LEAP Databases for Verification , Validation , and Calibration of Codes for Simulation of Liquefaction

This paper introduces LEAP, Liquefaction Experiments and Analysis Projects, intended to facilitate validation and verification of numerical procedures for liquefaction analysis. The protocols and information necessary are organized and archived in a set of databases that contain the specifications for validation exercises and experimental data for calibration of constitutive models. The structure of the database is explained and the utility is demonstrated by populating the database with results from LEAP GWU 2015, an exercise that duplicated one liquefaction lateral spreading experiment on six different centrifuge facilities on three different continents. This data has already been used for Class A validation exercises and is also currently being used for class B validation exercises. The archived data will remain as a reference for future calibration exercises. Most importantly, a protocol is being established that will be useful in future validation exercises. Introduction to LEAP and PLEAP LEAP (Liquefaction Experiments and Analysis Projects) is an international collaborative project with a primary goal to develop a protocol for verification, calibration, and validation of numerical simulations used for analysis of liquefaction problems (Manzari et al. 2014). In addition to being a rigorous evaluation that is satisfying to simulation specialists, another goal of LEAP is to ensure that the limitations and scope of the validation and verification are understandable and conclusive for the engineers that use the results of the simulations as well as to decision makers that act on the results. PLEAP is a planning project funded under the Network for Earthquake Engineering Simulation (NEES) with the primary goal to lay the groundwork for future validation exercises. The LEAP verification, calibration, and validation will be facilitated by data and documentation in a set of published databases, eventually with open public access. One database, described in Professor, Civil and Env. Engr. , Univ. of Calif. , Davis, California, USA, blkutter@udcdavis.edu Graduate Student Assistant, Civil and Env. Engr. , Univ. of Calif. , Davis, California, USA, tjcarey@ucdavis.edu Visting Scholar, Civil and Env. Engr. , Univ. of Calif. , Davis, California, USA, takhashimoto@ucdavis.edu Professor, Civil and Env. Engr. , The George Washington University, Washington DC, USA, manzari@gwu.edu Graduate Student Assistant, Civil and Env. Engr. , The George Washington University, Washington DC, USA, avasko@gwmail.gwu.edu Assoc. Professor, Civil and Env. Engr. , Rensselaer Polytechnic Institute, Troy, New York, USA, zegham@rpi.edu Assistant Professor, California State University, Sacramento, California, USA, richard.armstrong@csus.edu conceptual detail by Kutter et al. (2014), is intended to archive verification simulations from a range of numerical models; it is envisioned that this database will archive solutions to simple benchmark theoretical problems, where the ability of different codes to model different physics (e.g., a critical state line, or coupling between fluid flow and solid deformations) is tabulated and graphically compared to results of other codes. One database will document standard sand properties (e.g., grain size, maximum density) and element test data (e.g., triaxial test data). Another database will include specifications for performance of validation experiments and instructions to predictors validating numerical procedures. Class A, B, and C predictions will occur for most experiments. Adopting notation similar to that suggested by Lambe (1973), Class A predictions are completed prior to the experiment based on the experiment specifications; Class B predictions are completed after the event, with knowledge of the as-built properties of the experiment and actual input excitations; and Class C “predictions” involve after-the-event simulation of a known experimental result. Class C predictions may be more accurately viewed as calibrations. One validation experiment involving centrifuge testing of a saturated sand slope (LEAP GWU 2015) was completed in January; the extensive experimental results from that exercise are documented in a fourth database. Six universities participated in the centrifuge tests: Cambridge University, UK; Kyoto University, Japan; National Central University, Taiwan; Rensselaer Polytechnic Institute, New York; University of California, Davis; and Zhejiang University, Hongzhou, China. Overall Structure of the NEEShub LEAP Databases Figure 1 illustrates the contents of the four aforementioned LEAP databases. These databases use the database tool developed by NEEShub . Allmond et al. (2014) is a good example of an already-published database on NEEShub. LEAP verification simulations database The verification simulations database, described by Kutter et al. (2014) is intended to accomplish two goals: (1) to describe the physics that the model is intended to simulate and (2) to demonstrate how the model captures the physics. This will be accomplished by defining a set of standard problems for which simulations produced by different solution schemes can be compared to each other and to closed-form solutions, if available. One example illustrates the implementation of Rayleigh damping, which can have profound effects on solutions. Another example, following the closed-form solution described by Jeremic et al. (2008), illustrates how the Biot formulation, often used to model dissipation of pore water pressures, is implemented. With regard to the verification of the constitutive model, verification examples would illustrate, for instance, the existence and uniqueness of a critical state line, the ability to model grain crushing, and the effect of static shear stress on the cyclic strength of the soil. The LEAP Verification Simulations database illustrates the physics modeled by different simulation platforms so that users are aware of their capabilities and limitations. Figure 1: Outline and example contents of the four LEAP databases. LEAP soil properties and element test data database The LEAP Soil Properties and Element Test Data database presently contain experimental data to characterize Ottawa F-65 sand (and also Nevada Sand) used in validation experiments. Grain size distributions, index densities used to calculate relative density, and specific gravity are included. All of the data produced by different experimenters is included to help assess the reliability or uncertainty of the data. Each of these soil properties is to be referenced to specific batches of the sand, with the sources of the data, standard test procedures, and date of testing defined. The Soil Properties and Element Test Data database will also include, for a range of densities and confining pressures, results of element test data such as monotonic drained and undrained triaxial and direct simple shear tests, as well as cyclic tests to define the cyclic strength as a function of the number of cycles of loading. Examples of the monotonic drained triaxial tests are presented in Figure 2. LEAP specifications for experiments and numerical simulations database This database contains the specifications for different LEAP exercises. It presently only contains five fields: (1) LEAP name, (2) Experiment specifications, (3) Achieved input motions, (4) Specifications for Class A prediction, and (5) specifications for Class B predictions for the one LEAP event archived to date. The LEAP name identifies the name of the validation exercise. For example, the recently completed LEAP was called “LEAP GWU 2014,” for which Class A predictions were presented at a workshop in January 2015. Verification Simulations Numerical model •Integration scheme •Damping •Biot formulation Constitutive model •Undrained test paths •Critical state •Consolidation and reconsolidation Soil Properties and Element Test Data Grain characterization •Size distribution •Max and min densities •Specific gravity Element test data •Drained •Undrained •Triaxial •DSS Specifications for Experiments and Numerical Simulations Experiment specifications Class A prediction instructions Achieved input motions (for Class B predictions) Documentation of sample preparation procedures LEAP GWU 2015 Validation Experiment Results Basic info •Event ID's •g-level •Sampling rate Images and surface marker data for each event Sensor data for each event Figure 2: Examples of triaxial test data in the LEAP Soil Properties database (Vasko, 2015). Experiment specifications The experiment specifications may include multiple files used to specify the requirements for the experiments. For LEAP GWU 2015, the document evolved through several versions; the final specification was named Version 1.2 Model Specifications. This document included the scaling laws used, specification of the viscosity of the pore fluid, specification of Ottawa F-65 sand for the experiments, and a detailed procedure for saturation of the sand. The geometry of the sloping ground in the experiment and sensor locations were also specified, as illustrated in Figure 3. Figure 3: Surface geometry and sensor locations for GWU 2015 centrifuge test. To improve the likelihood of successful duplication of results in multiple centrifuges in LEAP GWU 2015, it was decided to use the simplest possible container: a rigid container. A rigid container (example in Figure 4a) would avoid nuances associated with one-of-a-kind specialized containers such as flexible shear beam, laminar box, or hinged plate containers. The prototype scale is 20 m long and 4 m deep ground with surface sloping at 5. The length scale factor L* is determined by the width of the model container. Sensors are specified to detect horizontal, vertical translational acceleration as well as rocking and twisting accelerations. These specifications were designed to be applicable to all six centrifuge facilities that performed the same experiment. Some of the centrifuges have hydraulic shakers