Instantaneous pressure determination from unsteady velocity fields using adjoint-based sequential data assimilation

被引:36
|
作者
He, Chuangxin [1 ,2 ]
Liu, Yingzheng [1 ,2 ]
Gan, Lian [3 ]
机构
[1] Shanghai Jiao Tong Univ, Sch Mech Engn, Key Lab Educ Minist Power Machinery & Engn, 800 Dongchuan Rd, Shanghai 200240, Peoples R China
[2] Shanghai Jiao Tong Univ, Gas Turbine Res Inst, 800 Dongchuan Rd, Shanghai 200240, Peoples R China
[3] Univ Durham, Dept Engn, Durham DH1 3LE, England
基金
英国工程与自然科学研究理事会; 中国国家自然科学基金;
关键词
LARGE-EDDY SIMULATION; PIV; CYLINDER; FLOWS;
D O I
10.1063/1.5143760
中图分类号
O3 [力学];
学科分类号
08 ; 0801 ;
摘要
A sequential data assimilation (DA) method is developed for pressure determination of turbulent velocity fields measured by particle image velocimetry (PIV), based on the unsteady adjoint formulation. A forcing term F, which is optimized using the adjoint system, is added to the primary Navier-Stokes (N-S) equations to drive the assimilated flow toward the observations at each time step. Compared with the conventional unsteady adjoint method, which requires the forward integration of the primary system and the backward integration of the adjoint system, the present approach integrates the primary-adjoint system all the way forward, discarding the requirement of data storage at every time step, being less computationally resource-consuming, and saving space. The pressure determination method of integration from eight paths [J. O. Dabiri et al., "An algorithm to estimate unsteady and quasi-steady pressure fields from velocity field measurements," J. Exp. Biol. 217, 331 (2014)] is also evaluated for comparison. Using synthetic PIV data of a turbulent jet as the observational data, the present DA method is able to determine the instantaneous pressure field precisely using the three-dimensional velocity fields, regardless of the observational noise. For the two-dimensional three-component (3C) or two-component (2C) velocity fields, which are not sufficient for pressure determination by the integration method due to the lack of off-plane derivatives, the present DA method is able to reproduce pressure fields whose statistics agree reasonably well with those of the referential results. The 3C and 2C velocity fields yield quite similar results, indicating the possibility of pressure determination from only planar-PIV measurements in turbulent flows. The tomography PIV measurements are also used as observational data, and a clear pressure pattern is obtained with the present DA method. Published under license by AIP Publishing.
引用
收藏
页数:15
相关论文
共 50 条
  • [21] PRESSURE AND ACCELERATION DETERMINATION METHODS USING PIV VELOCITY DATA
    Gharali, Kobra
    Johnson, David A.
    PROCEEDINGS OF THE ASME FLUIDS ENGINEERING DIVISION SUMMER CONFERENCE -2008, VOL 1, PT A AND B, 2009, : 657 - 664
  • [22] Instantaneous velocity determination and positioning using Doppler shift from a LEO constellation
    Guo, Fei
    Yang, Yan
    Ma, Fujian
    Zhu, Yifan
    Liu, Hang
    Zhang, Xiaohong
    SATELLITE NAVIGATION, 2023, 4 (01):
  • [23] An algorithm to estimate unsteady and quasi-steady pressure fields from velocity field measurements
    Dabiri, John O.
    Bose, Sanjeeb
    Gemmell, Brad J.
    Colin, Sean P.
    Costello, John H.
    JOURNAL OF EXPERIMENTAL BIOLOGY, 2014, 217 (03): : 331 - 336
  • [24] Instantaneous velocity determination and positioning using Doppler shift from a LEO constellation
    Fei Guo
    Yan Yang
    Fujian Ma
    Yifan Zhu
    Hang Liu
    Xiaohong Zhang
    Satellite Navigation, 2023, 4
  • [25] Using an adjoint model to improve an optimum interpolation-based data-assimilation system
    Huang, XY
    Gustafsson, N
    Kallen, ER
    TELLUS SERIES A-DYNAMIC METEOROLOGY AND OCEANOGRAPHY, 1997, 49 (02): : 161 - 176
  • [26] Ocean data assimilation using sequential methods based on the Kalman filter - From theory to practical implementations
    Brasseur, Pierre
    OCEAN WEATHER FORECASTING: AN INTEGRATED VIEW OF OCEANOGRAPHY, 2006, : 271 - 316
  • [27] Pressure from data-driven estimation of velocity fields using snapshot PIV and fast probes
    Chen, Junwei
    Raiola, Marco
    Discetti, Stefano
    EXPERIMENTAL THERMAL AND FLUID SCIENCE, 2022, 136
  • [28] Pressure from data-driven estimation of velocity fields using snapshot PIV and fast probes
    Chen, Junwei
    Raiola, Marco
    Discetti, Stefano
    Experimental Thermal and Fluid Science, 2022, 136
  • [29] Coupling of adjoint-based Markov/CCMT predictive analytics with data assimilation for real-time risk scenario forecasting of industrial digital process control systems
    Chenyu, Jiang
    Jun, Yang
    Ke, Xue
    Zhanyu, He
    Ming, Yang
    PROCESS SAFETY AND ENVIRONMENTAL PROTECTION, 2023, 171 : 951 - 974
  • [30] Adjoint-based direct data assimilation of GNSS time series for optimizing frictional parameters and predicting postseismic deformation following the 2003 Tokachi-oki earthquake
    Masayuki Kano
    Shin’ichi Miyazaki
    Yoichi Ishikawa
    Kazuro Hirahara
    Earth, Planets and Space, 72