Optimal designs for the propagation of uncertainty in computer experiments (original) (raw)

Response surfaces, or meta-models, and design of experiments are widely used for various experimental works. But numerous physical phenomenons are studied through complex and costly numerical simulators. In such cases, the response is influenced by factors but the link between these variables is deterministic. Nevertheless, factors are often known with uncertainty and the influence of this ignorance is important for the practician. Due to the computing time, it is not possible to obtain the uncertainty of the response through a standard Monte Carlo method and an approximation of the simulator, a meta-model, is needed. We present an optimality criterion, the MC-V, in order to evaluate the probability distribution of the response with a minimal error. We chose to apply the criterion on parts of 2 real cases derived from the petroleum industry. The simulator 2 nd order polynomial meta-model and the three distributions of input factors (uniform, gaussian, triangular) are among those use...