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This paper presents a summary of the element test simulations (calibration simulations) submitted by 11 numerical simulation (prediction) teams that participated in the LEAP-2017 prediction exercise. A significant number of monotonic and cyclic triaxial (Vasko, An investigation into the behavior of Ottawa sand through monotonic and cyclic shear tests. Masters Thesis, The George Washington University, 2015; Vasko et al., LEAP-GWU-2015 Laboratory Tests. DesignSafe-CI, Dataset, 2018; El Ghoraiby et al., LEAP 2017: Soil characterization and element tests for Ottawa F65 sand. The George Washington University, Washington, DC, 2017; El Ghoraiby et al., LEAP-2017 GWU Laboratory Tests. DesignSafe-CI, Dataset, 2018; El Ghoraiby et al., Physical and mechanical properties of Ottawa F65 Sand. In B. Kutter et al. (Eds.), Model tests and numerical simulations of liquefaction and lateral spreading: LEAP-UCD-2017. New York: Springer, 2019) and direct simple shear tests (Bastidas, Ottawa F-65 Sand Characterization. PhD Dissertation, University of California, Davis, 2016) are available for Ottawa F-65 sand. The focus of this element test simulation exercise is to assess the performance of the constitutive models used by participating team in simulating the results of undrained stress-controlled cyclic triaxial tests on Ottawa F-65 sand for three different void ratios (El Ghoraiby et al., LEAP 2017: Soil characterization and element tests for Ottawa F65 sand. The George Washington University, Washington, DC, 2017; El Ghoraiby et al., LEAP-2017 GWU Laboratory Tests. DesignSafe-CI, Dataset, 2018; El Ghoraiby et al., Physical and mechanical properties of Ottawa F65 Sand. In B. Kutter et al. (Eds.), Model tests and numerical simulations of liquefaction and lateral spreading: LEAP-UCD-2017. New York: Springer, 2019). The simulated stress paths, stress strain responses, and liquefaction strength curves show that majority of the models used in this exercise are able to provide a reasonably good match to liquefaction strength curves for the highest void ratio (0.585) but the differences between the simulations and experiments become larger for the lower void ratios (0.542 and 0.515).

Fugro participated in the Liquefaction Experiment and Analysis Projects (LEAP) by performing numerical simulations using two different constitutive models implemented in the software FLAC. Fugro developed a calibration framework based on soil-specific laboratory test data considering multiple elements of dynamic response such as liquefaction triggering criteria (i.e., number of cycles to a specified strain and pore pressure ratio threshold) as well as post-triggering strain accumulation rate. The calibrated model parameters were subsequently used to obtain “Type B (blind)” predictions of the centrifuge experiments with the opportunity to refine after the centrifuge results were provided (Type C simulations). Overall, Fugro’s blind predictions captured the centrifuge test responses well with small refinements needed during Type C simulations. Estimated deformations were within a factor of about two compared to the observed. The overall good comparison provides confidence in the proposed calibration framework, which can be implemented and used for different sand types and project conditions.

This paper describes the numerical sensitivity study requested prior to the December 2017 LEAP workshop. Several but not all of the simulation teams participated in this sensitivity study. The results of the sensitivity study are used to begin to map out the simulation response surfaces that relate residual displacement to PGAeff and relative density. The simulation response surfaces are compared to the corresponding response surfaces determined by nonlinear regression of the centrifuge test data. The definition of the experimental response surface allows a means to objectively reduce the influence of outliers in the experiment dataset. The residuals between the experiments and the regression surface are used to quantify the uncertainty associated with experiment-experiment variability. Some metrics for assessing the comparison between simulations and experiments are explored; it is suggested that differences in the logarithm of displacement are more meaningful than arithmetic differences. As expected, some models predicted the average displacement well and some predicted triggering of liquefaction and the shape of the response function better than others. LEAP-UCD-2017 is not a final assessment of simulation procedures; instead, the results can be used to improve simulation specifications and calibration procedures and as a stimulus for more careful review of simulation results before they are submitted.