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Quasi-Monte-Carlo-based probabilistic assessment of wall heat loss

Journal Contribution - Journal Article Conference Contribution

© 2017 The Authors. Published by Elsevier Ltd. In this paper, the potential of quasi-Monte Carlo methods for uncertainty propagation is assessed, via a case study of heat loss through a massive masonry wall. Four quasi-Monte Carlo sampling strategies-Optimized Latin hypercube, Sobol sequence, Niederreiter-Xing sequence and Good Lattice sequence-are applied and compared. Moreover, in order to terminate the quasi-Monte Carlo simulation when the desired accuracy is reached, an error estimation method is implemented. The outcomes show that all the four quasi-Monte Carlo methods outperform the standard Monte Carlo method; the Niederreiter-Xing sequence and Sobol sequence tend to be the best.
Journal: 2nd International Conference on Crystalline Silicon Photovoltaics - SiliconPV
ISSN: 1876-6102
Volume: 132
Pages: 705 - 710
Publication year:2017
BOF-keylabel:yes
IOF-keylabel:yes
Authors from:Higher Education
Accessibility:Open