This work explores the implementation of an adaptive strategy to design sparse ensembles of oceanic simulations suitable for constructing polynomial chaos surrogates. We use a recently developed pseudo-spectral algorithm that is based on a direct application of the Smolyak sparse grid formula and that allows the use of arbitrary admissible sparse grids. The adaptive algorithm is tested using an existing simulation database of the oceanic response to Hurricane Ivan in the Gulf of Mexico. The a priori tests demonstrate that sparse and adaptive pseudo-spectral constructions lead to substantial savings over isotropic sparse sampling in the present setting.
|Original language||English (US)|
|Number of pages||13|
|State||Published - Dec 2013|
Bibliographical noteFunding Information:
Acknowledgments This research was supported by the Office of Naval Research, award N00014-101-0498; by the US Department of Energy, Office of Advanced Scientific Computing Research, award numbers DE-SC0007020, DE-SC0008789, and DE-SC0007099; and by the Gulf of Mexico Research Initiative, contract numbers SA1207GOMRI005 (CARTHE) and SA12GOMRI008 (DEEP-C).
- Adaptive sampling
- Ocean modeling
- Polynomial chaos
- Sparse Smolyak quadrature
- Uncertainty quantification
ASJC Scopus subject areas
- Computer Science Applications
- Computers in Earth Sciences
- Computational Theory and Mathematics
- Computational Mathematics