1-Sentence-Summary: A predictive single-step model of coal pyrolysis suitable for CFD applications is developed and validated.
Authors: T. Maffei, A. Frassoldati, A. Cuoci, E. Ranzi, T. Faravelli
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Favourite quote from the paper:
The current authors develop a one step model where coal pyrolysis is determined by linearly weighting parameters from three reference coals. This model builds on the more detailed work of Sommariva et al., 2010 and and Maffei et al., 2012 to provide a simple approach suitable for CFD applications.
An automatic procedure is used to determine the one step parameters for a range of coal ranks. This involves optimizing the simple model parameters against the results of the detailed models previous developed. The end result is an Arrhenius expression where the parameters can be specified base on the % Carbon (daf) in the coal sample.
The one step model is able to characterized coal weight loss, tar species production, char production and volatile gas composition. The volatile composition is specified in terms of CO, H2O, CO2, H2, C2H4, HCN, and H2S, where all of the higher hydrocarbons are included in C2H4. However, the authors state that it is possible to “de-lump” this component into its internal distributions.
Three of the main findings from this paper are:
- One step Arrhenius parameters are specified based on coal carbon content.
- Product stoichiometric coefficients are determined by weighting the coal composition to reference coals.
- The resulting one step model is able to predict coal pyrolysis process and products.
The following sections outline the main findings in more detail. The interested reader is encouraged to view the complete article at the link provided below.
Finding #1: Predictive one step Arrhenius parameters are determined from carbon content
The authors use the automatic optimization process to determine Arrhenius parameters based on the coal carbon content. The database for optimization included 13 coals of different elemental composition from lignite to anthracite. The final parameters were fitted to the following relations:
\(A = 10^{22.1-0.67C_{\%}}\) (S-1)
\(E = 10^{-3}e^{\frac{C_{\%}}{6.35}} + 55,653\) (cal/mol)
where \(A\) is the Arrhenius pre exponential factor, \(E\) is the activation energy, and \(C_{\%}\) is the percent carbon by weight (daf).
Finding #2: Coal pyrolysis coefficients are determined from reference data
The products from the coal pyrolysis are assumed to take the following form:
\(\text{COAL} \rightarrow \alpha_{\text{CHAR}}\text{CHAR} + \alpha_{\text{TAR}}\text{TAR} + \alpha_{\text{CO}}\text{CO} + \alpha_{\text{CO2}}\text{CO2} + \alpha_{\text{H2O}}\text{H2O} + \alpha_{\text{H2}}\text{H2} + \alpha_{\text{C2H4}}\text{C2H4} + \alpha_{\text{HCN}}\text{HCN} + \alpha_{\text{H2S}}\text{H2S}\)
where the individual coefficients (\(\alpha_{i}\)) are derived from the coal composition in comparison to the reference coals. A detailed example case showing how to calculate these coefficients for a given coal is provided in the paper.
Finding #3: One step model is validated with experimental data
The one step model is compared to the detailed model and various experimental results (e.g., Xu and Tomita, 1987, Hambly, 1998, and Genetti and Fletcher, 1999). The comparison indicates relatively accurate prediction of weight loss rates, volatile species produced, tar and char production, and nitrogen and sulfur compounds released. The model is unable to capture low temperature mechanisms such as species being trapped in the metaplastic phase, and over predicts volatile release under these conditions. However, the model performs quite well at higher heating rates such as seen in industrial combustors or furnaces.
My Personal Take-Aways From
“Predictive One Step Kinetic Model of Coal Pyrolysis for CFD Applications”
This paper provides a useful approach for modeling coal pyrolysis for CFD applications. As specified by the authors, this approach can be used in computer simulation studies of coal combustion such as those by Williams et al. 2002, Alvarez et al., 2011, Al-Abbas et al., 2011, and Fang et al., 2012. Comparison of small to medium scale CFD simulations using this model to experimental data, would be a useful contribution to the literature.
Full Citation: [bibtex file=references.bib key=Maffei2013b]
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