Bulletin of the American Physical Society
77th Annual Meeting of the Division of Fluid Dynamics
Sunday–Tuesday, November 24–26, 2024; Salt Lake City, Utah
Session L23: Quantitative Flow Visualization I: PIV, PTV, PLIF |
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Chair: Peter Manovski, Defence Science and Technology Group Room: 251 A |
Monday, November 25, 2024 8:00AM - 8:13AM |
L23.00001: Single-camera 3D Lagrangian particle tracking in a microfluidic channel Charles Fort, Philippe M Bardet 'Shake-The-Box' (STB) is a widely used Lagrangian tracking method for reconstructing and tracking time-resolved particle fields in 3D. Traditionally, this requires multiple cameras from different angles, which can be costly and complex to align, especially in space-constrained setups. By employing Fourier light-field microscopy (FIMic), a form of single-camera plenoptic imaging, high-resolution 3D flow measurements are achieved with just one high-speed camera, eliminating the need for multiple imagers. This method offers a resolution of approximately 2 μm in 3D, with lateral and depth resolutions within 25% of each other, a first for 3D velocimeters. Particle positions can be resolved to less than the imaging wavelength. The method's effectiveness is demonstrated through flow analysis in a microfluidic device with a cross-junction channel. This technique will not only enhance microfluidic device design and performance understanding but also, due to its high spatial resolution, has the potential to probe the smallest scales of wall-bounded turbulent flows at high Reynolds numbers. |
Monday, November 25, 2024 8:13AM - 8:26AM |
L23.00002: Gypsum Slurry Flow during Deposition on the Belt under a Roller YONG IL KIM, Caesar Sanchez, David Podstawski, Alexander L. Yarin
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Monday, November 25, 2024 8:26AM - 8:39AM |
L23.00003: ABSTRACT WITHDRAWN
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Monday, November 25, 2024 8:39AM - 8:52AM |
L23.00004: A Physics-Informed and Uncertainty-Informed Radial Basis Function Meshless Proper Orthogonal Decomposition for 3D Particle Tracking Velocimetry (PTV) Abhishek Singh, Pranjal Anand, Hyeondong Yang, Brett A. Meyers, Pavlos P. Vlachos 3D Particle Track Velocimetry offers superior spatial resolution compared to window-based PIV by resolving flow for each tracked particle. However, experimental limitations such as inappropriate particle density and non-uniform illumination can result in incorrect or noisy particle tracks. Additionally, to visualize and evaluate flow quantities, it is essential to interpolate the velocities from unstructured tracks to a regular grid. We propose a Radial Basis Function (RBF) approach utilizing meshless Proper Orthogonal Decomposition (POD) for denoising and interpolating the particle tracks onto a structured grid. Denoising is achieved by rejecting modes with insignificant contributions to the physical flow variance via Student’s t-test. The interpolation is then performed based on the spatial structures of the significant POD modes, guided by the Nyquist frequency. These sparse tracks define the RBFs, whose scaling is determined using velocity and acceleration uncertainty-weighted Least Squares. Mass and momentum conservation are incorporated by enforcing divergence-free and vorticity conservation. Gradient operators up to the third order are computed analytically from infinitely differentiable RBFs. In contrast, traditional polynomial interpolants lose curvature and accuracy beyond the second-order differentiation. We compare our results with standard interpolation methods by evaluating the quality of virtual particle advection and Finite Lyapunov Exponents on Shake-the-Box datasets. |
Monday, November 25, 2024 8:52AM - 9:05AM |
L23.00005: Biodegradable Tracer Particles for Underwater Particle Image Velocimetry Yunxing Su, Nicole W Xu Particle Image Velocimetry (PIV) is an important tool for accurately measuring and visualizing fluid flow dynamics in various scientific and engineering fields. However, current commercial PIV particles (e.g., polymer and metal-coated microspheres) are typically not made with environmentally friendly materials and potentially pose longer term health risks for live animal experiments. As an alternative for PIV, we propose the use of biodegradable particles, which are nontoxic, more sustainable, readily accessible, and cost-effective. We tested a variety of food-grade and cosmetic-grade additives to identify suitable particles for PIV experiments in both fresh and saltwater (35 ppt). These particles closely match the density of water, with particle sizes ranging from 5 µm to 50 µm for applications of different scales. To test their feasibility and effectiveness, we conducted PIV experiments using both biodegradable options and commercial PIV particles (as a control) across different length scales, including a translating hydrofoil (2.5 cm) in freshwater, and swimming jellyfish (~10 cm) and brine shrimp (~ 5 mm) in saltwater. Compared to commercial PIV particles, our biodegradable particles not only demonstrated comparable laser scattering properties, but also accurately followed fluid velocities in various flow patterns (e.g., vortical flow, shear flow, etc.) with a low particle Stokes number (10-6 - 10-4), confirming their suitability for PIV applications. These particles’ biodegradability and minimal environmental impact make them a practical and effective choice for biological applications. |
Monday, November 25, 2024 9:05AM - 9:18AM |
L23.00006: Deep Learning-Based End-to-End Velocity Field Reconstruction for the Flow Field Around Two Cylinders Li Wei, Xiaoxian Guo Particle image velocimetry (PIV) is a widely used technique for flow field measurements, but its high equipment costs and limited algorithms restrict its broader application. We propose a deep learning-based end-to-end PIV velocity field reconstruction method. This method uses particle images captured with a standard camera and low-power continuous laser as input and outputs velocity fields. It is significantly less costly and complex than a full PIV setup. The training set is derived from experimental results, with numerical simulations aligning particle images with ground truth velocity fields. The flow around a single cylinder at subcritical Reynolds numbers was first investigated. The proposed method demonstrated superior resolution, accuracy, and efficiency compared to conventional cross-correlation method. Transfer learning was then applied to the flow around tandem cylinders, where the model showed great generalization capability. The model was also capable of reconstructing velocity fields in missing regions of the flow field and recovering clear flow structures. These findings indicate the potential of deep learning in enhancing PIV experimental techniques. |
Monday, November 25, 2024 9:18AM - 9:31AM |
L23.00007: Enhanced-resolution of flow kinematics from volumetric PTV measurements Yang Zhang, Michael Fenelon, Louis N Cattafesta Volumetric, 3D particle tracking velocimetry (PTV) is a nonintrusive technique for flow field measurements. Our previous study (Michael Fenelon, et al. 2023) developed a kinematic decomposition method on the unstructured Lagrangian data obtained from volumetric, 3D PTV using a 4-pulse system version. That method discretizes the domain using Delaunay triangulation, generating triangular and tetrahedral elements for the two and three-dimensional cases, respectively. In the current study, we demonstrate a different approach for the kinematic decomposition, using a specified number of nearest neighboring particles to form unstructured elements. The significant difference between the current approach and Delaunay triangulation is the overlapping of the elements. In numerical simulations, meshed elements are distinct and do not intersect with neighboring ones. In the new method, neighboring elements are permitted to intersect to enhance the resolution of the kinematic decomposition method. Unlike the Delaunay triangulation, the current method leverages connectivity between nearest neighbors to make the elements smaller than the Delaunay elements. As a result, the overlapped element increases the spatial resolution. We also evaluate the uncertainty associated with the current method and compare it with those using the Delaunay method. |
Monday, November 25, 2024 9:31AM - 9:44AM |
L23.00008: BOS for Internal Flows: Part 1 - Challenges for Density Gradient Measurements Jonathan C Roos, Alexander G Mychkovsky, James Wiswall, Nazmus Sakib, Barton L Smith The Background Oriented Schlieren (BOS) method can be used to experimentally characterize optical density (OD) fields. The line-of-sight (LOS) integrated OD gradient field is measured from the displacement vectors of a reference background pattern. The LOS integrated OD field is then computed by solving a Poisson equation. This method is readily applied to open flows, where the image displacement vectors are solely caused by density gradients in the flow, and quiescent boundary conditions are practical. For internal flows, viewing windows complicate the relationship between the image displacement field and the fluid gradient field and other bounding surfaces have unique boundary conditions. In this work, we discuss the challenges associated with the former by modeling and testing the impact of both “front” and “rear” viewing windows. |
Monday, November 25, 2024 9:44AM - 9:57AM |
L23.00009: BOS for Internal Flows: Part 2 - Challenges for Boundary Conditions Nazmus Sakib, Jonathan C Roos, James Wiswall, Alexander G Mychkovsky, Barton L Smith The Background Oriented Schlieren (BOS) method can be used to experimentally characterize optical density (OD) fields. The line-of-sight (LOS) integrated OD gradient field is measured determining the displacement vectors of a reference background pattern. The LOS integrated OD field is then computed by solving a Poisson equation. This method is readily applied to open flows, where the image displacement vectors are solely caused by density gradients in the flow, and quiescent boundary conditions are practical. For internal flows, viewing windows complicate the relationship between the image displacement field and the fluid gradient field and other bounding surfaces have unique boundary conditions. In this work, we discuss the challenges associated with the latter by using an analytical Green’s function approach. |
Monday, November 25, 2024 9:57AM - 10:10AM |
L23.00010: Scale-Resolving Neural Data Assimilation for Lagrangian Particle Tracking Ke Zhou, Samuel J Grauer Lagrangian particle tracking (LPT) is a powerful tool for measuring 3D turbulent velocity fields by tracking a dense set of particles trajectories in the flow, a.k.a. tracks. These tracks are scattered in space, and data assimilation (DA) algorithms are often used to reconstruct the flow (“fill in the gaps”) by combining the tracks with the governing equations. This task is complicated by large gaps between particles, localization and tracking errors, and inertial transport effects. To address these problems, we developed Neural-Implicit Particle Advection (NIPA): a novel LPT DA algorithm that simultaneously reconstructs flow states, corrects particle tracks, and accounts for particle dynamics to handle inertia. We assess NIPA and adaptive Gaussian windowing (an interpolation method) using experimental and synthetic LPT measurements of homogeneous isotropic turbulence and turbulent boundary layers. Various inter-particle distances, tracking error magnitudes, and particle Stokes numbers are tested. Kinetic energy, pressure, and velocity error spectra of the reconstructions are analyzed. Trends in reconstruction accuracy are presented relative to the particle-Nyquist frequency to elucidate the action of the DA algorithm. We comment on the performance limits of NIPA and speculate about the limits of DA for turbulent flow reconstruction using LPT data, in general. |
Monday, November 25, 2024 10:10AM - 10:23AM |
L23.00011: Optimization of Optical Filters for Ratiometric Laser Induced Fluorescence Thermometry using a Standard Color Camera David A Olson, Manoochehr M Koochesfahani This work is motivated by the development of Quantum Dot Thermometry, a ratiometric Laser Induced Fluorescence (LIF) based technique using nanocrystal quantum dots that are modified to disperse into the working fluid (Perfluoropentane) of the NASA ZBOT (Zero-Boil-Off Tank) experiment. The constraints associated with the experimentalimplementation on the ISS (International Space Station) present multiple challenges in translating the technique from the lab to the ISS experiment. One challenge is the requirement to utilize an off-the-shelf color camera with a standard Bayer color filter array. In this talk, we will discuss the optimization of the imaging filters based on the color response curves of the camera and the measured emission spectra of the quantum dots. We will demonstrate the use of the filter and show its impact on the temperature sensitivity while discussing the trade-offs in its deployment. |
Monday, November 25, 2024 10:23AM - 10:36AM |
L23.00012: Local flow characterization depending on a wire angular position of the wire-wrapped rod bundle Ilhoon Jang, Chaehyuk Im, Kyongwon Seo, Jee-Hyun Cho, Simon Song Sodium-cooled fast reactors (SFRs) represent a class of fourth-generation nuclear reactor technologies that utilize sodium as a coolant. The wire-wrapped fuel rod bundle constitutes a significant innovation in SFR design, facilitating enhanced thermal dissipation from the reactor core to its periphery, thereby markedly improving cooling efficiency. Detailed comprehension of local flow dynamics within these bundles is essential for optimizing heat transfer and ensuring the reactor's operational safety. In this study, we focused on the local flow characteristics within a 37-pin wire-wrapped rod bundle, employing three-dimensional, three-component (3D 3C) velocity fields derived from magnetic resonance velocimetry (MRV) measurements. We revealed a cyclic vortex evolution pattern in the wake region, characterized by vortices forming, growing, weakening, and dissipating at 60° intervals relative to the wire's angular position. Furthermore, we identified the periodic nature of flow split factor variations, elucidating their dependency on wire orientation within interior subchannels and the dominant influence of edge swirling in edge subchannels. Our quantitatively derived experimental findings offer critical insights into the flow patterns within the rod bundle, providing essential information for the optimization of reactor design and performance analysis. |
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