Vented gas explosion overpressure prediction of obstructed cubic chamber by Bayesian Regularization Artificial Neuron Network - Bauwens model
Date
2018
Authors
Shi, J.
Li, J.
Hao, H.
Pham, T.M.
Zhu, Y.
Chen, G.
Editors
Advisors
Journal Title
Journal ISSN
Volume Title
Type:
Journal article
Citation
Journal of Loss Prevention in the Process Industries, 2018; 56:209-216
Statement of Responsibility
Conference Name
Abstract
This study aims to develop an integrated model, namely Bauwens-BRANN model, to estimate the maximum overpressure of vented gas explosion. A series of experiments designed for cubic enclosures with and without obstacles are used in the development of Bauwens-BRANN model. Two important parameters are modified to address the pre-existing issues of Bauwens model. By incorporating the Bayesian Regularization Artificial Neuron Network (BRANN) algorithm into the Bauwens model, the Bauwens-BRANN model is developed. Improved pressure estimation accuracy is seen for the Bauwens-BRANN model in comparison with the NFPA-68 2013 model.
School/Discipline
Dissertation Note
Provenance
Description
Data source: Supplementary data, https://doi.org/10.1016/j.jlp.2018.05.016
Access Status
Rights
Copyright 2018 Elsevier Ltd. All rights reserved.