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Research Papers: Fuel Combustion

Combustion Simulation of Propane/Oxygen (With Nitrogen/Argon) Mixtures Using Rate-Controlled Constrained-Equilibrium

[+] Author and Article Information
Guangying Yu

Department of Mechanical and
Industrial Engineering,
Northeastern University,
Boston, MA 02115
e-mail: yu.g@husky.neu.edu

Hameed Metghalchi, Ziyu Wang

Department of Mechanical and
Industrial Engineering,
Northeastern University,
Boston, MA 02115

Omid Askari

Department of Mechanical Engineering,
Mississippi State University,
Starkville, MS 39762

*Corresponding author.

Contributed by the Advanced Energy Systems Division of ASME for publication in the JOURNAL OF ENERGY RESOURCES TECHNOLOGY. Manuscript received August 10, 2018; final manuscript received August 13, 2018; published online September 26, 2018. Assoc. Editor: Reza Sheikhi.

J. Energy Resour. Technol 141(2), 022204 (Sep 26, 2018) (8 pages) Paper No: JERT-18-1621; doi: 10.1115/1.4041289 History: Received August 10, 2018; Revised August 13, 2018

The rate-controlled constrained-equilibrium (RCCE), a model order reduction method, has been further developed to simulate the combustion of propane/oxygen mixture diluted with nitrogen or argon. The RCCE method assumes that the nonequilibrium states of a system can be described by a sequence of constrained-equilibrium states subject to a small number of constraints. The developed new RCCE approach is applied to the oxidation of propane in a constant volume, constant internal energy system over a wide range of initial temperatures and pressures. The USC-Mech II (109 species and 781 reactions, without nitrogen chemistry) is chosen as chemical kinetic mechanism for propane oxidation for both detailed kinetic model (DKM) and RCCE method. The derivation for constraints of propane/oxygen mixture starts from the eight universal constraints for carbon-fuel oxidation. The universal constraints are the elements (C, H, O), number of moles, free valence, free oxygen, fuel, and fuel radicals. The full set of constraints contains eight universal constraints and seven additional constraints. The results of RCCE method are compared with the results of DKM to verify the effectiveness of constraints and the efficiency of RCCE. The RCCE results show good agreement with DKM results under different initial temperature and pressures, and RCCE also reduces at least 60% CPU time. Further validation is made by comparing the experimental data; RCCE shows good agreement with shock tube experimental data.

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Figures

Grahic Jump Location
Fig. 1

Values of constraint potentials of the elemental constraints

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Fig. 2

Values of constraint potentials of the nonelemental constraints

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Fig. 3

Temperature comparison of RCCE with different number of constraints and DKM model of stoichiometric mixture with initial pressure 1 atm and initial temperature 1500 K

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Fig. 4

Comparison of RCCE and DKM with different initial temperatures from 1200 K to 1500 K. Initial pressure is 1 atm.

Grahic Jump Location
Fig. 5

Comparison of RCCE and DKM with initial temperature 1500 K and different initial pressures

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Fig. 6

CPU time comparison of RCCE and DKM model with different initial temperatures and pressures

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Fig. 7

Comparison of RCCE simulation and experimental data of Lam et al. [62] and Cadman et al. [57]. Initial composition is 0.8%C3H8/8%O2/91.2%Ar. Initial pressure is 6 atm.

Grahic Jump Location
Fig. 8

Comparison of RCCE simulation and shock tube experimental data of Peterson et al. [59] and Herzler et al. [58]. Initial composition is 2.1%C3H8/21%O2/76.9%N2 with initial pressure 30 atm.

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