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Sinkhole collapse may result in significant property damage and even loss of life. Early detection of sinkhole attributes (buried voids, raveling zones) is critical to limit the cost of remediation. One of the most promising ways to obtain subsurface imaging is 3D seismic full-waveform inversion. For demonstration, a recently developed 3D Gauss-Newton full-waveform inversion (3D GN-FWI) method is used to detect buried voids, raveling soils, and characterize variable subsurface soil/rock layering. It is based on a finite-difference solution of 3D elastic wave equations and Gauss-Newton optimization. The method is tested first on a data set constructed from the numerical simulation of a challenging synthetic model and subsequently on field data collected from two separate test sites in Florida. For the field tests, receivers and sources are placed in uniform 2D surface grids to acquire the seismic wavefields, which then are inverted to extract the 3D subsurface velocity structures. The inverted synthetic results suggest that the approach is viable for detecting voids and characterizing layering. The field seismic results reveal that the 3D waveform analysis identified a known manmade void (plastic culvert), unknown natural voids, raveling, as well as laterally variable soil/rock layering including rock pinnacles. The results are confirmed later by standard penetration tests, including depth to bedrock, two buried voids, and a raveling soil zone. Our study provides insight into the application of the 3D seismic FWI technique as a powerful tool in detecting shallow voids and other localized subsurface features.
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Centrifuge and Numerical Modeling of the Seismic Response of Buried Water Supply Reservoirs
Buried water reservoirs are increasingly being built to replace open aboveground municipal water supply reservoirs in urban areas to enhance water quality and utilize their surface footprint for other purposes such as public parks or placement of solar arrays. Many of these lifeline structures are in seismically active regions and, as such, need to be designed to remain operational after severe earthquake shaking. However, evaluating their seismic response is challenging and involves accounting for the interaction of the structure with the stored fluid and the retained soil; in other words, accounting for fluid–structure–soil interaction (FSSI). This paper presents a combined experimental–numerical study on the seismic behavior of buried water reservoirs while considering FSSI. Two series of centrifuge model tests were performed at different reservoir orientations to investigate one-dimensional (1D) and two-dimensional (2D) motion effects under full, half-full, and empty reservoir conditions. Corresponding numerical models were developed whereby the structure and the soil were represented by continuum Lagrangian finite elements, while the fluid was modeled via Arbitrary Lagrangian Eulerian formulation. Soil–structure and fluid–structure interface parameters were calibrated using the experimental measurements. The simulations successfully captured the measured reservoir responses in terms of accelerations, bending moment increments, and water pressures. The study found that the common assumption of plane strain is not applicable for reservoirs because their behavior was found to be truly three-dimensional (3D) whereby stresses accumulated at the corners. Furthermore, the full reservoir resulted in the highest seismic demands in the reservoir walls and roof while the empty reservoir yielded the highest base slippage. The study demonstrates that the complex reservoir seismic response is best captured by carrying out a 3D FSSI numerical simulation.
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- Award ID(s):
- 1763129
- PAR ID:
- 10483226
- Publisher / Repository:
- American Society of Civil Engineers
- Date Published:
- Journal Name:
- Journal of Geotechnical and Geoenvironmental Engineering
- Volume:
- 150
- Issue:
- 3
- ISSN:
- 1090-0241
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1061/JGGEFK.GTENG-11758
