Multiscale mixed methods with improved accuracy: The role of oversampling and smoothing

被引:0
|
作者
Zhou, Dilong [1 ]
Guiraldello, Rafael T. [2 ]
Pereira, Felipe [1 ]
机构
[1] Department of Mathematical Sciences, The University of Texas at Dallas, 800 W. Campbell Road, Richardson,TX,75080-3021, United States
[2] Piri Technologies, LLC 1000 E. University Ave., Dept. 4311, Laramie,WY,82071-2000, United States
基金
美国国家科学基金会;
关键词
D O I
10.1016/j.jcp.2024.113490
中图分类号
学科分类号
摘要
Multiscale mixed methods based on non-overlapping domain decompositions can efficiently handle the solution of significant subsurface flow problems in very heterogeneous formations of interest to the industry, especially when implemented on multi-core supercomputers. Efficiency in obtaining numerical solutions is dictated by the choice of interface spaces that are selected: the smaller the dimension of these spaces, the better, in the sense that fewer multiscale basis functions need to be computed, and smaller interface linear systems need to be solved. Thus, in solving large computational problems, it is desirable to work with piecewise constant or linear polynomials for interface spaces. However, for these choices of interface spaces, it is well known that the flux accuracy is of the order of 10−1. This study is dedicated to advancing an efficient and accurate multiscale mixed method aimed at addressing industry-relevant problems. A distinctive feature of our approach involves subdomains with overlapping regions, a departure from conventional methods. We take advantage of the overlapping decomposition to introduce a computationally highly efficient smoothing step designed to rectify small-scale errors inherent in the multiscale solution. The effectiveness of the proposed solver, which maintains a computational cost very close to its predecessors, is demonstrated through a series of numerical studies. Notably, for scenarios involving modestly sized overlapping regions and employing just a few smoothing steps, a substantial enhancement of two orders of magnitude in flux accuracy is achieved with the new approach. © 2024 Elsevier Inc.
引用
收藏
相关论文
共 50 条
  • [1] GENERALIZED MULTISCALE FINITE ELEMENT METHODS: OVERSAMPLING STRATEGIES
    Efendiev, Yalchin
    Galvis, Juan
    Li, Guanglian
    Presho, Michael
    INTERNATIONAL JOURNAL FOR MULTISCALE COMPUTATIONAL ENGINEERING, 2014, 12 (06) : 465 - 484
  • [2] RANDOMIZED OVERSAMPLING FOR GENERALIZED MULTISCALE FINITE ELEMENT METHODS
    Calo, Victor M.
    Efendiev, Yalchin
    Galvis, Juan
    Li, Guanglian
    MULTISCALE MODELING & SIMULATION, 2016, 14 (01): : 482 - 501
  • [3] Experimental Comparison of Oversampling Methods for Mixed Datasets
    Rodriguez-Torres, Fredy
    Carrasco-Ochoa, J. A.
    Martinez-Trinidad, Jose Fco
    PATTERN RECOGNITION (MCPR 2021), 2021, 12725 : 78 - 88
  • [4] Flow based oversampling technique for multiscale finite element methods
    Chu, J.
    Efendiev, Y.
    Ginting, V.
    Hou, T. Y.
    ADVANCES IN WATER RESOURCES, 2008, 31 (04) : 599 - 608
  • [5] Generalized Multiscale Finite Element Methods with energy minimizing oversampling
    Chung, Eric
    Efendiev, Yalchin
    Leung, Wing Tat
    INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN ENGINEERING, 2019, 117 (03) : 316 - 343
  • [6] Online Mixed Multiscale Finite Element Method with Oversampling and Its Applications
    Yang, Yanfang
    Fu, Shubin
    Chung, Eric T.
    JOURNAL OF SCIENTIFIC COMPUTING, 2020, 82 (02)
  • [7] Online Mixed Multiscale Finite Element Method with Oversampling and Its Applications
    Yanfang Yang
    Shubin Fu
    Eric T. Chung
    Journal of Scientific Computing, 2020, 82
  • [8] The Role of Mixed Methods in Improved Cookstove Research
    Stanistreet, Debbi
    Hyseni, Lirije
    Bashin, Michelle
    Sadumah, Ibrahim
    Pope, Daniel
    Sage, Michael
    Bruce, Nigel
    JOURNAL OF HEALTH COMMUNICATION, 2015, 20 : 84 - 93
  • [9] Multiscale AM-FM Demodulation and Image Reconstruction Methods With Improved Accuracy
    Murray, Victor
    Rodriguez, Paul
    Pattichis, Marios S.
    IEEE TRANSACTIONS ON IMAGE PROCESSING, 2010, 19 (05) : 1138 - 1152
  • [10] Spectra Smoothing by Multiple Radar Pattern Multiplication for Improved Accuracy
    Alistarh, Cristian A.
    Podilchak, Symon K.
    Goussestis, George
    Thompson, John S.
    Lee, Jaesup
    2018 18TH INTERNATIONAL SYMPOSIUM ON ANTENNA TECHNOLOGY AND APPLIED ELECTROMAGNETICS (ANTEM 2018), 2018,