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      KCI등재 SCIE SCOPUS

      Study of the influence of operational parameters on biomass conversion in a pyrolysis reactor via CFD

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      https://www.riss.kr/link?id=A108847419

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      Pyrolysis has been one of the technologies used to convert biomass into biofuels. Therefore, mathematical models that can represent its phenomena are of fundamental importance in understanding the reaction progression and optimizing the process. In th...

      Pyrolysis has been one of the technologies used to convert biomass into biofuels. Therefore, mathematical models that can represent its phenomena are of fundamental importance in understanding the reaction progression and optimizing the process. In this sense, this study compared the results obtained from the lumped-capacitance thermal model proposed in this work with the thermal discretization model that considers thermal conductivity as a function of temperature. Then, the effect of operational parameters such as temperature, gas velocity, and biomass particle diameter, was compared on the reaction conversion rate. To describe the behavior and interaction between the phases, we utilized an Eulerian-Lagrangian CFD modeling approach, solving the continuity, momentum, energy, species, and turbulence equations using OpenFOAM. A factorial design of the type 2k was used to manipulate the model’s input parameters, with biomass conversion as the response variable. The numerical results of biomass conversion from the lumped-capacitance model showed good agreement with the data reported in the literature for the discretized model. However, we observed a difference of 9.13% in the particle mass behavior and 7.63% in the particle residence time. The design of experiments (DoE) enabled us to determine the impact of individual parameters and their interactions on the pyrolysis conversion rate with temperature identified as the most sensitive parameter. Therefore, despite the observed errors when comparing the two models, the lumped-capacitance model accurately represented the reaction yields and proved to be suitable for simulations involving a large number of particles, facilitating optimization studies.

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