Research Papers

A Validation/Uncertainty Quantification Analysis for a 1.5 MW Oxy-Coal Fired Furnace: Sensitivity Analysis

[+] Author and Article Information
Oscar H. Díaz-Ibarra

Department of Chemical Engineering,
University of Utah,
Salt Lake City, UT 84112
e-mail: ohdiazi@gmail.com

Jennifer Spinti

Department of Chemical Engineering,
University of Utah,
Salt Lake City, UT 84112
e-mail: Jennifer.Spinti@utah.edu

Andrew Fry

Chemical Engineering Department,
Brigham Young University,
Provo, UT 84602

Benjamin Isaac, Michal Hradisky

Institute for Clean and Secure Energy,
University of Utah,
Salt Lake City, UT 84112

Jeremy N. Thornock, Sean Smith, Philip J. Smith

Department of Chemical Engineering,
University of Utah,
Salt Lake City, UT 84112

Manuscript received February 17, 2017; final manuscript received June 12, 2018; published online July 13, 2018. Assoc. Editor: Sumanta Acharya.

J. Verif. Valid. Uncert 3(1), 011004 (Jul 13, 2018) (13 pages) Paper No: VVUQ-17-1005; doi: 10.1115/1.4040585 History: Received February 17, 2017; Revised June 12, 2018

A validation/uncertainty quantification (VUQ) study was performed on the 1.5 MWth L1500 furnace, an oxy-coal fired facility located at the Industrial Combustion and Gasification Research Facility at the University of Utah. A six-step VUQ framework is used for studying the impact of model parameter uncertainty on heat flux, the quantity of interest (QOI) for the project. This paper focuses on the first two steps of the framework. The first step is the selection of model outputs in the experimental and simulation data that are related to the heat flux: incident heat flux, heat removal by cooling tubes, and wall temperatures. We describe the experimental facility, the operating conditions, and the data collection process. To obtain the simulation data, we utilized two tools, star-ccm+ and Arches. The star-ccm+ simulations captured flow through the complex geometry of the swirl burner while the Arches simulations captured multiphase reacting flow in the L1500. We employed a filtered handoff plane to couple the two simulations. In step two, we developed an input/uncertainty (I/U) map and assigned a priority to 11 model parameters based on prior knowledge. We included parameters from both a char oxidation model and an ash deposition model in this study. We reduced the active parameter space from 11 to 5 based on priority. To further reduce the number of parameters that must be considered in the remaining steps of the framework, we performed a sensitivity analysis on the five parameters and used the results to reduce the parameter set to two.

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Oberkampf, W. L. , and Roy, C. J. , 2010, Verification and Validation for Scientific Computing, Cambridge University Press, New York. [CrossRef]
Ferson, S. , 1996, “ What Monte Carlo Methods Cannot Do,” Human Ecological Risk Assess.: An Int. J., 2(4), pp. 990–1007. [CrossRef]
Ferson, S. , and Ginzburg, L. R. , 1996, “ Different Methods Are Needed to Propagate Ignorance and Variability,” Reliab. Eng. Syst. Saf., 54(2–3), pp. 133–144. [CrossRef]
Ferson, S. , and Hajagos, J. G. , 2004, “ Arithmetic With Uncertain Numbers: Rigorous and (Often) Best Possible Answers,” Reliab. Eng. Syst. Saf., 85(1–3), pp. 135–152. [CrossRef]
Kriegler, E. , and Held, H. , 2005, “ Utilizing Belief Functions for the Estimation of Future Climate Change,” Int. J. Approximate Reasoning, 39(2–3), pp. 185–209. [CrossRef]
Aughenbaugh, J. M. , and Paredis, C. J. J. , 2006, “ The Value of Using Imprecise Probabilities in Engineering Design,” ASME J. Mech. Des., 128(4), p. 969. [CrossRef]
ASME, 2009, “ Standard for Verification and Validation in Computational Fluid Dynamics and Heat Transfer,” American Society of Mechanical Engineers, New York, Standard No. V V 20-2009. https://www.asme.org/products/codes-standards/v-v-20-2009-standard-verification-validation
Russi, T. , Packard, A. , and Frenklach, M. , 2010, “ Uncertainty Quantification: Making Predictions of Complex Reaction Systems Reliable,” Chem. Phys. Lett., 499(1–3), pp. 1–8. [CrossRef]
Jatale, A. , Smith, P. J. , Thornock, J. N. , Smith, S. T. , and Hradisky, M. , 2015, “ A Validation of Flare Combustion Efficiency Predictions From Large Eddy Simulations,” ASME J. Verif. Valid. Uncertainty Quantif., 1(2), p. 021001. [CrossRef]
Jatale, A. , Smith, P. J. , Thornock, J. N. , Smith, S. T. , Spinti, J. P. , and Hradisky, M. , 2015, “ Application of a Verification, Validation and Uncertainty Quantification Framework to a Turbulent Buoyant Helium Plume,” Flow, Turbul. Combust., 95(1), pp. 143–168. [CrossRef]
Schroeder, B. B. , 2015, “ Scale-Bridging Model Development and Increased Model Credibility,” Ph.D. thesis, The University of Utah, Salt Lake City, UT. https://search.proquest.com/openview/df77af7220f95a52c75104a2b5c39fb4/1?pq-origsite=gscholar&cbl=18750&diss=y
Bayarri, M. J. , Berger, J. O. , Paulo, R. , Sacks, J. , Cafeo, J. A. , Cavendish, J. , Lin, C.-H. , and Tu, J. , 2007, “ A Framework for Validation of Computer Models,” Technometrics, 49(2), pp. 138–154. [CrossRef]
Feeley, R. P. , 2008, “ Fighting the Curse of Dimensionality: A Method for Model Validation and Uncertainty Propagation for Complex Simulation Models,” Ph.D. thesis, University of California, Berkeley, CA. https://jagger.me.berkeley.edu/~pack/library/FeeleyPhDThesis.pdf
Debusschere, B. , Sargsyan, K. , Safta, C. , and Chowdhary, K. , 2017, “ The Uncertainty Quantification Toolkit (UQTk),” Handbook of Uncertainty Quantification, Springer International Publishing, Cham, Switzerland, Chap. 53.
Kennedy, M. C. , and O'Hagan, A. , 2001, “ Bayesian Calibration of Computer Models,” J. R. Stat. Soc. Ser. B (Stat. Methodology), 63(3), pp. 425–464. [CrossRef]
Ahn, J. , Okerlund, R. , Fry, A. , and Eddings, E. G. , 2011, “ Sulfur Trioxide Formation During Oxy-Coal Combustion,” Int. J. Greenhouse Gas Control, 5(Suppl. 1), pp. S127–S135. [CrossRef]
Fry, A. , Adams, B. , Davis, K. , Swensen, D. , Munson, S. , and Cox, W. , 2011, “ An Investigation Into the Likely Impact of Oxy-Coal Retrofit on Fire-Side Corrosion Behavior in Utility Boilers,” Int. J. Greenhouse Gas Control, 5(Suppl. 1), pp. S179–S185. [CrossRef]
Nicoud, F. , and Ducros, F. , 1999, “ Subgrid-Scale Stress Modelling Based on the Square of the Velocity Gradient Tensor,” Flow, Turbul. Combust., 62(3), pp. 183–200. [CrossRef]
Luitjens, J. , Schmidt, J. , Humphrey, A. , de St. Germain, J. D. , Harman, T. , Guilkey, J. , Reid, C. , Hinckley, D. , Burghardt, J. , Schreiner, J. M. , Peterson, J. , Thornock, J. N. , Leavy, B. , Meng, Q. , Spinti, J. , Wight, C. , and Sutherland, J. , 2018, “The Uintah Software,” The University of UTAH, Uintah County, UT, accessed June 27, 2018, http://www.uintah.utah.edu/
Pedel, J. , Thornock, J. N. , and Smith, P. J. , 2012, “ Large Eddy Simulation of Pulverized Coal Jet Flame Ignition Using the Direct Quadrature Method of Moments,” Energy Fuels, 26(11), pp. 6686–6694. [CrossRef]
Pedel, J. , Thornock, J. N. , and Smith, P. J. , 2013, “ Ignition of Co-Axial Turbulent Diffusion Oxy-Coal Jet Flames: Experiments and Simulations Collaboration,” Combust. Flame, 160(6), pp. 1112–1128. [CrossRef]
Pedel, J. , Thornock, J. N. , Smith, S. T. , and Smith, P. J. , 2014, “ Large Eddy Simulation of Polydisperse Particles in Turbulent Coaxial Jets Using the Direct Quadrature Method of Moments,” Int. J. Multiphase Flow, 63, pp. 23–38. [CrossRef]
Versteeg, H. K. , and Malalaskekera, W. , 2007, “ The Finite Volume Method for Convection–Diffusion Problems,” An Introduction to Computational Fluid Dynamics. The Finite Volume Method, 2nd ed., Pearson Prentice Hall, Upper Saddle River, NJ, pp. 115–133.
Fox, R. O. , and Vedula, P. , 2010, “ Quadrature-Based Moment Model for Moderately Dense Polydisperse Gas-Particle Flows,” Ind. Eng. Chem. Res., 49(11), pp. 5174–5187. [CrossRef]
Fletcher, T. H. , Kerstein, A. R. , Pugmire, R. J. , Solum, M. , and Grant, D. M. , 1992, “ A Chemical Percolation Model for Devolatilization: Summary,” Sandia National Laboratories, Albuquerque, NM, Technical Report No. SAND92-8207. http://www2.et.byu.edu/~tom/cpd/CPD_Summary.pdf
Spinti, J. P. , Thornock, J. N. , Eddings, E. G. , Smith, P. J. , and Sarofim, A. F. , 2008, “ Heat Transfer to Objects in Pool Fires,” Transport Phenomena in Fires, M. Faghri and B. Sunden , eds., WIT Press, Boston, MA, pp. 69–136. [CrossRef]
Modest, M. F. , 2013, “ The Method of Discrete Ordinates (Sn-Approximation),” Radiative Heat Transfer, 3rd ed., M. F. Modest , ed., Academic Press, Boston, MA, pp. 541–584.
Brink, A. , Lindberg, D. , Hupa, M. , De Tejada, M. E. , Paneru, M. , Maier, J. , Scheffknecht, G. , Pranzitelli, A. , and Pourkashanian, M. , 2016, “ A Temperature-History Based Model for the Sticking Probability of Impacting Pulverized Coal Ash Particles,” Fuel Process. Technol., 141(Pt. 2), pp. 210–215. [CrossRef]
Hecht, E. S. , Shaddix, C. R. , Geier, M. , Molina, A. , and Haynes, B. S. , 2012, “ Effect of CO2 and Steam Gasification Reactions on the Oxy-Combustion of Pulverized Coal Char,” Combust. Flame, 159(11), pp. 3437–3447. [CrossRef]
Hecht, E. S. , Shaddix, C. R. , Molina, A. , and Haynes, B. S. , 2011, “ Effect of CO2 Gasification Reaction on Oxy-Combustion of Pulverized Coal Char,” Proc. Combust. Inst., 33(2), pp. 1699–1706. [CrossRef]
Erland, N. , Haugen, L. , Mitchell, R. E. , and Tilghman, M. B. , 2015, “ A Comprehensive Model for Char Particle Conversion in Environments Containing O2 and CO2,” Combust. Flame, 162(4), pp. 1455–1463. [CrossRef]
Smoot, L. D. , and Smith, P. J. , 1985, Coal Combustion and Gasification, Plenum Press, New York. [CrossRef]
Rezaei, H. R. , Gupta, R. P. , Bryant, G. W. , Hart, J. T. , Liu, G. S. , Bailey, C. W. , Wall, T. F. , Miyamae, S. , Makino, K. , and Endo, Y. , 2000, “ Thermal Conductivity of Coal Ash and Slags and Models Used,” Fuel, 79(13), pp. 1697–1710. [CrossRef]
Wall, T. F. , Lowe, A. , Wibberley, L. J. , and Stewart, I. M. , 1979, “ Mineral Matter in Coal and the Thermal Performance of Large Boilers,” Prog. Energy Combust. Sci., 1, pp. 1–29. [CrossRef]
Wall, T. F. , Bhattacharya, S. P. , Baxter, L. L. , Richards, G. , and Harb, J. N. , 1995, “ The Character of Ash Deposits and the Thermal Performance of Furnaces,” Fuel Process. Technol., 44(1–3), pp. 143–153. [CrossRef]
Hunsaker, I. L. , Glaze, D. J. , Thornock, J. N. , and Smith, P. J. , 2012, “ A New Model for Virtual Radiometers,” ASME Paper No. HT2012-58093.
Hunsaker, I. L. , 2013, “ Parallel-Distributed, Reverse Monte Carlo Radiation in Coupled, Large Eddy Combustion Simulations,” Ph.D. thesis, The University of Utah, Salt Lake City, UT. http://home.chpc.utah.edu/~u0258978/MyThesis.pdf
Childs, H. , Brugger, E. , Whitlock, B. , Meredith, J. , Ahern, S. , Pugmire, D. , Biagas, K. , Miller, M. , Harrison, C. , Weber, G. H. , Krishnan, H. , Fogal, T. , Sanderson, A. , Garth, C. , Bethel, E. W. , Camp, D. , Rübel, O. , Durant, M. , Favre, J. , and Návratil, P. , 2012, “ VisIt: An End-User Tool for Visualizing and Analyzing Very Large Data,” High Performance Visualization–Enabling Extreme-Scale Scientific Insight (CRC Computational Science Series, Vol. 1), Boca Raton, FL. [CrossRef]


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Fig. 3

Drawing of the L1500 reactor located at the industrial combustion and gasification research facility: (a) schematic of the L1500 multifuel combustion furnace and (b) schematic of the first four sections of the L1500 furnace

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Fig. 4

L1500 cooling tubes: (a) Cooling tubes are located in the first four sections of the furnace; view is looking toward the furnace exit and (b) dimensions of a set of cooling tubes (in inches)

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Fig. 5

Schematic of the swirl burner used in the L1500 furnace. Inlets are labeled.

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Fig. 2

Six-step methodology with consistency analysis. Steps 1 and 2 are analyzed in this paper.

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Fig. 1

Validation hierarchy for CCMSC

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Fig. 6

Swirl vanes in the burner at the 0% swirl and 100% swirl positions

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Fig. 7

Experimental PSD (from sieving and diffraction measurements) and fitted Rosin–Rammler PSD. Only the Beckman–Coulter diffraction data was used for the Rosin–Rammler fit.

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Fig. 9

L1500 simulation coupling between Arches and star-ccm+

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Fig. 10

Velocities (m/s) at plane of the burner tip; left are star-ccm+ results with a resolution of 0.5 × 10−3 m, right are Arches results with a resolution of 15 × 10−3 m (ratio = 30)

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Fig. 8

Thermocouple placement in furnace wall. Section 4 is shown but the placement is similar for all thermocouple measurements.

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Fig. 11

Shortened geometry for the L1500 simulations including the quarl, the eight sets of cooling tubes, and the step change in the reactor floor. Resolution is 15 mm.

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Fig. 14

Main sensitivity indices for wall temperature

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Fig. 15

Wall temperature at thermocouple locations computed with Arches. Horizontal red line is Tslag.

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Fig. 12

Main sensitivity indices for radiative heat flux measured by the radiometers

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Fig. 13

Main sensitivity indices for the heat removed by the cooling tubes



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