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Rayleigh-Bénard convection in air: out-of-plane vorticity from stereoscopic PIV measurements
Get PDFWe present results from stereoscopic PIV measurements in a Rayleigh-Benard convection (RBC) cell filled with (compressed) air at Rayleigh numbers: Ra = 1.5×104, 2×104, 1×105, 2×105, 5×105, and Prandtl number Pr \u27 0.7. The three largest Rayleigh numbers are obtained pressurising the whole set-up including cameras and objective lenses, up to 4.5 bars. The main goal of this study is to reproduce DNS data that are acquired at the same Rayleigh numbers to study far-tail events of the out-of-plane vorticity component (ωz). The measurements are performed in a RBC cell with aspect ratio Γ = W/H = 10, where W is the width and H = 3 cm is the height of the domain. The cell is equipped with a transparent bottom plate heated by a thin oxide layer (for details see Kastner et al. (2018)), which allows us to measure 3C2D velocity fields on ¨a horizontal plane at mid height of the cell. The RBC cell set-up is inserted in the SCALEX facility of TU Ilmenau, a pressure vessel with several optical accesses that can be pressurised up to 10 bars
The experiments aim firstly at improving the quality of previous measurements performed in the sameset-up [Kastner et al. (2018), Cierpka et al. (2019)], regarding the accuracy of the out-of-plane velocity ¨component. This has been realised by positioning the cameras at a larger stereo angle (about 25◦), which is possible by placing them inside the pressure vessel. Major challenges of the current measurements are caused by optical distortions due to the temperature gradients that are typical for thermal convection (see Valori (2018), Valori et al. (2019)).
Probability Density Functions (PDFs) of ωz from stereo PIV experiments and from DNS data are shown respectively in figure 1(a) and 1(b) for all Rayleigh numbers studied. We can observe that for both kind of data the tails of the PDF becomes wider while increasing the Rayleigh number, which may be connected to intermittency. This crossover from Gaussian to intermittent statistic was recently studied in Valori and Schumacher (2021) from DNS. Figure2(a) shows the temporal evolution of ωz at the position of its largest (extreme) value at Ra = 2.5 × 105, while figure2(b) shows the spatial distribution of ωz at the time of its extreme event in the experiments.
The experimental results are able to reproduce well the statistics of DNS data of the same flow, and allow the study of extreme events of ωz
Multi-resolution, time-resolved PIV measurements of a Decelerating Turbulent Boundary Layer near Separation
Get PDFWe report on measurements of the time-evolving velocity profile of a turbulent boundary layer subjected to a strong adverse pressure gradient (APG) at Reynolds numbers up to Reθ ≈ 55 000 with an upstream friction Reynolds number exceeding Reτ ≈ 10 000. Near the point of flow separation high-resolution imaging at high camera frame rates captured the time evolving velocity profile using the so-called “profile-PIV” technique in a nested imaging configuration of two cameras operating at different image magnifications. One camera used an image magnification better than unity to resolve the viscous scales directly at the wall while the remainder of the roughly 200 mm thick boundary layer is simultaneous captured by the second camera. In the APG the variance of the stream-wise velocity exhibits no “inner peak” commonly found in turbulent boundary layers without pressure gradient influence. Spectral analysis further shows that the peak energy within the boundary layer shifts away from the wall toward lower frequencies. The overlap between the simultaneously imaged areas allows to assess and, to first order, correct for the effect of spatial smoothing on statistical quantities, spectra and related quantities. A multi-frame cross-correlation algorithm was used to process the extensive data base. In addition, a newly developed 2D-2C “Shake-The-Box” algorithm (STB) provided highly resolved particle tracking data beyond the reach of conventional PIV processing
Gridless Determination of Aerodynamic Loads Using Lagrangian Particle Tracks
Get PDFThe aerodynamic loads on a flexible wing in terms of the surface pressure distribution and the lift force along the span are determined experimentally based on non-intrusive Lagrangian particle tracking (LPT) measurements. As the flexible wing deforms under the aerodynamic loads, its deformed shape is first reconstructed based on structural LPT measurements conducted together with the flow measurements in an integrated approach. Based on the reconstructed wing shape, flow tracers data are collected along surface normals to evaluate the surface pressure, as well as along elliptic paths around the wing to determine the circulation. The lift force is calculated from the surface pressure by integrating the pressure difference along the chord, as well as from the circulation using the Kutta-Joukowski theorem. The circulation-based lift results are in very good agreement with reference measurements from a force balance, with differences in the total lift force on the wing of less than 5%. The lift estimation based on the extrapolated surface pressure is consistently lower than the circulation-based lift, by about 10%, due to the limited accuracy of the pressure extrapolation near the leading edge region, where a considerable fraction of the lift is generated
Reynolds stress tensor and pressure-related turbulence transport terms measured by time-resolved tomographic-PIV
Get PDFTurbulence is inherently a three-dimensional and time dependent flow phenomenon (Pope, 2001). Because of the ubiquitous existence of turbulent flows in nature, accurate characterization of turbulent flows, either through experimental measurements or through direct numerical simulations, is of paramount importance for modeling turbulence (Liu and Katz, 2018). Since its inception in 1984 (Adrian, 1984), Particle Image Velocimetry (PIV), among several other conventional techniques used for turbulence measurements, has been a valuable tool for providing reliable experimental data for turbulence research. Several advancements in hardware such as high-speed cameras, together with innovative algorithms and procedures, have extended the scope of PIV to a variety of applications. Westerweel et al. (2013) point out in a recent review article that one of the main advantages of the PIV measurement is its unique ability in measuring quantitatively spatial derivatives of the flow field. With the development of Tomographic PIV introduced by Elsinga et al. (2006), it is now possible to measure simultaneously the distributions of three velocity components in a three-dimensional flow field, thus enabling us to measure all the velocity derivatives of a turbulent flow. However, for a thorough characterization of a turbulent flow, in addition to the velocity gradients, the instantaneous pressure distribution in the 3D flow field also needs to be measured
Examining the Effects of Fluid Velocity Gradients on 4D Digital Holographic PIV/PTV Measurements
Get PDF4D digital holographic PIV/PTV (4D-DHPIV/PTV) methods have demonstrated theoretical viability due to their relative ease of setup and high spatial resolution (Soria (2018)). This study investigates how velocity gradients related to different flow regimes and their magnitudes affect 3-component–3-dimensional (3C-3D) digital holographic PIV measurement uncertainty.
The error introduced by velocity gradients within the interrogation volume is studied by simulating particles in a velocity field, with a given constant velocity gradient superimposed on a uniform flow from which a time-series of hologram pairs are generated and the 3C-3D velocity fields and their errors are determined using 4D-DHPIV/PTV Sun et al. (2020). Hologram pairs are simulated by modelling the propagation and particlediffraction of coherent laser light using the angular spectrum method (Goodman (1996)). The hologram reconstruction then involves direct reconstruction, followed by deconvolution, a particle position refinement and a hologram subtraction step (Sun et al. (2020)). The particle positions obtained from 4D-DHPIV/PTV are then used to resolve particle displacement measurements using 3D cross-correlation digital analysis with a 3D Gaussian fit to sub-pixel resolution (Soria (2006)).
The effects of velocity gradients on the displacement uncertainty and bias error have been investigated by undertaking Monte Carlo simulations under a range of velocity gradient environments. Specifically, 5 common velocity gradients have been studied, which included pure strain, pure vorticity and x, y and z-directional shear.
The results indicate that the novel 4D-DHPIV/PTV has poorer accuracy and precision in the z-propagation axis, resulting in larger minimum uncertainties and bias errors. The errors in the z axis are also significantly less affected by velocity gradients in the z direction when compared to the effects of x and y directional velocity gradients on x and y errors respectively. Furthermore, the rate of cross-correlation maximum and SNR decrease are approximately 1.36 times slower due to velocity gradients in the z axis than other axes.
Energy spectra of Sub-Surface Velocity Fields Beneath Faraday Waves
Get PDFFaraday waves form on the surface of a fluid which is subject to vertical forcing, and are researched in a large range of applications. Some examples are the formation of ordered wave patterns and the controlled walking or orbiting of droplets (Couder et al. (2005); Saylor and Kinard (2005)). Moreover, recent studies discovered the existence of a horizontal velocity field at the fluid surface, called Faraday flow, which was shown to exhibit an inverse energy cascade and thus properties of two-dimensional turbulence (von Kameke et al., 2011, 2013; Francois et al., 2013). Additionally, three-dimensionality effects have been part of recent investigations in quasi-2D flows (both electromagnetically-driven (Kelley and Ouellette, 2011; Martell et al., 2019) or produced by parametrically-excited waves (Francois et al., 2014; Xia and Francois, 2017)). Furthermore, the occurrence of an inverse cascade in thick layers is also subject of current studies on the coexistence of 2D and 3D turbulence (Biferale et al., 2012; Kokot et al., 2017; Biferale et al., 2017). By performing 2D PIV measurements at horizontal planes beneath the Faraday waves, we recently showed that pronounced three dimensional flows occur in the bulk, with much larger spatial and temporal scales than those on the surface (Colombi et al., 2021), when the system is not shallow in comparison to typical length scales of the surface flow (fluid thickness exceeding half the Faraday wavelength λF). This in turn reveals that an inverse energy cascade and aspects of a confined 2D turbulence can coexist with a three dimensional bulk flow. In this work, 2D PIV measurements of the velocity fields are carried out at a vertical cross-section xz-plane and at four distinct horizontal xy-planes at different depths in Faraday waves. The results reveal that small and fast vertical jets penetrate from the surface into the bulk with fast accelerating bursts and strong momentum transport in the z−direction. Furthermore, the fraction of flow kinetic energy in the vertical direction is found to peak inside a layer of approximately 10 mm (one Faraday wavelength) below the fluid surface
Uncertainty of PIV/PTV based pressure, using velocity uncertainty
Get PDFPressure reconstruction from velocity measurements using particle image velocimetry (PIV) and particle tracking velocimetry (PTV) has drawn significant attention as it can provide instantaneous pressure fields without altering the flow. Previous studies have found that the accuracy of the calcualted pressure field depends on several factors including the accuarcy of the velocity measurement, the spatiotemporal resolutions, the method for calculating pressure-gradient, the algorithm for pressure-gradient integration, the pressure boundary condition, etc. Therefore, it is critical and challenging to quantify the uncertainty of the reconstructed pressure field. The recent development of the uncertainty quantification algorithms for PIV and PTV allows for the local and instantaneous uncertainty estimation of velocity measurement, which can be used to infer the pressure uncertainty. In this study, we introduce a framework that propagates the standard velocity uncertainty defined as the standard deviation of the velocity error distribution through the pressure reconstruction process to obtain the uncertainty of the pressure field. The uncertainty propagations through the calculation of the pressure-gradient and the pressure-gradient integration were modeled as linear transformations, which can reproduce the effects of the spatiotemporal resolutions, the numerical schemes, the integration algorithms, and the pressure boundary condition on the accuracy of the resulting pressure fields. The proposed uncertainty estimation approach also considers the effect of the spatiotemporal and componentwise correlation of the velocity errors in common PIV/PTV measurements on the pressure uncertainty
Determination of the Near Wall Flow of a Multi-Stage Tesla Diode Using PIV and PTV
Get PDFParticle image velocimetry (PIV) and particle tracking velocimetry (PTV) are two popular methods to measure the velocity in complex geometries such as the Tesla valve. This paper provides an investigation on the application of a tessellation meshing method for interpolating non-uniform velocity vectors calculated using PTV. The procedure to apply this method containing mask generation and mesh study is described. The results are compared to the PIV results particularly where the near wall results are important. The result of the flow field calculated by the application of the tessellation method on the PTV results are presented for a two-stage Tesla valve operated in the range of Re = 100 to 600 both in forward and reverse configuration
Investigation of the shear-layer instabilities in supersonic impinging jets using dual-time velocity measurements
Get PDFMotivated by applications in the propulsion industry, the fundamental study of phase-locked shear-layer instabilities in supersonic impinging jets has been of research interest for long time. While such flows have been experimentally investigated in various research studies using time-unresolved particle image velocimetry (PIV) techniques, the understanding of the shear-layer dynamics is limited, due to the absence of temporal information. Time-resolved PIV measurements for high-speed flows require a large bandwidth, which is challenging to achieve with the current state of technology. An alternate approach using time-unresolved double-PIV measurements is presented in the current study, which provides multiple samples of dual-time data, depicted in figure 1. Such data can be obtained using two co-visual PIV systems, triggered at a user-selectable time-offset, ∆t. As shown by Sikroria et al. (2020), the application of techniques like dynamic mode decomposition (DMD) on time-unresolved dual-time data provides valuable information about the flow structures governing the shear-layer instabilities. The experimental setup for such measurements in supersonic impinging jets, followed by the determination of the relevant dynamical flow structures from the data, will be presented in the conference
PIV measurements of entrainment process of directly injected media in internal combustion engines
Get PDFPIV measurements have been successfully applied to various flow fields relating internal combustion engines such as in-cylinder air motion, air flow in an intake port, and even a discharging passage of an ignition plug. Measurements of induced air motion around diesel sprays can be said to be a significant example of the PIV applications because the air motion is reflected in an unsteady complicated flow structure. Instead of the apparent entrainment exaggerated by spray droplet dispersing, substantial air entrainment through momentum exchange between liquid and gas was finally obtained by combining PIV and spray profile observation.
PIV measurements of this kind were extensionally applied to other direct fluid injection by the authors. The second object was a high-pressure gas jet directly injected under gas pressure as high as 30 MPa. It was found the gas jet has strong air entrainment through momentum exchange in a single gaseous phase between fuel gas and ambient air. The third directly injected medium in internal combustion engines should be torch flame ejected from nozzle holes of a pre-combustion chamber (PCC) to a main combustion chamber (MCC) of a so-called DF (dual-fuel) engine.
In this study, mixture entrainment process of torch flames is discussed on the PIV results for the first time. However, chamber configurations of a real DF engine are hard to simulate since itrequires several auxiliary PCC devices such as an ignition plug, a sub gas injector, and so on. All of them should be actuated synchronously with an engine crank angle. In the case of a constant volume vessel (CVV), the synchronization is not necessary, but the mixture control in the PCC becomes problematic because of the lack of compression and expansion strokes that assures PCCgas exchange. For overcoming the situation, rupture of a membrane was introduced in this study. The membrane turns the upper part of the PCC into an air pressure reservoir and low-pressure air jets eject from the nozzle holes after a solenoid-driven needle pierces the membrane for rupturing. The differential pressure between the upper chamber and the lower one was chosen as a main parameter of the experiment.
Since the measurements and analysis of the entrainment of the low-pressure air jets are yet to finalize, the outlook of the CVV, the PIV specifications, and prime results of the air entrainment are attached herewith. After all, the PIV measurements revealed essential difference among air entrainment processes of the above three directly injected media in internal combustion engines