Modeling methods used in bioenergy production processes: A review

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Date

2020

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Techno press

Abstract

The enhancements of bioenergy production effectiveness require the comprehensively experimental study of several parameters affecting these bioprocesses. The interpretation of the obtained experimental results and the estimation of optimum yield are extremely complicated such as misinterpreting the results of an experiment. The use of mathematical modeling and statistical experimental designs can consistently supply the predictions of the potential yield and the identification of defining parameters and also the understanding of key relationships between factors and responses. This paper summarizes several mathematical models used to achieve an adequate overall and maximal production yield and rate, to screen, to optimize, to identify, to describe and to provide useful information for the effect of several factors on bioenergy production processes. The usefulness, the validity and, the feasibility of each strategy for studying and optimizing the bioenergy-producing processes were discussed and confirmed by the good correlation between predicted and measured values

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Keywords

system modeling, experimental design methods, neural network design, identification, optimization, bioenergy

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