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

Application of Fuzzy Rayleigh Distribution in the Nonisothermal Pyrolysis of Loose Biomass AbstractThis 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. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Acta Environmentalica Universitatis Comenianae de Gruyter

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

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References (15)

Publisher
de Gruyter
Copyright
© 2016 Alok Dhaundiyal et al., published by De Gruyter Open
ISSN
1339-9802
eISSN
1339-9802
DOI
10.1515/aeuc-2016-0008
Publisher site
See Article on Publisher Site

Abstract

AbstractThis 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.

Journal

Acta Environmentalica Universitatis Comenianaede Gruyter

Published: Dec 1, 2016

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