Parameter study for dynamic models of power bursts for the KEWB5, CRAC, and SILENE experiments
| dc.contributor.advisor | Hetrick, David L. | en_US |
| dc.contributor.author | Singleterry, Robert Clay, 1961- | |
| dc.creator | Singleterry, Robert Clay, 1961- | en_US |
| dc.date.accessioned | 2013-03-28T10:36:31Z | |
| dc.date.available | 2013-03-28T10:36:31Z | |
| dc.date.issued | 1990 | en_US |
| dc.identifier.uri | http://hdl.handle.net/10150/277305 | |
| dc.description.abstract | Two models were investigated to predict the power and pressure behavior of three liquid Uranium fueled reactors (K sc EWB5, C sc RAC, and S sc ILENE) during fast power excursions. Both models use the point reactor kinetics equations to generate the power and energy distributions in time, and an equilibrium thermodynamic analysis to generate the pressure, temperature, and volume distributions. The first model uses equilibrium thermodynamics to generate an equation of state for bubble formation that is static in bubble radius versus time. The second model uses mass transport theory to generate an equation of state that is dynamic in bubble radius. Simulations of the power excursions were run for both models and the results were compared to the experimental data and to each other. The first model was analyzed by varying the threshold gas mass fraction and the static bubble radius verses a range of step reactivity inputs to determine the effect on peak power and pressure. The second model used a trial and error strategy to determine the adjustable parameters that best fit the experimental data, then was also analyzed against the same ranges of step reactivity input. In the comparison, the dynamic model predicts the power and pressure versus time traces better than the static model. | |
| dc.language.iso | en_US | en_US |
| dc.publisher | The University of Arizona. | en_US |
| dc.rights | Copyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author. | en_US |
| dc.subject | Engineering, Nuclear. | en_US |
| dc.subject | Energy. | en_US |
| dc.title | Parameter study for dynamic models of power bursts for the KEWB5, CRAC, and SILENE experiments | en_US |
| dc.type | text | en_US |
| dc.type | Thesis-Reproduction (electronic) | en_US |
| thesis.degree.grantor | University of Arizona | en_US |
| thesis.degree.level | masters | en_US |
| dc.identifier.proquest | 1340306 | en_US |
| thesis.degree.discipline | Graduate College | en_US |
| thesis.degree.discipline | Nuclear and Energy Engineering | en_US |
| thesis.degree.name | M.S. | en_US |
| dc.identifier.bibrecord | .b26253100 | en_US |
| refterms.dateFOA | 2018-08-15T23:35:55Z | |
| html.description.abstract | Two models were investigated to predict the power and pressure behavior of three liquid Uranium fueled reactors (K sc EWB5, C sc RAC, and S sc ILENE) during fast power excursions. Both models use the point reactor kinetics equations to generate the power and energy distributions in time, and an equilibrium thermodynamic analysis to generate the pressure, temperature, and volume distributions. The first model uses equilibrium thermodynamics to generate an equation of state for bubble formation that is static in bubble radius versus time. The second model uses mass transport theory to generate an equation of state that is dynamic in bubble radius. Simulations of the power excursions were run for both models and the results were compared to the experimental data and to each other. The first model was analyzed by varying the threshold gas mass fraction and the static bubble radius verses a range of step reactivity inputs to determine the effect on peak power and pressure. The second model used a trial and error strategy to determine the adjustable parameters that best fit the experimental data, then was also analyzed against the same ranges of step reactivity input. In the comparison, the dynamic model predicts the power and pressure versus time traces better than the static model. |
