Mechanics-informed machine learning for geospatial modeling of soil liquefaction: example model implementation in Jupyter Notebook and Matlab

This code repository contains an example Jupyter Notebook and Matlab script to implement a geospatial liquefaction model. This geospatial liquefaction model is designed to predict manifestation of earthquake-induced soil liquefaction at the ground surface through geospatial surrogate models of three standard-of-practice geotechnical models: the liquefaction potential index (LPI); a modified LPI, termed LPIISH; and the liquefaction severity number (LSN). Model users are referred to the journal publication for details regarding model development, performance, and use:

Sanger, M.D., Geyin, M., & Maurer, B.W. (2024). Mechanics-informed machine learning for geospatial modeling of soil liquefaction: global and national surrogate models for simulation and near-real-time response. In Review.