Stabilized FE simulation of prototype thermal-hydraulics problems with integrated adjoint-based capabilities
- Sandia National Lab. (SNL-NM), Albuquerque, NM (United States). Computational Mathematics Dept. and Dept. of Mathematics and Statistics
- Sandia National Lab. (SNL-NM), Albuquerque, NM (United States). Multiphysics Applications Dept.
- Sandia National Lab. (SNL-NM), Albuquerque, NM (United States). Computational Mathematics Dept.
- Sandia National Lab. (SNL-NM), Albuquerque, NM (United States). Optimization and UQ Dept.
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. 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 our 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. We present the initial results that show the promise of these computational techniques in the context of nuclear reactor relevant prototype thermal-hydraulics problems.
- Research Organization:
- Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
- Sponsoring Organization:
- USDOE Office of Nuclear Energy (NE); USDOE Office of Science (SC)
- Grant/Contract Number:
- AC04-94AL85000; AC05-00OR22725
- OSTI ID:
- 1338379
- Alternate ID(s):
- OSTI ID: 1329336
- Report Number(s):
- SAND2016-12353J; 649724
- Journal Information:
- Journal of Computational Physics, Vol. 321, Issue C; ISSN 0021-9991
- Publisher:
- ElsevierCopyright Statement
- Country of Publication:
- United States
- Language:
- English
Web of Science
Dimension reduction in magnetohydrodynamics power generation models: Dimensional analysis and active subspaces: GLAWS
|
journal | August 2017 |
| Dimension reduction in MHD power generation models: dimensional analysis and active subspaces | preprint | January 2016 |
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