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The stress-strain behavior of Ottawa F65 sand is investigated through an extensive series of constant volume stress-controlled cyclic direct simple shear (CDSS) tests performed at different densities, overburden pressures, and static shear stresses prior to cyclic shearing to quantify their effects on the cyclic strength of Ottawa F65 sand. Results of the CDSS tests are used in the constitutive model calibration exercise for the Liquefaction Experiments and Analysis Project (LEAP-2022). The collected database of CDSS tests is used to develop an Artificial Neural Network (ANN) model capable of predicting Ottawa F65 liquefaction strength for a specified set of relative density, overburden pressure, static shear stress ratio, and cyclic shear stress ratio. After training, validation and testing, the ANN model is further assessed using blind prediction of the liquefaction strength in new CDSS tests for a relative density and overburden stress that are not available in the training dataset. CDSS tests under similar conditions were then carried out in the laboratory for validation of the ANN model. The comparisons of the predictions with the experimental results have demonstrated the ANN model predictive capability for liquefaction strength and its sensitivity to changes in relative density, overburden stress and cyclic stress ratio. 

The stress-strain behavior and liquefaction strength of Ottawa F65 sand was investigated through an extensive series of cyclic direct simple shear (CDSS) tests. The study quantified the effects of static shear stress on the cyclic strength of Ottawa F65 sand. The database of CDSS tests was used to develop an Artificial Neural Networks model to predict Ottawa F65 cyclic strength. 

The stress-strain behavior and liquefaction strength of Ottawa F65 sand was investigated through an extensive series of cyclic direct simple shear (CDSS) tests. The study quantified the effects of relative density on the cyclic strength of Ottawa F65 sand. The database of CDSS tests was used to develop an Artificial Neural Networks model to predict Ottawa F65 cyclic strength. 

The stress-strain behavior and liquefaction strength of Ottawa F65 sand was investigated through an extensive series of cyclic direct simple shear (CDSS) tests. The study quantified the effects of overburden stress on the cyclic strength of Ottawa F65 sand. The database of CDSS tests was used to develop an Artificial Neural Networks model to predict Ottawa F65 cyclic strength. 

Cyclic triaxial strain controlled tests conducted to study the liquefaction strength of Ottawa F65 sand at three different densities. The dataset may be used in the assessment of the performance of current and future constitutive models for sands. 

Constitutive modeling of granular materials such as sands, non-plastic silts, and gravels has been significantly advanced in the past three decades. Several new constitutive models have been proposed and calibrated to simulate the results of various laboratory element tests. Due to this progress and owing to the surge of interest in geotechnical engineering community to use well-documented constitutive models in major geotechnical projects, a more thorough evaluation of these models is necessary. Performance of the current models should be particularly evaluated in the simulation of boundary value problems where stress/strain paths are much more complex than the element tests performed in laboratory. Such validation efforts will be an important step towards the use of these models in practice. This paper presents the results of an extensive validation study aimed at assessing the capabilities and limitations of a two-surface plasticity model for sands in two selected boundary value problems, i.e. lateral spreading of mildly sloping liquefiable grounds. The results of a large number of centrifuge tests conducted during the course of four consecutive international projects known as Liquefaction Experiments and Analysis Project (LEAP) are used in this validation study. The capabilities and limitations of the two-surface plasticity model, initially calibrated against element tests, will be carefully assessed by comparing the numerical simulations with the results of the centrifuge tests from recent LEAP projects. 

Cyclic direct simple shear tests were conducted to study the liquefaction-induced permanent deformations caused by non-uniform shear stress waves which mimic the acceleration time histories used in the LEAP centrifuge experiments. The experiments reported here were used as the basis for evaluation of a number of leading constitutive models for sands during LEAP-2020 type-A prediction exercise. The dataset may be used in the assessment of the performance of current and future constitutive models for sands. 

Cyclic response of Ottawa F65 Sand was investigated in constant-volume Direct Simple Shear tests. The resulting experimental data were used in the calibration of a number of leading constitutive models for sands during the LEAP-2020 prediction exercise. The dataset may be used in the assessment of the performance of current and future constitutive models for sands.