MIT Libraries homeMIT Libraries logoDSpace@MIT

MIT
View Item 
  • DSpace@MIT Home
  • MIT Libraries
  • MIT Theses
  • Undergraduate Theses
  • View Item
  • DSpace@MIT Home
  • MIT Libraries
  • MIT Theses
  • Undergraduate Theses
  • View Item
JavaScript is disabled for your browser. Some features of this site may not work without it.

Investigation of improved methods for assessing convergence of models in MCNP using Shannon entropy

Author(s)
Macdonald, Ruaridh (Ruaridh R.)
Thumbnail
DownloadFull printable version (7.761Mb)
Other Contributors
Massachusetts Institute of Technology. Dept. of Nuclear Science and Engineering.
Advisor
Benoit Forget.
Terms of use
M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission. http://dspace.mit.edu/handle/1721.1/7582
Metadata
Show full item record
Abstract
Monte Carlo computationals methods are widely used in academia to analyze nuclear systems design and operation because of their high accuracy and the relative ease of use in comparison to deterministic methods. However, current Monte Carlo codes require an extensive knowledge of the physics of a problem as well as the computational methods being used in order to ensure accuracy. This investigation aims to provide better on-the-fly diagnostics for convergence using Shannon entropy and statistical checks for tally undersampling in order to reduce the burden on the code user, hopfully increasing the use and accuracy of Monte Carlo codes. These methods were tested by simulating the OECD/NEA benchmark #1 problem in MCNP. It was found that Shannon entropy does accurately predict the number of batches required for a source distribution to converge, though only when when the Shannon entropy mesh was the size of the tally mesh. The investigation of undersampling showed evidence of methods to predict undersampling on-the-fly using Shannon entropy as well as laying out where future work should lead.
Description
Thesis (S.B.)--Massachusetts Institute of Technology, Dept. of Nuclear Science and Engineering, 2012.
 
"June 2012." Cataloged from PDF version of thesis.
 
Includes bibliographical references (p. 42).
 
Date issued
2012
URI
http://hdl.handle.net/1721.1/76954
Department
Massachusetts Institute of Technology. Department of Nuclear Science and Engineering
Publisher
Massachusetts Institute of Technology
Keywords
Nuclear Science and Engineering.

Collections
  • Undergraduate Theses

Browse

All of DSpaceCommunities & CollectionsBy Issue DateAuthorsTitlesSubjectsThis CollectionBy Issue DateAuthorsTitlesSubjects

My Account

Login

Statistics

OA StatisticsStatistics by CountryStatistics by Department
MIT Libraries homeMIT Libraries logo

Find us on

Twitter Facebook Instagram YouTube RSS

MIT Libraries navigation

SearchHours & locationsBorrow & requestResearch supportAbout us
PrivacyPermissionsAccessibility
MIT
Massachusetts Institute of Technology
Content created by the MIT Libraries, CC BY-NC unless otherwise noted. Notify us about copyright concerns.