Comparative Evaluation of Crisp and Fuzzy Schemes to Solve Chemical Kinetic Models

Comparative Evaluation of Crisp and Fuzzy Schemes to Solve Chemical Kinetic Models

Alok Dhaundiyal, Suraj B. Singh, Muammel M. Hanon
Copyright: © 2019 |Pages: 30
DOI: 10.4018/978-1-5225-5709-8.ch007
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This study investigates the application of the crisp and the fuzzy schemes to evaluate the kinetic parameters of thermal decomposition of biomass. A distributed reactivity model is considered for the demonstration of mathematical methods for pyrolysis of biomass. The numerical solution is assessed on the assumption that it follows Laplace's method for asymptotic evaluation of integral. A parabolic regime of temperature is subjected to examination by the thermal analysis. The relevant parameters and variables related to biomass and distribution function are assessed on the basis of crisp and fuzzy perspectives. A distributed reactivity method relies on the modelling of pyrolysis reactions where an overlapping of parallel reactions leads to reactivity distribution, which can be symbolised by any distribution functions. Therefore, the normal distribution pattern is assumed to be involved in the given problem of pyrolysis. The temperature regime is supposed to follow the equation of parabola, T=at^2+c.
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Chemical kinetics is related to transformations in chemical structure of the material which undergoes any chemical process. It can be bifurcated as fundamental, related to quantum mechanics, statistical mechanics or both; and phenomenological or global or Engineering kinetics, such as semi-empirical rate laws, concluded on basis of physical models, as it is derived for the application point of view rather than a fundamental comprehension. This work encompasses one of such phenomenological models for implementation of crisp and fuzzy scheme on plant derivative source of energy. Moreover, there are various types of chemical process and the gamut of fuzzy set-theory can be extended to estimation of kinetic parameters related to any chemical process. Here, one of thermo-chemical processes is chosen for analysis purpose.

Pyrolysis is one of thermal chemical processes which is widely being adopted for torrefaction, gasification, and the extraction of biofuels via Fischer Tropsch synthesis. By the definition, pyrolysis is a thermal decomposition of material in the absence of oxygen which resulting physical and chemical changes in the characteristics of biomass. Unlike combustion process, it is performed within temperature range of 200-600 °C, however it can be varied from application to application, namely torrefaction is a kind of mild pyrolysis where temperature range should be less than 600 °C, so that energetic and textural characteristic of biomass can be modified into the high energy fuel. There are numerous pre-defined kinetic models available to determine the attribute of chemical reactions which occur during thermal decomposition of the biomass.

Key Terms in this Chapter

Parabolic Regime: Temperature distribution of biomass sample with time in thermogravimetric analysis.

Palletisation: Conversion of biomass into pellet form to densify it so that its energy and transport cost could be cost-effective.

DTA: Differential thermal analysis is variation of temperature of biomass with respect to reference material in unit time and unit mass.

Convex Fuzzy: Whose membership values are strictly monotonically increasing or strictly monotonically decreasing, or combination of both for elements on the universe, X.

Support: Domain of membership function for some fuzzy set A at which the non-zero membership follow the inequality .

TGA: Thermogravimetric analysis of biomass sample in the inert atmosphere.

Boundary: The non-zero membership but not full membership in the set .

Torrefaction: A kind of pre-processing of biomass (mild pyrolysis) done between 200 to 400 °C.

Subnormal: If , fuzzy set is characterised as Subnormal in nature.

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