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Meta-modelling for fast analysis of CFD-simulated vapour cloud dispersion processes

Wang, K, Chen, T, Kwa, ST, Ma, Y and Lau, R (2014) Meta-modelling for fast analysis of CFD-simulated vapour cloud dispersion processes COMPUTERS & CHEMICAL ENGINEERING, 69. pp. 89-97.

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Abstract

Meta-modelling for fast analysis of CFD-simulated vapour cloud dispersion processes Abstract: Released flammable chemicals can form an explosible vapour cloud, posing safety threat in both industrial and civilian environments. Due to the difficulty in conducting physical experiments, computational fluid dynamic (CFD) simulation is an important tool in this area. However, such simulation is computationally too slow for routine analysis. To address this issue, a meta-modelling approach is developed in this study; it uses a small number of simulations to build an empirical model, which can be used to predict the concentration field and the potential explosion region. The dimension of the concentration field is reduced from around 43,421,400 to 20 to allow meta-modelling, by using the segmented principal component transform-principal component analysis. Moreover, meta-modelling-based uncertainty analysis is explored to quantify the prediction variance, which is important for risk assessment. The effectiveness of the methodology has been demonstrated on CFD simulation of the dispersion of liquefied natural gas

Item Type: Article
Divisions : Faculty of Engineering and Physical Sciences > Chemical and Process Engineering
Authors :
AuthorsEmailORCID
Wang, KUNSPECIFIEDUNSPECIFIED
Chen, TUNSPECIFIEDUNSPECIFIED
Kwa, STUNSPECIFIEDUNSPECIFIED
Ma, YUNSPECIFIEDUNSPECIFIED
Lau, RUNSPECIFIEDUNSPECIFIED
Date : 3 October 2014
Identification Number : 10.1016/j.compchemeng.2014.07.003
Uncontrolled Keywords : Science & Technology, Technology, Computer Science, Interdisciplinary Applications, Engineering, Chemical, Computer Science, Engineering, Computational fluid dynamics, Design of experiments, Gaussian process regression, Kriging, Surrogate modelling, Vapour cloud dispersion, PRINCIPAL COMPONENT ANALYSIS, MODELS, OPTIMIZATION, REGRESSION, OUTPUTS, CALIBRATION, MIXTURES, TUTORIAL, DESIGN
Related URLs :
Additional Information : NOTICE: this is the author’s version of a work that was accepted for publication in Computers & Chemical Engineering. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Computers & Chemical Engineering, 69, 3 October 2014, DOI 10.1016/j.compchemeng.2014.07.003.
Depositing User : Symplectic Elements
Date Deposited : 24 Feb 2015 10:02
Last Modified : 24 Feb 2015 10:10
URI: http://epubs.surrey.ac.uk/id/eprint/806978

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