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Title: | A Computational Benchmark Study of Forced Convective Heat Transfer to Water at Supercritical Pressure Flowing Within a 7 Rod Bundle |
Other Titles: | Submission to the GIF SCWR Computational Benchmark Exercise |
Authors: | McClure, Darryl |
Advisor: | Novog, David |
Department: | Engineering Physics |
Keywords: | CFD;Heat Transfer;Fluid mechanics;STAR-CCM+;Turbulence Modelling;SCWR |
Publication Date: | Jun-2014 |
Abstract: | The research and development effort for the next generation of nuclear power stations is being coordinated by the Generation IV International Forum (GIF). The supercritical water reactor (SCWR) is one of the six reactor technologies currently being pursued by the GIF. The unique nature of supercritical water necessitates further examination of its heat transfer regimes. The GIF SCWR blind computational benchmark exercise is focused on furthering the understanding of the heat transfer to supercritical water as well as its prediction. A methodology for computational fluid dynamics (CFD) simulations using STAR-CCM+ 9.02.005 has been developed for submission to the GIF SCWR computational benchmark exercise. The experiments of the GIF SCWR computational benchmark exercise were those conducted by the Japan Atomic Energy Agency (JAEA). They are of supercritical water flowing upward in a 7 rod bundle. Of the three experimental cases there are (i) an isothermal case, (ii) a low enthalpy, low heat flux case and (iii) a high enthalpy, high heat flux case. A separate effects study has been undertaken and the SST turbulence model has been chosen to model each of the three experiments. A near wall treatment that ensures a y+<0.09 has been used for both of the heated cases and a near wall treatment that ensures a y+<0.53 has been used for the isothermal case. This computational approach was determined to be the optimal choice which balances solution accuracy with computation time. Final simulation results are presented in advance of the release of the experimental results in June 2014. |
URI: | http://hdl.handle.net/11375/15392 |
Appears in Collections: | Open Access Dissertations and Theses |
Files in This Item:
File | Description | Size | Format | |
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D_McClure_MASc_Thesis.pdf | Thesis | 4.06 MB | Adobe PDF | View/Open |
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