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

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© 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.
Tijdschrift: Energy Procedia
Volume: 132
Pagina's: 705 - 710
Jaar van publicatie:2017