Prediction of alkaline treatment effect on the slow pyrolysis of the Pachira aquatica Aubl.fruit bark using artificial neural networks / Predição do efeito do tratamento alcalino na pirólise lenta da casca da fruta Pachira aquatica Aubl. utilizando redes neurais artificiais

Mateus da Silva Carvalho, Cesário Francisco das Virgens, Lucas Lima Carneiro, Erik Galvão Paranhos da Silva, Thiago Pereira das Chagas

Abstract


As crescentes preocupações com as fontes de fósseis fósseis geraram um crescimento no investimento em fontes renováveis. Uma pirólise lenta de materiais lignocelulósicos tornou-se favorável para produzir energia e ser capaz de fornecer produtos de alto valor agregado. Nesse sentido, por meio da aplicação de redes neurais artificiais, este estudo avaliou a cinética da pirólise lenta do pó compactação da casca do fruto de Pachira aquática Aubl. na forma natural e modificada quimicamente para determinar os parâmetros cinéticos usando os métodos de isoconversão de Friedman, Kissinger e Ozawa e introdução do método de deconvolução Fraser-Suzuki para obter os parâmetros cinéticos individuais para o componente de pseudo-celulose.Os resultados permitiram concluir que uma rede neural aplicada foi eficiente na predição dos dados térmicos, obtendo perfis termogravimétricos semelhantes aos experimentais e altos valores de determinação. O método de Friedman foi o melhor se ajustou aos dados, e como energias de ativação indiferentes que as submetidas ao tratamento químico obtiveram menor energia de ativação, devido à modificação dos componentes da matriz lignocelulósica.


Keywords


Biomass, Kinetic Parameters, Artificial Neural Network, Activation Energy, Chemical Treatment, Pyrolysis.

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DOI: https://doi.org/10.34117/bjdv6n10-444

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