Graduate Thesis Or Dissertation

Modeling and Scaling Studies on Heat Pipe Heat Transfer in INL MAGNET Tests

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  • Scaling analysis for nuclear reactors is a widely used process in safety testing and code validation with proven success through decades of experience. In this study, the Hierarchical Two-Tiered Scaling (H2TS) method and the Dynamical System Scaling (DSS) analysis are employed for the assessment of the heat transfer coefficient of a heat pipe to be employed in a heat pipe microreactor design. The test data were collected from the Microreactor Agile Non-Nuclear Experimental Testbed (MAGNET) of the Idaho National Laboratory (INL), which is part of the Dynamic Energy Transportation and Integration Laboratory (DETAIL) under the Integrated Energy Systems (IES) group. In support of the IES mission that utilizes nuclear energy in a mix of renewable energy sources, the MAGNET facility acts as a nuclear power source from a Microreactor that uses heat pipes to harvest nuclear energy. The purpose of this thesis is to perform an analysis of aspects related to the heat pipe heat transfer characterization and its scaling to the prototypic system. In this thesis, heat transfer models were derived to quantify the heat pipe heat transfer coefficient from the MAGNET tests. H2TS and DSS methodologies were utilized to develop governing equations, heat transfer relations, and similarity outcomes to quantify differences. The eventual full-scale design that the test article within MAGNET is based on will require a higher fidelity model and additional considerations for the more complex geometry and physical restraints for experimental testing. To circumvent the limitations of the experimental data relative to the objectives of this auxiliary analysis, a model for a blanket heat transfer coefficient with temperature-dependent sodium thermal conductivity was developed. This model was then applied in steady state and transient form using H2TS and DSS, respectively, to form a toolbox for integration with the other scaled facilities within DETAIL. With the influence of system parameters included in the heat transfer coefficient, the scaling parameters and non-dimensional groups have improved similarity with the experimental data. Using DSS, the unique null process type identified in the transient cooldown phase was assessed to provide further insight concerning the required fidelity for a more complex and accurate model. In lieu of the standard error analysis for DSS, which does not apply to the null process type, we propose the integrated change of frequency between the model and prototypic system to represent the differences.
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  • This research was partially funded on a sub-contract between Idaho National Laboratory and Oregon State University.



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