Advances in Soils/Water Modelling & AI

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• Prof (Associate) Xiaohui Chen, University of Leeds
• Wednesday 22 November 2023, 18:00-19:00
• Room 4 Cripps Court (Magdalene College), 1-3 Chesterton Road, Arbury, Cambridge, CB4 3AD.

If you have a question about this talk, please contact dmx20.

The interactions between soil, water, chemicals, and bacteria pose significant challenges to the development of foundational theories, which are crucial for accurate physics-based modelling. These challenges have constrained innovation in modern geotechnical engineering. In this presentation, we will introduce the concept of Mixture-Coupling theory as an alternative framework firmly rooted in non-equilibrium thermodynamics, complement to existing foundational theories in Geotechnical Engineering. Furthermore, in line with the advancements in physical theory, we have directed our focus towards machine learning to bridge the gap between physics and deep learning. This talk will also highlight our recent developments in physics-informed machine learning techniques, which aim to combine the power of physics based understanding with the data-driven capabilities of machine learning algorithms.

This talk is part of the Cambridge University Geotechnical Society (CUGS) series.

This talk is included in these lists:

• Cambridge University Geotechnical Society (CUGS)
• Room 4 Cripps Court (Magdalene College), 1-3 Chesterton Road, Arbury, Cambridge, CB4 3AD

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