TY - EJOUR
DO - 10.1016/j.cma.2017.07.030
AB - In this work we apply the Continuation Multi-Level Monte Carlo (C-MLMC) algorithm proposed in Collier et al. (2014) to efficiently propagate operating and geometric uncertainties in inviscid compressible aerodynamics numerical simulations. The key idea of MLMC is that one can draw MC samples simultaneously and independently on several approximations of the problem under investigations on a hierarchy of nested computational grids (levels). The expectation of an output quantity is computed as a sample average using the coarsest solutions and corrected by averages of the differences of the solutions of two consecutive grids in the hierarchy. By this way, most of the computational effort is transported from the finest level (as in a standard Monte Carlo approach) to the coarsest one. The continuation algorithm (C-MLMC) is a robust and self-tuning version that estimates on the fly the optimal number of level and realizations per level. In this work we describe in detail how C-MLMC can be adapted to perform uncertainty quantification analysis in compressible aerodynamics and we apply it to the relevant test cases of a quasi 1D convergent–divergent Laval nozzle and the 2D transonic RAE-2822 airfoil.
T1 - A Continuation Multi Level Monte Carlo (C-MLMC) method for uncertainty quantification in compressible inviscid aerodynamics
DA - 2017
AU - Pisaroni, Michele
AU - Nobile, Fabio
AU - Leyland, Pénélope
JF - Computer Methods in Applied Mechanics and Engineering
SP - 20-50
VL - 326
EP - 20-50
PB - Elsevier
PP - Lausanne
ID - 220617
KW - Multi level monte carlo
KW - Uncertainty quantification
KW - Aerodynamics
KW - Compressible flows
SN - 0045-7825
UR - http://infoscience.epfl.ch/record/220617/files/2017_Pisaroni_Nobile_Leyland_CMAME_Continuation.pdf
ER -