10 papers
Intermittency suppression in turbulence via forced light particles
André Freitas, Xander M. de Wit, Ziqi Wang +2
We investigate how turbulence is reshaped by the presence of externally forced light particles, using high-resolution direct numerical simulations with four-way coupling. The parti…
Policy heterogeneity improves collective olfactory search in 3-D turbulence
Lorenzo Piro, Robin A. Heinonen, Maurizio Carbone +2
We investigate the role of policy heterogeneity in enhancing the olfactory search capabilities of cooperative agent swarms operating in complex, real-world turbulent environments.…
Many wrong models approach to localize an odor source in turbulence with static sensors
Lorenzo Piro, Robin A. Heinonen, Massimo Cencini +1
The problem of locating an odor source in turbulent flows is central to key applications such as environmental monitoring and disaster response. We address this challenge by design…
Optimal trajectories for Bayesian olfactory search in turbulent flows: the low information limit and beyond
Robin A. Heinonen, Luca Biferale, Antonio Celani +1
In turbulent flows, tracking the source of a passive scalar cue requires exploiting the limited information that can be gleaned from rare, stochastic encounters with the cue. When…
Solver-in-the-loop approach to closure of shell models of turbulence
André Freitas, Kiwon Um, Mathieu Desbrun +2
This work studies an a posteriori data-driven approach (known as solver-in-the-loop) for sub-grid modeling of a shell model for turbulence. This approach takes advantage of the dif…
Exploring Bayesian olfactory search in realistic turbulent flows
Robin A. Heinonen, Luca Biferale, Antonio Celani +1
The problem of tracking the source of a passive scalar in a turbulent flow is relevant to flying insect behavior and several other applications. Extensive previous work has shown t…