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.