Combustion Characteristics of Alternative Fuels: Butanol Isomers

Introduction & Motivation

            Nearly 85% of the United States' energy needs, including essentially all of our transportation fuel requirements, are met with the burning of fossil fuels.  Furthermore, due to our high consumption, much of our fossil fuels are imported.  In an effort to decrease our dependency on foreign oil, innumerable resources have been dedicated to finding an alternative, carbon-neutral, renewable energy source.

            Deciding which alternative fuel to pursue is an arduous task.  Besides addressing the political questions of “food vs. fuel,” questions such as “does this fuel exhibit the desired combustion properties” and “are the fuel's emissions within the government's standards” must be answered.  Normally, the solutions to these questions are obtained by running numerous experiments, which come at the expense of the fuel.  Even once a candidate alternative fuel is identified, there is usually little insight gained into why this particular fuel exhibits the desired combustion characteristics while countless others do not.  Moreover, it is impossible to predict what engines will be used in the future or how emission standards will change; the results of either could render the alternative fuel source of today as the infeasible fuel source of tomorrow.

            Another means of accessing an alternative fuels' feasibility is by constructing a kinetic model for the fuel.  If the fuel chemistry can be validated against experiments, i.e. the model can be shown to capture the important combustion characteristics, e.g., the ignition delay and laminar flame speeds, one could then extend the chemistry of the base fuel to different molecules.  The chemistry model for the new species could then dictate whether experimental efforts should be devoted to this potential alternative fuel.  For example, if one had a validated chemistry model for the butanol isomers – the smallest alcohol system to contain a primary-, secondary-, and tertiary alcohol – it would be relatively straightforward to extend the kinetic mechanism to larger alcohols that would otherwise be computationally and experimentally expensive to study.

Computational Methodology

            One means of constructing these chemical mechanisms, in an automated fashion, is the open-source software package, Reaction Mechanism Generator (RMG).[1]  The software requires the user to enter the following information: the temperature and pressure of interest; the initial species and their concentrations; a termination criterion, either the desired conversion or reaction time; and an error tolerance, which controls how detailed (large) of a chemistry model is generated.  Using group additivity contributions to estimate a species' thermochemistry,[2] and 42 unique reaction families to estimate kinetics, the RMG software can readily construct a detailed mechanism for the combustion of any oxygenated hydrocarbon.  Additionally, the RMG software can compute pressure-dependent reaction rate coefficients using the steady-state master equation method[3] or the modified strong collision approximation.[4]

Results & Discussion

            Herein we present a reaction mechanism for the combustion and pyrolysis of normal-, secondary-, and tertiary-butanol; the mechanism was constructed using the RMG software.  This mechanism has been validated against data previously published in the literature, including: a doped methane diffusion flame,[5] ignition delay measurements at 1 bar obtained in shock tube experiments,[6] and laminar flame speed calculations.[7]^,[8]  Flux and sensitivity analysis revealed important species and pathways for which more accurate thermochemistry parameters were computed using statistical mechanics and quantum chemistry.  The dominant decomposition pathways for each isomer, in each reactor model, will be discussed.  The effect of the location of the hydroxyl group, i.e. whether the alcohol is primary, secondary, or tertiary, will also be discussed.

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[1] W.H. Green et al. “Reaction Mechanism Generator (RMG)” http://github.com/GreenGroup/RMG-Java

[2] S.W. Benson, “Thermochemical kinetics: Methods for the estimation of thermochemical data and rate parameters,” Wiley, New York, 1976.

[3] N.J.B. Green and Z.A. Bhatti, Phys. Chem. Chem. Phys. 9 (2007) 4275-4290

[4] A.Y. Chang, J.W. Bozzelli, and A.M. Dean, Z. Phys. Chemie 214 (2000) 1533-1568

[5] C.S. McEnally and L.D. Pfefferle, Proc. Combust. Inst. 30 (2005) 1363-1370

[6] J.T. Moss, A.M. Berkowitz, M.A. Oehlschlaeger, J. Biet, V. Warth, P.A. Glaude, and F. Battin-Leclerc, J. Phys. Chem. A 112 (2008) 10843-10855

[7] P.S. Veloo, Y.L. Wang, F.N. Egolfopoulos, and C.K. Westbrook, Combust. Flame doi:10.1016/j.combustflame.2010.04.001 (2010)

[8] P.S. Veloo, F.N. Egolfopoulos, to appear in Proc. Combust. Inst. 33 (2010)