A Domain Decomposition Reduced Order Model with Data Assimilation (DD-RODA)

被引:0
|
作者
Arcucci, Rossella [1 ]
Casas, Cesar Quilodran [1 ]
Xiao, Dunhui [1 ,2 ,3 ]
Mottet, Laetitia [3 ]
Fang, Fangxin [1 ,3 ]
Wu, Pin [4 ]
Pain, Christopher [1 ,3 ]
Guo, Yi-Ke [1 ]
机构
[1] Imperial Coll London, Dept Comp, Data Sci Inst, London, England
[2] Swansea Univ, Coll Engn, ZCCE, Swansea, W Glam, Wales
[3] Imperial Coll London, Dept Earth Sci & Engn, London, England
[4] Shanghai Univ, Sch Comp Sci & Engn, Shanghai, Peoples R China
来源
基金
英国工程与自然科学研究理事会;
关键词
Numerical simulations; Reduced Order Models; Data Assimilation; Domain Decomposition; FLOWS;
D O I
10.3233/APC200040
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
We present a Domain Decomposition Reduced Order Data Assimilation (DD-RODA) model which combines Non-Intrusive Reduced Order Modelling (NIROM) method with a Data Assimilation (DA) model. The NIROM is defined on a partition of the domain in sub-domains with overlapping regions and the DA is defined on a partition of the domain in sub-domains without overlapping regions. This choice allows to avoid communications among the processes during the Data Assimilation phase. However, during the balance phase, the model exploits the domain decomposition implemented in DD-NIROM which balances the results among the processes exploiting overlapping regions. The model is applied to the pollutant dispersion within an urban environment. Simulations are performed using the open-source, finite-element, fluid dynamics model Fluidity.
引用
收藏
页码:189 / 198
页数:10
相关论文
共 50 条
  • [11] Assimilation of Experimental Data to Create a Quantitatively Accurate Reduced-Order Thermoacoustic Model
    Garita, Francesco
    Yu, Hans
    Juniper, Matthew P.
    JOURNAL OF ENGINEERING FOR GAS TURBINES AND POWER-TRANSACTIONS OF THE ASME, 2021, 143 (02):
  • [12] Model-reduced variational data assimilation
    Vermeulen, P. T. M.
    Heemink, A. W.
    MONTHLY WEATHER REVIEW, 2006, 134 (10) : 2888 - 2899
  • [13] A reduced-order approach to four-dimensional variational data assimilation using proper orthogonal decomposition
    Cao, Yanhua
    Zhu, Jiang
    Navon, I. M.
    Luo, Zhendong
    INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN FLUIDS, 2007, 53 (10) : 1571 - 1583
  • [14] Continuous data assimilation reduced order models of fluid flow
    Zerfas, Camille
    Rebholz, Leo G.
    Schneier, Michael
    Iliescu, Traian
    COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING, 2019, 357
  • [15] EnKF data-driven reduced order assimilation system
    Liu, C.
    Fu, R.
    Xiao, D.
    Stefanescu, R.
    Sharma, P.
    Zhu, C.
    Sun, S.
    Wang, C.
    ENGINEERING ANALYSIS WITH BOUNDARY ELEMENTS, 2022, 139 : 46 - 55
  • [16] Particle filters for data assimilation based on reduced-order data models
    Maclean, John
    Van Vleck, Erik S.
    QUARTERLY JOURNAL OF THE ROYAL METEOROLOGICAL SOCIETY, 2021, 147 (736) : 1892 - 1907
  • [17] An Adaptive Data-Driven Reduced Order Model Based on Higher Order Dynamic Mode Decomposition
    Beltran, Victor
    Le Clainche, Soledad
    Vega, Jose M.
    JOURNAL OF SCIENTIFIC COMPUTING, 2022, 92 (01)
  • [18] An Adaptive Data-Driven Reduced Order Model Based on Higher Order Dynamic Mode Decomposition
    Víctor Beltrán
    Soledad Le Clainche
    José M. Vega
    Journal of Scientific Computing, 2022, 92
  • [19] A Pressure-Stabilized Continuous Data Assimilation Reduced Order Model for Incompressible Navier–Stokes Equations
    Xi Li
    Youcai Xu
    Minfu Feng
    Journal of Scientific Computing, 2025, 103 (1)
  • [20] A reduced-order Kalman filter for data assimilation in physical oceanography
    Rozier, D.
    Birol, F.
    Cosme, E.
    Brasseur, R.
    Brankart, J. M.
    Verron, J.
    SIAM REVIEW, 2007, 49 (03) : 449 - 465