Validation and uncertainty quantification of a multiphase computational fluid dynamics model

Aytekin Gel, Tingwen Li, Balaji Gopalan, Mehrdad Shahnam, Madhava Syamlal

Research output: Contribution to journalArticlepeer-review

21 Scopus citations

Abstract

We describe the application of a validation and uncertainty quantification methodology to multiphase computational fluid dynamics modeling, demonstrating the methodology with simulations of a pilot-scale circulating fluidized bed. The overall pressure drop is used as the quantity of interest (QoI); the solids circulation rate and the superficial gas velocity are chosen as the uncertain input quantities. The uncertainty in the QoI, caused by uncertainties in input parameters, surrogate model, spatial discretization, and time averaging, is calculated, and the model form uncertainty is estimated by comparing simulation results with experimental data. The spatial discretization error was determined to be the most dominant source of uncertainty, but the applicability of the method used to calculate that uncertainty needs to be further investigated. The results of the analysis are expressed as a probability box (p-box) plot. A p-box similarly constructed for predictive simulations will give the design engineer information about the confidence in the predicted values.

Original languageEnglish (US)
Pages (from-to)11424-11435
Number of pages12
JournalIndustrial and Engineering Chemistry Research
Volume52
Issue number33
DOIs
StatePublished - Aug 21 2013
Externally publishedYes

ASJC Scopus subject areas

  • Chemistry(all)
  • Chemical Engineering(all)
  • Industrial and Manufacturing Engineering

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