14th International Symposium on Particle Image Velocimetry
Welcome to the collection of final two-page abstracts and full-length papers (author's choice about which to submit) for the 14th International Symposium on Particle Image Velocimetry (ISPIV21). Particle Image Velocimetry (PIV) is an advanced optical measurement technique for non-intrusive analysis of microscopic and macroscopic flow fields in transparent fluids with high resolution. Thanks to the enormous developments in recent years in the fields of lasers, light emitting diodes (LEDs), digital cameras, computer performance, memory capacity, and processing algorithms, very precise measurements are now possible in many research areas and the field of application is being continuously expanded. Due to its performance and efficiency, PIV is also increasingly used in industry to answer various research questions. The technique can be extended by complementary techniques (e.g. laser-induced fluorescence) to simultaneously measure scalars such as concentration, pressure and temperature. At the same time, the measured 2D or 3D flow fields can be used to determine physical quantities that cannot be measured with other techniques. The measurement technology thus provides deep insights into the flow phenomena, no matter how high the flow velocities are. This biannual symposium series brings together leading PIV experts and users from all over the world to exchange and discuss the latest innovative developments and applications of the technology. The 14th edition of this symposium series was originally planned as an in-person meeting in Chicago, Illinois USA for August 1-4, 2021, following successful previous symposia in Munich (2019) and Busan (2017). However, owing to COVID-19 circumstances, it was moved to a virtual modality. In addition to these written contributions, authors also pre-recorded 15-minute presentations of their work that were shared with conference participants on demand. Finally, live keynote presentations were given by leading researchers in the PIV field: Prof. Yizheng Liu (Shanghai Jiao Tong University), Prof. Markus Raffel (German Aerospace Center, DLR), and Prof. Minami Yoda (Georgia Tech).
Copyright for all articles and abstracts is retained by their respective authors
Particle position prediction based on Lagrangian coherency for flow over a cylinder in 4D-PTV
Recent developments in time-resolved Particle Tracking Velocimetry (4D-PTV) consistently improved tracking accuracy and robustness. We propose a novel technique named ”Lagrangian coherent predictor” to estimate particle positions within the 4D-PTV algorithm. We add spatial and temporal coherency information of neighbour particles to predict a single trajectory using Lagrangian Coherent Structures (LCS). We found that even a weak signal from coherent neighbour motions improves particle prediction accuracy in complex flow regions. We applied Finite Time Lyapunov Exponent (FTLE) to quantify local boundaries (i.e. ridges) of coherent motions. Synthetic analysis of the wake behind a smooth cylinder at Reynolds number equal to 3900 showed enhanced estimation compared with the recent predictor functions employed in 4D-PTV. Results of the experimental study of the same flow configuration are reported. We compared predicted positions with the optimised final positions of Shake The Box (STB). It was found that the Lagrangian coherent predictor succeeded in estimating particle positions with minimum deviation to the optimised positions.
Copyright (c) 2021 Ali Rahimi Khojasteh, Dominique Heitz, Yin Yang
Development of Echo-LPT for the study of particle-wall interactions in dense suspensions
Examining the behaviour of dense suspensions has proven to be difficult, both experimentally and numerically. Using super water–absorbent polymer, PIV measurement was successfully conducted in a hydrogel suspension with a volume fraction (VF) of Φ =20% (see Zhang and Rival, 2018). However, due to the slightly refractive index mismatch, the image quality will degrade significantly as the particle loading of the hydrogel is increased. In order to achieve flow measurements in suspensions with high volume fractions, non-optical based techniques such as ultrasound imaging velocimetry (UIV) should be implemented. UIV has been developed for fluid dynamics applications and embraced by many researchers to study fluid flows (Gurung and Poelma, 2016; Jeronimo et al., 2019). Although, UIV provides useful information about the flow physics, it is unable to provide Lagrangian quantities such as particle trajectories, which is a key parameter to study entrainment and particle-wall interactions.
Copyright (c) 2021 Milad Samie, Kai Zhang, Mohammad Reza Najjari, David E. Rival
Spatially and temporally resolved measurements of turbulent Rayleigh-Bénard convection by Lagrangian particle tracking of long-lived helium-filled soap bubbles
We present spatially and temporally resolved velocity and acceleration measurements of turbulent RayleighBénard convection spanning the whole volume (~ 1 m³) of a cylindrical sample with aspect ratio one. With the "Shake-The-Box" (STB) Lagrangian particle tracking (LPT) algorithm, we were able to instantaneously track up to 560,000 particles, corresponding to mean inter-particle distances down to 6 - 8 Kolmogorov lengths. We used the data assimilation scheme ‘FlowFit’, which involves continuity and Navier-Stokesconstraints, to map the scattered velocity and acceleration data on cubic grids, herewith recovering the smallest flow scales. Lagrangian and Eulerian visualizations reveal the dynamics of the large-scale circulation and its interplay with small scale structures, such as thermal plumes and turbulent background fluctuations. As a result, the complex time-dependent behavior of the LSC comprising azimuthal rotations, torsional oscillation and sloshing can be extracted from the data. Further, we found more seldom dynamic events, such as spontaneous reorientations of the LSC in the data from long-term measurements.
Copyright (c) 2021 Johannes Bosbach, Daniel Schanz, Phillip Godbersen, Andreas Schröder
Robust approach to monitoring Lagrangian transport in very large volume
State-of-the-art flow measurements utilize four or more high-speed cameras to perform highly-accurate Lagrangian particle tracking (LPT) in small to medium-sized measurement volumes (Schanz et al., 2016). Hou et al. (2021) suggested a novel approach to allow measurements in significantly larger measurement volumes (O(10m3 )) while reducing the experimental effort. A single camera is used to track centimeter-sized soap bubbles in three dimensions by not only evaluating the bubble-center location but also the bubbleimage size. Possible applications of the suggested approach include - but are not limited to - measurements in industrial wind tunnels (Hou et al., 2021), full-scale measurements in the atmospheric boundary layer (Rosi et al., 2014; Toloui et al., 2014), and the characterization of airflow in indoor spaces, such as offices or classrooms (Kahler et al., 2020). In the context of the recent pandemic, the latter application could ¨help to reduce infection risk by designing appropriate air circulation. Hereby, frequent air exchange is recommended, while direct airflow from individual to individual should be avoided (WHO, 2020). The present study strives to optimize and simplify the experimental set-up as well as to characterize the accuracy of the novel single-camera approach. Figure 1(a) shows the set-up used to characterize the novel approach.
Copyright (c) 2021 Frieder Kaiser, Andreas Haramis, Joshua Galler, David E. Rival
Three-dimensional temperature and velocity measurements in fluids using thermographic phosphor tracer particles
Many flows of technical and scientific interest are intrinsically three-dimensional. Extracting slices using planar measurement techniques allows only a limited view into the flow physics and can introduce ambiguities while investigating the extent of 3D regions. Nowadays, thanks to tremendous progress in the field of volumetric velocimetry, full 3D-3C velocity information can be gathered using tomographic PIV or PTV hence eliminating many of these ambiguities (Discetti and Coletti, 2018; Westerweel et al., 2013). However, for scalar quantities like temperature, 3D measurements remain challenging. Previous approaches for coupled 3D thermometry and velocimetry combined astigmatism PTV with encapsulated europium chelates particles (Massing et al., 2018) or tomographic PIV with thermochromic liquid crystals particles (Schiepel et al., 2021). Here we present a new technique based on solid thermographic phosphor tracer particles, which have been extensively used for planar fluid temperature and velocity measurements (Abram et al., 2018) and are applicable in a wide range of temperatures. The particles are seeded into a gas flow where their 3D positions are retrieved by triangulation from multiple views and their temperatures are derived from two-colour luminescence ratio imaging. In the following, the experimental setup and key processing steps are described before a demonstration of the concept in a turbulent heated jet is shown.
Copyright (c) 2021 Moritz Stelter, Fabio J. W. A. Martins, Frank Beyrau, Benoît Fond
Large-scale 3D flow investigations around a cyclically breathing thermal manikin in a 12 m³ room using HFSB and STB
Exhalation of small aerosol droplets and their transport, dispersion and (local) accumulation in closed rooms have been identified as the main pathway for indirect or airborne respiratory virus transmission from person to person, e.g. for SARS-CoV 2 or measles (Morawska and Cao 2020). Understanding airborne transport mechanisms of viruses via small bio-aerosol particles inside closed populated rooms is an important key factor for optimizing various mitigation strategies (Morawska et al. 2020), which can play an important role for damping the infection dynamics of any future and the ongoing present pandemic scenario, which unfortunately, is still threatening due to the spreading of several SARS-CoV2 variants of concern, e.g. delta (Kupferschmidt and Wadman 2021). Therefore, a large-scale 3D Lagrangian Particle Tracking experiment using up to 3 million long lived and nearly neutrally buoyant helium-filled soap bubbles (HFSB) with a mean diameter of ~ 370 µm as passive tracers in a 12 m³ generic test room has been performed, which allows to fully resolve the Lagrangian transport properties and flow field inside the whole room around a cyclically breathing thermal manikin (Lange et al. 2012) with and without mouth-nose-masks and shields applied. Six high-resolution CMOS streaming cameras, a large array of powerful pulsed LEDs have been used and the Shake-The-Box (STB) (Schanz et al. 2016) Lagrangian particle tracking algorithm has been applied in this experimental study of internal flows in order to gain insight into the complex transient and turbulent aerosol particle transport and dispersion processes around seated breathing persons.
Copyright (c) 2021 Andreas Schröder, Daniel Schanz, Johannes Bosbach, Matteo Novara, Reinhard Geisler, Janos Agocs, Andreas Kohl
The continuous advancements of particle imaging techniques for flow field measurements have led to imaging systems and processing approaches matching the demands for 3D velocimetry at large scale (Schanz et al., 2016; Discetti and Coletti, 2018). Often, the flow past an object immersed in the fluid is of key interest, and in some cases the experimentalist exploits the velocimetry data for analysis of the near-surface flow properties such as pressure. It follows that knowledge of the object shape and position is essential. For 2D studies, the issue of identifying the fluid-solid interface often reduces to detection of the intensity gradient resulting from the light sheet striking the object. The latter task is well explored, with a variety of methods providing the object interface in the measurement plane (Canny, 1986; Malik et al., 2001; Gui et al., 2003, among others). These approaches, however, are not applicable in volumetric studies where the illumination is diffuse. A frequently applied alternative in fluid-structure-interaction studies is a dual-measurement approach, where a second measurement system tracks the object shape (e.g., Acher et al., 2019; Zhang et al., 2019) The complexity of operating two measurement systems may not be affordable however, motivating the development of 3D interface detection methods that rely solely on the flow imaging system. Particle imaging based interface detection approaches in 3D have been addressed from various perspectives, containing the detection of fluid-fluid interfaces. Examples utilizing tomographic PIV measurements include the studies of Adhikari and Longmire (2012), Im et al. (2014), and Ebi and Clemens (2016). The two latter examples identify the fluid-solid interface by discriminating a seeded phase (the fluid) from a void phase (the solid). The present work is inspired by this principle, but it assumes a discrete 3D particle distribution as obtained from a generic particle tracking algorithm such as IPR by Wieneke (2012), or “Shake-The-Box” by Schanz et al. (2016), as a foundation. Summarizing, this work aims to detect the surface of a solid object immersed in a seeded flow, solely based on the spatial distribution of flow tracers as recorded by a generic 3D PTV measurement.
Copyright (c) 2021 Constantin Jux, Fulvio Scarano, Andrea Sciacchitano
Aerodynamics of a cycling wheel in crosswind by coaxial volumetric velocimetry
The aerodynamic characteristics of a modern road cycling wheel in crosswind are studied through force measurements and 3D velocimetry in TU Delft’s Open Jet Facility. The performance of the 62 mm deep rim is evaluated for two tire profiles, and yaw angles up to 20◦ . All measurements are executed at 12.5 m/s (45 km/h) freestream- and wheel-rotational velocity. The wheel’s rim-tire section in crosswind is found to behave similar to an airfoil at incidence, ultimately resulting in a reduction of the wheel’s aerodynamic resistance with increasing yaw angle magnitude. This trend, also referred to as the sail-effect, is limited by the stall angle of the tire-rim profile. The stall angle is found to be dependent on the tire surface texture and varies between 14◦ and 20◦.
Copyright (c) 2021 Constantin Jux, Andrea Sciacchitano, Fulvio Scarano
Investigation on computed pressures from PIV, a study of how boundary definitions affect pressure accuracy along objects on the example of a cylinder flow.
This work discusses an approach to compute pressure fields from planar PIV measurement using standard CFD tools. In particular, we propose a combination of interpolation and mesh adaptation to import the PIV measurements on a grid that is morphed around objects, and is fine enough to solve the Poisson equation accurately. The whole process of meshing, interpolation and pressure computation is carried out using the popular open-source solver OpenFoam®. The method is tested and validated on a classic benchmark test case, namely, the unsteady flow past a cylinder. A 3D multiphase flow simulation is used to generate the reference data and analyze the impact of both, the PIV interrogation and the interpolation on the morphed grid. The simulation uses an Euler-Lagrangian one-way coupling approach to simulate the flow field and the dynamics of seeding particles. The analysis compares the pressure field from the 3D CFD simulation with the solution of a 2D Poisson equation based on the 2D velocity field obtained by either down-sampling the CFD data or by PIV interrogation of synthetic images built from the CFD data. Finally, we challenge the proposed method with the pressure reconstruction in a TR-PIV experiment in similar conditions.
Copyright (c) 2021 Francisco Felis-Carrasco, David Hess, Bo Beltoft Watz, Miguel Alfonso Mendez
An experimental investigation on stall flutter over a vertically mounted rigid finite wing
As stall flutter has relevant engineering implications, such as in blades of wind turbine and HALE (highaltitude long-endurance aircraft). This work presents the experimental investigation of rigid wing setup in a closed-circuit wind tunnel having 2.1 m × 1.5 m test section. The experimental campaign reached stable and symmetrical LCO within the freestream range from 9 m/s up to 14 m/s (1.69 × 105 < Re < 2.63 × 105 ). Two techniques were used for position tracking: one mechatronic and one image-based. The latter used ‘shakethe-box’ method applied to a body, which has proven a successful approach as a non-intrusive tool.
Copyright (c) 2021 Renan Francisco Soares, Ilyas Karasu, Bharath Ganapathisubramani
Particle Image Velocimetry Measurements of a Dry Powder Inhaler Flow
Inhalation therapy for respiratory disorders is being increasingly delivered via dry powder inhalers (DPIs), which are breath-actuated devices that deliver pharmaceutical drug particles to the lungs. The motion of inhalation air, produced when a patient inhales through this device, supplies all energy for the entrainment, de-agglomeration, and dispersion of powder drug agglomerates into a fine drug particle aerosol. The aerosol performance is directly related to the fluid-mechanics of a given DPI device. These flow mechanisms are complex as they depend on the device design, inhalation flow rate, and the properties of the dry powder formulation used. Among these, the role of device design is crucial as it significantly affects not only the generation and properties of delivered aerosol, but also the capability of targeted regional drug deposition.
Copyright (c) 2021 14th International Symposium on Particle Image Velocimetry
Main results of the first Data Assimilation Challenge
This work presents the main results of the first Data Assimilation (DA) 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 was jointly organised by the research groups of DLR, ONERA and TU Delft. The same synthetic test case as in the Lagrangian Particle Tracking (LPT) challenge (also presented in this symposium) was considered, reproducing the flow in the wake of a cylinder in proximity of a flat wall. The participants were provided with three datasets containing the measured particles locations and their trajectories identification numbers, at increasing tracers concentrations from 0.04 to 1.4 particles/mm3 . The requested outputs were the three components of the velocity, the nine components of the velocity gradient and the static pressure, defined on a Cartesian grid at one specific time instant. The results were analysed in terms of errors of the output quantities and their distributions. Additionally, the performances of the different DA algorithms were compared with that of a standard linear interpolation approach. Although the velocity errors were found to be in the same range as those of the linear interpolation algorithm, typically between 3% and 12% of the bulk velocity, the use of the DA algorithms enabled an increase of the measurement spatial resolution by a factor between 3 and 4. The errors of the velocity gradient were of the order of 10-15% of the peak vorticity magnitude. Accurate pressure reconstruction was achieved in the flow field, whereas the evaluation of the surface pressure revealed more challenging.
Main results of the first Lagrangian Particle Tracking Challenge
This 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.
PIV and deformation measurements on the rotor blade of a rotating, scaled model wind turbine with flexible blades under tailored inflow conditions
Wind turbines face harsh inflow conditions when operating in the atmospheric boundary layer or in the wake of other wind turbines. The incoming velocity field can change within seconds due to the turbulent structures it contains, resulting in a rapid change of several degrees in the angle of attack for the rotating blade. Aerodynamics are hence rapidly altered, leading to changes of the occurring forces on the rotor. Such dynamic forces cause the blades to twist and bend, accelerating fatigue and reducing the lifetime of a turbine Spinato et al. (2009).
Peregrine falcon wakes examined using Volumetric PIV
This study presents time-resolved volumetric measurements in the wake of a peregrine falcon model. The experiments were performed in a water flume with a freestream velocity of 10 cm/s and at an angle of 3.25°. The TSI volumetric PIV system, using Insight V3V-4G software, was used to capture the time-resolved volumetric flow field. The results compare well with previous Stereo PIV measurements; however, the present results also provide true 3-dimensional flow field information which helps decode the reason for the superior maneuverability. This is attributable to the vortex dominated flow field promoted by its morphology.
Physics-based universal outlier detector for flow statistics
Outlier detection for PIV velocity fields is still nowadays an active field of research. In the last decades, several image pre-processing and processing algorithms have been developed aiming at increasing the dynamic velocity range of PIV measurements and reducing the measurement uncertainty. Nevertheless, PIV velocity fields are still often characterised by the presence of outliers, which potentially hamper the correct interpretation of the flow physics and negatively affect the evaluation of the flow statistics. The outlier detection strategies presented in literature are mainly based on the statistical analysis of the velocity vector with its immediate neighbour. Most of these algorithms have been demonstrated to be effective for instantaneous flow fields, where the errors associated with the outliers are order of magnitude larger than the expected measurement uncertainty. However, these approaches are not as effective for the flow statistics, where the outliers yield errors of the same order of the measurement uncertainty. To overcome this limitation, this paper proposed an outlier detection approach based on the agreement of the flow statistics to the constitutive equations, more specifically to the turbulent kinetic energy (TKE) transport equation. The focus is posed on the ratio between the local advection terms of TKE and a robust estimation of the TKE production along the local streamline. It is demonstrated that, in presence of outliers, the proposed principle yields a clear separation between the correct and the erroneous vectors. In order to assess the performance of the proposed principle, three different test cases are considered. For all of them, the results are compared with a reference outlier detection methodology, namely the universal outlier detection method proposed by Westerweel and Scarano (2005). The proposed turbulence transport-based approach exhibits higher performance in terms of percentage of outliers correctly identified in the flow statistics.
A novel volumetric velocity measurement method for small seeding tracers in large volumes
This paper presents the volumetric velocity measurement method of small seeding tracer with diameter 5µm ∼ 100µm for volumes of ≥ 500cm3. The size of seeding tracer is between helium-filled soap bubbles (HFSB) and di-ethyl-hexyl-sebacic acid ester(DEHS) droplets. The targeted measurement volume dimension is equivalent to the volume of HFSB, which will give a higher resolution of turbulence study. The relations between particle size, imaging and light intensity are formulated. The estimation of the imaging results is computed for the setup design. Finally, the methodology is demonstrated for turbulence velocity measurements in the jet flow, in which the velocities of averaged diameter 15µm air filled soap bubbles are measured in a volume of 7200cm3.
Velocity measurements of dilute suspensions over and through various porous media models
This study is focused on the motion of a dilute suspension containing rigid, spherical, non-Brownian, noncolloidal particles flowing over and through porous media models. The flow is confined to very low Reynolds numbers. To examine the velocity distribution particle image velocimetry (PIV) was applied in conjunction with refractive index matching (RIM) techniques. This study is the first of its kind analyzing the interaction between two common engineering systems: suspension fluid and porous media.
Lagrangian Strain- and Rotation-Rate Tensor Evaluation Based on Multi-pulse Particle Tracking Velocimetry (MPTV) and Radial Basis Functions(RBFs)
Physical conservation laws are inherently Lagrangian. However, analyses in fluid mechanics using the Lagrangian framework are often forgone in favor of those using the Eulerian framework. This is perhaps due to a lack of experimental techniques with high temporal and spatial resolution that track the movement of fluid tracers in a flow domain. The development of time-resolved Particle Tracking Velocimetry/Accelerometry (TR-PTV/A) that measures flows with high seeding density has made the use of the Lagrangian framework more accessible. A challenge facing PTV/A is the need for robust mesh-free numerical schemes that handle random particle locations. Such a scheme can be created with high-order accuracy using Radial Basis Functions (RBFs). RBFs allow direct evaluation of derivatives of vector and scalar fields at random locations with infinite-order smoothness. The current work uses RBF-based differential schemes to develop a post-processing tool for PTV/A data, which can accurately evaluate spatial derivatives directly from Lagrangian particle tracks. This RBF-based strain/rotation-rate tensor evaluation tool is validated with two and three-dimensional flows from analytical solutions and is then tested with experimental data measured by a multi-pulse PTV/A system.
Error propagation dynamics of velocimetry-based pressure field calculations (2): on the error profile
This work investigates the propagation of error in a Velocimetry-based Pressure field reconstruction (VPressure) problem to determine and explain the effects of error profile of the data on the error propagation. The results discussed are an extension to those found in Pan et al. (2016). We first show how to determine the upper bound of the error in the pressure field, and that this worst scenario for error in the data field is unique and depends on the characteristics of the domain. We then show that the error propagation for a V-Pressure problem is analogous to elastic deformation in, for example, a Euler-Bernoulli beam or Kirchhoff-Love plate for one- and two-dimensional problems, respectively. Finally, we discuss the difference in error propagation near Dirichlet and Neumann boundary conditions, and explain the behavior using Green’s function and the solid mechanics analogy. The methods discussed in this paper will benefit the community in two ways: i) to give experimentalists intuitive and quantitative insights to design tests that minimize error propagation for a V-pressure problem, and ii) to create tests with significant error propagation for the benchmarking of V-Pressure solvers or algorithms. This paper is intended as a summary of recent research conducted by the authors, whereas the full work has been recently published (Faiella et al., 2021).
An experimental approach to analyze aerosol and splatter formation in a dental practice
The flow velocity, trajectories, and size distribution of droplets produced during a dental scaling procedure using a Cavitron ultrasonic scalar (CUS) has been investigated by optical flow tracking velocimetry and shadowgraphy measurements. The droplet sizes are found to vary from 5 -500 µm; these correspond to droplet nuclei that could carry viruses. The droplet velocities also vary between 0.7 m/s and 1.3 m/s. These observations confirm the critical role of aerosols in the transmission of disease during dental procedures, providing invaluable knowledge for developing protocols and procedures to ensure the safety of both dentists and patients especially during COVID-19 pandemic.
Quantification of Brownian motion under presence of flow using particle diffusometry
Particle diffusometry (PD), a quantification method for the Brownian motion, is performed by recording temporally sequential images and using correlation analysis to obtain an ensemble diffusion coefficient for all particles captured in the imaging region (Clayton et al., 2017). PD is proven to be successful in the detection of the waterborne pathogen V. cholerae in environmental samples using different imaging techniques, including an inverted fluorescence microscope as well as a handheld hardware device operated with a smartphone (Clayton et al., 2019; Moehling et al., 2020). Although we intend to use PD to calculate diffusion coefficients in quiescent fluid, oftentimes unintentional fluid flows occur, creating measurement error when calculating the diffusion coefficient. In previous work, recordings under the presence of flow were discarded to avoid incorrect measurements of the sample.
Lagrangian Particle Tracking: a link between localization error and fraction of missed particles
This paper aims at analysing the behaviour of particle localisation error in 3D Lagrangian Particle Tracking (LPT) techniques, with a particular emphasis on general properties, independent of a specific algorithm. Based on the hypothesis that in LPT algorithms, errors on the image formation models are solely due to random noise, we show/prove the existence of a best achievable root mean square error (RMSE) on particle localisation, that, for a setup at a given seeding density, depends only on the noise level. We provide a procedure to estimate this lower bound, and show that it can only be reached if there are no missed detections; further on, we establish a link between localisation error and fraction of missed particles. We illustrate the consistency of this model on the results of the recent First Challenge on LPT (see ISPIV21 papers by Leclaire et al. and Sciacchitano et al.)
Numerical Uncertainty in Density Estimation for Background Oriented Schlieren
Background Oriented Schlieren (BOS) is an image-based density measurement technique. BOS estimates the density gradient from the apparent distortion of a target pattern viewed through a medium with varying density using cross-correlation, tracking, or optical flow algorithms. The density gradient can then be numerically integrated to yield a spatially resolved estimate of the density [1]. A method was recently proposed to estimate the a-posteriori instantaneous and spatially resolved density uncertainty for BOS [2] and showed good agreement between the propagated uncertainties and the random error. However, the density uncertainty quantification method could not account for the systematic uncertainty in the density field due to the discretization errors introduced during the numerical integration, which could be much larger than the displacement random errors [2]. In this work, we propose a method to estimate the numerical uncertainty introduced by the density integration in BOS measurements, using a Richardson extrapolation framework. A procedure is also introduced to combine this systematic uncertainty with the random uncertainty from the previous work to provide an instantaneous, spatially-resolved total uncertainty on the density estimates. The method will be tested with synthetic fields and synthetic BOS images.
PIV measurements of entrainment process of directly injected media in internal combustion engines
PIV 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 it requires 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 PCC gas 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.
Combustion, Convection and Heat Transfer
Development of micro soap bubble generator for PIV tracer using home stereolithography 3D printer
A micro soap bubble generator for tracers for PIV measurement was developed using a home stereolithography 3D printer. The nozzle has a coaxial triple pipe structure, and an orifice cap is attached to the nozzle head. The inner diameter of the central pipe is 0.7 mm, and the wall thickness of the central pipe is 0.7 mm. From the comparison of the smoke wire visualization result of the flow around the cylinder placed under the mainstream flow velocity of 3 m/s and the PIV measurement result, it was confirmed that the generated micro soap bubbles have good followability to the flow. Generated bubbles’ particle size was estimated to be Φ0.2 mm at the minimum and Φ6.3 mm at the maximum. The most common was Φ0.9 mm ± 0.1 mm, accounting for more than 50% of the total.
Particle Detection by means of Machine Learning in Defocusing PTV
The accurate measurement of a fluid flow inside a measurement volume (MV) with limited optical access poses a challenge since the view on the MV is often partially obstructed for all but one viewing angle. Defocusing particle tracking velocimetry (DPTV) can be used to determine the instantaneous threedimensional velocity field of the flow with a standard PIV setup, requiring only a single optical axis. Current detection algorithms reach an out-of-plane accuracy in an order of magnitude lower than the planar accuracy, on top of a low rate of detected particles in comparison to other PTV approaches. These drawbacks originate from the low image quality due to noise, fluctuations in illumination, reflections and overlapping particle images. It has been shown that Machine Learning (ML) based detection is more robust against these adverse effects, due to the ability to leverage a higher amount of optical features for detection than conventional algorithms (Lecun et al. (1998)). Therefore, the present work addresses the applicability of ML algorithms in the post-processing of DPTV experiments, which will be evaluated on the ground of the DPTV experiments conducted by Leister and Kriegseis (2019). The setup of these experiments can be seen in Figure 1(a) and a section of a raw image recorded during the experiments in Figure 1(b).
Defocusing Particle Tracking Velocimetry
Noise canceling to compute second order statistic from SPIV
Stereoscopic PIV (SPIV) is performed near the wall in a turbulent boundary layer at high Reynolds numbers (Reτ = 2272, 3840) in the streamwise-wallnormal plane. A novel method for denoising the statistics is proposed by the use to two independent SPIV systems to capture the same field of view, with the objective being that the random noise associated with the velocity fluctuations are not correlated between two independent PIV systems. The derivatives in the third (spanwise) direction are obtained by axisymmetry assumptions [George and Hussein (1991)] and continuity equation. The statistics are in agreement with that of DNS at comparable Reynolds number, from y + = 25 for lower Reτ experiment and from y + = 40 for higher Reτ experiment.
Pressure reconstruction of a planar turbulent flow field within a multiply-connected domain with arbitrary boundary shapes
Over the past two decades, it has been demonstrated that the instantaneous spatial pressure distribution in a turbulent flow field can be reconstructed from the pressure gradient field non-intrusively measured by Particle Image Velocimetry (PIV). Representative pressure reconstruction methods include the omnidirectional integration (Liu and Katz, 2006; Liu et al., 2016; Liu and Moreto, 2020), the Poisson equation approach (Violato et al., 2011; De Kat and Van Oudheusden, 2012), the least-square method (Jeon et al., 2015), and most recently, the adjoint-based sequential data assimilation method, which also essentially utilizes the Poisson equation to reconstruct the pressure(He et al., 2020). Most of these previous pressure reconstruction examples, however, were applied to simply-connected domains (Gluzman et al., 2017) only. None of these previous studies have discussed how to apply the pressure reconstruction procedures to a multiply-connected domain (Gluzman et al., 2017). To fill in this gap, this paper presents a detailed report for the first time documenting the implementation procedures and validation results for pressure reconstruction of a planar turbulent flow field within a multiply-connected domain that has arbitrary inner and outer boundary shapes. The pressure reconstruction algorithm used in the current study is the rotating parallelray omni-directional integration algorithm, which, as demonstrated in reference (Liu and Moreto, 2020) based on simply-connected flow domains, offers high-level of accuracy in the reconstructed pressure. While preserving the nature and advantage of the parallel ray omni-directional pressure reconstruction at places with flow data, the new implementation of the algorithm is capable of processing an arbitrary number of inner void areas with arbitrary boundary shapes. Validation of the multiply-connected domain pressure reconstruction code is conducted using the DNS (Direct Numerical Simulation) isotropic turbulence field available at the Johns Hopkins Turbulence Databases, with 1000 statistically independent pressure gradient field realizations embedded with random noise used to gauge the code performance. For further validation, the code is also applied for pressure reconstruction from the DNS pressure gradient in the ambient flow field of a shock-induced non-spherical bubble collapse in water (Johnsen and Colonius, 2009). The successful implementation of the parallel ray pressure reconstruction method to multiply-connected domains paves the way for a variety of important applications including, for example, experimental characterization of pressure field changes during the process of cavitation bubble inception, growth and collapse, non-intrusive unsteady aerodynamic force assessment for an arbitrary body shape immersed in flows, and multi-phase flow investigations, etc. In particular, as an immediate follow-up effort, the parallel ray pressure code will be used for the instantaneous pressure distribution reconstruction of the turbulent flow surrounding cavitation inception bubbles occurring on top of a cavity trailing corner based on high-speed PIV measurements.
Investigation of the shear-layer instabilities in supersonic impinging jets using dual-time velocity measurements
Motivated 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.