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This paper investigates and presents the numerical modeling and validation of the response of a uniform clean sand using monotonic and cyclic laboratory tests as well as a centrifuge model test comprised of a submerged slope. The dynamic response of the sand is modeled using a critical state compatible, stress ratio-based, bounding surface plasticity constitutive model (PM4Sand), implemented in the commercial finite-difference platform FLAC, and PM4Sand’s performance is evaluated against a comprehensive testing program comprised of laboratory data and a well-instrumented centrifuge model test. Three different calibrations informed by the lab and centrifuge data are performed and the goodness of the predictions is discussed. Conclusions are drawn with regards to the performance of the simulations against the laboratory and centrifuge data, and recommendations about the calibration of the model are provided.
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Cone Penetration Testing to Constrain the Calibration Process of a Sand Plasticity Model for Nonlinear Deformation Analysis
A reliable prediction of liquefaction-induced damage typically requires nonlinear deformation analyses with an advanced constitutive soil model calibrated to the site conditions. The calibration of constitutive models can be performed by relying primarily on a combination of commonly available properties and empirical or semi-empirical relationships, on laboratory tests on site-specific soils, on in-situ penetration tests, or a combination thereof. Chiaradonna et al. (2022) described a laboratory-based calibration approach of the PM4Sand constitutive model and evaluated the prediction accuracy against the response of a centrifuge experiment of a submerged slope. This paper addresses an alternate calibration approach in which the PM4Sand model is calibrated using centrifuge in-situ CPT data. The model performance for the resulting calibration is evaluated against the centrifuge experimental data and prior simulations from Chiaradonna et al. (2022). In this case, the CPT-based calibration resulted in more accurate estimations of the dynamic response and permanent displacements.
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- PAR ID:
- 10335420
- Date Published:
- Journal Name:
- Cone Penetration Testing 2022
- Page Range / eLocation ID:
- 325-331
- 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
- Conference Paper:
- https://doi.org/10.1201/9781003308829-43
