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On the uncertainty of defocus methods for 3D particle tracking velocimetry
Get PDFDefocus methods have become more and more popular for the estimation of the 3D position of particles in flows (Cierpka and Kahler, 2011; Rossi and K ¨ ahler, 2014). Typically the depth positions of particles are ¨ determined by the defocused particle images using image processing algorithms. As these methods allow the determination of all components of the velocity vector in a volume using only a single optical access and a single camera, they are often used in, but not limited to microfluidics. Since almost no additional equipment is necessary they are low-cost methods that are meanwhile widely applied in different fields. To overcome the ambiguity of perfect optical systems, often a cylindrical lens is introduced in the optical system which enhances the differences of the obtained particle images for different depth positions. However, various methods are emerging and it is difficult for non-experienced users to judge what method might be best suited for a given experimental setup. Therefore, the aim of the presentation is a thorough evaluation of the performance of general advanced methods, including also recently presented neural networks (Franchini and Krevor, 2020; Konig et al., 2020) based on typical images
PIV Measurements of the Wake Formation from a Rough Flat Plate
Get PDFWake flows are prevalent in a wide range of engineering applications and their behaviour can significantly impact engineering design and performance. A considerable body of work exists on smooth body wake structures and flows over rough bodies, however, there is a lack of fundamental physical understanding of the amalgamation of the two fields. Two-component two-dimension particle image velocimetry (2C-2D PIV) is used to investigate the effect of surface roughness on the formation of large scale structures in the near wake of a thin flat plate. Both high-speed and low-speed, high-resolution PIV setups have been used to investigate the effect of surface roughness on the boundary layer and the near wake of the plate to gain insight into the underlying physical connection between these regions
Moving Surface Actuation, Effects of Frequency-based Shear Layer Excitation on the Response of a Bluff Body Wake
Get PDFThe effect of actuation frequency, using moving surface actuation, is investigated for a square cylinder bluff body wake. Pressure sensor data are used to optimize actuation characteristics through the implementation of an NSGA-II evolutionary algorithm. Velocity field data are obtained using Particle Image Velocimetry (PIV) for baseline and optimized actuation cases. A Proper Orthogonal Decomposition (POD) analysis shows that the vortex shedding frequency shifts between frequencies associated with the actuation, moving between regions of lock-on and quasi-periodicity. Additionally, the POD shows that the energy contained in the coherent shedding motion is reduced through actuation, while the total energy in the velocity field stays relatively constant. A reconstruction of the first 10 POD modes indicates that the coherent contribution to the Reynolds stresses significantly decreases compared to the non-actuated case. The mechanism for drag reduction is investigated using the shed circulation flux and Kochin’s drag formulation model. The drag obtained using PIV measurements and Kochin’s formulation is consistent with trends observed for the base pressure as a function of actuation frequency
3D pressure field reconstruction from time-resolved stereoscopic PIV measurements by relaxation of Taylor\u27s hypothesis
Get PDFThis work presents reconstructions of 3D pressure fields starting from 2D3C stereoscopic-PIV (SPIV) measurements. In Fratantonio et al. (2021), we presented a new reconstruction algorithm, the “Instantaneous convection” method, capable of producing 3D velocity fields from time-resolved SPIV measurements. For reconstructions in flows with strong shear layers and high turbulence intensity, this method is able to provide time-resolved 3D velocity volumes that are more accurate than those that can be obtained from the more frequently employed reconstruction method based on the Taylor’s hypothesis and on the use of a mean convective field. Here we investigate the possibility of reconstructing the 3D pressure field from the timeresolved series of reconstructed 3D velocity data. A pseudo-tracking method is employed for computing the velocity material derivative, and the pressure field is then reconstructed by solving the 3D Poisson equation. The velocity and pressure reconstructions are validated on the Direct Numerical Simulation data of the turbulent channel flow taken from the John Hopkins Turbulence Database (JHTDB), and an application to experimental SPIV measurements of an air jet flow in coflow carried out at the Turbulent Mixing Tunnel (TMT) facility at Los Alamos National Laboratory is presented
Effect of Gust Wind on Flow over a Wall-Mounted Fence
Get PDFIn this work, the characteristics of incoming and wake flows downstream of wall-mounted fences under wind gust were explored with wind tunnel experiments. A time-resolved particle image velocimetry was used to capture the flow dynamics across two different fence heights. The results show that during the gust period, the wake presents distinct meandering and strong flow mixing. The Probability Density Function distribution of flow velocities indicates that the mixing effect increases with the streamwise distances. Specifically, for locations above the fence top tip, the growth of streamwise distance decreases the footprint of wind gust. However, for locations lower than the fence top tip, the local wind flows exhibit stronger variations before and after wind gust with the growth of downstream distance. Overall, at the same relative streamwise and spanwise locations downstream of fences within the wake region, the higher fence better suppresses the influence of gust wind
Detecting vortical structures in time-resolved volumetric flow fields
Get PDFThe detection of three-dimensional coherent vortical structures that get advected as well as deformed with time is a challenge. However, it is critical for the statistical analysis of these vortices, for example, the quasi-streamwise vortices (QSVs) in the near field of a turbulent shear layer, where cavitation inception typically occurs. These structures exhibit underlying correlations among different properties that can be derived from the velocity gradients. Exploiting these correlations, a pseudo-Lagrangian vortex detection method is proposed that uses k-means clustering based on vorticity magnitude and direction, values of λ2, strain rate structure, axial stretching, and location. The method facilitates the finding that QSVs have pressure minima that are lower than those in the surrounding flow, including the primary spanwise vortices. These minima typically appear after a period of axial stretching and before contraction events
Extended-POD based acoustic analysis of separated aerofoils via simultaneous time-resolved PIV and force measurements
Get PDFWe present a cross-correlation based analysis of the acoustic field generated in the wake of NACA 0012 and NACA 65410 aerofoils at a chord-based Reynolds number Rec = 75000 as obtained from pressure fields reconstructed from a series of planar time-resolved Particle Image Velocimetry (PIV) experiments. The experiments are performed in a water channel facility located at the University of Southampton with an overhead carriage system to allow precise control of the angle of attack α of the aerofoils as well as to mount them to a six-axis force/torque transducer to allow for simultaneous load measurements. Angles of attack in the range 4◦ < α < 17◦ are explored corresponding to a range of conditions from zero flow separation to fully stalled
Uncertainty Estimation for Ensemble Particle Image Velocimetry
Get PDFWe present a novel approach to estimate the uncertainty in ensemble particle image velocimetry (PIV) measurements. Ensemble PIV is widely used when the cross-correlation signal-to-noise ratio (SNR) is insufficient to perform a reliable instantaneous velocity measurement. Despite the utility of ensemble PIV, uncertainty quantification for this type of measurement has not been studied. The existing uncertainty quantification algorithms for PIV are developed and used only for instantaneous PIV measurement and do not account for the improved SNR in ensemble PIV. Existing instantaneous uncertainty quantification methods can be divided into direct and indirect categories. Indirect methods require calibration based on the effect of various image parameters (such as noise, particle size, density, velocity gradient, etc.) on the correlation SNR. Indirect methods have not been calibrated for error sources relevant in an Ensemble PIV measurement. Also, they have lower sensitivity to the error sources compared to direct approaches. Direct methods, such as the moment of correlation (MC) and Image Matching (IM), find the uncertainty based on the images and correlation planes without any calibration and are more reliable (Bhattacharya et al., 2018; Sciacchitano et al., 2013). Ensemble PIV is based on ensemble correlations; therefore, MC, which uses the generalized cross-correlation (GCC) plane as a measure of uncertainty, is the most suitable method to be modified to be applicable for the ensemble PIV. The GCC plane is the inverse Fourier transform of the phase correlation and represents the probability density function (PDF) of particles’ displacements (Bhattacharya et al., 2018; Eckstein and Vlachos, 2009). We replaced instantaneous GCC with ensemble GCC and modified MC’s normalization factor to account for the number of ensembles. The MC’s primary limitation is that it assumes a Gaussian shape for the PDF of displacements and estimate the standard deviation of the underlying PDF using a fitted Gaussian. However, the PDF deviates from Gaussian distribution due to velocity gradient or non-Gaussian random displacements. Therefore, MC’s reliability and applicability are reduced for flow fields with non-Gaussian PDFs. Also, our analysis shows that ensemble MC consistently underestimates the uncertainty. So, a generalized and reliable method for uncertainty quantification for ensemble PIV is needed
Using differential phase for 3D localization of tracer particles in digital inline holographic microscopy PIV/PTV (DIHM-PIV/PTV)
Get PDFDigital inline holographic microscopy PIV/PTV (DIHM-PIV/PTV) has the ability to provide 4-dimensional (4D), i.e. time-resolved, 3-component 3-dimensional (3C-3D) flow measurement with high spatial and temporal resolution, compact optical setup and minimal calibration Sun et al. (2020) compared to most other volumetric techniques such as tomo-PIV, defocusing PIV, etc. Despite all these advantages DIHMPIV/PTV has not yet developed into a standard laboratory tool due to some major limitations such as the extended depth-of-focus (DOF) problem and the virtual image effect which cause artefacts in the standard reconstruction volume limiting the seeding concentration and thus the achievable velocity spatial resolution. In order to mitigate the above-mentioned limitations we present a novel particle localization and extraction methodology which allows the minimization of these artefacts from the standard reconstruction and perform PIV/PTV analysis on the particle volume fields only. The proposed algorithm is based on the differential phase, which is the axial phase shift of the object wave compared to the reference plane wave propagation
Validation of model-based correction for non-Stokesian tracers
Get PDFIn-situ flow-tracking measurements at scales on the order of 10 m3 and larger remain a challenge. The large size of the tracers required for optical visibility results in an inertial lag and inherently low seeding density. For instance, natural snowfall, fake snow and soap bubbles on the order of 2 cm have been used as tracers for field measurements and extracted statistical quantities (Nemes et al., 2017; Wei et al., 2021; Rosi et al., 2014). There is also growing interest in networks of sensors for remote- measurement where optical access is impossible (Bolt et al. 2020; Villa et al. 2016). Onboard inertial measurement units (IMU) are a promising tool for high-resolution measurements over large spatial domains without optical access. However, due to the intrinsic lag, a dynamic-model-based correction is required for the tracking of transient phenomena, sketched in figure 1. In the present study, the tracer-velocity correction is evaluated by quantifying the residual error in measured flow velocity after the method of Galler et al. (2021) is applied