{"id":{"repo_id":"mit","oai_identifier":"oai:dspace.mit.edu:1721.1/97963"},"canonical_url":"https://search.dev.ndltd.org/etd/mit/oai:dspace.mit.edu:1721.1/97963","repository":{"repo_id":"mit","name":"MIT","base_url":"https://dspace.mit.edu/oai/request"},"display":{"title":"LWR fuel reactivity depletion verification using 2D full core MOC and flux map data","abstract":"Experimental quantification of PWR fuel reactivity burnup decrement biases and uncertainties using in-core flux map data from operating power reactors has previously been conducted employing analytical methods to systematically determine experimental fuel reactivities that best match measured fission rate distributions. This optimal core reactivity distribution that best matches the measured fission rate distribution is assumed to be associated with the true fuel reactivity distribution. Some parties have questioned whether fortuitous cancellation of errors between various approximations inherent in the 3D nodal diffusion core analysis models might have caused reactivity decrement biases and uncertainties to be unrealistically small. In this study, the BEAVRS benchmark is modeled with both 2D, full-core, multi-group transport calculations and 2D and 3D nodal diffusion calculations. The calculated reaction rates are compared with measured in-core detector reaction rates supplied in the benchmark. These models are used in conjunction with analytical methods to obtain fuel reactivity biases and uncertainties. Results demonstrate that fuel batch reactivities inferred from flux map data using full-core transport calculations are nearly identical to those inferred using nodal diffusion calculations. Consequently, nodal methods do not contribute significantly to reactivity decrement biases. Fuel reactivity biases and uncertainties inferred from 3D nodal diffusion calculations remain valid.","abstract_html":"Experimental quantification of PWR fuel reactivity burnup decrement biases and uncertainties using in-core flux map data from operating power reactors has previously been conducted employing analytical methods to systematically determine experimental fuel reactivities that best match measured fission rate distributions. This optimal core reactivity distribution that best matches the measured fission rate distribution is assumed to be associated with the true fuel reactivity distribution. Some parties have questioned whether fortuitous cancellation of errors between various approximations inherent in the 3D nodal diffusion core analysis models might have caused reactivity decrement biases and uncertainties to be unrealistically small. In this study, the BEAVRS benchmark is modeled with both 2D, full-core, multi-group transport calculations and 2D and 3D nodal diffusion calculations. The calculated reaction rates are compared with measured in-core detector reaction rates supplied in the benchmark. These models are used in conjunction with analytical methods to obtain fuel reactivity biases and uncertainties. Results demonstrate that fuel batch reactivities inferred from flux map data using full-core transport calculations are nearly identical to those inferred using nodal diffusion calculations. Consequently, nodal methods do not contribute significantly to reactivity decrement biases. Fuel reactivity biases and uncertainties inferred from 3D nodal diffusion calculations remain valid.","abstract_has_math":false,"creators":["Gunow, Geoffrey Alexander"],"institution":"Massachusetts Institute of Technology","degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":"Massachusetts Institute of Technology. Department of Nuclear Science and Engineering.","school":null,"contributors":[],"advisors":["Kord Smith and Benoit Forget."],"committee_chairs":[],"committee_members":[],"year":2015,"date_issued":"2015","date_published":"2015","updated_at":"2026-07-22T22:21:57Z","subjects":["Nuclear Science and Engineering."],"languages":["eng"],"rights":["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."],"rights_urls":["http://dspace.mit.edu/handle/1721.1/7582"],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/1721.1/97963","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Kord Smith and Benoit Forget."]},{"key":"dc:contributor.department","label":"Department","values":["Massachusetts Institute of Technology. Department of Nuclear Science and Engineering."]},{"key":"dc:contributor.other","label":"Dc Contributor Other","values":["Massachusetts Institute of Technology. Department of Nuclear Science and Engineering."]},{"key":"dc:creator","label":"Author","values":["Gunow, Geoffrey Alexander"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2015-07-31T19:08:34Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2015-07-31T19:08:34Z"]},{"key":"dc:date.issued","label":"Date","values":["2015"]},{"key":"dc:publisher","label":"Institution","values":["Massachusetts Institute of Technology"]},{"key":"dc:type","label":"Dc Type","values":["Thesis"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Nuclear Science and Engineering."]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language.iso","label":"Language (ISO)","values":["eng"]},{"key":"dc:rights","label":"Dc Rights","values":["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."]},{"key":"dc:rights.uri","label":"Rights URI","values":["http://dspace.mit.edu/handle/1721.1/7582"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["http://hdl.handle.net/1721.1/97963"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Thesis: S.M., Massachusetts Institute of Technology, Department of Nuclear Science and Engineering, 2015.","Cataloged from PDF version of thesis.","Includes bibliographical references (pages 89-90)."]},{"key":"dc:description.abstract","label":"Abstract","values":["Experimental quantification of PWR fuel reactivity burnup decrement biases and uncertainties using in-core flux map data from operating power reactors has previously been conducted employing analytical methods to systematically determine experimental fuel reactivities that best match measured fission rate distributions. This optimal core reactivity distribution that best matches the measured fission rate distribution is assumed to be associated with the true fuel reactivity distribution. Some parties have questioned whether fortuitous cancellation of errors between various approximations inherent in the 3D nodal diffusion core analysis models might have caused reactivity decrement biases and uncertainties to be unrealistically small. In this study, the BEAVRS benchmark is modeled with both 2D, full-core, multi-group transport calculations and 2D and 3D nodal diffusion calculations. The calculated reaction rates are compared with measured in-core detector reaction rates supplied in the benchmark. These models are used in conjunction with analytical methods to obtain fuel reactivity biases and uncertainties. Results demonstrate that fuel batch reactivities inferred from flux map data using full-core transport calculations are nearly identical to those inferred using nodal diffusion calculations. Consequently, nodal methods do not contribute significantly to reactivity decrement biases. Fuel reactivity biases and uncertainties inferred from 3D nodal diffusion calculations remain valid."]},{"key":"dc:description.degree","label":"Dc Description Degree","values":["S.M."]},{"key":"dc:title","label":"Title","values":["LWR fuel reactivity depletion verification using 2D full core MOC and flux map data"]}]}],"canonical_facts":{"dc:contributor.advisor":["Kord Smith and Benoit Forget."],"dc:contributor.department":["Massachusetts Institute of Technology. Department of Nuclear Science and Engineering."],"dc:contributor.other":["Massachusetts Institute of Technology. Department of Nuclear Science and Engineering."],"dc:creator":["Gunow, Geoffrey Alexander"],"dc:date.accessioned":["2015-07-31T19:08:34Z"],"dc:date.available":["2015-07-31T19:08:34Z"],"dc:date.issued":["2015"],"dc:description":["Thesis: S.M., Massachusetts Institute of Technology, Department of Nuclear Science and Engineering, 2015.","Cataloged from PDF version of thesis.","Includes bibliographical references (pages 89-90)."],"dc:description.abstract":["Experimental quantification of PWR fuel reactivity burnup decrement biases and uncertainties using in-core flux map data from operating power reactors has previously been conducted employing analytical methods to systematically determine experimental fuel reactivities that best match measured fission rate distributions. This optimal core reactivity distribution that best matches the measured fission rate distribution is assumed to be associated with the true fuel reactivity distribution. Some parties have questioned whether fortuitous cancellation of errors between various approximations inherent in the 3D nodal diffusion core analysis models might have caused reactivity decrement biases and uncertainties to be unrealistically small. In this study, the BEAVRS benchmark is modeled with both 2D, full-core, multi-group transport calculations and 2D and 3D nodal diffusion calculations. The calculated reaction rates are compared with measured in-core detector reaction rates supplied in the benchmark. These models are used in conjunction with analytical methods to obtain fuel reactivity biases and uncertainties. Results demonstrate that fuel batch reactivities inferred from flux map data using full-core transport calculations are nearly identical to those inferred using nodal diffusion calculations. Consequently, nodal methods do not contribute significantly to reactivity decrement biases. Fuel reactivity biases and uncertainties inferred from 3D nodal diffusion calculations remain valid."],"dc:description.degree":["S.M."],"dc:identifier.uri":["http://hdl.handle.net/1721.1/97963"],"dc:language.iso":["eng"],"dc:publisher":["Massachusetts Institute of Technology"],"dc:rights":["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."],"dc:rights.uri":["http://dspace.mit.edu/handle/1721.1/7582"],"dc:subject":["Nuclear Science and Engineering."],"dc:title":["LWR fuel reactivity depletion verification using 2D full core MOC and flux map data"],"dc:type":["Thesis"]},"updated_at":"2026-07-22T22:21:57Z"}