Journal
JOURNAL OF LOSS PREVENTION IN THE PROCESS INDUSTRIES
Volume 56, Issue -, Pages 209-216Publisher
ELSEVIER SCI LTD
DOI: 10.1016/j.jlp.2018.05.016
Keywords
NFPA-68 2013; Bayesian Regularization Artificial Neuron; Network; Bauwens analytical model; Better generalization; Vented explosion of obstructed cubic chamber
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Funding
- National Key R&D Program of China [2017YFC0804501]
- Fundamental Research Funds for Innovation Program of Seventh-generation Ultra Deepwater Drilling Platform [2016[24]]
- National Basic Research Program of China (973 Program) [2015CB058000]
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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.
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