Published 1997
| Version v1
Miscellaneous
Analysis and optimization of gas-centrifugal separation of uranium isotopes by neural networks
Creators
- 1. Instituto de Pesquisas Energeticas e Nucleares (IPEN), Sao Paulo, SP (Brazil)
- 2. Sao Paulo Univ., SP (Brazil). Escola Politecnica
- 3. Centro Tecnologico da Marinha (CTMSP), Sao Paulo, SP (Brazil)
Description
Neural networks are an attractive alternative for modeling complex problems that show too many difficulties to be solved by phenomenological model. A feed-forward neural network was used to model a uranium isotopes gas-centrifugal separation. The prediction showed good agreement with the experimental data. An optimization study was performed. The optimal operation condition was tested by a new experiment and a difference of less than 1% was found. (author). 18 refs., 9 figs., 1 tab
Additional details
Publishing Information
- Imprint Title
- Proceedings of the 11. ENFIR: Meeting on reactor physics and thermal hydraulics
- Imprint Pagination
- 838 p.
- Journal Page Range
- p. 350-356.
Conference
- Title
- Meeting on reactor physics and thermal hydraulics.
- Acronym
- 11. ENFIR
- Dates
- 18-22 Aug 1997.
- Place
- Pocos de Caldas, MG (Brazil).
INIS
- Country of Publication
- Brazil
- Country of Input or Organization
- Brazil
- INIS RN
- 28074793
- Subject category
- S11: NUCLEAR FUEL CYCLE AND FUEL MATERIALS;
- Resource subtype / Literary indicator
- Conference, Non-conventional Literature
- Descriptors DEI
- ARTIFICIAL INTELLIGENCE; EXPERT SYSTEMS; FUEL CYCLE; GAS CENTRIFUGATION; GAS CENTRIFUGES; ISOTOPE SEPARATION; NEURAL NETWORKS; NUCLEAR ENGINEERING; NUCLEAR FUELS; NUCLEAR MATERIALS MANAGEMENT; REACTOR TECHNOLOGY; REACTORS; SEPARATION PROCESSES; URANIUM
- Descriptors DEC
- ACTINIDES; CENTRIFUGATION; CENTRIFUGES; CONCENTRATORS; ELEMENTS; ENERGY SOURCES; ENGINEERING; FUELS; MANAGEMENT; MATERIALS; METALS; REACTOR MATERIALS
Optional Information
- Notes
- Imprint:Joint nuclear conference with the 4. ENAN: Brazilian meeting on nuclear applications.