Nuclear nonproliferation research and forensics have a need for improved software solutions, particularly in the estimates of the transmutation of nuclear fuel during burnup and depletion. At the same time, parallel computers have become effectively sized to enable full core simulations using highly-detailed 3d mesh models. In this work, the capability for modeling 3d reactor models is researched with PENBURN, a burnup/depletion code that couples to the PENTRAN Parallel Sn Transport Solver and also to the Monte Carlo solver MCNP5 using the multigroup option. This research is computationally focused, but will also compare a subset of results of experimental Pressurized Water Reactor (PWR) burnup spectroscopy data available with a designated BR3 PWR burnup benchmark. Also, this research will analyze large-scale Cartesian mesh models that can be feasibly modeled for 3d burnup, as well as investigate the improvement of finite differencing schemes used in parallel discrete ordinates transport with PENTRAN, in order to optimize runtimes for full core transport simulation, and provide comparative results with Monte Carlo simulations. Also, the research will consider improvements to software that will be parallelized, further improving large model simulation using hybrid OpenMP-MPI. The core simulations that form the basis of this research, utilizing discrete ordinates methods and Monte Carlo methods to drive time and space dependent isotopic reactor production using the PENBURN code, will provide more accurate detail of fuel compositions that can benefit nuclear safety, fuel management, non-proliferation, and safeguards applications.
| Identifer | oai:union.ndltd.org:GATECH/oai:smartech.gatech.edu:1853/50351 |
| Date | 13 January 2014 |
| Creators | Manalo, Kevin |
| Contributors | Sjoden, Glenn E. |
| Publisher | Georgia Institute of Technology |
| Source Sets | Georgia Tech Electronic Thesis and Dissertation Archive |
| Language | en_US |
| Detected Language | English |
| Type | Dissertation |
| Format | application/pdf |
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