A Validation/Uncertainty Quantification Analysis for a 1.5 MW Oxy-Coal Fired Furnace: Sensitivity Analysis
| Autor: | Jennifer Spinti, Jeremy N. Thornock, Oscar H. Diaz-Ibarra, Sean T. Smith, Michal Hradisky, Philip J. Smith, Benjamin Isaac, Andrew Fry |
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| Rok vydání: | 2018 |
| Předmět: |
Statistics and Probability
business.industry Fuel gasification 02 engineering and technology Coal fired 021001 nanoscience & nanotechnology Combustion Computer Science Applications 020401 chemical engineering Computational Theory and Mathematics Heat flux Modeling and Simulation Environmental science Coal Engineering simulation Sensitivity (control systems) 0204 chemical engineering Uncertainty quantification 0210 nano-technology Process engineering business |
| Zdroj: | Journal of Verification, Validation and Uncertainty Quantification. 3 |
| ISSN: | 2377-2166 2377-2158 |
| DOI: | 10.1115/1.4040585 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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