁，其预测和防治一直是学术和工程界探索的重大难题。岩爆发生过程的力学机理复杂，其强度大小、发生时间和位置均具有高度不确定性。因此，如何定量描述岩爆强度，探索新型防护方法，有效解决岩爆防治问题是地下工程领域急需解决的重要科技问题。本项目采用资料收集、现场调研、理论分析、物理实验、数值模拟和现场试验等手段，研究不同地质条件下岩爆弹射块体尺寸和速度特征，建立基于主要控制因素的块体动能快速智能预测模型；在此基础上，构建岩爆防治的吸能型柔性防护网体系，研究其防护原理、在冲击作用下的动力响应力学机理；采用人工智能方法，建立基于岩爆块体动能的柔性防护体系智能动态设计方法，并通过现场试验反馈信息验证和优化。研究成果不仅可以填补国内外岩爆强度定量评估方法的不足，而且可以为岩爆灾害防治提供柔性吸能型新方法，为高地应力条件地下工程建设减灾防灾和安全施工提供理论和技术支撑。

我国西南地区地质条件复杂，高地应力环境下深埋硬岩隧道的岩爆灾害问题十分突出，给隧道施工安全构成了重大威胁。本项目凝练出“岩爆柔性防护网力学机理及其智能设计”这一重要科学和技术问题，以巴陕高速公路米仓山隧道为研究背景，通过大量真三轴卸荷室内岩爆物理模型试验、数值模拟试验、全尺寸柔性防护网冲击试验和现场岩爆灾害调查，掌握了岩爆弹射块体尺寸、速度和动能特征，阐明了柔性防护网在不同冲击工况下的力学机理。在此基础上，提出了岩爆弹射块体速度理论计算公式，构建了以钢丝绳网、支撑绳和涨壳式锚杆为主要部件的岩爆柔性防护网系统，提出了具体的设计原型和施工方案。基于动能匹配原则，提出了岩爆柔性防护网智能快速设计方法，并在巴陕高速公路米仓山隧道岩爆段落实现了691.6m的成功应用。相关试验和应用结果表明，本项目提出和构建的岩爆柔性防护网可以达到“轻微岩爆不坏、中等岩爆可修、强烈岩爆不垮塌”的防护目的。.本项目研究成果对我国西部地区深埋长大硬岩隧道开挖过程中的岩爆灾害防护具有重要的理论意义和应用价值。项目组在《Rock Mechanics and Rock Engineering》、《Engineering Geology》、《岩石力学与工程学报》、《岩土力学》等权威杂志发表SCI论文14篇，EI论文5篇，申请和授权专利10项，软件著作权3项。.研究成果已经在四川省巴陕高速公路米仓山隧道建设中得到实际应用，成果获得省部级科学技术奖2项，培养博士研究生1名、硕士研究生2名，实现了项目的预期目标。研究成果提高了我国重大地下工程地质灾害防治水平，促进了岩爆地质灾害防护理论的发展，产生了良好的社会和经济效益。