Research programs have focused on addressing the challenges inherent in applying iterative systems analysis to complex engineering applications where simulations are expensive to evaluate and the response metrics may be poorly behaved (i.e., noisy, multimodal, discontinuous). This has motivated research in the following areas (with links to selected publications):
- Uncertainty quantification.
- Local and global reliability methods, with application to MEMS.
- Stochastic expansion methods: polynomial chaos and stochastic collocation.
- Epistemic methods.
- Surrogate-based optimization (SBO).
- SBO formulations.
- SBO with data fits, multifidelity models, and reduced-order models.
- Optimization and model calibration under uncertainty.
- Surrogate-based.
- Reliability-based.
- Stochastic expansion-based.
- Model calibration under uncertainty.
- Parallel processing.
- Research in multilevel parallel computing.
- Large-scale applications in structural dynamics and chemically-reacting flows.
