Experimental Investigation on the Loss Production Mechanisms in Transitional Boundary Layers

2020 ◽  
Author(s):  
M. Dellacasagrande ◽  
D. Lengani ◽  
D. Simoni ◽  
M. Ubaldi ◽  
P. Zunino
Keyword(s):  
Boundary Layer ◽  
Strain Rate ◽  
Boundary Layers ◽  
Separated Flow ◽  
Reduced Order Model ◽  
Mean Flow ◽  
Order Model ◽  
Data Set ◽  
Reduced Order ◽  
Stress Tensors

Abstract The present paper discusses the results of a large experimental data set describing transitional boundary layers. Time resolved Particle Image Velocimetry (PIV) measurements have been adopted to survey the boundary layer developing over a flat plate under prescribed adverse pressure gradients typical of turbomachinery components. The tests have been performed while varying the pressure gradient, the Reynolds number and the inlet free-stream turbulence intensity (FSTI). Two exemplary cases, referring to bypass and separated flow transition, are discussed by means of principal axis analysis and proper orthogonal decomposition (POD). The POD is used to provide statistical representation of the flow structures and to compute the turbulence production (i.e., the mean flow energy dissipation) due to the dynamical features observed for the different transition types. Reduced order model representations of the flow field are provided and their contribution to the total turbulence kinetic energy production is isolated. This analysis is closed by the inspection of the eigenvectors of the strain rate and Reynolds stress tensors. For the separated flow case, it is shown that the eigenvectors of strain rate and shear tensor are almost perfectly aligned downstream of the maximum displacement of the bubble. The reduced order model reconstruction of the Kelvin-Helmholtz shed vortices provides the largest part of the overall TKE production. For the high FSTI induced transition, the eigenvectors of the shear and stress tensors do not have the same direction. The loss generation is related to the local maximum Reynolds normal stress in the streamwise direction, induced by the boundary layer streaks and their breakdown.

Using Functional Gains for Optimal Sensor Placement in Fluid-Structure Interaction

2009 ◽  
Author(s):  
Imran Akhtar ◽  
Jeff Borggaard ◽  
John A. Burns ◽  
Lizette Zietsman
Keyword(s):  
Differential Equations ◽  
Stokes Equations ◽  
Reduced Order Model ◽  
Navier Stokes ◽  
Cylinder Surface ◽  
Mean Flow ◽  
Order Model ◽  
Navier Stokes Equations ◽  
Reduced Order ◽  
Functional Gains

Functional gains are integral kernels of the standard feedback operator and are useful in control of partial differential equations (PDEs). These functional gains provide physical insight into how the control mechanism is operating. In some cases, these functional gains can provide information about the optimal placement of actuators and sensors. The study is motivated by fluid flow control and focuses on the computation of these functions. However, for practical purposes, one must be able to compute these functions for a wide variety of PDEs. For higher dimensional systems, computing these gains is at least as challenging as the original simulation problem. To reduce the complexity of the governing equations, reduced-order models are often developed by reducing the PDEs to ordinary-differential equations (ODEs). In this study, we use proper orthogonal decomposition (POD)-Galerkin based approach and develop a reduced-order model of a bluff body wake. We solve the incompressible Navier-Stokes equations, simulate the flow past a circular cylinder, and record the snapshots of the flow field. We compute the POD eigenfunctions and project the Navier-Stokes equations onto these few of these eigenfunctions to develop a reduced-order model. Later, we modify the model by introducing a control function simulating suction actuation on the cylinder surface. We linearize the model about the mean flow and apply feedback control to suppress vortex shedding. We then compute the functional gains for the applied control. We identify these gains at various stations in the wake region and suggest optimum locations for the sensors.

scholarly journals A reduced-order model of three-dimensional unsteady flow in a cavity based on the resolvent operator

2016 ◽  
Vol 798 ◽  
Author(s):  
F. Gómez ◽  
H. M. Blackburn ◽  
M. Rudman ◽  
A. S. Sharma ◽  
B. J. McKeon
Keyword(s):  
Time Series Data ◽  
Three Dimensional ◽  
Dynamical Behaviour ◽  
Reduced Order Model ◽  
Series Data ◽  
Mean Flow ◽  
Order Model ◽  
Full Field ◽  
Reduced Order ◽  
The Mean

A novel reduced-order model for time-varying nonlinear flows arising from a resolvent decomposition based on the time-mean flow is proposed. The inputs required for the model are the mean-flow field and a small set of velocity time-series data obtained at isolated measurement points, which are used to fix relevant frequencies, amplitudes and phases of a limited number of resolvent modes that, together with the mean flow, constitute the reduced-order model. The technique is applied to derive a model for the unsteady three-dimensional flow in a lid-driven cavity at a Reynolds number of 1200 that is based on the two-dimensional mean flow, three resolvent modes selected at the most active spanwise wavenumber, and either one or two velocity probe signals. The least-squares full-field error of the reconstructed velocity obtained using the model and two point velocity probes is of the order of 5 % of the lid velocity, and the dynamical behaviour of the reconstructed flow is qualitatively similar to that of the complete flow.

scholarly journals An Eddy–Zonal Flow Feedback Model for Propagating Annular Modes

2021 ◽  
Vol 78 (1) ◽  
pp. 249-267
Author(s):  
Sandro W. Lubis ◽  
Pedram Hassanzadeh
Keyword(s):  
Large Scale ◽  
Interaction Mechanism ◽  
Zonal Flow ◽  
Reanalysis Data ◽  
Reduced Order Model ◽  
Mean Flow ◽  
Order Model ◽  
Reduced Order ◽  
Annular Modes ◽  
Lag Times

AbstractThe variability of the zonal-mean large-scale extratropical circulation is often studied using individual modes obtained from empirical orthogonal function (EOF) analyses. The prevailing reduced-order model of the leading EOF (EOF1) of zonal-mean zonal wind, called the annular mode, consists of an eddy–mean flow interaction mechanism that results in a positive feedback of EOF1 onto itself. However, a few studies have pointed out that under some circumstances in observations and GCMs, strong couplings exist between EOF1 and EOF2 at some lag times, resulting in decaying-oscillatory, or propagating, annular modes. Here, we introduce a reduced-order model for coupled EOF1 and EOF2 that accounts for potential cross-EOF eddy–zonal flow feedbacks. Using the analytical solution of this model, we derive conditions for the existence of the propagating regime based on the feedback strengths. Using this model, and idealized GCMs and stochastic prototypes, we show that cross-EOF feedbacks play an important role in controlling the persistence of the annular modes by setting the frequency of the oscillation. We find that stronger cross-EOF feedbacks lead to less persistent annular modes. Applying the coupled-EOF model to the Southern Hemisphere reanalysis data shows the existence of strong cross-EOF feedbacks. The results highlight the importance of considering the coupling of EOFs and cross-EOF feedbacks to fully understand the natural and forced variability of the zonal-mean large-scale circulation.

scholarly journals The Behaviour of the Normal Fluctuation Terms in the Case of Attached or Detached Turbulent Boundary Layers

1984 ◽  
Author(s):  
G. A. Gerolymos ◽  
Y. N. Kallas ◽  
K. D. Papailiou
Keyword(s):  
Boundary Layer ◽  
Shock Wave ◽  
Turbulent Boundary Layer ◽  
Boundary Layers ◽  
Separated Flow ◽  
Flow Region ◽  
Boundary Layer Separation ◽  
Turbulent Boundary Layers ◽  
Mean Flow ◽  
Boundary Layer Interaction

The turbulent normal fluctuation terms have been found from measurements to be very important, when approaching separation, inside the separated flow region, as well as, in the region where a shock wave interacts with a turbulent boundary layer. In the present work correlations are developped on the basis of available experimental results, which relate the normal fluctuation terms, appearing in integral formulations for turbulent boundary layer calculation methods, to mean flow quantities. These correlations are valid, as far as compressible attached or separated turbulent boundary layers are concerned, as well as in the case of a shock wave/turbulent boundary layer interaction which leads to boundary layer separation. Furthermore, correlations are developed for the maxima of the velocity fluctuation terms.

scholarly journals Nonlinear reduced-order model for vertical sloshing by employing neural networks

2021 ◽  
Author(s):  
Marco Pizzoli ◽  
Francesco Saltari ◽  
Franco Mastroddi ◽  
Jon Martinez-Carrascal ◽  
Leo M. González-Gutiérrez
Keyword(s):  
Neural Network ◽  
Fluid Structure Interaction ◽  
Oscillation Amplitude ◽  
Reduced Order Model ◽  
Order Model ◽  
Data Set ◽  
Fluid Structure ◽  
Reduced Order ◽  
Structure Interaction ◽  
Bouncing Ball

AbstractThe aim of this work is to provide a reduced-order model to describe the dissipative behavior of nonlinear vertical sloshing involving Rayleigh–Taylor instability by means of a feed forward neural network. A 1-degree-of-freedom system is taken into account as representative of fluid–structure interaction problem. Sloshing has been replaced by an equivalent mechanical model, namely a boxed-in bouncing ball with parameters suitably tuned with performed experiments. A large data set, consisting of a long simulation of the bouncing ball model with pseudo-periodic motion of the boundary condition spanning different values of oscillation amplitude and frequency, is used to train the neural network. The obtained neural network model has been included in a Simulink®  environment for closed-loop fluid–structure interaction simulations showing promising performances for perspective integration in complex structural system.

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