Kinetic Parameter using Genetic algorithm Gandhi Akila M.1,*, Prof. Patel Narendra M.2,** 1ME Scholar, L.D. College of Engineering, Ahmadabad, Gujarat-15 2Associate Professor & in charge Principal, Govt. Engineering College, Valsad *Email: akilamgandhi@gmail.com
**nm_chemldce@yahoo.com
Online published on 4 November, 2017. Abstract Parameter estimation is a key step in establishing the kinetic models. For consecutive chemical reactions, the determination of the rate constants is very difficult and a time consuming process. The aim of this research work is to estimate kinetic parameters using genetic algorithm. The use of such algorithm can be very helpful in the control of industrial processes as well as in the study of the reaction mechanisms. Determination of the accurate values of the rate constants would help in establishing the optimum conditions of reactor design including pressure, temperature, and other parameters of the chemical reaction. Many non linear regression techniques like non linear least square method were used for estimating kinetic parameters. In this paper genetic algorithm is used for estimation of kinetic parameters. A genetic algorithm is applied to get the best fit between the calculation results and the experimental data. A case study of esterification of ethylene glycol with acetic acid is taken. This includes 4 kinetic parameters model. The rate equations (system of simultaneous differential equations) of the reaction were solved to get the analytical concentration versus time profiles. The simulation results are compared with experimental results at each measured point. All deviations between experimental and calculated values are squared and summed up to form a new function. This function is minimized using genetic algorithm that gives the optimal rate constants. The proposed methodology could be used to determine the rate constants of any reaction at a certain temperature, with the possibility of expanding the program for other types of reactions. The proposed program was independent on the nature of the reaction, only the rate equations and the initial conditions had to be modified for any new reaction. Top Keywords Kinetic parameters, kinetic model, optimization, genetic algorithm, esterification reaction. Top |