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Machine Learning for Unsaturated Soil Models by Felipe is a document available to read on EtoBox.
What is Machine Learning for Unsaturated Soil Models about?
This paper presents a machine learning-based approach for developing constitutive models that describe the soil-water retention, hydraulic conductivity, and shear strength of unsaturated saprolitic soils. Utilizing comprehensive soil characterization data and triaxial test results, the models demonstrate high precision and practical applicability, serving as a complementary tool to conventional testing. The study aims to enhance understanding of unsaturated soil mechanics in the context of significant geote
- Author
- Felipe
- Language
- EN