Undrained Seismic Compression of Unsaturated Sand

Rong, Wenyong; McCartney, John S.

doi:10.1061/(asce)gt.1943-5606.0002420

Cited by 19 publications

(31 citation statements)

References 35 publications

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“…that were modeled in this study Table 3: Summary of initial testing conditions and final shear strain for the undrained cyclic simple shear experiments (after Rong and McCartney 2020b).…”

Section: List Of Figuresmentioning

confidence: 99%

“…Drainage conditions for the pore fluids in a soil is known to have a major effect on the seismic shearing response. The pore air and water pressures may change during this process during undrained shearing, which may occur in a soil layer with no drainage boundaries or when the rate of shearing is faster than the rate of pore fluid drainage (Okamura and Soga 2006;Unno et al 2008;Okamura and Noguchi 2009;Rong and McCartney 2020b). Regardless of the drainage conditions, the degree of saturation is expected to increase as the volume of voids decreases McCartney 2020a, 2020b).…”

Section: Research Motivationmentioning

confidence: 99%

“…However, there are cases where unsaturated soils with relatively high initial degrees of saturation can still liquefy under seismic excitation (Unno et al 2008). In unsaturated soils with lower initial degrees of saturation, seismic compression is expected during strong shaking by earthquakes with shear strain amplitudes greater than the cyclic threshold shear strain (Stewart et al 2004, Rong and McCartney 2019, 2020b. Earthquakes and aftershocks often have rapid shearing with short durations that can lead to undrained conditions even for sands.…”

Section: Seismic Compression Of Unsaturated Soils In Literaturementioning

confidence: 99%

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Hyperbolic Hydro-mechanical Model for Seismic Compression Prediction of Unsaturated Soils in the Funicular Regime

Kinikles¹,

McCartney²

2022

PEER Reports

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A semi-empirical elasto-plastic constitutive model with a hyperbolic stress-strain curve was developed with the goal of predicting the seismic compression of unsaturated sands in the funicular regime of the soil-water retention curve (SWRC) during undrained cyclic shearing. Using a flow rule derived from energy considerations, the evolution in plastic volumetric strain (seismic compression) was predicted from the plastic shear strains of the hysteretic hyperbolic stress-strain curve. The plastic volumetric strains are used to predict the changes in degree of saturation from phase relationships and changes in pore air pressure from Boyle’s and Henry’s laws. The degree of saturation was used to estimate changes in matric suction from the transient scanning paths of the SWRC. Changes in small-strain shear modulus estimated from changes in mean effective stress computed from the constant total stress and changes in pore air pressure, degree of saturation and matric suction, in turn affect the hyperbolic stress-strain curve’s shape and the evolution in plastic volumetric strain. The model was calibrated using experimental shear stress-strain backbone curves from drained cyclic simple shear tests and transient SWRC scanning path measurements from undrained cyclic simple shear tests. Then the model predictions were validated using experimental data from undrained cyclic simple shear tests on unsaturated sand specimens with different initial degrees of saturation in the funicular regime. While the model captured the coupled evolution in hydro-mechanical variables (pore air pressure, pore water pressure, matric suction, degree of saturation, volumetric strain, effective stress, shear modulus) well over the first 15 cycles of shearing, the predictions were less accurate after continued cyclic shearing up to 200 cycles. After large numbers of cycles of undrained shearing, a linear decreasing trend between seismic compression and initial degree of saturation was predicted from the model while a nonlinear increasing-decreasing trend was observed in the cyclic simple shear experiments. This discrepancy may be due to not considering post shearing reconsolidation in the model, calibration of model parameters, or experimental issues including a drift in the position of the hysteretic shear-stress strain curve. Nonetheless, the trend from the model is consistent with predictions from previously- developed empirical models in the funicular regime of the SWRC. The developments of the new mechanistic model developed in this study will play a key role in the future development of a holistic model for predicting the seismic compression across all regimes of the SWRC.

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“…that were modeled in this study Table 3: Summary of initial testing conditions and final shear strain for the undrained cyclic simple shear experiments (after Rong and McCartney 2020b).…”

Section: List Of Figuresmentioning

confidence: 99%

Section: Research Motivationmentioning

confidence: 99%

Section: Seismic Compression Of Unsaturated Soils In Literaturementioning

confidence: 99%

See 1 more Smart Citation

Hyperbolic Hydro-mechanical Model for Seismic Compression Prediction of Unsaturated Soils in the Funicular Regime

Kinikles¹,

McCartney²

2022

PEER Reports

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show abstract

“…The stress-strain relationships are highly nonlinear and path-dependent due to coupling effects of changes in volume, matric suction, degree of saturation, effective stress, shear modulus, etc. [75]. Modeling such path-dependent material behaviors by a phenomenological approach is challenging and complicated, which often relies on certain phenomenological ISVs.…”

Section: Modeling Soil Under Cyclic Shear Loadingmentioning

confidence: 99%

Thermodynamically Consistent Machine-Learned Internal State Variable Approach for Data-Driven Modeling of Path-Dependent Materials

He,

Chen

2022

Preprint

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Characterization and modeling of path-dependent behaviors of complex materials by phenomenological models remains challenging due to difficulties in formulating mathematical expressions and internal state variables (ISVs) governing path-dependent behaviors. Data-driven machine learning models, such as deep neural networks and recurrent neural networks (RNNs), have become viable alternatives. However, pure black-box data-driven models mapping inputs to outputs without considering the underlying physics suffer from unstable and inaccurate generalization performance. This study proposes a machinelearned physics-informed data-driven constitutive modeling approach for pathdependent materials based on the measurable material states. The proposed data-driven constitutive model is designed with the consideration of universal thermodynamics principles, where the ISVs essential to the material pathdependency are inferred automatically from the hidden state of RNNs. The RNN describing the evolution of the data-driven machine-learned ISVs follows the thermodynamics second law. To enhance the robustness and accuracy of RNN models, stochasticity is introduced to model training. The effects of the number of RNN history steps, the internal state dimension, the model complexity, and the strain increment on model performances have been investigated. The effectiveness of the proposed method is evaluated by modeling soil material behaviors under cyclic shear loading using experimental stress-strain data.

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“…Contact problems are highly non-linear and one of the most challenging problems in computational mechanics (Wriggers and Laursen, 2006). Compared to materials such as steel, soils often exhibit a very limited elasticity range and their behavior depends on factors such as the presence of water inside their pores, hydraulic hysteresis, shear strain amplitude, and drainage conditions (Khosravi and McCartney, 2012, Kodikara et al, 2018, Dong et al, 2018, Rong and McCartney, 2021, Rong and McCartney, 2020. Including these aspects in geotechnical analyses increases the degree of nonlinearity.…”

Section: Introductionmentioning

confidence: 99%

Improving Efficiency, Stability, and Accuracy of Finite Element Solutions for Solving Dynamic Contact Problems Involving Unsaturated Soils

Ghorbani

Chen

Kodikara

et al. 2022

Challenges and Innovations in Geomechanics

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The paper investigates the efficiency, stability, and accuracy of finite element solutions based on the mortar approach in solving dynamic contact problems that involve unsaturated soils. We employ a fully coupled finite element solution and a recently developed bounding surface model for describing the hydro-mechanical hysteresis of unsaturated soils. The paper discusses a key source of instability in numerical simulations of this class of problems which is stress overshooting. We evaluate the efficiency of a solution for this problem and discuss the impact of this solution on improving the accuracy and stability of numerical simulations. Numerical simulations are presented for verification and analysis of efficiency, stability, and accuracy.

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Undrained Seismic Compression of Unsaturated Sand

Cited by 19 publications

References 35 publications

Hyperbolic Hydro-mechanical Model for Seismic Compression Prediction of Unsaturated Soils in the Funicular Regime

Hyperbolic Hydro-mechanical Model for Seismic Compression Prediction of Unsaturated Soils in the Funicular Regime

Thermodynamically Consistent Machine-Learned Internal State Variable Approach for Data-Driven Modeling of Path-Dependent Materials

Improving Efficiency, Stability, and Accuracy of Finite Element Solutions for Solving Dynamic Contact Problems Involving Unsaturated Soils

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