Global sensitivity analysis for subsoil parameter estimation in mechanized tunneling

The present paper validates two alternative global sensitivity analysis methods, namely variance-based and elementary effect, for the purpose of detecting key subsoil parameters that influence the output of mechanized tunnel finite element simulation. In the elementary effect method, a strategy for considering the dependencies, that result from a set of constraints between different parameters, is proposed. Moreover, because the numerical implementation of variance-based sensitivity estimates, in particular, has been proven to require intensive evaluations of the system under investigation, a practical surrogate modeling technique is utilized. This technique is based on quadratic polynomial regression and represents a reliable approximation of the computationally expensive mechanized tunnel simulation. Furthermore, a convergence analysis based on Central Limit Theorem for the numerical implementation of the methods is introduced. The adopted analysis highlights model evaluations needed for the sensitivity measures to converge, as well as the uncertainty involved in these measures.