An interpretable surrogate modeling framework for rice husk ash concrete using copula-based virtual sampling (opens in new tab)

This study proposes an interpretable and variance-aware sensitivity analysis framework for analyzing the compressive strength of rice husk ash concrete under correlated input conditions, using statistically consistent virtual sampling and surrogate-based sensitivity analysis. A Gaussian copula is used to construct a virtual design space that preserves empirical marginal distributions and inter-variable dependencies. An Extreme Gradient Boosting surrogate optimized using the Covariance Matrix ...