隧道突水突泥灾变机理研究现状及发展趋势

Catastrophic Mechanisms and Research Development Trends of Water and Mud Inrushes in Tunnels

  • 摘要: 为深化对隧道及地下工程突水突泥形成机制的科学认知,从地质发育特征及致灾构造分类、破坏失稳模式、最小安全厚度、多场信息演化规律4个层面,综述突水突泥灾害地质发育特征及前兆信息,确立在水压和爆破共同作用下防突岩体最小安全厚度计算方法,探讨数值模拟及模型试验等研究方法及其存在的问题,并展望多场耦合动力灾害机理研究的未来发展趋势。研究表明,突水突泥致灾构造可划分为岩溶类、断层类、特殊地质类;隧道施工临近突水突泥致灾构造时,会存在岩体呈铁锈状或湿化、剥落块增多、渗流水量增大且含泥砂等地质前兆;突水突泥发生时,岩体温度、渗压、电阻率等参数突降,微震、位移等参数突增;连续-非连续多尺度流固耦合模拟分析方法、真三轴地质力学可视化物理模型试验技术和基于人工智能解译多源异构前兆信息的融合分析是未来灾变演化机理研究的发展方向。

     

    Abstract: This study systematically investigates the formation mechanisms of water-mud inrushes in tunnel and underground engineering through comprehensive analysis of geological development characteristics, disaster-causing structure classification, failure modes, minimum safe thickness calculations, and multi-field information evolution patterns. The research summarizes the geological development characteristics and geological precursor information of water and mud inrush, establishes a computational method for determining the minimum safe thickness of inrushresistan rock masses under combined water pressure and blasting loads, while critically examining current research methodologies including numerical simulations and physical model tests along with their limitations. Key findings reveal that disaster-causing structures can be categorized into karst-type, fault-type, and special geological types.Distinct precursor signals are identified during tunnel construction near these structures, including rust-colored or wetted rock masses, increased spalling, and muddy seepage flows with sediment content. The onset of water-mud inrushes is characterized by abrupt decreases in rock temperature, seepage pressure and resistivity, coupled with sudden increases in microseismic activity and displacement monitoring data. The study highlights three emerging research directions for catastrophic evolution mechanism: continuum-discontinuum multiscale fluid-solid coupling analysis methods, true triaxial geomechanical visualization physical model testing techniques, and artificial intelligence interpretation-based fusion analysis of multi-source heterogeneous precursor information.

     

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