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Related papers: Full-depth snow avalanches

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We study segregation of granular mixtures in the continuous avalanche regime (for frequencies above ~ 1 rpm) in thin rotating drums using a continuum theory for surface flows of grains. The theory predicts profiles in agreement with…

Statistical Mechanics · Physics 2009-10-31 Hernan A. Makse

Snow density estimates below the surface, used with airplane-acquired ice-penetrating radar measurements, give a site-specific history of snow water accumulation. Because it is infeasible to drill snow cores across all of Antarctica to…

Applications · Statistics 2021-07-20 Philip A. White , Durban G. Keeler , Summer Rupper

Aerodynamic models are developed to describe coherent structures and transport processes in hurricanes moving over open seas. The models consist of the lower boundary layer and upper adiabatic layer. Except friction at the air/sea…

Atmospheric and Oceanic Physics · Physics 2008-12-18 Arkady I. Leonov

Turbulence is ubiquitous in nonequilibrium systems, and it has been noted that even dense granular flows exhibit characteristics that are typical of turbulent flow, such as the power-law energy spectrum. However, studies on the…

Soft Condensed Matter · Physics 2023-04-18 Norihiro Oyama , Hideyuki Mizuno , Kuniyasu Saitoh

Plastic deformation of crystals proceeds through a sequence of intermittent slip avalanches with scale-free (power-law) size distribution. On macroscopic scales, however, plastic flow is known to be smooth and homogeneous. In the present…

Statistical Mechanics · Physics 2009-11-13 Michael Zaiser , Nikos Nikitas

Sudden avalanches of magnetic flux bursting into a superconducting sample undergo deflections of their trajectories when encountering a conductive layer deposited on top of the superconductor. Remarkably, in some cases flux is totally…

The integration of machine learning (ML) with traditional physics-based models is reshaping the landscape of weather and climate prediction. On their own, ML-based and physics-based approaches each have significant benefits - but also…

We present in this paper a simplification of the dune model proposed by Sauermann et al. which keeps the basic mechanisms but allows analytical and parametric studies. Two kinds of purely propagative two dimensional solutions are exhibited:…

Condensed Matter · Physics 2015-06-24 Bruno Andreotti , Philippe Claudin

Existing learning-based atmospheric particle-removal approaches such as those used for rainy and hazy images are designed with strong assumptions regarding spatial frequency, trajectory, and translucency. However, the removal of snow…

Computer Vision and Pattern Recognition · Computer Science 2018-05-09 Yun-Fu Liu , Da-Wei Jaw , Shih-Chia Huang , Jenq-Neng Hwang

See the updated version arXiv:nlin/0111028.

Adaptation and Self-Organizing Systems · Physics 2010-09-08 Chaohong Lee , Xiwen Zhu , Kelin Gao

Two-dimensional free-surface potential flows of an ideal fluid over a strongly inhomogeneous bottom are investigated with the help of conformal mappings. Weakly-nonlinear and exact nonlinear equations of motion are derived by the…

Fluid Dynamics · Physics 2016-09-08 V. P. Ruban

Correctly forecasting the timing and location of changes in winter precipitation type could help decision makers mitigate the worst impacts of winter storms. Multiple precipitation type algorithms have been developed from both physical and…

As we deal with the effects of climate change and the increase of global atmospheric temperatures, the accurate tracking and prediction of ice layers within polar ice sheets grows in importance. Studying these ice layers reveals climate…

Machine Learning · Computer Science 2023-06-27 Benjamin Zalatan , Maryam Rahnemoonfar

In the present article we consider the problem of underwater avalanches propagating over moderate slopes. The main goal of our work is to investigate the avalanche front velocity selection mechanism when it propagates downwards. In…

Fluid Dynamics · Physics 2020-02-20 V. Yu Liapidevskii , Denys Dutykh

We introduce a three-dimensional, computationally feasible, mesoscopic model for snow crystal growth, based on diffusion of vapor, anisotropic attachment, and a semi-liquid boundary layer. Several case studies are presented that faithfully…

Mathematical Physics · Physics 2007-11-27 Janko Gravner , David Griffeath

Cluster analysis plays an indispensable role in machine learning and data mining. Learning a good data representation is crucial for clustering algorithms. Recently, deep clustering, which can learn clustering-friendly representations using…

Machine Learning · Computer Science 2022-10-11 Yazhou Ren , Jingyu Pu , Zhimeng Yang , Jie Xu , Guofeng Li , Xiaorong Pu , Philip S. Yu , Lifang He

Novel techniques in evolutionary optimization, simulation and machine learning allow for a broad analysis of domains like fluid dynamics, in which computation is expensive and flow behavior is complex. Under the term of full domain analysis…

Machine Learning · Computer Science 2025-05-29 Alexander Hagg , Adam Gaier , Dominik Wilde , Alexander Asteroth , Holger Foysi , Dirk Reith

Shallow landslides pose a significant threat to people and infrastructure. While often modeled based on limit equilibrium analysis, finite or discrete elements, continuum particle-based approaches like the Material Point Method (MPM) have…

Geophysics · Physics 2023-01-18 Louis Guillet , Lars Blatny , Bertil Trottet , Johan Gaume

Surface flow of granular material is investigated within a continuum approach in two dimensions. The dynamics is described by a non-linear coupling between the two `states' of the granular material: a mobile layer and a static bed.…

Statistical Mechanics · Physics 2009-11-10 Thorsten Emig , Philippe Claudin , Jean-Philippe Bouchaud

A unifying framework to describe dense flows of dry, deformable grains is proposed. Perturbative analysis of a granular temperature equation describing flows with contact stresses, supported by the recovery of the nonlocal granular fluidity…

Soft Condensed Matter · Physics 2026-01-06 Benjamin M. Alessio , Matthew R. Edwards , Ching-Yao Lai
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