1 code implementation • 17 Jul 2023 • Tianyi Li, Luca Biferale, Fabio Bonaccorso, Martino Andrea Scarpolini, Michele Buzzicotti

Lagrangian turbulence lies at the core of numerous applied and fundamental problems related to the physics of dispersion and mixing in engineering, bio-fluids, atmosphere, oceans, and astrophysics.

no code implementations • 18 Jan 2023 • Tianyi Li, Michele Buzzicotti, Luca Biferale, Fabio Bonaccorso

We perform a systematic quantitative benchmark of point-wise and statistical reconstruction capabilities of the linear Extended Proper Orthogonal Decomposition (EPOD) method, a non-linear Convolutional Neural Network (CNN) and a Generative Adversarial Network (GAN).

no code implementations • 21 Oct 2022 • Tianyi Li, Michele Buzzicotti, Luca Biferale, Fabio Bonaccorso, Shiyi Chen, Minping Wan

Different gap sizes and gap geometries are investigated in order to assess the importance of coherency and multi-scale properties of the missing information.

no code implementations • 3 Jan 2022 • Michele Buzzicotti, Fabio Bonaccorso

The problem of classifying turbulent environments from partial observation is key for some theoretical and applied fields, from engineering to earth observation and astrophysics, e. g. to precondition searching of optimal control policies in different turbulent backgrounds, to predict the probability of rare events and/or to infer physical parameters labelling different turbulent set-ups.

no code implementations • 27 Feb 2021 • Michele Buzzicotti, Luca Biferale, Fabio Bonaccorso, Patricio Clark Di Leoni, Kristian Gustavsson

In this case, we optimize a linear combination between the total navigation time and the total time the engine is switched off.

no code implementations • 17 Jul 2019 • Luca Biferale, Fabio Bonaccorso, Michele Buzzicotti, Patricio Clark Di Leoni, Kristian Gustavsson

To find the path that minimizes the time to navigate between two given points in a fluid flow is known as Zermelo's problem.

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