Predictive Modelling of Wind-Influenced Dynamic Fire Spread Probability in Tank Farm Due to Domino Effect by Integrating Numerical Simulation with ANN

نویسندگان

چکیده

Pool fires cause immense damage to fuel storage tank farms. Reduced fire escalation risk in farms improves safety. Computational fluid dynamics (CFD) has proven effective assessing of fire-related domino effects and is being utilized for pool consequences The past CFD-based analysis focused on primary secondary targets. This study used simulator (FDS) model complete evolution the effect under different wind speeds locations. Dynamic probability (DEP) spread farm were calculated. Offset failure increased by 3% 31%, while inline dropped 36% 90%, at 2 8 m/s, respectively. An artificial neural network (ANN) incorporating Levenberg–Marquardt algorithm predict based numerical data set. use ANNs this purpose one first attempts regard. can reliably dynamic could be manage fire-induced effects. Moreover, obtained from ANN modelling safety applications, such as updating mitigation time when unacceptable a specific speed.

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ژورنال

عنوان ژورنال: Fire

سال: 2023

ISSN: ['2571-6255']

DOI: https://doi.org/10.3390/fire6030085