Collective Behaviour in Fish, FLow Sensing and PPE Design
Siddhartha Verma, FAU

Can fish reduce their energy expenditure by schooling? We answer this long standing question by integrating Direct Numerical Simulations with deep reinforcement learning, which confers adaptive decision-making capability to simulated fish. Our results demonstrate that locomotion in coordinated groups may lead to energy savings when individual fish interact judiciously with their companions' unsteady wakes. In natural swimmers, optimal decision-making in response to an unsteady environment also requires fine-tuned sensory capabilities. By combining Navier-Stokes simulations with Bayesian experimental design, we were able to identify sensor arrangements that allow simulated swimmers to maximize the information gathered from the surrounding  flow. The resulting optimal sensor distributions resemble neuromast arrangements found in fish, and provide evidence for optimality of  sensor distribution for natural swimmers. I will also highlight recent work where we have investigated aerosol dispersal patterns for various types of facemasks and shields, which are simple yet critical tools in  the worldwide effort to combat the spread of COVID-19.