Bulletin of the American Physical Society
75th Annual Meeting of the Division of Fluid Dynamics
Volume 67, Number 19
Sunday–Tuesday, November 20–22, 2022; Indiana Convention Center, Indianapolis, Indiana.
Session G15: Experimental Techniques: Schlieren |
Hide Abstracts |
Chair: Chitrarth Prasad, The Ohio State Unversity; Steven Ceccio, University of Michigan Room: 142 |
Sunday, November 20, 2022 3:00PM - 3:13PM |
G15.00001: Monitoring heterogeneity and diffusive processes in therapeutic samples using schlieren Andres Barrio Zhang, Rishabh V More, Sadegh Dabiri, Arezoo M Ardekani Heterogeniety in therapeutic samples can result in an overall reduction in quality. We present a simple and portable all-lens Schlieren setup to detect, visualize, and quantify heterogeneities in therapeutic solutions during and after thawing in real-time. The local concentration gradients in a thawing sample lead to light intensity variations which are captured using the Schlieren technique. The sample heterogeneity can be quantified by relating these light intensity variations to concentration gradients. To this end, we first measure the refractive index of the sample solutions, which varies linearly with the sample concentration. This linear relation is then used to extract the concentration gradient field from the light intensity data. We illustrate the capabilities of the proposed method by visualizing and quantifying heterogeneities during the thawing of different protein solutions. We establish the validity of the proposed approach by demonstrating its accuracy in measuring the diffusion coefficient of a diffusing interface. |
Sunday, November 20, 2022 3:13PM - 3:26PM |
G15.00002: Reconstructing Experimental Measurements of Supersonic Flow via Physics-Informed BOS Joseph P. Molnar, Samuel J Grauer We report a new workflow for background-oriented schlieren (BOS) to extract density, velocity, and pressure fields from reference and distorted images. Our method uses a physics-informed neural network (PINN) to represent a high-speed flow, for which we specify a physics loss based on the Euler and irrotationality equations. In BOS, images of a background pattern are processed using computer vision and tomography algorithms to determine the density field. Crucially, BOS features a series of ill-posed problems that require supplemental information. Current workflows interpolate the images or add a penalty term to promote globally- or piecewise-smooth solutions. However, these algorithms are incompatible with the flow physics, leading to reconstruction artifacts. Physics-informed BOS directly reconstructs all the flow fields using a PINN that includes the measurement model and governing equations. This improves the accuracy of density estimates and also yields (previously unavailable) velocity and pressure data. We demonstrate our approach with synthetic and experimental data. Reconstructions produced by physics-informed BOS are significantly more accurate than conventional estimates, and this work is the first use of a PINN to reconstruct a supersonic flow from experimental data. |
Sunday, November 20, 2022 3:26PM - 3:39PM |
G15.00003: Dynamic density modes of high-speed cavity flow from low sampling rate Schlieren YANG ZHANG, Louis N Cattafesta, Lawrence Ukeiley, Kunihiko Taira Open cavity flows are associated with strong tonal and broadband velocity and pressure field fluctuations. To study the dynamics of high-speed cavity flows, time-resolved measurements are generally required. In our past study, we developed a method called 'spectral analysis modal method (SAMM)' (DOI: 10.1007/s00348-020-03057-8) to extract the dynamically coherent structures using synchronized non-time-resolved (NTR) PIV and time-resolved (TR) pressure measurements. The NTR method yields the uncovers the SPOD modes from TR PIV. In the current study to investigate the compressibility effects of cavity flows at Mach 0.6, NTR Schlieren was similarly synchronized with TR surface pressure measurements in the cavity. The Schlieren images were converted into the vertical density gradient field using a knife edge cut-off calibration and the Gladstone-Dale relationship. The density field is then computed by integrating in the vertical direction from the top of the domain. Applying SAMM to snapshots of the density fields and pressure data from the three Kulite sensors, the density modes at the first four Rossiter frequencies are obtained. These modes show both downstream traveling waves and upstream propagating pressure waves identifying the feedback mechanism of the classic cavity flow. |
Sunday, November 20, 2022 3:39PM - 3:52PM |
G15.00004: Uncovering Hidden Features from High-speed Schlieren Images Chitrarth Prasad, Datta Gaitonde Schlieren imaging is a widely used flow visualization technique that has seen rapid improvements in spatio-temporal resolution and fidelity in recent years. Schlieren data is often used with data-driven approaches such as Spectral Proper Orthogonal Decomposition (SPOD) to extract frequency-specific coherent structures in the flow. This investigation presents a sifting procedure based on Momentum Potential Theory (MPT) that substantially improves results from the subsequent application of data-driven approaches, with a focus on the hidden irrotational signature of the turbulent flow structures. The key step involves the extraction of an irrotational scalar potential, which is exact even in the presence of large fluctuations and non-linearities. When the resulting sifted data are combined with SPOD, the MPT-filtered schlieren images offer superior insights that are not evident in raw schlieren data. Two examples illustrate the unique strengths of the approach. First, when applied to a screeching twin rectangular jet configuration, the resulting SPOD modes independently capture the flapping screech mode and the symmetric super-directive noise radiation. For a transitioning hypersonic boundary layer, the MPT-filtered SPOD modes capture the acoustic and thermal characteristics associated with second-mode transition. The method is free of geometrical constraints and problem-dependent parameters and has the potential to greatly enhance the use of high-speed diagnostics with feedback control implications. |
Follow Us |
Engage
Become an APS Member |
My APS
Renew Membership |
Information for |
About APSThe American Physical Society (APS) is a non-profit membership organization working to advance the knowledge of physics. |
© 2024 American Physical Society
| All rights reserved | Terms of Use
| Contact Us
Headquarters
1 Physics Ellipse, College Park, MD 20740-3844
(301) 209-3200
Editorial Office
100 Motor Pkwy, Suite 110, Hauppauge, NY 11788
(631) 591-4000
Office of Public Affairs
529 14th St NW, Suite 1050, Washington, D.C. 20045-2001
(202) 662-8700