On Developing a Multifidelity Modeling Algorithm for System-Level Engineering Analysis
Multifidelity modeling, in which one component of a system is modeled at a significantly different level of fidelity than another, has several potential advantages. For example, a higher-fidelity component model can be evaluated in the context of a lower-fidelity full system model that provides more realistic boundary conditions and yet can be executed quickly enough for rapid design changes or design optimization. Developing such multifidelity models presents challenges in several areas, including coupling models with differing spatial dimensionalities. In this report we describe a multifidelity algorithm for thermal radiation problems in which a three-dimensional, finite-element model of a system component is embedded in a system of zero-dimensional (lumped-parameter) components. We tested the algorithm on a prototype system with three problems: heating to a constant temperature, cooling to a constant temperature, and a simulated fire environment. The prototype system consisted of an aeroshell enclosing three components, one of which was represented by a three-dimensional finite-element model. We tested two versions of the algorithm; one used the surface-average temperature of the three dimensional component to couple it to the system model, and the other used the volume-average temperature. Using the surface-average temperature provided somewhat better temperature predictions than using the volume-average temperature. Our results illustrate the difficulty in specifying consistency for multifidelity models. In particular, we show that two models may be consistent for one application but not for another. While the temperatures predicted by the multifidelity model were not as accurate as those predicted by a full three-dimensional model, our results show that a multifidelity system model can potentially execute much faster than a full three-dimensional finite-element model for thermal radiation problems with sufficient accuracy for some applications, while still predicting internal temperatures for the higher fidelity component. These results indicate that optimization studies with mixed-fidelity models are feasible when they may not be feasible with three-dimensional system models, if the concomitant loss in accuracy is within acceptable bounds.
- Research Organization:
- Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Sandia National Lab. (SNL-CA), Livermore, CA (United States)
- Sponsoring Organization:
- US Department of Energy (US)
- DOE Contract Number:
- AC04-94AL85000
- OSTI ID:
- 820880
- Report Number(s):
- SAND2003-0399; TRN: US200407%%3
- Resource Relation:
- Other Information: PBD: 1 Feb 2003
- Country of Publication:
- United States
- Language:
- English
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