Prioritization of VHTR system modeling needs based on phenomena identification, ranking and sensitivity studies.

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Quantification of uncertainty is a key requirement for the design of a nuclear power plant and the assurance of its safety. Historically the procedure has been to perform the required uncertainty assessment through comparison of the analytical predictions with experimental simulations. The issue with this historical approach has always been that the simulations through experiments could not be at full scale for the practical reasons of cost and scheduling. Invariably, only parts of the system were tested separately or if integral testing was performed for the complete system, the size or scale of the experimental apparatus was significantly smaller than ... continued below

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Vilim, R. B.; Pointer, W. D.; Wei, T. Y. C. & Division, Nuclear Engineering April 30, 2006.

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Description

Quantification of uncertainty is a key requirement for the design of a nuclear power plant and the assurance of its safety. Historically the procedure has been to perform the required uncertainty assessment through comparison of the analytical predictions with experimental simulations. The issue with this historical approach has always been that the simulations through experiments could not be at full scale for the practical reasons of cost and scheduling. Invariably, only parts of the system were tested separately or if integral testing was performed for the complete system, the size or scale of the experimental apparatus was significantly smaller than the actual plant configuration.

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  • Report No.: ANL-GEN-IV-071
  • Grant Number: DE-AC02-06CH11357
  • DOI: 10.2172/915026 | External Link
  • Office of Scientific & Technical Information Report Number: 915026
  • Archival Resource Key: ark:/67531/metadc886112

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  • April 30, 2006

Added to The UNT Digital Library

  • Sept. 22, 2016, 2:13 a.m.

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  • Sept. 28, 2016, 6:22 p.m.

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Vilim, R. B.; Pointer, W. D.; Wei, T. Y. C. & Division, Nuclear Engineering. Prioritization of VHTR system modeling needs based on phenomena identification, ranking and sensitivity studies., report, April 30, 2006; United States. (digital.library.unt.edu/ark:/67531/metadc886112/: accessed August 17, 2017), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT Libraries Government Documents Department.