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020 ▼a 9780438206571
035 ▼a (MiAaPQ)AAI10787711
035 ▼a (MiAaPQ)rpi:11270
040 ▼a MiAaPQ ▼c MiAaPQ ▼d 248032
0820 ▼a 621.3
1001 ▼a Li, Jason.
24510 ▼a Stochastic Variational Multiscale Method for Error Estimation and Adaptivity in Uncertain Transport Problems.
260 ▼a [S.l.] : ▼b Rensselaer Polytechnic Institute., ▼c 2018
260 1 ▼a Ann Arbor : ▼b ProQuest Dissertations & Theses, ▼c 2018
300 ▼a 147 p.
500 ▼a Source: Dissertation Abstracts International, Volume: 79-12(E), Section: B.
500 ▼a Adviser: Onkar Sahni.
5021 ▼a Thesis (Ph.D.)--Rensselaer Polytechnic Institute, 2018.
520 ▼a The focus of this work is the formulation and application of an adaptive approach based on the variational multiscale (VMS) method for stochastic PDEs with uncertain input data. Uncertainty leads to complicated solution behavior and features in
520 ▼a In this approach, we employ finite elements in the spatial domain and spectral approximation (based on generalized polynomial chaos) in the stochastic domain. The stochastic VMS method allows in computing an accurate solution while accounting fo
520 ▼a Similarly, a model term is derived to explicitly estimate the error in a local or element-wise fashion. This model term is approximated using the components of the stabilization parameter used in computing the numerical solution, making error es
590 ▼a School code: 0185.
650 4 ▼a Computer engineering.
650 4 ▼a Fluid mechanics.
690 ▼a 0464
690 ▼a 0204
71020 ▼a Rensselaer Polytechnic Institute. ▼b Aeronautical Engineering.
7730 ▼t Dissertation Abstracts International ▼g 79-12B(E).
773 ▼t Dissertation Abstract International
790 ▼a 0185
791 ▼a Ph.D.
792 ▼a 2018
793 ▼a English
85640 ▼u http://www.riss.kr/pdu/ddodLink.do?id=T14997414 ▼n KERIS
980 ▼a 201812 ▼f 2019
990 ▼a 관리자