<abstract xmlns="http://www.w3.org/1999/xhtml"><p>This paper describes the influence of some parameters significant to biomass pyrolysis on the numerical solutions of the non-isothermal nth order distributed activation energy model (DAEM) using the Gamma distribution and discusses the special case for the positive integer value of the scale parameter (λ), i.e. the Erlang distribution. Investigated parameters are the integral upper limit, the frequency factor, the heating rate, the reaction order, and the shape and rate parameters of the Gamma distribution. Influence of these parameters has been considered for the determination of the kinetic parameters of the non-isothermal nth order Gamma distribution from the experimentally derived thermoanalytical data of biomass pyrolysis. Mathematically, the effect of parameters on numerical solution is also used for predicting the behaviour of the unpyrolysized fraction of biomass with respect to temperature. Analysis of the mathematical model is based upon asymptotic expansions, which leads to the systematic methods for efficient way to determine the accurate approximations. The proposed method, therefore, provides a rapid and highly effective way for estimating the kinetic parameters and the distribution of activation energies.</p></abstract>

This paper describes the influence of some parameters significant to biomass pyrolysis on the numerical solutions of the non-isothermal nth order distributed activation energy model (DAEM) using the Gamma distribution and discusses the special case for the positive integer value of the scale parameter (λ), i.e. the Erlang distribution. Investigated parameters are the integral upper limit, the frequency factor, the heating rate, the reaction order, and the shape and rate parameters of the Gamma distribution. Influence of these parameters has been considered for the determination of the kinetic parameters of the non-isothermal nth order Gamma distribution from the experimentally derived thermoanalytical data of biomass pyrolysis. Mathematically, the effect of parameters on numerical solution is also used for predicting the behaviour of the unpyrolysized fraction of biomass with respect to temperature. Analysis of the mathematical model is based upon asymptotic expansions, which leads to the systematic methods for efficient way to determine the accurate approximations. The proposed method, therefore, provides a rapid and highly effective way for estimating the kinetic parameters and the distribution of activation energies.

Asymptotic Approximations to the Non-Isothermal Distributed Activation Energy Model for Bio-Mass Pyrolysis

Faculty of Mechanical Engineering, Mechanical Engineering PhD School

Department of Mathematics, Statistics and Computer Science

Govind Ballabh Pant University of Agriculture and Technology

Acta Mechanica et Automatica

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

This paper describes the influence of some parameters significant to biomass pyrolysis on the numerical solutions of the non-isothermal nth order distributed...

Asymptotic Approximations to the Non-Isothermal Distributed Activation Energy Model for Bio-Mass Pyrolysis

Data publikacji: 30 gru 2017

Zakres stron: 293 - 301

Otrzymano: 17 cze 2016

Przyjęty: 28 lis 2017

DOI: https://doi.org/10.1515/ama-2017-0045

Słowa kluczowe
Biomass Pyrolysis, Distributed Activation Energy Model (DAEM), Non-Isothermal Kinetics, Gamma Distribution, Asymptotic Expansion, Erlang Distribution

© 2017 Alok Dhaundiyal et al., published by De Gruyter Open

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Asymptotic Approximations to the Non-Isothermal Distributed Activation Energy Model for Bio-Mass Pyrolysis

Data publikacji: 30 gru 2017

Zakres stron: 293 - 301

Otrzymano: 17 cze 2016

Przyjęty: 28 lis 2017

DOI: https://doi.org/10.1515/ama-2017-0045

Słowa kluczoweBiomass Pyrolysis, Distributed Activation Energy Model (DAEM), Non-Isothermal Kinetics, Gamma Distribution, Asymptotic Expansion, Erlang Distribution

© 2017 Alok Dhaundiyal et al., published by De Gruyter Open

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Słowa kluczowe
Biomass Pyrolysis, Distributed Activation Energy Model (DAEM), Non-Isothermal Kinetics, Gamma Distribution, Asymptotic Expansion, Erlang Distribution