Bulletin of the American Physical Society
74th Annual Meeting of the APS Division of Fluid Dynamics
Volume 66, Number 17
Sunday–Tuesday, November 21–23, 2021; Phoenix Convention Center, Phoenix, Arizona
Session E13: Biological Fluid Dynamics: Locomotion II |
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Chair: Donald Webster, Georgia Institute of Technology Room: North 127 ABC |
Sunday, November 21, 2021 2:45PM - 2:58PM |
E13.00001: Walk on water: Fluid dynamics of microvelia locomotion Johnathan O'Neil, Victor Ortega-Jimenez, Xingwan Zhu, Saad Bhamla Microvelia water striders are semiaquatic insects that live in low flow streams. They walk on the water surface through an alternating tripod gait. In nature, these insects can be found on land and water, yet we discovered adult microvelia are faster on the surface of water than on land. In this talk, we will discuss how the microvelia are able to use the alternating tripod gait to locomote better on water than on styrofoam. When calculating the Reynolds, Bond, and Baudoin numbers, we show the forces responsible for locomotion. We hypothesize that they can achieve these faster speeds due to the surface properties that reduce the shear stress and allow them to deform the surface of the water. Through particle image velocimetry and schlieren imaging we will obtain the forces used for propulsion and determine the shear stress observed on the legs of the microvelia. We will then compare how these forces change with body size to scale performance among age classes. |
Sunday, November 21, 2021 2:58PM - 3:11PM |
E13.00002: The Optimal Gaits of Fish-like Locomotion Xuanhong An, Daniel Floryan, Clarence W Rowley In this work, we investigated the optimal gaits for fish-like swimming. Specifically, we develop and use an efficient adjoint-based optimization algorithm to find the periodic gaits that maximize the time-average thrust or propulsive efficiency. The optimization algorithm consists of three components: (1) an immersed boundary DNS solver, which is employed to solve for the flow field and compute the lift and drag on an oscillating 2D plate; (2) an iterative adjoint-based optimizer, formulated to compute the gradient of the objective function with respect to the parameters and obtain the optimal gaits; and (3) a Newton-GMRES solver, which is used to accelerate the calculation of the flowfield associated with the periodically oscillating plate. We will discuss the optimal gaits and associated flows in detail, including the sensitivity information furnished by the adjoint method. |
Sunday, November 21, 2021 3:11PM - 3:24PM |
E13.00003: Optimum gaits and synchronization of a self-propelled undulatory motion in fish pair and fish arrays. Ahmed Abouhussein, Yulia T Peet The bio-locomotion of self-propelled underwater undulatory swimmers is investigated and optimized using a high-fidelity computational framework. The kinematic gaits and the phase lag between two side by side self-propelled swimmers are optimized for swimming efficiency using a global surrogate based optimization algorithm. Hydrodynamic trends governing optimal and sub-optimal swimming behaviour are investigated using modes which arise from the optimization procedure. Additionally, we vary the distance between the two swimmers to investigate separation effects on kinematics in fish pair swimming. Our results confirm the superiority of anti-phase lag between swimming pair and provide a measure of sensitivity of swimming efficiency to phase lag. Moreover, the optimal kinematic gait is shown to be dependent on the separation distance up to a certain point, D*, where the optimal kinematic gaits approach the single swimmer limit. Finally, we extend our analysis to the case of optimal swimming efficiency for an infinite array of side-by-side swimmers. |
Sunday, November 21, 2021 3:24PM - 3:37PM |
E13.00004: Sensorimotor control of fish rheotaxis Chenchen Huang, Eva Kanso Most aquatic animals can navigate in complex flow environments. Fish, for example, can consistently orient and swim against oncoming flow (rheotaxis) even without visual cues. Rheotaxis is a challenging process that involves multiple steps, including flow sensing and motor control. Previous studies proposed a data-driven model of rheotaxis in which fish rely on temporal changes in the local curl of the background flow, measured via the mechanosensory lateral line system. Here, we revisit this model in the context of a simplified mathematical fish, consisting of a self-propel dipole swimming in a two dimensional flow channel. We propose an ensemble of sensorimotor feedback laws, and we test these laws by carrying out stability analysis and parametric studies. Specifically, we compare two classes of control models, discontinuous time delayed models that stagger sensing and response and continuous models with instantaneous response. We find that both models can achieve rheotaxis but with distinct performanceand dynamic behaviors. These results suggest that the existence of many sensorimotor rules for rheotaxis and establish bio-inspired design rules for underwater robotics design. |
Sunday, November 21, 2021 3:37PM - 3:50PM |
E13.00005: The colloidal nature of complex fluids leads to enhanced motility of flagellated bacteria Seunghwan Shin, Xiang Cheng, Shashank Kamdar, Lorraine Francis, Xinliang Xu The natural habitats of microorganisms in human microbiome and ocean and soil ecosystems are full of colloids and macromolecules, which impart non-Newtonian flow properties drastically affecting the locomotion of swimming microorganisms. Although the low-Reynolds-number hydrodynamics of the swimming of flagellated bacteria in simple Newtonian fluids has been well developed, our understanding of bacterial motility in complex non-Newtonian fluids is still primitive. Even after six decades of research, fundamental questions about the nature and origin of bacterial motility enhancement in polymer solutions are still under debate. Here, we study the motility of flagellated bacteria in colloidal suspensions of varying sizes and volume fractions. We find that bacteria in dilute colloidal suspensions display quantitatively the same motile behaviors as those in dilute polymer solutions, where a universal particle-size-dependent motility enhancement up to 80% is uncovered, accompanied by a strong suppression of bacterial wobbling. By virtue of the well-controlled size and the hard-sphere nature of colloids, the finding not only resolves the long-standing controversy over bacterial motility enhancement in complex fluids, but also challenges all the existing theories using polymer dynamics to address the swimming of flagellated bacteria in dilute polymer solutions. We further develop a simple physical model incorporating the colloidal nature of complex fluids, which quantitatively explains bacterial wobbling dynamics and mobility enhancement in both colloidal and polymeric fluids. Our study sheds light on the puzzling motile behaviors of bacteria in complex fluids relevant to a wide range of microbiological processes, and provides a cornerstone in engineering bacterial swimming in complex environments. |
Sunday, November 21, 2021 3:50PM - 4:03PM |
E13.00006: Bacteria Swimming in finitely extensible viscoelastic fluids Kourosh Shoele, Hadi Mohammadigoushki Locomotion in viscoelastic fluids is critical for many biological systems. Depending on the shape and kinematics of microswimmer, swimming performance in viscoelastic fluids can be enhanced or reduced compared to that of Newtonian fluids. To date, most of the theoretical and computational studies assume infinitely stretched polymer assumptions in the formulation, while realistic polymeric fluids have finitely extensible polymers. In this work, we provide a systematic numerical and experimental investigation on the effects of polymer extensibility on swimming dynamics of the helical swimmer shape. Adaptive mesh refinement is used to model the swimmer body and helix and FENE-P model is assumed to calculate the viscoelastic stress tensor. We will discuss the relationship between the pitch angle and thickness of the helix and the viscoelastic properties of the flow for optimal swimming performance. The changes of the far-field front-back flow symmetry of the flow are correlated to the formation of a strong negative wake in the rear of the swimmer in viscoelastic fluid. Our analysis indicates that finite extensibility of the fluid affects the near helix strain-rate tensor and modifies the contribution of the viscoelastic stress tensor in the free-force locomotion. This illustrates the importance of elasticity and the presence of a feedback loop between the near body flow and swimmer characteristics in finitely extensible polymeric flows. |
Sunday, November 21, 2021 4:03PM - 4:16PM |
E13.00007: Extreme Maneuvering and Hydrodynamics of Rhagovelia Water Striders Victor M Ortega-Jimenez, Saad Bhamla Millimeter-sized Rhagovelia are remarkable among water striders because they can stand tempestuous rapids and coastal waters. These outstanding abilities mainly come from special fan-like structures located on their middle legs, which allows them to effect sudden turns. However, it is unknown how capillary phenomena influence fan performance, as well as the hydrodynamics of rapid maneuvering. We found that the fan is hydrophilic, which permits a passive spreading and folding, when placed in or out the water, respectively. Biomechanical and Particle Image Velocimetry (PIV) indicate that Rhagovelia’s turning is driven by a reverse stroke and asymmetric impulse produced by only one leg’s fan. Accordingly, Rhagovelia can turn up to 180 deg in less than ~30 ms, with average speeds and turning rates up to 22 m/s and 4000 deg/s, respectively. Side-view PIV revealed that these insects may be using unsteady hydrodynamics for propulsion. Besides, complex fluid dynamics of Rhagovelia’s natural streams were obtained using in-situ PIV. Thus, Rhagovelia’s extreme turning seems to be driven by a passive fan spreading, an asymmetrical reverse stroke and unsteady hydrodynamics, which can be used in the design of a robot with the capacity to move on unsteady water surfaces. |
Sunday, November 21, 2021 4:16PM - 4:29PM |
E13.00008: Neuromechanical control in highly damped environments Christopher J Pierce, Lucinda Peng, Gongchen Song, Hang Lu, Daniel I Goldman Biological locomotors must contend with environmental complexity and variability; thus control strategies underlying movement need to be flexible, robust, and environmentally adaptive. We investigated this adaptivity in the context of undulatory locomotion using the mm-scale nematode C. elegans, which permits interrogation of neuromuscular dynamics through calcium imaging. We imaged muscle activity in organisms locomoting in diverse settings: fluids, crawling on agar and burrowing within hydrogels. In each condition, neuromechanical phase lags (delays between waves of muscle activation and body curvature) arise, which depend on the physical properties of the surrounding medium, yielding phase lags which either shift continually down the body (viscous fluids) or remain constant (agar surfaces) These experimental results are captured by Resistive Force Theory model which in turn allows comparisons across taxa (Ding et al., 2013). The muscle activity pattern adopted by the nematode in viscous fluids displays similarities to those of cm-scale sandfish lizards swimming in frictional fluids (e.g. sand, Sharpe et al., 2012) indicating the importance of the environment on neuromechanical control in highly damped locomotion. |
Sunday, November 21, 2021 4:29PM - 4:42PM |
E13.00009: Learning underwater navigation using egocentric sensory cues Yusheng Jiao, Eva Kanso Navigation in the presence of background flows is an essential yet challenging task for autonomous underwater vehicles. In contrast, fish naturally accomplish such tasks by exploiting ambient flow features. Two major difficulties exist in solving this problem: First, the vehicle has access to flow information only in its immediate surroundings, which discounts an optimization approach over the entire flow field. Second, flow information and target position are available in the vehicle frame of reference. Recent studies proved that reinforcement learning is an effective tool for flow navigation but training a control policy directly with CFD data is very costly in time and memory. Here, we design a reduced-order von Kármán vortex street that resembles a drag wake and we train a swimmer to reach a given target against strong background flows by exploiting the wake. The swimmer uses only local sensory information to perform a continuous reorientation. To compare, we also train the swimmer in the CFD wake and test the two trained policies in each other's environment. We found that while egocentric sensory input poses an obstacle to navigation compared to lab frame data, increasing the number of sensors and proper configuration of the sensors significantly improve the success rate. |
Sunday, November 21, 2021 4:42PM - 4:55PM |
E13.00010: Pairing Bayesian statistics with transition networks: A data-driven approach for aerodynamic state estimation Frieder Kaiser, Giovanni Iacobello, David E Rival Swimmers and flyers in nature utilize haptic sensor feedback to control the interaction between the surrounding fluid and their bodies, even in challenging environments such as wake flows or gusts. Inspired by this behavior, a series of data-driven, bio-inspired works have been proposed that utilize real-time sensor input for aerial vehicle control. To tackle unsteady, highly separated, and high Reynolds number flows and their highly non-linear dynamics with a sparse set of pressure sensors and limited training data, advanced data-driven approaches are required. In the present work, a transition network approach relying on a Markov model is employed. We extend previous transition network-based approaches through a Bayesian estimation process to account for the typically high noise levels in realistic experimental data. The flow around an accelerating elliptical plate is selected as a test case. The plate is accelerated and decelerated at various (fixed) angles of attack, and the aerodynamic loads are estimated from a set of sparse pressure measurements. Results show that the combination of transition networks with Bayes' theorem can lead to good load estimation in real-time when facing the issue of noise in the measured quantities. |
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