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Advanced monitoring of tailings dam performance using seismic noise and stress models

Earth Sciences

Advanced monitoring of tailings dam performance using seismic noise and stress models

S. M. Ouellet, J. Dettmer, et al.

Discover groundbreaking advancements in dam monitoring with ambient noise interferometry (ANI). This research, conducted by Susanne M. Ouellet, Jan Dettmer, Gerrit Olivier, Tjaart DeWit, and Matthew Lato, showcases how seismic velocity changes correlate with water levels, providing vital insights into dam performance over time.

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~3 min • Beginner • English
Abstract
Tailings dams retain the waste by-products of mining operations and are among the world's largest engineered structures. Recent tailings dam failures highlight important gaps in current monitoring methods. Here we demonstrate how ambient noise interferometry can be applied to monitor dam performance at an active tailings dam using a geophone array. Seismic velocity changes of less than 1% correlate strongly with water level changes at the adjacent tailings pond. We implement a power-law relationship between effective stress and shear wave velocity, using the pond level recordings with shear wave velocity profiles obtained from cone penetration tests to model changes in shear wave velocities. The resulting one-dimensional model shows good agreement with the seismic velocity changes. As shear wave velocity provides a direct measure of soil stiffness and can be used to infer numerous other geotechnical design parameters, this method provides important advances in understanding changes in dam performance over time.
Publisher
Communications Earth & Environment
Published On
Nov 30, 2022
Authors
Susanne M. Ouellet, Jan Dettmer, Gerrit Olivier, Tjaart DeWit, Matthew Lato
Tags
tailings dam failures
monitoring methods
ambient noise interferometry
seismic velocity
effective stress
shear wave velocity
dam performance
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