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

University Of Utah, Salt Lake City UT

Investigators

Abstract

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.