Chemical Engineering Research & Design, Vol.122, 273-279, 2017
Estimation of kinetic parameters from adiabatic calorimetric data by a hybrid Particle Swarm Optimization method
Due to the intense non-linear behavior in the task of estimation of the kinetic parameters from the experimental adiabatic data, a hybrid Particle Swarm Optimization (PSO) is proposed to estimate the kinetic parameters. This method is applied to two real cases: decomposition of DTBP and a nitro-compound under adiabatic conditions. By comparing the experimental and calculated temperature rise rate curve, the accuracy of the fitted parameters is verified. These two cases reasonably prove the validation of this hybrid PSO algorithm in the estimation of kinetic model parameters of adiabatic data. (C) 2017 Published by Elsevier B.V. on behalf of Institution of Chemical Engineers.