Sensitivity of the Two-Fluid Model to Constitutive Correlations for Large Diameter Pipes
type: CreativeWork
description: "Multiphase flows are a significant factor in nuclear reactor operations. In order to understand this behavior in reactor systems, system analysis codes are used to simulate reactor conditions. Due to the nature of the nuclear industry, simulations predicting the void development in the core are required to be highly accurate. This work evaluated the sensitivity of the void fraction and interfacial area concentration predictions to changes in correlations used to calculate three parameters that are used to complete the interfacial drag calculation. The three parameters evaluated were drift-flux, void fraction covariance, and interfacial area concentration. The change in drift-flux correlation was found to have a significant effect on the void fraction prediction. The two-group approach for calculating drift-flux was found to have a higher accuracy than the one-group approach. A new drift-flux correlation was developed using the two-group approach, and was able to predict void fraction with a RMS error of 10.5%. The change in the void fraction covariance correlation was not found to have a significant effect on the void fraction predictive accuracy for the flow conditions evaluated in this work. The interfacial area transport equation (IATE) was found to have higher predictive accuracy for both void fraction and interfacial area concentration compared to interfacial area concentration correlations. An IATE was optimized for prediction of the individual groups of void fraction and interfacial area concentration and was able to reduce RMS error of the Group 1 and 2 void fraction from 41.6% to 20.8% and from 72.6% to 35.3%, respectively Group 1 and 2 interfacial area concentration from 43.3% to 28.3% and from 54.6% to 47.5% respectively"--Abstract, p. iv
abstract: "Multiphase flows are a significant factor in nuclear reactor operations. In order to understand this behavior in reactor systems, system analysis codes are used to simulate reactor conditions. Due to the nature of the nuclear industry, simulations predicting the void development in the core are required to be highly accurate. This work evaluated the sensitivity of the void fraction and interfacial area concentration predictions to changes in correlations used to calculate three parameters that are used to complete the interfacial drag calculation. The three parameters evaluated were drift-flux, void fraction covariance, and interfacial area concentration. The change in drift-flux correlation was found to have a significant effect on the void fraction prediction. The two-group approach for calculating drift-flux was found to have a higher accuracy than the one-group approach. A new drift-flux correlation was developed using the two-group approach, and was able to predict void fraction with a RMS error of 10.5%. The change in the void fraction covariance correlation was not found to have a significant effect on the void fraction predictive accuracy for the flow conditions evaluated in this work. The interfacial area transport equation (IATE) was found to have higher predictive accuracy for both void fraction and interfacial area concentration compared to interfacial area concentration correlations. An IATE was optimized for prediction of the individual groups of void fraction and interfacial area concentration and was able to reduce RMS error of the Group 1 and 2 void fraction from 41.6% to 20.8% and from 72.6% to 35.3%, respectively Group 1 and 2 interfacial area concentration from 43.3% to 28.3% and from 54.6% to 47.5% respectively"--Abstract, p. iv
author: Swearingen, Alexander Lee
keywords: Drift-flux model, Interfacial area concentration, Large diameter pipe, Sensitivity, Two-fluid model, Void fraction covariance, Engineering, Nuclear Engineering
date modified: 2026-07-24T03:18:26Z
provider: Missouri University of Science and Technology
publisher: Networked Digital Library of Theses and Dissertations
type: WebPage
source organization: Missouri University of Science and Technology