| LDR | | 00000nmm u2200205 4500 |
| 001 | | 000000332975 |
| 005 | | 20241209170044 |
| 008 | | 181129s2018 ||| | | | eng d |
| 020 | |
▼a 9780355966053 |
| 035 | |
▼a (MiAaPQ)AAI10792380 |
| 035 | |
▼a (MiAaPQ)colorado:15424 |
| 040 | |
▼a MiAaPQ
▼c MiAaPQ
▼d 248032 |
| 049 | 1 |
▼f DP |
| 082 | 0 |
▼a 519 |
| 100 | 1 |
▼a Fairbanks, H. R. |
| 245 | 10 |
▼a Low-Rank, Multi-Fidelity Methods for Uncertainty Quantification of High-Dimensional Systems. |
| 260 | |
▼a [S.l.] :
▼b University of Colorado at Boulder.,
▼c 2018 |
| 260 | 1 |
▼a Ann Arbor :
▼b ProQuest Dissertations & Theses,
▼c 2018 |
| 300 | |
▼a 194 p. |
| 500 | |
▼a Source: Dissertation Abstracts International, Volume: 79-10(E), Section: B. |
| 500 | |
▼a Advisers: Alireza Doostan |
| 502 | 1 |
▼a Thesis (Ph.D.)--University of Colorado at Boulder, 2018. |
| 520 | |
▼a Characterizing and incorporating uncertainties when simulating physical phenomena is essential for improving model-based predictions. These uncertainties may stem from a lack of knowledge regarding the underlying physical processes or from impre |
| 520 | |
▼a For systems exhibiting high-dimensional uncertainty, performing either forward or inverse UQ presents a significant computational challenge, as these methods require a large number forward solves of the high-fidelity model, that is, the model th |
| 520 | |
▼a To reduce the cost of performing UQ on high-dimensional systems, we apply multi-fidelity strategies to both the forward problem, in order to estimate moments of the quantity of interest, and inverse problem, to approximate the posterior covarian |
| 590 | |
▼a School code: 0051. |
| 650 | 4 |
▼a Applied mathematics. |
| 690 | |
▼a 0364 |
| 710 | 20 |
▼a University of Colorado at Boulder.
▼b Applied Mathematics. |
| 773 | 0 |
▼t Dissertation Abstracts International
▼g 79-10B(E). |
| 773 | |
▼t Dissertation Abstract International |
| 790 | |
▼a 0051 |
| 791 | |
▼a Ph.D. |
| 792 | |
▼a 2018 |
| 793 | |
▼a English |
| 856 | 40 |
▼u http://www.riss.kr/pdu/ddodLink.do?id=T14997705
▼n KERIS |
| 980 | |
▼a 201812
▼f 2019 |
| 990 | |
▼a 관리자
▼b 관리자 |