Uncertainty quantification for chaotic computational fluid dynamics

被引：26

作者：

Yu, Y. ^{[1
]}

Zhao, M.

Lee, T.

Pestieau, N.

Bo, W.

Glimm, J.

Grove, J. W.

机构：

[1] SUNY Stony Brook, Dept Appl Math & Stat, Stony Brook, NY 11794 USA

[2] Los Alamos Natl Lab, Los Alamos, NM 87545 USA

[3] Brookhaven Natl Lab, Computat Sci Ctr, Upton, NY 11973 USA

来源：

JOURNAL OF COMPUTATIONAL PHYSICS | 2006年 / 217卷 / 01期

关键词：

uncertainty quantification; chaotic flow;

D O I：

10.1016/j.jcp.2006.03.030

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

We seek error models for simulations that model chaotic flow. Stable statistics for the solution and for the error are obtained after suitable averaging procedures. (c) 2006 Elsevier Inc. All rights reserved.

引用

页码：200 / 216

页数：17

共 50 条

[31] IMPROVED EFFICIENCY OF A MULTI-INDEX FEM FOR COMPUTATIONAL UNCERTAINTY QUANTIFICATION [J].

Dick, Josef ;

Feischl, Michael ;

Schwab, Christoph .

SIAM JOURNAL ON NUMERICAL ANALYSIS, 2019, 57 (04) :1744-1769

[32] A Computational Inverse Technique for Uncertainty Quantification in an Encounter Condition Identification Problem [J].

Zhang, W. ;

Han, X. ;

Liu, J. ;

Chen, R. .

CMES-COMPUTER MODELING IN ENGINEERING & SCIENCES, 2012, 86 (05) :385-408

[33] Use of GPU computing for uncertainty quantification in computational mechanics: A case study [J].

Gaurav ;

Wojtkiewicz, Steven F. .

SCIENTIFIC PROGRAMMING, 2011, 19 (04) :199-212

[34] Data-driven uncertainty quantification in computational human head models [J].

Upadhyay, Kshitiz ;

Giovanis, Dimitris G. ;

Alshareef, Ahmed ;

Knutsen, Andrew K. ;

Johnson, Curtis L. ;

Carass, Aaron ;

Bayly, Philip, V ;

Shields, Michael D. ;

Ramesh, K. T. .

COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING, 2022, 398

[35] Multi-frequency model reduction for uncertainty quantification in computational vibroacoutics [J].

Reyes, J. ;

Desceliers, C. ;

Soize, C. ;

Gagliardini, L. .

COMPUTATIONAL MECHANICS, 2022, 69 (03) :661-682

[36] Advanced Computational Tools for Optimization and Uncertainty Quantification of Carbon Capture Processes [J].

Miller, David C. ;

Ng, Brenda ;

Eslick, John ;

Tong, Charles ;

Chen, Yang .

PROCEEDINGS OF THE 8TH INTERNATIONAL CONFERENCE ON FOUNDATIONS OF COMPUTER-AIDED PROCESS DESIGN, 2014, 34 :202-211

[37] Error Estimation and Uncertainty Quantification Based on Adjoint Methods in Computational Electromagnetics [J].

Notaros, Branislav M. ;

Harmon, Jake ;

Key, Cam ;

Estep, Donald ;

Butler, Troy .

2019 IEEE INTERNATIONAL SYMPOSIUM ON ANTENNAS AND PROPAGATION AND USNC-URSI RADIO SCIENCE MEETING, 2019, :221-222

[38] Uncertainty quantification in computational stochastic multiscale analysis of nonlinear elastic materials [J].

Clement, A. ;

Soize, C. ;

Yvonnet, J. .

COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING, 2013, 254 :61-82

[39] A BAYES NETWORK APPROACH TO UNCERTAINTY QUANTIFICATION IN HIERARCHICALLY DEVELOPED COMPUTATIONAL MODELS [J].

Urbina, Angel ;

Mahadevan, Sankaran ;

Paez, Thomas L. .

INTERNATIONAL JOURNAL FOR UNCERTAINTY QUANTIFICATION, 2012, 2 (02) :173-193

[40] Strategies for Computational Fluid Dynamics Validation Experiments [J].

Gargiulo, Aldo ;

Duetsch-Patel, Julie E. ;

Borgoltz, Aurelien ;

Devenport, William J. ;

Roy, Christopher J. ;

Lowe, K. Todd .

JOURNAL OF VERIFICATION, VALIDATION AND UNCERTAINTY QUANTIFICATION, 2023, 8 (03)

← 1 2 3 4 5 →