Title
Optimal fidelity multi-level Monte Carlo for quantification of uncertainty in simulations of cloud cavitation collapse.
Abstract
We quantify uncertainties in the location and magnitude of extreme pressure spots revealed from large scale multi-phase flow simulations of cloud cavitation collapse. We examine clouds containing 500 cavities and quantify uncertainties related to their initial spatial arrangement. The resulting 2000-dimensional space is sampled using a non-intrusive and computationally efficient Multi-Level Monte Carlo (MLMC) methodology. We introduce novel optimal control variate coefficients to enhance the variance reduction in MLMC. The proposed optimal fidelity MLMC leads to more than two orders of magnitude speedup when compared to standard Monte Carlo methods. We identify large uncertainties in the location and magnitude of the peak pressure pulse and present its statistical correlations and joint probability density functions with the geometrical characteristics of the cloud. Characteristic properties of spatial cloud structure are identified as potential causes of significant uncertainties in exerted collapse pressures.
Year
Venue
Field
2017
arXiv: Computational Engineering, Finance, and Science
Magnitude (mathematics),Monte Carlo method,Mathematical optimization,Random variate,Joint probability distribution,Optimal control,Variance reduction,Order of magnitude,Mathematics,Speedup
DocType
Volume
Citations 
Journal
abs/1705.04374
1
PageRank 
References 
Authors
0.37
11
5
Name
Order
Citations
PageRank
Jonas Sukys1213.76
Ursula Rasthofer210.37
Fabian Wermelinger311.38
Panagiotis E. Hadjidoukas410918.24
Petros Koumoutsakos5106584.99