<abstract xmlns="http://www.w3.org/1999/xhtml"><p>This paper studied the implementation of fuzzy logic on the relevant parameter of biomass pyrolysis. Frequency factor, the upper limit of ‘dE’, and the scale parameter of Rayleigh distribution are fuzzified in order to estimate the randomness in estimating the parametric values. Distribution function, <italic>f</italic>(<italic>E</italic>), of activation energies is assumed to follow the Rayleigh distribution. Thermo-analytical data has been found experimentally with the help of TGA/DTG analysis. The approximated solution of distributed activation energy model (DAEM) is obtained by using asymptotic approach.</p></abstract>

This paper studied the implementation of fuzzy logic on the relevant parameter of biomass pyrolysis. Frequency factor, the upper limit of ‘dE’, and the scale parameter of Rayleigh distribution are fuzzified in order to estimate the randomness in estimating the parametric values. Distribution function, f(E), of activation energies is assumed to follow the Rayleigh distribution. Thermo-analytical data has been found experimentally with the help of TGA/DTG analysis. The approximated solution of distributed activation energy model (DAEM) is obtained by using asymptotic approach.

Application of Fuzzy Rayleigh Distribution in the Nonisothermal Pyrolysis of Loose Biomass

Department of Mathematics, Statistics and Computer Science

G. B. Pant University of Agriculture and Technology

Acta Environmentalica Universitatis Comenianae

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

This paper studied the implementation of fuzzy logic on the relevant parameter of biomass pyrolysis. Frequency factor, the upper limit of ‘dE’, and the scale...

Application of Fuzzy Rayleigh Distribution in the Nonisothermal Pyrolysis of Loose Biomass

Pubblicato online: 24 gen 2018

Pagine: 14 - 22

DOI: https://doi.org/10.1515/aeuc-2016-0008

Parole chiave
Fuzzy number, Rayleigh distribution, distributed activation energy model, kinetic parameters, biomass pyrolysis

© 2016 Alok Dhaundiyal et al., published by De Gruyter Open

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Application of Fuzzy Rayleigh Distribution in the Nonisothermal Pyrolysis of Loose Biomass

Pubblicato online: 24 gen 2018

Pagine: 14 - 22

DOI: https://doi.org/10.1515/aeuc-2016-0008

Parole chiaveFuzzy number, Rayleigh distribution, distributed activation energy model, kinetic parameters, biomass pyrolysis

© 2016 Alok Dhaundiyal et al., published by De Gruyter Open

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Parole chiave
Fuzzy number, Rayleigh distribution, distributed activation energy model, kinetic parameters, biomass pyrolysis