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Comparison of Three-Dimensional Flux Synthesis and Full Three-Dimensional Discrete Ordinates Methods for the Calculation of Reactor Cavity Bioshield Heat Generation Rates

Joel A. Kulesza

Nuclear Technology / Volume 175 / Number 1 / July 2011 / Pages 228-237

Technical Paper / Special Issue on the 16th Biennial Topical Meeting of the Radiation Protection and Shielding Division / Radiation Transport and Protection

In the computational fluid dynamics analysis to determine the necessary cooling airflow rates in the reactor cavity of a nuclear power plant during operation, the heat generated in the sacrificial bioshield and adjacent components is a significant source term. Traditionally, a three-dimensional (3-D) flux synthesis method is used to calculate the heat generation rate in the bioshield for reactors with a cylindrical reactor cavity because there is minimal azimuthal variation. However, the AP1000™ reactor incorporates an octagonal reactor cavity design with 12 ex-core detectors, leading to potentially significant impacts on the azimuthal heat generation rate distribution. Therefore, it was of interest to benchmark the traditional flux synthesis method with full 3-D discrete ordinates methods. Because of an uncertainty in the amount of mesh refinement necessary to have confidence in the results, a sensitivity study on the mesh refinement was performed with a parallel 3-D discrete ordinates code. This allowed a comparison with an industry-standard serial 3-D discrete ordinates code in terms of both execution speed and calculated results.

The results suggest that for angular positions where the flux synthesis method incorporates an axial model, there is relatively good agreement with 3-D methods (within ±20%). In areas remote from axial models, there are differences of up to a factor of 2 in a nonconservative direction. Furthermore, a recently developed parallel 3-D discrete ordinates radiation transport code was shown to produce results generally consistent with the industry-standard 3-D code used (within 2.5%). Finally, the parallel code completed its calculations in 10% of the time required by the serial code for an identically sized problem.

 
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