Name
Abstract | ||
|---|---|---|
•Multifidelity method that enables estimation of failure probabilities for expensive-to- evaluate models.•For turbulent jet application, it reduces the CPU time to compute the biasing density by 65%.•The new approach draws from information fusion, importance sampling and multifidelity modeling.•The fused estimator is optimal in that it has minimal variance among all possible combinations of the estimators. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1016/j.jcp.2019.04.071 | Journal of Computational Physics |
Keywords | DocType | Volume |
Multifidelity modeling,Uncertainty quantification,Information fusion,Reduced-order modeling,Failure probability estimation,Turbulent jet | Journal | 392 |
ISSN | Citations | PageRank |
0021-9991 | 0 | 0.34 |
References | Authors | |
0 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Boris Kramer | 1 | 6 | 4.19 |
| Alexandre Noll Marques | 2 | 17 | 3.00 |
| Benjamin Peherstorfer | 3 | 113 | 13.66 |
| Umberto Villa | 4 | 30 | 6.64 |
| K WILLCOX | 5 | 305 | 36.62 |