Nonintrusive Uncertainty Quantification of Computational Fluid Dynamics Simulations of a Bench-Scale Fluidized-Bed Gasifier Article Swipe
Aytekin Gel
,
Mehrdad Shahnam
,
Jordan Musser
,
Arun Subramaniyan
,
Jean-François Dietiker
·
YOU?
·
· 2016
· Open Access
·
· DOI: https://doi.org/10.1021/acs.iecr.6b02506
YOU?
·
· 2016
· Open Access
·
· DOI: https://doi.org/10.1021/acs.iecr.6b02506
Uncertainty quantification (UQ) analysis is increasingly becoming one of the major requirements of simulation-based engineering to assess the confidence in the results and make better-informed decisions based on the insight derived from the simulations. In an earlier study, Bayesian UQ analysis was applied to existing bench-scale fluidized-bed gasifier experiment results. In the current study, a series of simulations were carried over with the open-source computational fluid dynamics software MFiX to reproduce the experimental conditions, where three operating factors, i.e., coal flow rate, coal particle diameter, and steam-to-oxygen ratio, were systematically varied to understand their effect on the syngas composition. Bayesian UQ analysis was this time performed on the numerical results for comparison purposes. This is part of ongoing research efforts to explore the applicability of advanced UQ methods and processes such as Bayesian methods for large-scale complex multiphase flow simulations. As part of Bayesian UQ analysis, a global sensitivity analysis was performed based on the simulation results, which shows that the predicted syngas composition is strongly affected not only by the steam-to-oxygen ratio (which was observed in experiments as well) but also by variation in the coal flow rate and particle diameter (which was not observed in experiments). The carbon monoxide mole fraction is underpredicted at lower steam-to-oxygen ratios and overpredicted at higher steam-to-oxygen ratios. The opposite trend is observed for the carbon dioxide mole fraction. These discrepancies are attributed to either excessive segregation of the phases that leads to the fuel-rich or -lean regions or alternatively the selection of reaction models, where different reaction models and kinetics can lead to different syngas compositions throughout the gasifier.
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- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1021/acs.iecr.6b02506
- OA Status
- green
- Cited By
- 14
- References
- 15
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W2538530659
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W2538530659Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1021/acs.iecr.6b02506Digital Object Identifier
- Title
-
Nonintrusive Uncertainty Quantification of Computational Fluid Dynamics Simulations of a Bench-Scale Fluidized-Bed GasifierWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2016Year of publication
- Publication date
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2016-10-20Full publication date if available
- Authors
-
Aytekin Gel, Mehrdad Shahnam, Jordan Musser, Arun Subramaniyan, Jean-François DietikerList of authors in order
- Landing page
-
https://doi.org/10.1021/acs.iecr.6b02506Publisher landing page
- Open access
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YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
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https://www.osti.gov/biblio/1480085Direct OA link when available
- Concepts
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Wood gas generator, Coal, Integrated gasification combined cycle, Fluidized bed, Fraction (chemistry), Syngas, Gas composition, Process engineering, Environmental science, Nuclear engineering, Chemistry, Thermodynamics, Waste management, Engineering, Hydrogen, Chromatography, Physics, Organic chemistryTop concepts (fields/topics) attached by OpenAlex
- Cited by
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14Total citation count in OpenAlex
- Citations by year (recent)
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2025: 1, 2024: 1, 2023: 1, 2021: 1, 2020: 1Per-year citation counts (last 5 years)
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15Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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