A Simple Computational Model for the Prediction of Fuel Pin Failure During A Transient-Overpower Accident
Mast, Peter Karl
This item is only available for download by members of the University of Illinois community. Students, faculty, and staff at the U of I may log in with your NetID and password to view the item. If you are trying to access an Illinois-restricted dissertation or thesis, you can request a copy through your library's Inter-Library Loan office or purchase a copy directly from ProQuest.
Permalink
https://hdl.handle.net/2142/67782
Description
Title
A Simple Computational Model for the Prediction of Fuel Pin Failure During A Transient-Overpower Accident
Author(s)
Mast, Peter Karl
Issue Date
1980
Department of Study
Nuclear Engineering
Discipline
Nuclear Engineering
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
Ph.D.
Degree Level
Dissertation
Keyword(s)
Engineering, Nuclear
Energy
Language
eng
Abstract
A fuel pin failure model is developed and incorporated into a fast-running computer program. The model is designed to predict irradiated fuel-pin cladding rupture during a hypothetical transient-overpower (TOP) accident in a liquid metal fast breeder reactor. The principal failure mechanisms of fuel-cladding differential thermal expansion and fission-gas pressurization are accounted for.
The prediction of cladding failure is based on a mechanistic calculation of the time-dependent cladding temperature and stress. A finite-difference thermal solution is used to obtain the radial temperature distribution in the pin. The pin mechanics calculation uses a very efficient few-fuel-node/single-cladding-node algorithm that utilizes the Tresca yield criterion to determine the onset of cladding plastic deformation.
Comparisons are made between model predictions and the results of a number of Transient Reactor Test Facility TOP experiments. The importance of accurately modeling the fuel radial and circumferential crack characterization is investigated and discussed. The effect of model limitations is discussed and recommendations for future work are made.
Use this login method if you
don't
have an
@illinois.edu
email address.
(Oops, I do have one)
IDEALS migrated to a new platform on June 23, 2022. If you created
your account prior to this date, you will have to reset your password
using the forgot-password link below.
