Pathway to a fully data-driven geotechnics: Lessons from materials informatics

Pathway to a fully data-driven geotechnics: Lessons from materials informatics

Blog Article

This paper elucidates the challenges and opportunities inherent in integrating data-driven methodologies into geotechnics, drawing inspiration from the success of materials Clothing - Mens Bottoms - Pants informatics.Highlighting the intricacies of soil complexity, heterogeneity, and the lack of comprehensive data, the discussion underscores the pressing need for community-driven database initiatives and open science movements.By leveraging the transformative power of deep learning, particularly in feature extraction from high-dimensional data and the potential of SHELF transfer learning, we envision a paradigm shift towards a more collaborative and innovative geotechnics field.The paper concludes with a forward-looking stance, emphasizing the revolutionary potential brought about by advanced computational tools like large language models in reshaping geotechnics informatics.