2016
DOI: 10.5027/jnrd.v6i0.10
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Asymptotic solution to the isothermal nth order distributed activation energy model using the Rayleigh Distribution

Abstract: This article focuses on the influence of relevant parameters of biomass pyrolysis on the numerical solution of the isothermal n th-order distributed activation energy model (DAEM) using the Rayleigh distribution as the initial distribution function F(E) of the activation energies. In this study, the integral upper limit, the frequency factor, the reaction order and the scale parameters are investigated. This paper also derived the asymptotic approximation for the DAEM. The influence of these parameters is used… Show more

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Cited by 4 publications
(3 citation statements)
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“…from which it is seen that increase in reaction order (n) causes (1−X ) curves to shift up. Unlike Gaussian [29], Weibull [30] and Rayleigh [31] distribution functions, Gamma distribution relatively converges at very low value of activation energies. It also implies that sensitivity of Gamma distribution while modeling the biomass pyrolysis is quite high.…”
Section: Resultsmentioning
confidence: 99%
“…from which it is seen that increase in reaction order (n) causes (1−X ) curves to shift up. Unlike Gaussian [29], Weibull [30] and Rayleigh [31] distribution functions, Gamma distribution relatively converges at very low value of activation energies. It also implies that sensitivity of Gamma distribution while modeling the biomass pyrolysis is quite high.…”
Section: Resultsmentioning
confidence: 99%
“…Furthermore, the crisp nature of the solution has a degree of randomness and is sometimes unrealistic due to the likelihood of the existence of more than one solution for the same function. In 2017, Dhaundiyal and Tewari trifurcated biomass into its three major constituent parts, namely Cellulose, Hemicellulose and Lignin [2]. They derived the approximate solution for each of constitutes and then summed them.…”
Section: Numerical Illustrationmentioning
confidence: 99%
“…Talking about false certainty is bad science and it can be dangerous if it stunts articulation of critical choices. Although probability theory claims to model decision making imprecision [2], there are qualitatively different facets of indeterminacy which are not covered by probabilistic tools. In some situations where doubt arises about the exactness of a concept, correctness of statements and judgments have little to do with the occurrence of events, the backbone of probability theory.…”
Section: Introductionmentioning
confidence: 99%