Stabilized FE simulation of prototype thermal-hydraulics problems with integrated adjoint-based capabilities
- Sandia National Laboratories, Multiphysics Applications Department (United States)
- Sandia National Laboratories, Computational Mathematics Department (United States)
- Sandia National Laboratories, Optimization and UQ Department (United States)
A critical aspect of applying modern computational solution methods to complex multiphysics systems of relevance to nuclear reactor modeling, is the assessment of the predictive capability of specific proposed mathematical models. In this respect the understanding of numerical error, the sensitivity of the solution to parameters associated with input data, boundary condition uncertainty, and mathematical models is critical. Additionally, the ability to evaluate and or approximate the model efficiently, to allow development of a reasonable level of statistical diagnostics of the mathematical model and the physical system, is of central importance. In this study we report on initial efforts to apply integrated adjoint-based computational analysis and automatic differentiation tools to begin to address these issues. The study is carried out in the context of a Reynolds averaged Navier–Stokes approximation to turbulent fluid flow and heat transfer using a particular spatial discretization based on implicit fully-coupled stabilized FE methods. Initial results are presented that show the promise of these computational techniques in the context of nuclear reactor relevant prototype thermal-hydraulics problems.
- OSTI ID:
- 22572348
- Journal Information:
- Journal of Computational Physics, Vol. 321; Other Information: Copyright (c) 2016 Elsevier Science B.V., Amsterdam, The Netherlands, All rights reserved.; Country of input: International Atomic Energy Agency (IAEA); ISSN 0021-9991
- Country of Publication:
- United States
- Language:
- English
Dimension reduction in magnetohydrodynamics power generation models: Dimensional analysis and active subspaces: GLAWS
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journal | August 2017 |
| Dimension reduction in MHD power generation models: dimensional analysis and active subspaces | preprint | January 2016 |
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