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Main results of the first Lagrangian Particle Tracking Challenge
Get PDFThis work presents the main results of the first Lagrangian Particle Tracking challenge, conducted within the framework of the European Union’s Horizon 2020 project HOMER (Holistic Optical Metrology for Aero-Elastic Research), grant agreement number 769237. The challenge, jointly organised by the research groups of DLR, ONERA and TU Delft, considered a synthetic experiment reproducing the wall-bounded flow in the wake of a cylinder which was simulated by LES. The participants received the calibration images and sets of particle images acquired by four virtual cameras, and were asked to produce as output the particles positions, velocities and accelerations (when possible) at a specific time instant. Four different image acquisition strategies were addressed, namely two-pulse (TP), four-pulse (FP) and time-resolved (TR) acquisitions, each with varying tracer particle concentrations (or number of particles per pixel, ppp). The participants’ outputs were analysed in terms of percentages of correctly reconstructed particles, missed particles, ghost particles, correct tracks and wrong tracks, as well as in terms of position, velocity and acceleration errors, along with their distributions. The analysis of the results showed that the best-performing algorithms allow for a correct reconstruction of more than 99% of the tracer particles with positional errors below 0.1 pixels even at ppp values exceeding 0.15, whereas other algorithms are more prone to the presence of ghost particles already for ppp < 0.1. While the velocity errors remained contained within a small percentage of the bulk velocity, acceleration errors as large as 50% of the actual acceleration magnitude were retrieved
Investigating Algorithmic Decision-Making with Applications to Student Diversity at Illinois Tech
Get PDFThis study focuses on algorithmic decision-making and how structural inequalities can introduce inadvertent bias in an algorithm. There are a lot of efforts by universities in the United States to diversify the student body. Most of these efforts focus on outreach, but few focus on improving any internal processes first.
This study aimed to look for room for improvement to make internal processes more equitable so the rest of the efforts to diversify a student body would be more effective. Specifically, Illinois Tech admissions data was observed and patterns found were tested for statistical significance
An Experimental Investigation on the Wind-driven Runback Motion of Water Droplets over Solid Surfaces with Different Wettabilities
Get PDFAircraft icing is widely recognized as one of the most serious weather hazards to flight safety. Specially designed hydro-/ice-phobic coatings are currently undergoing development for aircraft icing mitigation. It was found that hydro-/icephobic coatings would delay the ice accretion iover airframe surfaces so that the impacted supercooled water droplets could be blown away by the airflow from the airframe surface before being frozen into ice. It is of fundamental importance to understand the wind-driven runback behavior of water droplets over surfaces treated with different coatings, since the corresponding knowledge would be very helpful and essential to develop more efficient anti-/de-icing systems for aircraft icing protection.
With the rapid development of surface engineering, a series of specially designed surface coatings succeed in icing mitigation using airflow to remove the remained water. While various hydro-/ice-phobic coatings/surfaces have been developed in recent years, the “state-of-the-art” icephobic coatings/surfaces can be generally divided into three categories, i.e., 1). Lotus-leaf-inspired superhydrophobic surfaces (SHS) with micro-/nano-scale surface textures to achieve very high contact angles (typically > 150°); 2). Pitcherplant-inspired slippery liquid infused porous surfaces (SLIPS) with a layer of liquid lubricant (which is immiscible with water) being sandwiched between ice and solid substrate materials; and 3). Icephobic elastic materials/surfaces with deformable structures/surfaces. SHS has a water droplet contact angle (CA) larger than 150° and a sliding angle (SA) less than 10° . SHS always has a hierarchical structure which is similar to the lotus leaf, and water droplets on SHS appear as water beads which can easily roll off the surface by wind or gravity before frozen. Another strategy to reduce ice adhesion strength to a solid surface is to use a layer of liquid lubricant, which is immiscible with water, between ice and the solid surface. The use of such lubricated surfaces was investigated as early as 1960s, and has gained increasing attentions again recently with the introduction of a concept called Slippery Liquid-Infused Porous Surfaces (SLIPS). SLIPS concept is inspired by the Nepenthes pitcher plants, which have evolved highly slippery, liquidinfused micro-textured rim to capture insects. SLIPS surfaces were not only found to be able to suppress ice/frost accretion by effectively removing condensed moisture even in high humidity conditions, but also exhibit at least an order of magnitude lower ice adhesion than most SHS coatings. More recently, elastic materials/surfaces, such as Polydimethylsiloxane or PDMS in short, which would be structurally deformed/altered dynamically upon applying extra mechanical stress, have also been suggested for icing mitigation. Elastic materials display ultra-low adhesion to ice due to their low work of adhesion and liquidlike deformability, while maintaining good mechanical durability due to their solid-like rigidity. It is found that water droplets would not only be more readily rebounding away from the surface after impingement, but also be able to roll away before frozen due to the hydrophobicity of PDMS. Considering the differences in wettabilities and mechanisms of water repellency, it is necessary to have a systematic understanding of how efficient the surfaces are when the aerodynamic force is applied to remove the adhered water droplets. In the present study, a comprehensive experimental campaign was conducted to characterize the transient runback behaviors of wind-driven water droplets over the surfaces of test plates coated with different hydro-/icephobic coatings (i.e., SHS, SLIPS and PDMS). A high-resolution Particle Image Velocimetry (PIV) system was used to achieve quantitative measurements of the velocity field of the airflow around the wind-driven water droplets on the test surfaces with different wettabilities. With the detailed PIV measurements of the airflow field around the runback water droplets and the droplet profiles, the aerodynamic forces and the adhesion forces acting on the water droplets were estimated. While Fig. 1 shows the experimental setup used in the present study, Fig. 2 to Fig. 3 given some of the typical measurement results. More measurement results and comprehensive analysis and discussions will be provided in the full version of this research paper
Ultrasound PIV Uncertainty Quantification
Get PDFUltrasound Particle image velocimetry (UPIV) is a non-invasive flow measurement technique where acousticopaque flow tracers are injected into a working fluid and ensonified to create ultrasound images. These images are processed using PIV cross-correlation based algorithms to measure the velocity field (Kim et al., 2004). UPIV is useful for opaque flows, primarily where complex flows exist, accordingly, it is used in many industrial and clinical research applications such as studying intracardiac flow (Crase et al., 2007). Furthermore, the measurement provides suitable temporal and spatial resolutions for improved diagnostic metrics. Mentioned applications and the sensitive diagnostic industrial and clinical decisions made based on these measurements intensifies the importance of characterizing the UPIV measurement accuracy and associated uncertainty. However, quantifying UPIV measurement uncertainty is non-trivial due to the complexity of possible uncertainty sources, their combination, and propagation through the measurement chain.
The formation of a particle image by ultrasound significantly differs from optical imaging, introducing unique aspects to image quality that must be considered. Particle images are formed across several ultrasound scan lines, yielding an elliptical particle image shape. Furthermore, the particle’s reflected pressure wave is converted to a digital signal that undergoes signal modulation, and this process forms a non-Gaussian point spread function (PSF) along the scan line direction. Additionally, clusters of tracers produce a single, bright image intensity and speckle image pattern. Compared to conventional PIV images, UPIV incurs significantly higher image noise due to lack of filtration for the ultrasound reflection of the non-tracer obstacles
Validation of Multi-Frame PIV Image Interrogation Algorithms in the Spectral Domain
Get PDFMulti-frame correlation algorithms for time-resolved PIV have been shown in previous studies to reduce noise and error levels in comparison with conventional two-frame correlations. However, none of these prior efforts tested the accuracy of the algorithms in spectral space. Even should a multi-frame algorithm reduce the error of vector computations summed over an entire data set, this does not imply that these improvements are observed at all frequencies. The present study examines the accuracy of velocity spectra in comparison with simultaneous hot-wire data. Results indicate that the high-frequency content of the spectrum is very sensitive to choice of the interrogation algorithm and may not return an accurate response. A top-hat-weighted sliding sum-of-correlation is contaminated by high-frequency ringing whereas Gaussian weighting is indistinguishable from a low-pass filtering effect. Some evidence suggests the pyramid correlation modestly increases bandwidth of the measurement at high frequencies. The apparent benefits of multi-frame interrogation algorithms may be limited in their ability to reveal additional spectral content of the flow
Characterisation of vortex shedding on a hydrofoil using PIV measurements
Get PDFAn experimental study of vortex shedding on a hydrofoil Eppler 817 was conducted using two-dimensional two components Particle Image Velocimetry. This foil section’s characteristics are adapted for naval applications but sparsely documented. The characterization of the flow modes was realized based on statistical data such as the mean velocity field and the standard deviation of the vertical velocities. The data were acquired at very low Reynolds number which are not often covered for such hydrofoil and at four angles of attack ranging from 2◦ to 30◦. A map of different characteristic flow modes was made for this space of parameters and was used to identify flow configurations exhibiting particular dynamics
TrackFit: Uncertainty Quantification, Optimal Filtering and Interpolation of Tracks for Time-Resolved Lagrangian Particle Tracking
Get PDFAdvanced Lagrangian Particle Tracking methods (such as the STB algorithm (Schanz et al. 2016)) are a very useful tool for uncovering properties of flow. As a measurement technique, the results of such methods are perturbed by different sources of errors and noise. This work addresses the problem of optimal filtering of particle tracks as well as estimating uncertainties of derived quantities such as location, velocity and acceleration of observed particles. The behavior and performance of this new filtering method (“TrackFit”), first introduced at Gesemann et al. (2016) is analyzed and compared to the Savitzky–Golay filter (Savitzky and Golay (1964)) which is commonly used for these purposes. The optimal choice of parameters of this filtering method as well as the uncertainty quantification of the reconstructed tracks can be extracted from a spectral analysis of the recorded raw particle tracking data. This is in contrast to a Savitzky–Golay filter where the choice of parameters might often be driven by experience and gut feeling. Estimating the power spectral density (PSD) of the particle trajectory signals for the purpose of optimal filtering parameter selection represents a challenge due to possibly short trajectory signals. In the following work we will present a method for PSD estimation that is applicable in this scenario. In addition, we show that regardless of the choice of Savitzky–Golay filter parameters, the resulting filter will not approximate the ideal noise reduction filter well unlike the “TrackFit” described in this work
Combining high-speed planar PIV and motion tracking of a flexible cylinder in cross-flow
Get PDFMost modeling studies investigating the flow dynamics in vegetation canopies are limited to rigid models as proxies for vegetation elements. However, most canopies embody some degree of structural flexibility, resulting in aeroelastic mechanisms coupling the motion of the vegetation with the surrounding flow. Studies addressing flexible canopies typically quantify either the flow or the plant motion independently, thus missing the instantaneous coupling between turbulent stresses and structural deformations. Few experiments have been devoted to measuring both quantities simultaneously. Okamoto and Nezu (2009) utilized a combined PIV-PTV technique to capture both flow and canopy motion. However, only the motion of the stem tips was captured, as opposed to the deformation of the entire stem. Py et al. (2006) employed digital image correlation (DIC) to quantify the motion of crop canopies using in-field images. However, the wind itself was not measured across the domain.
The present work presents an experimental technique that can be utilized to study the flow–structure interaction in flexible canopies, and that could be extended to other flexible and/or moving objects. High-speed PIV data of the flow surrounding an idealized canopy element, consisting of a flexible cylinder, together with the corresponding displacement field throughout the cylinder were simultaneously obtained combining fluorescent imaging and refractive index matching (RIM)
Three-dimensional density measurements of a heated jet using laser-speckle tomographic background-oriented schlieren
Get PDFThree-dimensional density field measurement techniques can be used to understand the complex heat transfer and mixing processes that occur in turbulent flows. Tomographic background-oriented schlieren (BOS) is an optical technique that can be used to measure the instantaneous three-dimensional density field in turbulent flows. Light rays propagating through the flow are deflected from their ambient path due to variations in refractive index related to the spatial density gradients. In BOS, a camera is placed looking through the flow at a reference image, which captures path-integrated information on the refractive index gradients in the form of apparent image displacements Richard and Raffel (2001). The displacements recorded simultaneously from many cameras placed around the flow form the basis of a tomographic reconstruction of the three-dimensional refractive index gradients Goldhahn and Seume (2007), from which the density field is obtained through integration of the gradients and application of the Gladstone-Dale relation
Uncertainty Quantification for PTV/LPT data and Adaptive Track Filtering
Get PDFParticle Tracking Velocimetry (PTV) or Lagrangian Particle Tracking (LPT) picked up a lot of interest over the last years due to their ability to acquire global flow fields at high spatial and temporal resolution. The most recent research focused mainly on algorithmic advancements in order to increase the obtainable data density and on its application to new flow cases. Only a small amount of studies tried to quantify the measurement uncertainties linked to these volumetric measurement approaches. Within this contribution we want to present how to acquire measurement uncertainties for the position, velocity and acceleration for each data point along a trajectory by means of linear regression analysis tools. Based on these uncertainties, an adaptive filtering approach is introduced, which eliminates the user’s choice of the filter kernel length and which automatically determines its optimal value