Dataset of Simulated CRS Tests for Advanced Soil Parameter Identification

This extensive dataset contains the results of 30,000 simulated Constant Rate Strain (CRS) tests, comprising three constitutive models with 10,000 simulations each: linear-elastic perfectly-plastic soil model (Mohr-Coulomb), Hardening Soil, and Hypoplasticity with intergranular strain. These simulations are all conducted using the finite element software, Plaxis. Within the simulations, the model parameters were altered in order to generate an extensive data bank with various system responses. The primary purpose of this dataset is to serve as a training foundation for an Artificial Neural Network (ANN). The goal of the ANN is to efficiently and accurately identify suitable parameter sets for the three widely used soil models, based on data sets provided from numerical CRS tests. This identification is critical for enhancing the precision of soil behaviour predictions in numerical structure-soil interaction models.