Iterative acceleration methods for Monte Carlo and deterministic criticality calculations

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If you have ever given up on a nuclear criticality calculation and terminated it because it took so long to converge, you might find this thesis of interest. The author develops three methods for improving the fission source convergence in nuclear criticality calculations for physical systems with high dominance ratios for which convergence is slow. The Fission Matrix Acceleration Method and the Fission Diffusion Synthetic Acceleration (FDSA) Method are acceleration methods that speed fission source convergence for both Monte Carlo and deterministic methods. The third method is a hybrid Monte Carlo method that also converges for difficult problems where the ... continued below

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157 p.

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Urbatsch, T.J. November 1, 1995.

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Description

If you have ever given up on a nuclear criticality calculation and terminated it because it took so long to converge, you might find this thesis of interest. The author develops three methods for improving the fission source convergence in nuclear criticality calculations for physical systems with high dominance ratios for which convergence is slow. The Fission Matrix Acceleration Method and the Fission Diffusion Synthetic Acceleration (FDSA) Method are acceleration methods that speed fission source convergence for both Monte Carlo and deterministic methods. The third method is a hybrid Monte Carlo method that also converges for difficult problems where the unaccelerated Monte Carlo method fails. The author tested the feasibility of all three methods in a test bed consisting of idealized problems. He has successfully accelerated fission source convergence in both deterministic and Monte Carlo criticality calculations. By filtering statistical noise, he has incorporated deterministic attributes into the Monte Carlo calculations in order to speed their source convergence. He has used both the fission matrix and a diffusion approximation to perform unbiased accelerations. The Fission Matrix Acceleration method has been implemented in the production code MCNP and successfully applied to a real problem. When the unaccelerated calculations are unable to converge to the correct solution, they cannot be accelerated in an unbiased fashion. A Hybrid Monte Carlo method weds Monte Carlo and a modified diffusion calculation to overcome these deficiencies. The Hybrid method additionally possesses reduced statistical errors.

Physical Description

157 p.

Notes

INIS; OSTI as DE96008884

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  • Other Information: DN: Thesis submitted to Univ. of Michigan, Ann Arbor, MI (US); TH: Thesis (Ph.D.)

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  • Other: DE96008884
  • Report No.: LA--13052-T
  • Grant Number: W-7405-ENG-36
  • DOI: 10.2172/212566 | External Link
  • Office of Scientific & Technical Information Report Number: 212566
  • Archival Resource Key: ark:/67531/metadc672924

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Office of Scientific & Technical Information Technical Reports

Reports, articles and other documents harvested from the Office of Scientific and Technical Information.

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  • November 1, 1995

Added to The UNT Digital Library

  • June 29, 2015, 9:42 p.m.

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  • Feb. 25, 2016, 8:01 p.m.

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Urbatsch, T.J. Iterative acceleration methods for Monte Carlo and deterministic criticality calculations, report, November 1, 1995; New Mexico. (digital.library.unt.edu/ark:/67531/metadc672924/: accessed June 21, 2018), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT Libraries Government Documents Department.