Developing a reliable approach to estimate the stoichiometric ratio of O/U in UO2 pellets using MCNP-5 and artificial intelligence
Uranium dioxied is used as a nuclear fuel. Depending on the temperature and oxygen partial pressure, it is incredibly versatile and can accept a wide variety of stoichiometry. Many methods are used to estimate the non-stoichiometric O/U ratio such as the coulometric titration, gravimetric...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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VINCA Institute of Nuclear Sciences
2022-01-01
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| Series: | Nuclear Technology and Radiation Protection |
| Subjects: | |
| Online Access: | https://doiserbia.nb.rs/img/doi/1451-3994/2022/1451-39942204302S.pdf |
| _version_ | 1797807557806391296 |
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| author | Shaban Sameh E. Agha Ahmad R. Aladham Karim A. |
| author_facet | Shaban Sameh E. Agha Ahmad R. Aladham Karim A. |
| author_sort | Shaban Sameh E. |
| collection | DOAJ |
| description | Uranium dioxied is used as a nuclear fuel. Depending on the temperature and
oxygen partial pressure, it is incredibly versatile and can accept a wide
variety of stoichiometry. Many methods are used to estimate the
non-stoichiometric O/U ratio such as the coulometric titration, gravimetric
and voltammetric methods. These methods have some disadvantages and may be
time and cost-consuming. This work develops an approach to determine the
stoichiometric ratio by using MCNP-5 code and hyper pure germanium detector
to estimate the count rate at 185.7 keV for UO2 pellets. The studied
pellets are proposed to have 235U mass content (3 %, 4 %, and 5 %) and 1 cm
away from the detector. The mass of the oxide within the pellets is 7.8995
grams. The relation between volume and density has been studied during
different steps in which temperature increases. Finally, a reliable model is
established to describe the process of converting green pellets to sintered
pellets. The model is supported by employing artificial intelligence to
predict some features and the overall correlation equals 0.99929. |
| first_indexed | 2024-03-13T06:24:23Z |
| format | Article |
| id | doaj.art-019897f86b25469193c589a35d9ce75b |
| institution | Directory Open Access Journal |
| issn | 1451-3994 1452-8185 |
| language | English |
| last_indexed | 2024-03-13T06:24:23Z |
| publishDate | 2022-01-01 |
| publisher | VINCA Institute of Nuclear Sciences |
| record_format | Article |
| series | Nuclear Technology and Radiation Protection |
| spelling | doaj.art-019897f86b25469193c589a35d9ce75b2023-06-09T10:42:54ZengVINCA Institute of Nuclear SciencesNuclear Technology and Radiation Protection1451-39941452-81852022-01-0137430230710.2298/NTRP2204302S1451-39942204302SDeveloping a reliable approach to estimate the stoichiometric ratio of O/U in UO2 pellets using MCNP-5 and artificial intelligenceShaban Sameh E.0Agha Ahmad R.1Aladham Karim A.2Nuclear Safeguards and Physical Protection Department, Nuclear and Radiological Safety Research Center, Egyptian Atomic Energy Authority, Cairo, EgyptSafety of Nuclear Fuel Cycle Department, Nuclear and Radiological Safety Research Center, Egyptian Atomic Energy Authority, Cairo, EgyptSafety of Nuclear Fuel Cycle Department, Nuclear and Radiological Safety Research Center, Egyptian Atomic Energy Authority, Cairo, EgyptUranium dioxied is used as a nuclear fuel. Depending on the temperature and oxygen partial pressure, it is incredibly versatile and can accept a wide variety of stoichiometry. Many methods are used to estimate the non-stoichiometric O/U ratio such as the coulometric titration, gravimetric and voltammetric methods. These methods have some disadvantages and may be time and cost-consuming. This work develops an approach to determine the stoichiometric ratio by using MCNP-5 code and hyper pure germanium detector to estimate the count rate at 185.7 keV for UO2 pellets. The studied pellets are proposed to have 235U mass content (3 %, 4 %, and 5 %) and 1 cm away from the detector. The mass of the oxide within the pellets is 7.8995 grams. The relation between volume and density has been studied during different steps in which temperature increases. Finally, a reliable model is established to describe the process of converting green pellets to sintered pellets. The model is supported by employing artificial intelligence to predict some features and the overall correlation equals 0.99929.https://doiserbia.nb.rs/img/doi/1451-3994/2022/1451-39942204302S.pdfstoichiometryuo2 pelletartificial intelligencemcnp-5 |
| spellingShingle | Shaban Sameh E. Agha Ahmad R. Aladham Karim A. Developing a reliable approach to estimate the stoichiometric ratio of O/U in UO2 pellets using MCNP-5 and artificial intelligence Nuclear Technology and Radiation Protection stoichiometry uo2 pellet artificial intelligence mcnp-5 |
| title | Developing a reliable approach to estimate the stoichiometric ratio of O/U in UO2 pellets using MCNP-5 and artificial intelligence |
| title_full | Developing a reliable approach to estimate the stoichiometric ratio of O/U in UO2 pellets using MCNP-5 and artificial intelligence |
| title_fullStr | Developing a reliable approach to estimate the stoichiometric ratio of O/U in UO2 pellets using MCNP-5 and artificial intelligence |
| title_full_unstemmed | Developing a reliable approach to estimate the stoichiometric ratio of O/U in UO2 pellets using MCNP-5 and artificial intelligence |
| title_short | Developing a reliable approach to estimate the stoichiometric ratio of O/U in UO2 pellets using MCNP-5 and artificial intelligence |
| title_sort | developing a reliable approach to estimate the stoichiometric ratio of o u in uo2 pellets using mcnp 5 and artificial intelligence |
| topic | stoichiometry uo2 pellet artificial intelligence mcnp-5 |
| url | https://doiserbia.nb.rs/img/doi/1451-3994/2022/1451-39942204302S.pdf |
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