Application of a Neuro-Fuzzy System to calculate the Uncertainty of the peak pressure value during the deflagrations of air – hydrogen mixtures

Intheproblemoftheprotectionbytheconsequencesofanexplosionisactualformanyindustrial application involving storage of gas like methane or hydrogen, refuelling stations and so on. A simple and economicwaytoreducethepeakpressureassociatedtoadeflagrationistosupplytotheconfinedenvironmentan opportune surface substantially less resistant then the protected structure, typically in stoichiometric conditions, the peak pressure reduction is around the 8 bars for a generic hydrocarbon combustion in an adiabatic system lacking of whichever mitigation system. In general the problem is the forecast of the peak pressure value (PM )o f the explosion.This problem is faced using CFD codes modelling the structure in which the explosion is located andsettingthemainparameterslikeconcentrationofthegasinthemixture,thevolumeavailable,thesizeofvent area and obstacles (if included) and so on. In this work the idea is to start from empirical data to train a Neural Network (NN) in order to find the correlation among the parameters regulating the phenomenon.Associated to this prediction a fuzzy model will provide to quantify the uncertainty of the predicted value.