Abstract submission for the Special Session on Image Analysis and Machine Learning for Geomechanics in ISMLG 2023

The rising interest and demand for energy geo-structures and energy storage  systems require a fundamental understanding of the  hydro-chemo-thermo-mechanically coupled processes in soils and rocks for  thermal piles, nuclear waste disposal, gas storage and caprock integrity, etc. Advanced imaging techniques provide essential insights  into the behaviour of geomaterials under various applied conditions,  including hydraulic pressure, chemical reaction, temperature, and  mechanical loading. For example, X-ray micro-tomography is a  non-destructive 3D imaging tool for the in-situ multi-physical  characterisation of geomaterials. Other imaging techniques include  digital cameras, neutron tomography, X-ray diffraction, and magnetic  resonance imaging.
Image  analysis and machine learning apply widely in our daily life, from face  recognition to self-driving cars. In geomechanics, machine learning is  becoming increasingly popular to enhance the quantitative information  that image analysis can provide through phase segmentation, fracture  recognition, particle tracking, etc. This session aims to attract  high-quality contributions that use image analysis and machine learning  in geomechanics.
The relevant topics include but are not limited to:

  •  Soil mechanics
  • Rock mechanics
  • Multiphase flow
  • Hydraulic-induced instability
  • Dissolution and precipitation
  • Freezing and thawing
  • Fines migration and clogging
  • Microbially induced calcite precipitation

More information on https://www.ismlg2023.com/special-session7.

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