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May 9, 2026MineralsOpen Access

Macro–Meso-Parameter Calibration of Green Sandstone via XGBoost Screening and Stepwise Regression with Application to Impact-Fragmentation Analysis

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Authors

YCYu ChaoCZChuan ZhangHTHan Tian

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Overview

Randomized trial calibrates geotechnical parameters for green sandstone, suggesting enhanced rock fragmentation modeling efficiency.

Key Points

  • This research aims to establish a framework for calibrating macro and meso parameters of green sandstone for effective rock fragmentation modeling. It specifically looks at the interaction of various parameters influencing peak strength, elastic modulus, and Poisson’s ratio.
  • Incorporated uniaxial compression tests and PFC3D simulations in a calibration framework.
  • Employed XGBoost for parameter identification and stepwise regression for nonlinear mapping equations.
  • Introduced quadratic and interaction terms to enhance model fit, leading to adjusted R2 increases.
  • Identified shear strength τcp and normal strength σcp as key factors for peak strength.
  • Achieved a model error range of 0.09%–3.745% for mechanical indices post-calibration.
  • Revealed the energy transformation process during crack propagation through impact-fragmentation simulations.

Cite This Study

Chao et al. (2026) studied this question.

synapsesocial.com/papers/69fecf49b9154b0b828764b8https://doi.org/10.3390/min16050490
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