Cristian de Santos

Leveraging AI for the Integration of Field Data into Numerical Models in Geotechnical Engineering

In this presentation, we will introduce DAARWIN, an AI-powered geotechnical software designed to bridge the gap between field observations and numerical modelling. By leveraging machine learning and data assimilation techniques, DAARWIN enables engineers to calibrate and update numerical models in real time using actual site data.

We will showcase a case study focused on pile load tests, demonstrating how DAARWIN integrates field measurements to refine soil parameters and improve the accuracy and reliability of geotechnical simulations. This approach not only enhances model performance but also supports more confident and data-driven design decisions.

About

Dr. de Santos holds a Master’s degree in Geotechnical Engineering and a Ph.D. in Soil Mechanics from the Polytechnical University of Catalonia (UPC). He currently serves as the CEO and Co-founder of SAALG Geomechanics. Prior to establishing SAALG Geomechanics, he dedicated over 8 years to research and consultancy at the same university. His research interests lie in advanced numerical solutions, numerical model calibrations, and the characterization of soil and rock parameters through backanalysis.

During his doctoral studies, Dr. de Santos furthered his expertise as a visiting researcher at the California Institute of Technology (Caltech) in the USA. He is renowned for his proficiency in Finite Elements software and geotechnical backanalysis.

Over the course of his career, he has made significant contributions to a multitude of global projects, including Metro Lines, High-Speed Trains, Deep Shafts, Hydraulic Tunnels, Land Reclamation initiatives, and the construction of Large Buildings with subterranean levels, among others. His wealth of experience underscores his standing as a distinguished figure in the field of geomechanics.