On-line generation and error handling for surrogate models within multifidelity uncertainty quantification (PI)
- Goal: This project aims to integrate reduced-order model methods within a multifidelity uncertainty quantification framework and to demonstrate the greater efficiency and generality of this approach for several test problems with respect to their state-of-the-art counterparts.
- Sandia collaborators: Gianluca Geraci (Co-PI), Mike Eldred, Kevin Carlberg.
- External collaborators: Francesco Rizzi (NexGen).
- Research topics: nonlinear model reduction; uncertainty quantification
- Funding source: Sandia National Laboratories’ Laboratory-Directed Research & Development.