RESEARCH

Animated mineral-scale rock mechanics experiment and microstructure view

EXPERIMENT

Mineral-Rock Physics: Experiments & Database

We are developing a microscale rock mechanics experimental system to investigate how mineral-scale microstructures and micromechanical properties govern the physical and mechanical behaviour of rocks in deep-Earth and planetary environments. Designed specifically for small, rare, and valuable samples, the platform enables high-resolution mechanical characterization while requiring minimal material. In parallel, we are building a database of deep-Earth cores, meteorites, lunar regolith, and relevant analogue materials to advance scientific discovery and support the development of physics-informed generative AI models.

EXPLORE
Accelerated AI-Rock workflow from well-log input and component analysis to digital-core and mechanical results

GENERATIVE AI

AI-Rock

To address the limited availability of rock samples and direct observations in deep-Earth and deep-space environments, we are developing the AI-Rock framework, which integrates generative AI, geological knowledge, and physics-based simulations. Using indirect observations—such as images, geophysical surveys and remote-sensing data—as multimodal constraints, AI-Rock generates high-fidelity three-dimensional digital rocks for more reliable prediction of their physical and mechanical properties.

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AiFrac platform interface displaying a three-dimensional geological simulation

COMPUTATIONAL MODELLING

AIFRAC & DYNAETM

AiFrac is an open-source computational platform for modelling rock fracturing under coupled HMTC processes. Coupled with the TOUGH simulator, TOUGH–AiFrac has been successfully applied to hydraulic-fracturing simulation and design.

DynaETM is a computational platform based on the Energy Tracking Method for simulating the motion, collision, and fragmentation of multiple bodies. Its applications include rockfall and block caving.

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