Moving Horizon Trend Identification Based on Switching Models for Data Driven Decomposition of Fluid Flows

Modal decomposition is pretty popular in fluid mechanics, especially for data-driven analysis. Dynamic mode decomposition (DMD) allows to identify the modes that describe complex phenomenona such as those physically modelled by the Navier-Stokes equation. The identified modes are associated with residuals, which can be used to detect a meaningful change of regime, e.g., the formation of a vortex. Toward this end, moving horizon estimation (MHE) is applied to identify the trend of the norm of the residuals that result from the application of DMD for the purpose to automatically classify the time evolution of fluid flows. The trend dynamics is modelled as a switching nonlinear system and hence an MHE problem is solved in such a way to monitor the time behavior of the fluid and quickly identify changes of regime. The stability of the estimation error given by MHE is proved. The combination of DMD and MHE provide successful results as shown by processing experimental datasets of the velocity field of fluid flows obtained by a particle image velocimetry

A procedure for computing the spot production rate in transitional boundary layers

The present work describes a method for the computation of the nucleation rate of turbulent spots in transitional boundary layers from particle image velocimetry (PIV) measurements. Different detection functions for turbulent events recognition were first tested and validated using data from direct numerical simulation, and this latter describes a flat-plate boundary layer under zero pressure gradient. The comparison with a previously defined function adopted in the literature, which is based on the local spanwise wall-shear stress, clearly highlights the possibility of accurately predicting the statistical evolution of transition even when the near-wall velocity field is not directly available from the measurements. The present procedure was systematically applied to PIV data collected in a wall-parallel measuring plane located inside a flat plate boundary layer evolving under variable Reynolds number, adverse pressure gradient (APG) and free-stream turbulence. The results presented in this work show that the present method allows capturing the statistical response of the transition process to the modification of the inlet flow conditions. The location of the maximum spot nucleation is shown to move upstream when increasing all the main flow parameters. Additionally, the transition region becomes shorter for higher Re and APG, whereas the turbulence level variation gives the opposite trend. The effects of the main flow parameters on the coefficients defining the analytic distribution of the nucleation rate and their link to the momentum thickness Reynolds number at the point of transition are discussed in the paper.[GRAPHICS]

Effects of Upstream Wakes on the Boundary Layer Over a Low-Pressure Turbine Blade

In the present work, the evolution of the boundary layer over a low-pressure turbine blade is studied using direct numerical simulations, with the aim of investigating the unsteady flow field induced by the rotor-stator interaction. The freestream flow is characterized by the high level of freestream turbulence and periodically impinging wakes. As in the experiments, the wakes are shed by moving bars modeling the rotor blades and placed upstream of the turbine blades. To include the presence of the wake without employing an ad-hoc model, we simulate both the moving bars and the stationary blades in their respective frames of reference and the coupling of the two domains is done through appropriate boundary conditions. The presence of the wake mainly affects the development of the boundary layer on the suction side of the blade. In particular, the flow separation in the rear part of the blade is suppressed. Moreover, the presence of the wake introduces alternating regions in the streamwise direction of high- and low-velocity fluctuations inside the boundary layer. These fluctuations are responsible for significant variations of the shear stress. The analysis of the velocity fields allows the characterization of the streaky structures forced in the boundary layer by turbulence carried by upstream wakes. The breakdown events are observed once positive streamwise velocity fluctuations reach the end of the blade. Both the fluctuations induced by the migration of the wake in the blade passage and the presence of the streaks contribute to high values of the disturbance velocity inside the boundary layer with respect to a steady inflow case. The amplification of the boundary layer disturbances associated with different spanwise wavenumbers has been computed. It was found that the migration of the wake in the blade passage stands for the most part of the perturbations with zero spanwise wavenumber. The non-zero wavenumbers are found to be amplified in the rear part of the blade at the boundary between the lowand high-speed regions associated with the wakes. [DOI: 10.1115/1.4056108

A Method for the Determination of Turbulence Intensity by Means of a Fast Response Pressure Probe and its Application in a LP Turbine

This paper describes the measurements and the post-processing procedure adopted for the determination of the turbulence intensity in a low pressure turbine (LPT) by means of a single sensor fast response aerodynamic pressure probe. The rig was designed in cooperation with MTU Aero Engines and considerable efforts were put into the adjustment of all relevant model parameters. Blade count ratio, airfoil aspect ratio, reduced massflow, reduced speed, inlet turbulence intensity and Reynolds numbers were chosen to reproduce the full scale LP turbine. Measurements were performed adopting a phase-locked acquisition technique in order to provide the time resolved flow field downstream of the turbine rotor. The total pressure random fluctuations are obtained by selectively filtering, in the frequency domain, the deterministic unsteadiness due to the rotor blades and coherent structures. The turbulence intensity is derived from the inverse Fourier transform and the correlations between total pressure and velocity fluctuations. The determination of the turbulence intensity allows the discussion of the interaction processes between the stator and rotor for engine-representative operating conditions of the turbine

A data-driven optimal disturbance procedure for free-stream turbulence induced transition

The investigation of free-stream turbulence induced transition by means of simple and effective numerical methods traditionally represents a major challenge in the aerodynamic field. In this work, a data-driven algorithm aimed at obtaining optimal forcing and response concerning free-stream turbulence induced boundary layer transition is introduced. The method, referred to as Data-driven Optimal Disturbance (DOD) in the following, relies on dynamic mode decomposition to compute the linear matrix responsible for disturbance evolution in the streamwise direction and opens the possibility for optimal disturbance analysis in an equation-free manner. The procedure has been applied to high-fidelity large-eddy simulation (LES) results concerning zero pressure gradient flows. Four different combinations of turbulence intensity Tu and integral length scale L-g have been adopted as boundary conditions to investigate the sensitivity of the transition route to the free-stream turbulence properties. Overall, DOD applied within the transitional region identifies highly energetic turbulent scales embedded in the free-stream as the optimal forcing inducing the formation of streaky structures within the boundary layer. Furthermore, streaky structures characterized by the same spanwise wavelength observed in the LES results are identified by DOD as the boundary layer response to the optimal forcing. Finally, the amplification of disturbances provided by DOD along the streamwise direction clearly resembles the well-established transient growth. Thus, DOD appears a useful tool to analyze the free-stream turbulence induced transition of boundary layers by a simple equation-free algorithm merely based on data analytics. Published under an exclusive license by AIP Publishing