State estimation in wall-bounded flow systems. Part 3. The ensemble Kalman filter

2011 ◽  
Vol 682 ◽  
pp. 289-303 ◽  
Author(s):  
C. H. COLBURN ◽  
J. B. CESSNA ◽  
T. R. BEWLEY
Keyword(s):  
Kalman Filter ◽  
State Estimation ◽  
Channel Flow ◽  
Ensemble Kalman Filter ◽  
Accurate Estimation ◽  
Wall Region ◽  
Flow State ◽  
Model Based ◽  
Wall Flow ◽  
Near Wall

State estimation of turbulent near-wall flows based on wall measurements is one of the key pacing items in model-based flow control, with low-Re channel flow providing the canonical testbed. Model-based control formulations in such settings are often separated into two subproblems: estimation of the near-wall flow state via skin friction and pressure measurements at the wall, and (based on this estimate) control of the near-wall flow field fluctuations via actuation of the fluid velocity at the wall. In our experience, the turbulent state estimation sub-problem has consistently proven to be the more difficult of the two. Though many estimation strategies have been tested on this problem (by our group and others), none have accurately captured the turbulent flow state at the outer boundary of the buffer layer (5 ≤ y+ ≤ 30), which is deemed to be an important milestone, as this is the approximate range of the characteristic near-wall turbulent structures, the accurate estimation of which is important for the control problem. Leveraging the ensemble Kalman filter (an effective variant of the Kalman filter which scales well to high-dimensional systems), the present paper achieves at least an order of magnitude improvement (in the near-wall region) over the best results available in the published literature on the estimation of low-Reynolds number turbulent channel flow based on wall information alone.

scholarly journals The New Trend of State Estimation: From Model-Driven to Hybrid-Driven Methods

Sensors ◽  
2021 ◽  
Vol 21 (6) ◽  
pp. 2085
Author(s):  
Xue-Bo Jin ◽  
Ruben Jonhson Robert RobertJeremiah ◽  
Ting-Li Su ◽  
Yu-Ting Bai ◽  
Jian-Lei Kong
Keyword(s):  
Kalman Filter ◽  
State Estimation ◽  
Future Development ◽  
Data Driven ◽  
Estimation Methods ◽  
Multiple Model ◽  
Development Trends ◽  
Research Results ◽  
Model Driven ◽  
Model Based

State estimation is widely used in various automated systems, including IoT systems, unmanned systems, robots, etc. In traditional state estimation, measurement data are instantaneous and processed in real time. With modern systems’ development, sensors can obtain more and more signals and store them. Therefore, how to use these measurement big data to improve the performance of state estimation has become a hot research issue in this field. This paper reviews the development of state estimation and future development trends. First, we review the model-based state estimation methods, including the Kalman filter, such as the extended Kalman filter (EKF), unscented Kalman filter (UKF), cubature Kalman filter (CKF), etc. Particle filters and Gaussian mixture filters that can handle mixed Gaussian noise are discussed, too. These methods have high requirements for models, while it is not easy to obtain accurate system models in practice. The emergence of robust filters, the interacting multiple model (IMM), and adaptive filters are also mentioned here. Secondly, the current research status of data-driven state estimation methods is introduced based on network learning. Finally, the main research results for hybrid filters obtained in recent years are summarized and discussed, which combine model-based methods and data-driven methods. This paper is based on state estimation research results and provides a more detailed overview of model-driven, data-driven, and hybrid-driven approaches. The main algorithm of each method is provided so that beginners can have a clearer understanding. Additionally, it discusses the future development trends for researchers in state estimation.

scholarly journals Large eddy simulation of turbulent channel flow using differential equation wall model

2018 ◽  
Vol 15 (2) ◽  
pp. 75-89
Author(s):  
Muhammad Saiful Islam Mallik ◽  
Md. Ashraf Uddin
Keyword(s):  
Differential Equation ◽  
Flow Field ◽  
Channel Flow ◽  
Turbulent Channel Flow ◽  
Wall Region ◽  
Computational Domain ◽  
Wall Model ◽  
Eddy Simulation ◽  
Large Eddy ◽  
Near Wall

A large eddy simulation (LES) of a plane turbulent channel flow is performed at a Reynolds number Re? = 590 based on the channel half width, ? and wall shear velocity, u? by approximating the near wall region using differential equation wall model (DEWM). The simulation is performed in a computational domain of 2?? x 2? x ??. The computational domain is discretized by staggered grid system with 32 x 30 x 32 grid points. In this domain the governing equations of LES are discretized spatially by second order finite difference formulation, and for temporal discretization the third order low-storage Runge-Kutta method is used. Essential turbulence statistics of the computed flow field based on this LES approach are calculated and compared with the available Direct Numerical Simulation (DNS) and LES data where no wall model was used. Comparing the results throughout the calculation domain we have found that the LES results based on DEWM show closer agreement with the DNS data, especially at the near wall region. That is, the LES approach based on DEWM can capture the effects of near wall structures more accurately. Flow structures in the computed flow field in the 3D turbulent channel have also been discussed and compared with LES data using no wall model.

scholarly journals Exact coherent states of attached eddies in channel flow

2019 ◽  
Vol 862 ◽  
pp. 1029-1059 ◽  
Author(s):  
Qiang Yang ◽  
Ashley P. Willis ◽  
Yongyun Hwang
Keyword(s):  
Reynolds Number ◽  
Channel Flow ◽  
Coherent Structures ◽  
Time Scale ◽  
Coherent States ◽  
Plane Channel ◽  
Reynolds Numbers ◽  
Wall Region ◽  
Self Similar ◽  
Near Wall

A new set of exact coherent states in the form of a travelling wave is reported in plane channel flow. They are continued over a range in $Re$ from approximately $2600$ up to $30\,000$, an order of magnitude higher than those discovered in the transitional regime. This particular type of exact coherent states is found to be gradually more localised in the near-wall region on increasing the Reynolds number. As larger spanwise sizes $L_{z}^{+}$ are considered, these exact coherent states appear via a saddle-node bifurcation with a spanwise size of $L_{z}^{+}\simeq 50$ and their phase speed is found to be $c^{+}\simeq 11$ at all the Reynolds numbers considered. Computation of the eigenspectra shows that the time scale of the exact coherent states is given by $h/U_{cl}$ in channel flow at all Reynolds numbers, and it becomes equivalent to the viscous inner time scale for the exact coherent states in the limit of $Re\rightarrow \infty$. The exact coherent states at several different spanwise sizes are further continued to a higher Reynolds number, $Re=55\,000$, using the eddy-viscosity approach (Hwang & Cossu, Phys. Rev. Lett., vol. 105, 2010, 044505). It is found that the continued exact coherent states at different sizes are self-similar at the given Reynolds number. These observations suggest that, on increasing Reynolds number, new sets of self-sustaining coherent structures are born in the near-wall region. Near this onset, these structures scale in inner units, forming the near-wall self-sustaining structures. With further increase of Reynolds number, the structures that emerged at lower Reynolds numbers subsequently evolve into the self-sustaining structures in the logarithmic region at different length scales, forming a hierarchy of self-similar coherent structures as hypothesised by Townsend (i.e. attached eddy hypothesis). Finally, the energetics of turbulent flow is discussed for a consistent extension of these dynamical systems notions to high Reynolds numbers.

Effects of Spatial Resolution and Box Size on Numerical Solutions of Turbulent Flows

2005 ◽  
Author(s):  
Dongmei Zhou ◽  
Kenneth S. Ball
Keyword(s):  
Drag Reduction ◽  
Channel Flow ◽  
Spatial Resolution ◽  
Numerical Solutions ◽  
Velocity Profiles ◽  
Wall Region ◽  
Computational Domain ◽  
Mean Velocity ◽  
Significant Difference ◽  
Near Wall

This paper has two objectives, (1) to examine the effects of spatial resolution, (2) to examine the effects of computational box size, upon turbulence statistics and the amount of drag reduction with and without the control scheme of wall oscillation. Direct numerical simulation (DNS) of the fully developed turbulent channel flow was performed at Reynolds number of 200 based on the wall-shear velocity and the channel half-width by using spectral methods. For the first objective, four different grids were applied to the same computational domain and the biggest impact was observed on the logarithmic law of mean velocity profiles and on the amount of drag reduction with 28.3% for the coarsest mesh and 35.4% for the finest mesh. Other turbulence features such as RMS velocity fluctuations, RMS vorticity fluctuations, and bursting events were either overpredicted or underpredicted through coarse grids. For the second objective, two different minimal channels and one natural full channel were studied and 3% drag reduction difference was observed between the smallest minimal channel of 39.1% and the natural full channel of 36.2%. In the near-wall region, however, the minimal channel flow did not exhibit significant difference in the mean velocity profiles and other lower-order statistics. Finally, from this systematical study, it showed that the accuracy of DNS depends more on the spanwise resolution, and it also confirmed that a minimal channel model is able to catch key structures of turbulence in the near-wall region but is much less expensive.

Assessing the Effects of Near Wall Corrections of the Force Acting on Particles in Gas-Solid Channel Flows

2005 ◽  
Author(s):  
Boris Arcen ◽  
Anne Tanie`re ◽  
Benoiˆt Oesterle´
Keyword(s):  
Channel Flow ◽  
Lift Force ◽  
Particle Concentration ◽  
Turbulent Channel Flow ◽  
Shear Velocity ◽  
Solid Particles ◽  
Wall Region ◽  
Wall Effects ◽  
Strong Shear ◽  
Near Wall

The importance of using the lift force and wall-corrections of the drag coefficient for modeling the motion of solid particles in a fully-developed channel flow is investigated by means of direct numerical simulation (DNS). The turbulent channel flow is computed at a Reynolds number based on the wall-shear velocity and channel half-width of 185. Contrary to most of the numerical simulations, we consider in the present study a lift force formulation that accounts for the weak and strong shear as well as for the wall effects (hereinafter referred to as optimum lift force), and the wall-corrections of the drag force. The DNS results show that the optimum lift force and the wall-corrections of the drag together have little influence on most of the statistics (particle concentration, mean velocities, and mean relative and drift velocities), even in the near wall region.

Sign in / Sign up

Export Citation Format

Share Document