Research Notes

Exploring computational geomechanics, numerical modelling, and AI-enabled engineering workflows. These updates capture in-progress thinking, published work, and prototypes that move research ideas into the field.

  • The Rapid Evolution of AI Tooling: From Function Calling to MCP Apps

    A reflection on the rapid evolution of AI tool development—from manual function calling to the Model Context Protocol (MCP) and Agent Skills—and why staying ahead means building for adaptability, not just the latest standard.

    AI, Software Engineering, MCP, LLM, Geotechnical Engineering

  • GeoSim.AI: A New Paradigm in Computational Geomechanics

    Introducing GeoSim.AI - a suite of AI assistants for numerical simulations in geomechanics that demonstrates the transformative potential of generative AI in geotechnical engineering.

    AI, geomechanics, numerical simulation, LLM, generative AI

  • Physics-Informed Neural Networks for One-dimensional Consolidation

    Physics-informed neural networks (PINNs) for forward and inverse problems in one-dimensional consolidation are presented. The governing partial differential equation is applied as a constraint in the neural network using automatic differentiation. The model performance is demonstrated...

    PINNs, Deep Learning, Machine Learning, Geomechanics, 1D Consolidation

  • Porous Media Theory: Summary for Coupled Problems in Science and Engineering

    The fundamental concepts and formulations in porous media theory are presented, covering volume fraction concept, conservation laws, thermodynamics, phase transitions, and coupled problem formulations for hydraulic, hydro-mechanical, and thermo-hydro-mechanical processes.

    porous media, geomechanics, continuum mechanics, coupled processes, THM

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