TY - JOUR
T1 - Validation and uncertainty quantification of a multiphase computational fluid dynamics model
AU - Gel, Aytekin
AU - Li, Tingwen
AU - Gopalan, Balaji
AU - Shahnam, Mehrdad
AU - Syamlal, Madhava
PY - 2013/8/21
Y1 - 2013/8/21
N2 - 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.
AB - 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.
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U2 - 10.1021/ie303469f
DO - 10.1021/ie303469f
M3 - Article
AN - SCOPUS:84883157582
VL - 52
SP - 11424
EP - 11435
JO - Industrial & Engineering Chemistry Research
JF - Industrial & Engineering Chemistry Research
SN - 0888-5885
IS - 33
ER -