Kinetic modeling and simulation: Pyrolysis of Jatropha residue de-oiled cake. (February 2016)

• Record Type: Journal Article
• Authors: Sharma, Rajeev; Sheth, Pratik N.; Gujrathi, Ashish M.
• Is Part Of: Renewable energy. Volume 86(2016)
• Page Start: 554
• Page End: 562
• Publication Date: 2016-02
• Subjects: Pyrolysis -- Jatropha de-oiled cake -- Thermogravimetry -- Kinetic modeling -- Simulation; Renewable energy sources -- Periodicals; Power resources -- Periodicals; Énergies renouvelables -- Périodiques; Ressources énergétiques -- Périodiques; 333.794
• DOI: 10.1016/j.renene.2015.08.066
• Languages: English
• ISSNs: 0960-1481

Abstract

Abstract: An improved kinetic model based on thermal decomposition of biomass constituents, i.e. cellulose, hemicellulose and lignin, is developed in the present study. The model considers the independent parallel reactions of order n producing volatiles and charcoal from each biomass constituent. While estimating the kinetic parameters, the order of degradation of biomass constituents is also checked and found to be matching with the order of degradation reported in the literature. The results of thermo-gravimetric analysis of Jatropha de-oiled cakes are used to find the kinetic parameters. The experimental runs are carried out using a thermo-gravimetric analyzer (TGA 4000, Perkin Elmer). TGA study is performed in a nitrogen atmosphere under non-isothermal conditions at different heating rates and the thermal decomposition profiles are used. The model is simulated using finite difference method to predict the pyrolysis rate. The corresponding parameters of the model are estimated by minimizing the square of the error between the model predicted values of residual weight fraction and the experimental data of thermogravimetry. The minimization of square of the error is performed using non-traditional optimization technique logarithmic differential evolution (LDE). Highlights: Kinetic model development based on parallel decomposition of biomass constituents. Kinetic parameter estimation using Logarithmic Differential Evolution Algorithm. Improved model predicting the degradation order of biomass constituents accurately.