Rock Slope Instability Characterization and Progressive Failure Monitoring from in situ Ambient Resonance Data

滑坡在世界范围内对基础设施造成重大破坏和生命损失，因此需要改进方法来更好地减轻滑坡的危害和风险。边坡稳定性表征和监测是危害分析的核心，但许多常用的技术都是昂贵和侵入性的，或者只能提供单一点的信息。研究人员将在岩石边坡不稳定地点使用环境振动测量，为滑坡结构表征和渐进破坏监测创造新的概念和实用方法。这些方法基于结构动力学的概念，其中计算和监测边坡不稳定的共振特性，揭示滑坡结构组成的独特信息，并提供新的指标来预测破坏时间。研究人员还将使用数值模拟来测试滑坡破坏类型对预测共振响应的作用，从而产生新的理论认识，帮助解释现场数据，并为未来在其他地点应用该技术提供指导。不稳定岩质边坡的共振特性随着几何形状、材料特性和边界条件的变化而变化，这为基于现场环境振动测量的非侵入式边坡稳定性表征和监测奠定了基础。研究人员将进行一系列实验，旨在探索如何使用现场环境振动数据来解释岩质边坡不稳定的结构条件，包括深度边界条件，并监测和解释随时间推移的渐进破坏。他们假设，将现场环境振动数据与3D特征频率模型一起解释，可以改进岩质边坡不稳定性的材料、动力和结构特性的表征，并且环境共振监测提供独特的信息，有助于边坡稳定性危害评估和破坏时间预测。研究人员将使用现场实验和数值模型相结合的方法来验证这些假设。从环境振动阵列部署的现场测量数据，结合数值模拟进行解释，用于开发表征岩石边坡不稳定的结构特性和边界条件的新方法，支持改进的危害评估。同时，对两个现场产生的环境振动监测数据进行了分析，以开发精细的分析，能够区分环境驱动漂移中与渐进破坏相关的细微频率变化。最后，通过一系列数值实验，对斜坡运动学如何影响渐进式破坏过程中的共振频率演变进行了新的概念理解，并将共振监测与破坏指标结合起来解释，以证明环境振动数据如何用于破坏时间预测。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

Landslides cause significant damage to infrastructure and loss of life worldwide, and thus improved approaches are needed to better mitigate landslide hazards and risk. Slope stability characterization and monitoring form the core of hazard analysis, yet many commonly used techniques are costly and invasive, or only provide information at a single point. The investigators will use ambient vibration measurements at rock slope instability sites to create new conceptual and practical approaches for landslide structural characterization and progressive failure monitoring. These approaches are based on concepts of structural dynamics, where the resonance properties of slope instabilities are computed and monitored over time, revealing unique information on landslide structural composition and providing new metrics to anticipate the time of failure. The investigators will also use numerical simulations to test the role of landslide failure type on the predicted resonance response, generating new theoretical understanding aiding interpretation of field data and providing guidance for future application of the technique at other sites.The resonance properties of an unstable rock slope vary with geometry, material properties, and boundary conditions, creating the foundation for non-invasive slope stability characterization and monitoring based on in situ ambient vibration measurements. The investigators will conduct a suite of experiments designed to explore how in situ ambient vibration data can be used to interpret the structural conditions of rock slope instabilities, including boundary conditions at depth, and monitor and interpret progressive failure over time. They hypothesize that in situ ambient vibration data interpreted together with 3D eigenfrequency models allows improved characterization of the material, dynamic and structural properties of rock slope instabilities, and that ambient resonance monitoring provide unique information aiding slope stability hazard assessment and time-of-failure prediction. The investigators will test these hypotheses using a combination of field experiments and numerical models. Field measurements from ambient vibration array deployments, interpreted together with numerical simulations, are used to develop a new approach for characterizing the structural properties and boundary conditions of rock slope instabilities, supporting improved hazard assessment. Meanwhile, ambient vibration monitoring data generated at two field sites are analyzed to develop refined analyses able to distinguish subtle frequency changes associated with progressive failure amidst environmentally-driven drifts. Finally, a series of numerical experiments are used to develop new conceptual understanding of how slope kinematics influence resonant frequency evolution during progressive failure, and interpret failure metrics in tandem with resonance monitoring to demonstrate how ambient vibration data may be used for time-of-failure forecasting.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.