Bulletin of the American Physical Society
APS March Meeting 2023
Volume 68, Number 3
Las Vegas, Nevada (March 5-10)
Virtual (March 20-22); Time Zone: Pacific Time
Session S18: Fluids X |
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Sponsoring Units: DFD Chair: Mostafa Atalla, TU Delft Room: Room 210 |
Thursday, March 9, 2023 8:00AM - 8:12AM |
S18.00001: Convective transport and absorption of drug solute in soft skin tissue Dingding Han, Ziyang Huang, Ehsan Rahimi, Hector Gomez, Arezoo M Ardekani The subcutaneous (SC) injection is widely used for drug delivery of biotherapeutics, especially for self-administration. Interstitial fluid pressure (IFP) plays a key role in regulating the fluid flow and mass transport in the SC tissue. In this paper, an approximate continuum poroelasticity model is developed to simulate the pressure evolution in the soft porous tissue during a SC injection. This poroelastic model mimics the deformation of the tissue by introducing the time variation of the IFP. The advantage of this method lies in its time efficiency and simplicity, and it can accurately model the relaxation of pressure. The interstitial fluid pressure obtained using the proposed model is validated against both the analytical and the numerical solutions of poroelastic tissue model. The pressure build-up in the proposed poroelastic medium is investigated for a wide range of elasticity and permeability during and after the injection. The decreasing elasticity elongates the relaxation time of pressure, and the sensitivity of pressure relaxation to elasticity decreases with the increasing hydraulic permeability. The increasing porosity and permeability due to deformation alleviates the high pressure and reduces the deformation during the injection. By implementing the Darcy-Brinkman-Forchheimer equation, the non-Darcy flow effect is investigated on the pressure build-up. At last, the convective transport and lymphatic uptake of drug solute are investigated in a multi-layered poroelastic tissue embedded with a hybrid discrete-continuum vessel network. Our model provides an efficient way to estimate the pressure build-up in the soft tissue. Coupled with the hybrid vessel network, this computational model can be used to study and predict drug clearance at the injection site. |
Thursday, March 9, 2023 8:12AM - 8:24AM Author not Attending |
S18.00002: Formation and structure of a spontaneous geostrophic edge current in the steady state of a chiral active fluid Anthony R Poggioli, David T Limmer Chiral active fluids are composed of particles that convert energy into rotational motion in a preferred direction. Their unforced steady states violate time-reversal and parity symmetry, leading to a taxonomy of exotic transport phenomena unobservable in ordinary passive fluids whose quiescent states are in equilibrium. The most famous such phenomenon is the odd viscosity, linking forcing to fluid motion in an orthogonal direction. Microscopically, chiral active fluids are characterized by the local injection of spin angular momentum. However, the free spin of individual constituent particles is frustrated by interparticle interaction at finite density. With a combination of theory and simulation, we show that this frustration, along with angular momentum conservation, leads to the spontaneous formation of a boundary current whose direction is determined by the chirality of the system. We further develop hydrodynamic equations governing our model system and use these equations to derive the structure of this boundary current. The hydrodynamic results are in excellent agreement with the profile observed in simulations, allowing us to extract estimates of the odd and shear viscosities governing the flow. We finally demonstrate that this boundary flow is an exact mathematical analogy of an oceanographic current known as a geostrophic coastally bound current, which forms when buoyant water flows between oceanographic basins or from estuaries into coastal environments. |
Thursday, March 9, 2023 8:24AM - 8:36AM |
S18.00003: Parity Odd Viscosity in Ferrofluids Dylan Reynolds, Gustavo M Machado Monteiro, Sriram Ganeshan Ferrofluids are a synthetic magnetic colloid consisting of magnetized nanoparticles surrounded by a repulsive surfactant layer which prevents clumping. When subjected to an external magnetic field the ferrofluid acquires a macroscopic magnetization density which leads to novel magnetic behavior. In this work, within a Hamiltonian framework, we introduce a new coupling between the fluid vorticity $vec{omega}$ and the magnetization $vec{M}$, proportional to $vec{omega}cdotvec{M}$. This coupling gives rise to an additional anti-symmetric stress tensor, and if the magnetization is relaxed to the direction of a uniform and static applied field, gives rise to a parity odd transport coefficient. We show that when confined to a Hele-Shaw cell this coupling reproduces the parity odd generalization of Darcy's Law, seen in [1]. We discuss possible origins of this new coupling, and a series of experiments are proposed that may extract the strength of this coupling in a ferrofluid confined to a Hele-Shaw cell. |
Thursday, March 9, 2023 8:36AM - 8:48AM |
S18.00004: Dancing Raisins Saverio E Spagnolie Bodies immersed in gaseous fluids are natural sites for the nucleation of bubbles. These bubbles confer the bodies with additional buoyancy which can lift them upward against gravity. But a free-surface can clean the body of these lifting agents as the gas escapes which may result in plummeting, as the body begins the process anew. We characterize this system using experiments, simulations, and theory, showing periodic and aperiodic orbits across a wide range of fluids and body surface parameters. Body rotations at the surface are shown to play particularly important roles in both single- and multi-body systems, and a phase-change is observed at a critical volume fraction of particles. This tabletop-scale system may speak to related phenomena in biology (blood during decompression), engineering (oil extraction), and geophysics (supersaturated magma and volcanic eruptions). |
Thursday, March 9, 2023 8:48AM - 9:00AM |
S18.00005: Boundary-driven Surface Wave Forces from a Self-propelling Vibrating Robot Boat Steven Tarr, Joseph S Brunner, Daniel Daniel Soto, Daniel I Goldman Active agents on fluid surfaces can perturb their surroundings by creating waves that reciprocally affect the agent. Inspired by the wave-mediated dynamics of surface-bouncing droplets, we study the motion and wave-field dynamics of a 6 cm radius, 9 cm tall, eccentric motor-driven vibrating robot boat on the surface of a 5 cm deep pool of water. The boat's vibration creates radially propagating gravity-capillary waves with frequency range 6-42 Hz and maximum amplitude 0.6 mm; a Schlieren method enables surface wave visualization with submillimeter resolution. The waves possess bow-stern and port-starboard symmetry, yielding a net-zero radiation force on the boat far from boundaries. When near a wall below a threshold distance, the boat's emitted waves interact with waves reflected off the boundary, creating a net field with reduced amplitude traveling toward the boundary. Meanwhile, waves emitted on the far side of the boat remain unchanged. Hence, the net wave force yields a boat-wall attraction, which we measure using the boat's displacement. Near the threshold, no reduced-amplitude field is born, and the boat experiences a slight repulsion. We observe the threshold to depend on wave frequency; a boat generating high-frequency waves will experience an attraction further from the wall than with low-frequency waves. |
Thursday, March 9, 2023 9:00AM - 9:12AM |
S18.00006: The Discretized Motion of an Anisotropic Magnetic Particle under a Non-Uniform AC Magnetic Field Yiping Zhao, Yanjun Yang An anisotropic magnetic particle or cluster near a surface in liquid can perform a translational motion under a non-uniform alternating magnetic field. Unlike a permanent magnet pulling a magnetic particle, the particle moves away from the magnetic source. The moving speed can be tuned by varying the magnetic field strength and gradient, its alternating frequency, and the particle size, magnetic moment and its orientation. When the orientation of the magnetic moment of the particle changes 90o, the motion of the particle evolves from rolling to precession, then to tumbling. Systematic investigations on the translational velocity versus the magnitude and frequency of the applied magnetic field show that the overall motion of the particle can be divided into four different zones: Brownian motion zone, synchronized zone, asynchronized zone, and oscillation zone. High speed movies reveal that both the tumbling and precession motions of the particles have a discretized nature. An intrinsic quality factor q for the motion of a magnetically driven particle is defined, and based on the nature of the discretized motion, an analytic expression for q is found to be determined by the shape of the particle, the hydrodynamics near a wall, and the magnetic properties of the particle. |
Thursday, March 9, 2023 9:12AM - 9:24AM |
S18.00007: Visualizing electron drift velocity Mahala Wanner, Niklas Manz We are using chemical reaction-diffusion waves propagating in a quasi-one-dimensional channel to visualize the drift velocities of electrons in a conductor. Though electrons move very fast, the actual drift velocity along the wire is surprisingly small. In our simple analogue, we employ the chemical Belousov-Zhabotinsky reaction to create easily visible, colorful fronts moving in several parallel channels. Depending on the chemical composition of the reaction, we can illustrate the electron drift velocity of, for example, i) different applied voltages, ii) different wire radii, or iii) within different materials |
Thursday, March 9, 2023 9:24AM - 9:36AM |
S18.00008: Space-local turbulence Ryo ARAKI, Wouter Bos, Susumu Goto Turbulent flow is a complex multi-scale phenomenon, but its small-scales exhibit universal statistics (K41 universality) almost regardless of its macroscopic configuration. The small-scale universality is associated with scale locality; the nonlinear interaction in Fourier space is dominated by modes with similar scales. |
Thursday, March 9, 2023 9:36AM - 9:48AM |
S18.00009: Singularities in two phase viscoelastic displacement flows in a rectilinear Hele-Shaw cell Prabir Daripa
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Thursday, March 9, 2023 9:48AM - 10:00AM |
S18.00010: Life, death, and propagation of an isolated turbulent blob fed by vortex loops Takumi Matsuzawa, Minhui Zhu, Nigel Goldenfeld, William T Irvine We create and sustain an isolated blob of turbulence by repeatedly firing together vortex loops. |
Thursday, March 9, 2023 10:00AM - 10:12AM |
S18.00011: Numerical investigation of secondary instabilities along helical disturbances in a swirling liquid jet Toshan lal sahu, Prasanta Kumar Das, Rajaram Lakkaraju This work is an approach to understanding the generation of secondary instabilities developing along the helical disturbance in a rotating liquid jet injected in a quiescent gaseous phase. Three-dimensional numerical simulations are performed to find the fundamental flow behavior of the swirling liquid jet for axial Reynolds numbers of 50≤ Re ≤ 300 and swirl numbers range of 0.50≤ S ≤ 1.55 corresponding to two control parameters, the mean injection velocity and angular velocity applied at the nozzle inlet. There are two main objectives of this paper (1) To explain the physical mechanism behind the evolution of the secondary instabilities at the interface and (2) To understand the impact of varying rotation rates on the generation of these secondary instabilities. The results indicate that initial small bulges form along each helical disturbance, which subsequently grow into thick liquid sheets and ligaments under the action of centrifugal force. Further, the liquid sheets and ligaments disintegrate into smaller satellite drops giving rise to smaller droplets. Also, the growth of secondary instabilities along helical disturbance strongly depends on the injection velocity applied at the inlet. As the injection velocity dominates over the rotation applied at the inlet, the generation of the secondary instabilities occurs at farther downstream locations compared to lower injection velocities. A parameter space plot is suggested to demarcate the Reynolds number and swirl number range for which secondary instabilities could be observed. Also, vortex structures are identified with Q-criterion to demarcate rotational dominance zones, which lie along the helical disturbance appearing at the interface giving rise to secondary instabilities. The thickness of axial and azimuthal shear layers is studied to explore the unstable helical disturbances at the interface. |
Thursday, March 9, 2023 10:12AM - 10:24AM |
S18.00012: Role of stochasticity in the transition to turbulence in pipe flow Xueying Wang, Hong-Yan Shih, Nigel Goldenfeld In transitional pipe turbulence, a sequence of phases is observed experimentally in the range of Reynolds numbers between 1900 and 5000, passing through the laminar-turbulent transition at Re ~ 2040. These phases are characterized by transient decay of puffs (Re 4500). We propose a statistical mechanics model of transitional pipe flow turbulence based on energy balance in the interaction between turbulence, zonal flow, and the baseline shear flow. The resulting model recapitulates the entire phase diagram of the transition, including decaying and splitting puff, the puff-slug transition, and weak and strong slugs. We demonstrate the critical role of stochasticity in all phases. Specifically, we show how stochasticity induces a decaying profile in the low-Reynolds regime and how it reveals the deep connection between the subcritical bifurcation picture and the directed percolation picture of the transition. The model is not restricted to pipe flow geometry and is extendable to other transitional shear flows like quasi-one-dimensional Taylor-Couette flow. |
Thursday, March 9, 2023 10:24AM - 10:36AM |
S18.00013: Higher-order large eddy simulations for engineering applications and science Kalyani Bhide Understanding turbulent flows in various regimes is crucial in science and in engineering applications. Large eddy simulations (LES) provide useful insights about the complex flow physics of turbulent flows since it resolves the large scales and models only the smallest or subgrid scales. The goal of this work is to present some key results of higher-order LES for a variety of flow regimes conducted on highly parallel HPC clusters. The results cover versatile flow regimes, such as, subsonic, and supersonic flow; wall-bounded and external flow; incompressible and compressible flow; rotating and non-rotating flow; Newtonian, non-Newtonian flow as in hemodynamics. Various important aspects are discussed, and the focus is given on improving the physics-capture using accurate boundary conditions, meshing and resolving near-wall regions. Spatial, temporal discretization and resolved to total Turbulent Kinetic Energy (TKE) ratios are discussed. Sufficiently long computational times are used to obtain most relevant details. Comparisons with experimental data are made where available. Turbulence capture using LES for a wide range of Reynolds numbers is demonstrated. |
Thursday, March 9, 2023 10:36AM - 10:48AM |
S18.00014: Leveraging deep learning to predict small scale dynamics of turbulence at higher unseen Reynolds numbers Dhawal Buaria, Katepalli R Sreenivasan Turbulent flows in nature and engineering are characterized by a wide range of interacting scales, which must all be resolved for an accurate direct numerical simulation of the problem. However, despite ever improving supercomputing capabilities, such simulations in all circumstances are still not feasible and modeling remains unavoidable. In this regard, the notion of small scale universality, captured by velocity gradient statistics (for instance), has been very useful. Similarly, when considering the mixing and transport of scalars by turbulence, the statistics of scalar gradients are treated in the same spirit. In recent years, deep learning algorithms have emerged as promising modeling tools because of their ability to directly learn from data. Here, we present such an analysis in which tensor-based deep neural networks are utilized to model the gradient dynamics of velocity and scalars in turbulence. We learn from a massive direct numerical simulation database at various Reynolds numbers and demonstrate that our model can predict statistics at higher, yet unseen, Reynolds numbers. Likewise, extensions to turbulent mixing are illustrated. Our work demonstrates that prohibitively expensive simulations can be avoided and the small scale dynamics of turbulence can be adequately modeled from the already available datasets. |
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