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Simulation of pellet model with multicomponent mass diffusion closure using least squares spectral element solution method
Author(s) -
Rout K. R.,
Jakobsen H. A.
Publication year - 2013
Publication title -
the canadian journal of chemical engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.404
H-Index - 67
eISSN - 1939-019X
pISSN - 0008-4034
DOI - 10.1002/cjce.21765
Subject(s) - diffusion , pellet , mass flux , diffusion process , chemistry , flux (metallurgy) , least squares function approximation , closure (psychology) , process (computing) , mechanics , thermodynamics , mathematics , materials science , physics , computer science , statistics , knowledge management , innovation diffusion , organic chemistry , estimator , composite material , economics , market economy , operating system
Mass‐ and mole‐based pellet models have been solved using least‐squares formulation to describe the evolution of species composition, pressure, velocity, total concentration and mass diffusion fluxes in porous pellets for the steam methane reforming (SMR) process. The objective of this work has been to compare the mass‐ and mole‐based diffusion flux models, convection and fluid velocity for the SMR process using the least‐squares spectral element method (LS‐SEM). The diffusion–reaction problems are computationally intensive, requiring efficient numerical methods for dealing with them. This paper presents formulation and algorithm of LS‐SEM for solving multicomponent mass diffusion pellet models. The mass diffusion flux is described according to the rigorous Maxwell Stefan model. This flux may be defined either with molar‐ or mass‐averaged velocities. The effectiveness factors have been calculated for the SMR process and compared with the literature data. The model evaluations revealed that: ‐ The least‐squares method is well‐suited for solving the multicomponent mass diffusion pellet models for the SMR process, achieving exponential convergence. ‐ Molar‐ and mass‐based pellet models do not give fully identical results for the SMR process, since the pellet model is not completely consistent.