期刊
PROCESS SAFETY AND ENVIRONMENTAL PROTECTION
卷 149, 期 -, 页码 698-710出版社
ELSEVIER
DOI: 10.1016/j.psep.2021.03.023
关键词
Neural network (NN); Numerical simulation (NS); Vapor cloud explosion (VCE); Peak pressure prediction; Domino effect assessment
资金
- State Key Laboratory of Explosion Science and Technology in Beijing Institute of Technology
- National Key Research and Development Program of China [2017YFC0804702]
- National Natural Science Foundation of China [51678050, 51811530109]
A novel methodology fusing numerical simulation with a neural network technique is proposed for predicting explosion consequences, selecting 6 parameters and using CFD method to simulate VCEs in a chemical site, adopting a progressive training method and data self-improvement for model development.
Vapor cloud explosions (VCEs) have been considered as a major hazard in petrochemical industry, accompanying with wide-ranging impact and huge destruction. The existing methods are incapable to make a rapid and accurate estimation when considering multi-factor coupling effects. Therefore, this study proposed a novel methodology of fusing numerical simulation (NS) with neural network (NN) technique for the prediction of explosion consequences. First, 6 parameters of VCEs influencing overpressure are selected as variables of a database. A CFD method is employed for simulating VCEs in a chemical site, by which sufficient blast data are generated. After the architecture of a NN model is determined, data on three generic VCEs are extracted for further model training process. A progressive training method is adopted to develop a general prediction model. Furthermore, data derived from ongoing simulation results are imported into the model for its constant self-improvement. The output of the well-trained model is subsequently transformed into a probabilistic function to assess the domino effect. The integrating NS with NN approach provides an accurate and efficient way to predict the blast effects, which can support more scientific rescue decision-making. Finally, the proposed model is applied to a case study for illustration. ? 2021 Institution of Chemical Engineers. Published by Elsevier B.V. All rights reserved.
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