| dc.contributor.author | Remedes, Tyler J.;Ramsey, Scott D.;Baciak, James E. | |
| dc.date.accessioned | 2022-12-27T23:21:36Z | |
| dc.date.available | 2022-12-27T23:21:36Z | |
| dc.date.copyright | 8/3/2022 12:00:00 AM | |
| dc.date.issued | 2022 | |
| dc.identifier.issn | 2377-2158 | |
| dc.identifier.other | vvuq_007_03_031002.pdf | |
| dc.identifier.uri | http://yetl.yabesh.ir/yetl1/handle/yetl/4288463 | |
| dc.description.abstract | Nuclear science and engineering is a field increasingly dominated by computational studies resulting from increasingly powerful computational tools. As a result, analytical studies, which previously pioneered nuclear engineering, are increasingly viewed as secondary or unnecessary. However, analytical solutions to reduced-fidelity models can provide important information concerning the underlying physics of a problem and aid in guiding computational studies. Similarly, there is increased interest in sensitivity analysis studies. These studies commonly use computational tools. However, providing a complementary sensitivity study of relevant analytical models can lead to a deeper analysis of a problem. This work provides the analytical sensitivity analysis of the one-dimensional (1D) cylindrical mono-energetic neutron diffusion equation using the forward sensitivity analysis procedure (FSAP) developed by Cacuci. Further, these results are applied to a reduced-fidelity model of a spent nuclear fuel cask, demonstrating how computational analysis might be improved with a complementary analytic sensitivity analysis. | |
| dc.publisher | The American Society of Mechanical Engineers (ASME) | |
| dc.title | Analytical Sensitivity Analysis of a Spent Nuclear Fuel Cask | |
| dc.type | Journal Paper | |
| dc.journal.volume | 7 | |
| dc.journal.issue | 3 | |
| dc.journal.title | Journal of Verification, Validation and Uncertainty Quantification | |
| dc.identifier.doi | 10.1115/1.4055013 | |
| dc.journal.fristpage | 31002 | |
| dc.journal.lastpage | 31002_21 | |
| dc.page | 21 | |
| dc.tree | Journal of Verification, Validation and Uncertainty Quantification:;2022:;volume( 007 ):;issue: 003 | |
| dc.contenttype | Fulltext | |