A statistical emulator is a fast proxy for a complex computer model which predicts model output at arbitrary parameter settings from a limited ensemble of training data. Regular grid designs for the training set are commonly used for their simplicity. However, Latin hypercube designs have well known theoretical advantages in the design of computer experiments, especially as the dimension of the...

A recently developed Centroidal Voronoi Tessellation (CVT) sampling method is investigated here to assess its suitability for use in statistical sampling applications. CVT efficiently generates a highly uniform distribution of sample points over arbitrarily shaped M-Dimensional parameter spaces. On several 2-D test problems CVT has recently been found to provide exceedingly effective and effici...

The Management and Uncertainties of Severe Accidents (MUSA) project, funded in HORIZON 2020 coordinated by CIEMAT (Spain), aims at consolidating a harmonized approach for the analysis uncertainties sensitivities associated with (SAs) focusing on Source Term (ST). In this framework, objectives Innovative Spent Fuel Pool (IMSFP – WP6), led IRSN (France), are to quantify rank affecting accident an...

[1] Representation of model input uncertainty is critical in ensemble‐based data assimilation. Monte Carlo sampling of model inputs produces uncertainty in the hydrologic state through the model dynamics. Small Monte Carlo ensemble sizes are desirable because of model complexity and dimensionality but potentially lead to sampling errors and correspondingly poor representation of probabilistic s...

Several methods for reducing the variance in the context of Monte Carlo simulation are based on correlation induction. This includes antithetic variates, Latin hypercube sampling, and randomized version of quasi-Monte Carlo methods such as lattice rules and digital nets, where the resulting estimators are usually weighted averages of several dependent random variables that can be seen as functi...

1. Abstract The growing power of computers enabled techniques coined for design and analysis of simulations to be applied to a large spectrum of problems and to reach high level of acceptance among practitioners. Generally, when simulations are time consuming, a surrogate model replaces the computer code in further studies. The very first step for successful surrogate modeling and statistical a...