Computational approaches for modeling biomass pyrolysis: slow pyrolysis process of apricot kernel shells controled by nonisothermal simultaneous thermal analysis (STA)

Abstract

Pyrolysis of lignocellulosic biomass is a promising process capable of producing renewable fuels and chemicals that are currently derived from non-renewable sources. However, industrial pyrolysis processes to make these products from biomass are not yet economically viable and require significant optimization before they can contribute to existing oil-based transportation and chemical systems. One means of optimization uses kinetic and transport models for predicting the products of biomass pyrolysis, which serve as the basis for designing pyrolysis reactors capable of producing the highest value products. In this work, two computational approaches applied in modeling the complex pyrolysis process of biomass were presented. First approach encompasses iterative isoconversional method established in generic codes in MATLAB program. Second approach represents the use of Fraser-Suzuki fitting function for resolving the rate curves that arise from complex process of lignocellulosic materials. In the latter case, every identified reaction step was considered through mechanistic description, which involves selection the appropriate kinetic model function. Comparison of the results as well as discrepancies between them has been discussed. As an example, the slow pyrolysis of apricot (Prunus armeniaca) kernel shells was taken into the consideration, where devolatilization process is monitored using the simultaneous thermal analysis (STA).