Publications by authors named "L Biferale"
We present a study of the intermittent properties of a shell model of turbulence with statistics of ∼10^{7} eddy turn over time, achieved thanks to an implementation on a large-scale parallel GPU factory. This allows us to quantify the inertial range anomalous scaling properties of the velocity fluctuations up to the 24th-order moment. Through a careful assessment of the statistical and systematic uncertainties, we show that none of the phenomenological and theoretical models previously proposed in the literature to predict the anomalous power-law exponents in the inertial range are in agreement with our high-precision numerical measurements.
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- - Metastability in liquids affects phase transformation processes like nucleation and cavitation, influenced mainly by intermolecular interactions and thermal fluctuations.
- - The Shan-Chen lattice Boltzmann model excels in simulating hydrodynamics in metastable states, providing precise theoretical and numerical results for density fluctuations across various conditions.
- - As temperature nears the critical point or density reaches the spinodal line, the static structure factor shows significant divergence, and critical exponents align with theoretical predictions, mirroring patterns noted in molecular dynamics simulations.
Instanton-based importance sampling for extreme fluctuations in a shell model for turbulent energy cascade.
Eur Phys J E Soft Matter
December 2023
Many out-of-equilibrium flows present non-Gaussian fluctuations in physically relevant observables, such as energy dissipation rate. This implies extreme fluctuations that, although rarely observed, have a significant phenomenology. Recently, path integral methods for importance sampling have emerged from formalism initially devised for quantum field theory and are being successfully applied to the Burgers equation and other fluid models.
View Article and Find Full Text PDFTopical issue on quantitative AI in complex fluids and complex flows: challenges and benchmarks.
Eur Phys J E Soft Matter
October 2023
Article Synopsis
- Flying insects face challenges in locating cues in turbulent wind, as these cues are mixed into high and low concentration patches, making them difficult to follow through standard chemotactic methods.
- The study models the search as a partially observable Markov decision process, applying the Perseus algorithm to develop near-optimal strategies for reducing arrival time compared to various heuristic approaches.
- Results show that the Perseus-based strategy significantly outperforms other methods, revealing insights on search difficulty based on starting location and discussing the implications of initial beliefs and environmental changes on policy robustness.