Numerical Simulation of Non-Stationary Turbulent Flows using Double Exponential Dynamic Time Filtering Technique

被引:0
|
作者
Jamal, Tausif [1 ]
Bhushan, Shanti [2 ]
Walters, D. Keith [1 ]
机构
[1] Univ Oklahoma, Sch Aerosp & Mech Engn, Norman, OK 73019 USA
[2] Mississippi State Univ, Dept Mech Engn, Starkville, MS USA
关键词
STATE-OF-ART; LAMINAR; LAYER;
D O I
暂无
中图分类号
TH [机械、仪表工业];
学科分类号
0802 ;
摘要
Temporally varying turbulent flows are of considerable interest in complex engineering problems such as combustion, hydrodynamics, and hemodynamics. These types of flows are often associated with complex flow physics such as varying mean pressure gradients, interactions of different scales of motion, and complex boundary layer separations. Hybrid Reynolds-averaged Navier- Stoke s (RANS)/Large-Eddy Simulation (LES) methods have recently shown promise for accurate and computationally efficient simulation of these flows. One such method is the dyanamic hybrid RANS-LES (DHRL) model which has been demonstrated for numerous statistically stationary turbulent flows. More recently, it has been shown that Exponential Time-Averaging (ETA) and Dynamic Time Filtering (DTF) methods for obtaining resolved flow statistics have significantly improved the predictive capabilities of the Dynamic Hybrid RANS-LES (DHRL) model perfounance for a non-stationary turbulent flows with periodically time-varying statistics. However, for non-periodic temporally evolving flows with monotonically varying statistics, a more suitable alternative is desired. In this study, the performance of the Dynamic Hybrid RANS-LES (DHRL) model with a double exponential dynamic time filtering (DDTF) methodology is evaluated against a Reynolds-Averaged Navier-Stokes (RANS) model, a conventional Hybrid RANS-LES (HRL) model, implicit LES, and the DHRL model with DTF for a pulsating channel and a temporally-varying turbulent mixing layer. Model performance is evaluated based on comparisons to existing experimental and Direct Numerical Simulation (DNS) results. A comprehensive analysis of the results highlights key similarities and differences between the models and indicates that the use of a double exponential DTF technique improves the accuracy of the baseline DHRL model. It is concluded that the DDTF is a useful alternative to simulate unsteady non-periodic temporally evolving turbulent flows.
引用
收藏
页数:18
相关论文
共 50 条
  • [21] Non-stationary turbulent wind field simulation of bridge deck using non-negative matrix factorization
    Wang, Hao
    Xu, Zidong
    Feng, Dongming
    Tao, Tianyou
    JOURNAL OF WIND ENGINEERING AND INDUSTRIAL AERODYNAMICS, 2019, 188 : 235 - 246
  • [22] Non-stationary and stationary prediction of financial time series using dynamic ridge polynomial neural network
    Ghazali, Rozaida
    Hussain, Abir Jaafar
    Nawi, Nazri Mohd
    Mohamad, Baharuddin
    NEUROCOMPUTING, 2009, 72 (10-12) : 2359 - 2367
  • [23] SIMULATION METHODS FOR SOLVING NON-STATIONARY FILTERING AND PREDICTION PROBLEMS WITH ARBITRARY NOISE
    GULKO, FB
    NOVOSELT.ZA
    AUTOMATION AND REMOTE CONTROL, 1966, 27 (10) : 1798 - &
  • [24] Extraction and Classification of Non-Stationary Acoustic Signals via Dynamic Subspace Filtering
    Pollwaththage, N. N.
    Nettasinghe, D. B. W.
    Ratnayake, T. A.
    Godaliyadda, G. M. R. I.
    Ekanayake, M. P. B.
    Wijayakulasooriya, J. V.
    2013 8TH IEEE INTERNATIONAL CONFERENCE ON INDUSTRIAL AND INFORMATION SYSTEMS (ICIIS), 2013, : 415 - 420
  • [25] Simulation of non-stationary wind speed and direction time series
    Solari, Sebastian
    Angel Losada, Miguel
    JOURNAL OF WIND ENGINEERING AND INDUSTRIAL AERODYNAMICS, 2016, 149 : 48 - 58
  • [26] Fitting dynamic factor models to non-stationary time series
    Eichler, Michael
    Motta, Giovanni
    von Sachs, Rainer
    JOURNAL OF ECONOMETRICS, 2011, 163 (01) : 51 - 70
  • [27] A NUMERICAL-SIMULATION OF THE NON-STATIONARY ELECTRON ACCELERATION IN THE PULSAR MAGNETOSPHERE
    RYLOV, YA
    ASTRONOMICHESKII ZHURNAL, 1987, 64 (06): : 1220 - 1232
  • [28] Numerical simulation of non-stationary regime of a submerged combustion setup operation
    Demin, V. A.
    Kostyrya, A. V.
    BULLETIN OF THE TOMSK POLYTECHNIC UNIVERSITY-GEO ASSETS ENGINEERING, 2024, 335 (07): : 174 - 184
  • [29] Numerical simulation of the North Atlantic response to the non-stationary wind forcing
    Ivanov, YA
    Lebedev, KV
    IZVESTIYA AKADEMII NAUK FIZIKA ATMOSFERY I OKEANA, 1996, 32 (05): : 672 - 679
  • [30] A Model for Non-Stationary Time Series and Its Applications in Filtering and Anomaly Detection
    Wang, Shixiong
    Li, Chongshou
    Lim, Andrew
    IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT, 2021, 70