Subscribe to the gold package and get unlimited access to Shamra Academy
Register a new userStealthy Movements and Concealed Swarms of Swimming micro-Robots
138
0
0.0
(
0
)
Ask ChatGPT about the research
No Arabic abstract
Here we show that micro-swimmers can form a concealed swarm through synergistic cooperation in suppressing one anothers disturbing flows. We then demonstrate how such a concealed swarm can actively gather around a favorite spot, point toward a target, or track a desired trajectory in space, while minimally disturbing the ambient fluid. Our findings provide a clear road map to control and lead flocks of swimming micro-robots in stealth versus fast modes, tuned through their active collaboration in minimally disturbing the host medium.
rate research
Read More
We study the fluid dynamics of two fish-like bodies with synchronised swimming patterns. Our studies are based on two-dimensional simulations of viscous incompressible flows. We distinguish between motion patterns that are externally imposed on the swimmers and self-propelled swimmers that learn manoeuvres to achieve certain goals. Simulations of two rigid bodies executing pre-specified motion indicate that flow-mediated interactions can lead to substantial drag reduction and may even generate thrust intermittently. In turn we examine two self-propelled swimmers arranged in a leader-follower configuration, with a-priori specified body-deformations. We find that the swimming of the leader remains largely unaffected, while the follower experiences either an increase or decrease in swimming speed, depending on the initial conditions. Finally, we consider a follower that synchronises its motion so as to minimise its lateral deviations from the leaders path. The leader employs a steady gait while the follower uses a reinforcement learning algorithm to adapt its swimming-kinematics. We find that swimming in a synchronised tandem can yield up to about 30% reduction in energy expenditure for the follower, in addition to a 20% increase in its swimming-efficiency. The present results indicate that synchronised swimming of two fish can be energetically beneficial.
In this fluid dynamics video, we demonstrate the microscale mixing enhancement of passive tracer particles in suspensions of swimming microalgae, Chlamydomonas reinhardtii. These biflagellated, single-celled eukaryotes (10 micron diameter) swim with a breaststroke pulling motion of their flagella at speeds of about 100 microns/s and exhibit heterogeneous trajectory shapes. Fluorescent tracer particles (2 micron diameter) allowed us to quantify the enhanced mixing caused by the swimmers, which is relevant to suspension feeding and biogenic mixing. Without swimmers present, tracer particles diffuse slowly due solely to Brownian motion. As the swimmer concentration is increased, the probability density functions (PDFs) of tracer displacements develop strong exponential tails, and the Gaussian core broadens. High-speed imaging (500 Hz) of tracer-swimmer interactions demonstrates the importance of flagellar beating in creating oscillatory flows that exceed Brownian motion out to about 5 cell radii from the swimmers. Finally, we also show evidence of possible cooperative motion and synchronization between swimming algal cells.
By synergistically combining modeling, simulation and experiments, we show that there exists a regime of self-propulsion in which the inertia in the fluid dynamics can be separated from that of the swimmer. This is demonstrated by the motion of an asymmetric dumbbell that, despite deforming in a reciprocal fashion, self-propagates in a fluid due to a non-reciprocal Stokesian flow field. The latter arises from the difference in the coasting times of the two constitutive beads. This asymmetry acts as a second degree of freedom, recovering the scallop theorem at the mesoscopic scale.
To evaluate the swimming performances of aquatic animals, an important dimensionless quantity is the Strouhal number, St = fA/U, with f the tail-beat frequency, A the peak-to-peak tail amplitude, and U the swimming velocity. Experiments with flapping foils have exhibited maximum propulsive efficiency in the interval 0.25 < St < 0.35 and it has been argued that animals likely evolved to swim in the same narrow interval. Using Lighthills elongated-body theory to address undulatory propulsion, it is demonstrated here that the optimal Strouhal number increases from 0.15 to 0.8 for animals spanning from the largest cetaceans to the smallest tadpoles. To assess the validity of this model, the swimming kinematics of 53 different species of aquatic animals have been compiled from the literature and it shows that their Strouhal numbers are consistently near the predicted optimum.
Particular types of plankton in aquatic ecosystems can coordinate their motion depending on the local flow environment to reach regions conducive to their growth or reproduction. Investigating their swimming strategies with regard to the local environment is important to obtain in-depth understanding of their behavior in the aquatic environment. In the present research, to examine an impact of the shape and gravity on a swimming strategy, plankton is considered as settling swimming particles of ellipsoidal shape. The Q-learning approach is adopted to obtain swimming strategies for smart particles with a goal of efficiently moving upwards in a two-dimensional steady flow. Strategies obtained from reinforcement learning are compared to those of naive gyrotactic particles that is modeled considering the behavior of realistic plankton. It is found that elongation of particles improves the performance of upward swimming by facilitating particles resistance to the perturbation of vortex. In the case when the settling velocity is included, the strategy obtained by reinforcement learning has similar performance to that of the naive gyrotactic one, and they both align swimmers in upward direction. The similarity between the strategy obtained from machine learning and the biological gyrotactic strategy indicates the relationship between the aspherical shape and settling effect of realistic plankton and their gyrotactic feature.
Log in to be able to interact and post comments
comments
Fetching comments
Sign in to be able to follow your search criteria
