19 citations · 84 across the 13 of their papers we have counts for
13 papers
Learning turbulent transport via Mori--Zwanzig graph neural networks
André Freitas, Xander M. de Wit, Alessandro Gabbana +4
We introduce a Mori--Zwanzig graph neural network (MZ--GNN) framework for learning reduced-order Lagrangian dynamics of tracer particles in homogeneous isotropic turbulence. The mo…
The multi-fractal nature of pedestrian arrival times
Caspar A. S. Pouw, Alessandro Corbetta, Alessandro Gabbana +1
Pedestrian arrival times exhibit complex temporal organization across multiple scales, shaped by working hours, transportation schedules, and collective behaviors - features often…
Avalanches of choice: how stranger-to-stranger interactions shape crowd dynamics
Ziqi Wang, Alessandro Gabbana, Federico Toschi
Pedestrian routing choices play a crucial role in shaping collective crowd dynamics, yet the influence of interactions among unfamiliar individuals remains poorly understood. In th…
Flow-driven hysteresis in the transition boiling regime
Alessandro Gabbana, Xander M. de Wit, Linlin Fei +3
Transition boiling is an intermediate regime occurring between nucleate boiling, where bubbles at the surface efficiently carry heat away, and film boiling, where a layer of vapor…
Data-driven Mori-Zwanzig modeling of Lagrangian particle dynamics in turbulent flows
Xander de Wit, Alessandro Gabbana, Michael Woodward +3
The dynamics of Lagrangian particles in turbulence play a crucial role in mixing, transport, and dispersion in complex flows. Their trajectories exhibit highly non-trivial statisti…
Perfectly Matched Layers and Characteristic Boundaries in Lattice Boltzmann: Accuracy vs Cost
Friedemann Klass, Alessandro Gabbana, Andreas Bartel
Artificial boundary conditions (BCs) play a ubiquitous role in numerical simulations of transport phenomena in several diverse fields, such as fluid dynamics, electromagnetism, aco…
Vielbein Lattice Boltzmann approach for fluid flows on spherical surfaces
Victor E. Ambrus, Elisa Bellantoni, Sergiu Busuioc +2
In this paper, we develop a lattice Boltzmann scheme based on the Vielbein formalism for the study of fluid flows on spherical surfaces. The Vielbein vector field encodes all detai…
Enhancing lattice kinetic schemes for fluid dynamics with Lattice-Equivariant Neural Networks
Giulio Ortali, Alessandro Gabbana, Imre Atmodimedjo +1
We present a new class of equivariant neural networks, hereby dubbed Lattice-Equivariant Neural Networks (LENNs), designed to satisfy local symmetries of a lattice structure. Our a…
Kinetic data-driven approach to turbulence subgrid modeling
Giulio Ortali, Alessandro Gabbana, Nicola Demo +2
Numerical simulations of turbulent flows are well known to pose extreme computational challenges due to the huge number of dynamical degrees of freedom required to correctly descri…
High-statistics pedestrian dynamics on stairways and their probabilistic fundamental diagrams
Caspar A. S. Pouw, Alessandro Corbetta, Alessandro Gabbana +2
Staircases play an essential role in crowd dynamics, allowing pedestrians to flow across large multi-level public facilities such as transportation hubs, and office buildings. Achi…
Towards learning Lattice Boltzmann collision operators
Alessandro Corbetta, Alessandro Gabbana, Vitaliy Gyrya +3
In this work we explore the possibility of learning from data collision operators for the Lattice Boltzmann Method using a deep learning approach. We compare a hierarchy of designs…
Fluctuations in pedestrian dynamics routing choices
Alessandro Gabbana, Federico Toschi, Philip Ross +2
Routing choices of walking pedestrians in geometrically complex environments are regulated by the interplay of a multitude of factors such as local crowding, (estimated) time to de…
Quantum computation of thermal averages in the presence of a sign problem
Giuseppe Clemente, Marco Cardinali, Claudio Bonati +8
We illustrate the application of Quantum Computing techniques to the investigation of the thermodynamical properties of a simple system, made up of three quantum spins with frustra…