Rheological characterization of debris flows in the western himalayas using XGBoost and laboratory data
摘要
Debris flows are destructive mass movements that pose multifaceted challenges with profound social and environmental implications in the Western Himalayas. For precise modeling and flow behavior prediction, it is essential to understand the rheological characteristics of debris flow material. In the current study, rheological characteristics like yield stress and viscosity were determined by a series of lab tests using a parallel plate setup in a rheometer. An optimized sampling approach created the reconstituted soil samples of finer particles to change the solid volume concentration and volumetric water content (w/c). Later, the feature importance of finer particles in debris flow rheology was determined using a machine learning regressor. Non-Newtonian behavior was shown by each composition and was similar to Herschel–Bulkley’s rheological model. The eXtreme Gradient Boosting (XGBoost) regression model was developed for rheological parameters with robust model fitting with