Research Papers: Gas Turbines: Combustion, Fuels, and Emissions

Thermal and Transport Properties for the Simulation of Direct-Fired sCO2 Combustor

[+] Author and Article Information
K. R. V. Manikantachari

Center for Advanced Turbomachinery and
Energy Research,
University of Central Florida,
Orlando, FL 32816
e-mail: raghuvmkc@Knights.ucf.edu

Scott Martin

Eagle Flight Research Center,
Embry-Riddle Aeronautical University,
Daytona Beach, FL 32114
e-mail: Martis38@erau.edu

Jose O. Bobren-Diaz

Center for Advanced Turbomachinery and
Energy Research,
University of Central Florida,
Orlando, FL 32816
e-mail: jobobren@Knights.ucf.edu

Subith Vasu

Center for Advanced Turbomachinery and
Energy Research,
University of Central Florida,
Orlando, FL 32816
e-mail: subith@ucf.edu

Contributed by the Combustion and Fuels Committee of ASME for publication in the JOURNAL OF ENGINEERING FOR GAS TURBINES AND POWER. Manuscript received June 9, 2017; final manuscript received July 4, 2017; published online September 6, 2017. Editor: David Wisler.

J. Eng. Gas Turbines Power 139(12), 121505 (Sep 06, 2017) (14 pages) Paper No: GTP-17-1210; doi: 10.1115/1.4037579 History: Received June 09, 2017; Revised July 04, 2017

The direct-fired supercritical CO2 (sCO2) cycle is currently considered as a zero-emission power generation concept. It is of interest to know how to optimize various components of this cycle using computational tools; however, a comprehensive effort in this area is currently lacking. In this work, the behavior of thermal properties of sCO2 combustion at various reaction stages has been investigated by coupling real gas CHEMKIN (CHEMKIN-RG) (Schmitt et al., 1994, Chemkin Real Gas: A Fortran Package for Analysis of Thermodynamic Properties and Chemical Kinetics in Nonideal Systems, University of Iowa, Iowa City, IA) with an in-house premixed conditional moment closure code (Martin, 2003, “The Conditional Moment Closure Method for Modeling Lean Premixed Turbulent Combustion,” Ph.D. thesis, University of Washington, Seattle, WA) and the high-pressure Aramco 2.0 kinetic mechanism. Also, the necessary fundamental information for sCO2 combustion modeling is reviewed. The Soave–Redlich–Kwong equation of state (SRK EOS) is identified as the most accurate EOS to predict the thermal states at all turbulence levels. Also, a model for the compression factor Z is proposed for sCO2 combustors, which is a function of mixture inlet conditions and the reaction progress variable. This empirical model is validated between the operating conditions 250–300 bar, inlet temperatures of 800–1200 K, and within the currently designed inlet mole fractions, and the accuracy is estimated to be less than 0.5% different from the exact relation. For sCO2 operating conditions, the compression factor Z always decreases as the reaction progresses, and this leads to the static pressure loss between inlet and exit of the sCO2 combustor. Further, the Lucas et al. and Stiel and Thodos methods are identified as best suitable models for predicting the viscosity and thermal conductivity of the sCO2 combustion mixtures.

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Fig. 1

Schematic state diagram of a pure CO2

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Fig. 2

P–T–ρ correlation of various EOS models for sCO2 (a) and sO2 (b)

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Fig. 3

Schematic diagram to illustrate the mixture conditions considered for comparing the EOS

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Fig. 4

Comparison of PRS and SRK EOS with NIST for the turbulent dissipation rates N = 1 and N = 10,000

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Fig. 5

Variation of Z with respect to RPV for various sCO2 operating conditions

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Fig. 6

Error plot for the Z from model and SRK EOS

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Fig. 7

Specific heats for sCO2 combustor

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Fig. 8

Enthalpy–entropy diagram for sCO2 combustor

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Fig. 9

Pressure exponent and isothermal compressibility in sCO2 combustor

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Fig. 10

The speed of sound in sCO2 combustor

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Fig. 11

Standard practices for viscosity modeling in supercritical combustion simulations

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Fig. 12

The comparison of modeled individual species viscosity with NIST

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Fig. 13

Viscosity of sCO2 combustion mixture using various models

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Fig. 14

The computational time for calculating viscosity of sCO2 combustion mixture using various models

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Fig. 15

Standard practices for thermal conductivity modeling in supercritical combustion applications

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Fig. 16

The comparison of modeled individual species thermal conductivities with NIST

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Fig. 17

The comparison of modeled mixture thermal conductivities

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Fig. 18

The computational time between the modeled mixture thermal conductivities



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