Development of Adaptive Model Refinement (AMoR) for Multiphysics and Multifidelity Problems
This project investigated the development and utilization of Adaptive Model Refinement (AMoR) for nuclear systems simulation applications. AMoR refers to utilization of several models of physical phenomena which differ in prediction fidelity. If the highest fidelity model is judged to always provide or exceeded the desired fidelity, than if one can determine the difference in a Quantity of Interest (QoI) between the highest fidelity model and lower fidelity models, one could utilize the fidelity model that would just provide the magnitude of the QoI desired. Assuming lower fidelity models require less computational resources, in this manner computational efficiency can be realized provided the QoI value can be accurately and efficiently evaluated. This work utilized Generalized Perturbation Theory (GPT) to evaluate the QoI, by convoluting the GPT solution with the residual of the highest fidelity model determined using the solution from lower fidelity models. Specifically, a reactor core neutronics problem and thermal-hydraulics problem were studied to develop and utilize AMoR. The highest fidelity neutronics model was based upon the 3D space-time, two-group, nodal diffusion equations as solved in the NESTLE computer code. Added to the NESTLE code was the ability to determine the time-dependent GPT neutron flux. The lower fidelity neutronicsmore »
- Publication Date:
- OSTI Identifier:
- 1169938
- Report Number(s):
- 09-793
09-793
- DOE Contract Number:
- AC07-05ID14517
- Resource Type:
- Technical Report
- Research Org:
- North Carolina State Univ., Raleigh, NC (United States)
- Sponsoring Org:
- USDOE Office of Nuclear Energy (NE)
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS
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