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pro vyhledávání: '"Danniëll Botes"'
Autor:
Botes, Danniëll
This thesis addresses the problem of representing few group, homogenised neutron cross sections as a function of state parameters (e.g. burn-up, fuel and moderator temperature, etc.) that describe the conditions in the reactor. The problem is multi-d
Externí odkaz:
http://hdl.handle.net/10394/8845
Publikováno v:
Nuclear Technology and Radiation Protection, Vol 36, Iss 2, Pp 107-115 (2021)
This work addresses the problem of propagating uncertainty from group-wise neutron cross-sections to the results of neutronics diffusion calculations. Automatic differentiation based on dual number arithmetic was applied to uncertainty propagation in
Publikováno v:
Annals of Nuclear Energy. 99:444-454
Nodal diffusion methods are often used for full core neutronic analysis. They require few-group homogenised neutron cross sections for every heterogeneous sub-region of the core. The homogenised cross sections are pre-calculated at various reactor st
Publikováno v:
Annals of Nuclear Energy. 151:107925
Automatic differentiation (AD) is a set of techniques which allows the numeric evaluation of derivatives of functions calculated by a computer program. In recent years, interest in AD has grown significantly in many disciplines, especially in the con
Autor:
Maria Avramova, Adam Rosenkrantz, Danniëll Botes, Kostadin Ivanov, Khalid Elsakhawy, Rian H. Prinsloo
Publikováno v:
Annals of Nuclear Energy. 73:122-130
The purpose of this study was to develop a coupled accurate multi-physics model of the SAFARI-1 Material Testing Reactor (MTR), a facility that is used for both research and the production of medical isotopes. The model was developed as part of the S
Autor:
Pavel M. Bokov, Danniëll Botes
Publikováno v:
Annals of Nuclear Energy. 64:156-168
Few group, homogenized neutron cross sections are represented as a function of various state parameters through multidimensional Lagrange interpolation. The interpolation is built on a Clenshaw-Curtis sparse grid by applying the method of mean weight