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Laboratory experiments and theoretical modelling are conducted to determine the raindrop size distribution (DSD) resulting from distinct fragmentation processes under various upward airstreams. Since weather radar echoes are proportional to…

Modeling the risk of extreme weather events in a changing climate is essential for developing effective adaptation and mitigation strategies. Although the available low-resolution climate models capture different scenarios, accurate risk…

Atmospheric and Oceanic Physics · Physics 2022-12-06 Anamitra Saha , Sai Ravela

The water uptake by roots of plants is examined for an ideal situation, with an approximation that resembles plants growing in pots, meaning that the total soil volume is fixed. We propose a coupled water uptake-root growth model. A…

Biological Physics · Physics 2015-03-12 J. L. Blengino Albrieu , J. C. Reginato , D. A. Tarzia

Turbulent mixing and entrainment at the boundary of a cloud is studied by means of direct numerical simulations that couple the Eulerian description of the turbulent velocity and water vapor fields with a Lagrangian ensemble of cloud water…

Fluid Dynamics · Physics 2013-10-14 Bipin Kumar , Joerg Schumacher , Raymond A. Shaw

As deposits accumulate in a granular filter, pressure drop across the filter bed required to maintain a constant fluid flow rate may increase. Two pressure drop increase patterns had been observed. In slow sand filters pressure drop remains…

Soft Condensed Matter · Physics 2014-05-20 Zhaohui Qin , Richard H. Pletcher

The demixing of a binary fluid mixture, under gravity, is a two stage process. Initially droplets, or in general aggregates, grow diffusively by collecting supersaturation from the bulk phase. Subsequently, when the droplets have grown to a…

Statistical Mechanics · Physics 2014-12-01 Martin Rohloff , Tobias Lapp , Jürgen Vollmer

Employing a long-wave mesoscopic hydrodynamic model for the film height evolution we study ensembles of pinned and sliding drops of a volatile liquid that continuously condense onto a chemically heterogeneous inclined substrate. Our…

Fluid Dynamics · Physics 2019-11-05 Sebastian Engelnkemper , Uwe Thiele

The representation of clouds and associated processes of rain and snow formation remains one of the major uncertainties in climate and weather prediction models. In a companion paper (Part I), we systematically derived a two moment bulk…

Atmospheric and Oceanic Physics · Physics 2016-06-08 David Collins , Boualem Khouider

Context: There is increasing need for good algorithms for modeling the aggregation and fragmentation of solid particles (dust grains, dust aggregates, boulders) in various astrophysical settings, including protoplanetary disks, planetary-…

Astrophysics · Physics 2009-11-13 A. Zsom , C. P. Dullemond

Stochastic differential equations are often simulated with the Monte Carlo Euler method. Convergence of this method is well understood in the case of globally Lipschitz continuous coefficients of the stochastic differential equation. The…

Numerical Analysis · Mathematics 2011-11-18 Martin Hutzenthaler , Arnulf Jentzen

Modeling transformations between arbitrary data distributions is a fundamental scientific challenge, arising in applications like drug discovery and evolutionary simulation. While flow matching offers a natural framework for this task, its…

Machine Learning · Computer Science 2025-10-09 Shiye Su , Yuhui Zhang , Linqi Zhou , Rajesh Ranganath , Serena Yeung-Levy

The condensational growth of spherical water microdroplets is studied in a laboratory setup and with a mathematical model. In the experiment, droplet clusters are kept in a freely levitated state within an upward-oriented flow of water…

Soft Condensed Matter · Physics 2019-06-25 Dmitrii N. Gabyshev , Alexander A. Fedorets , Nurken E. Aktaev , Otto Klemm , Stepan N. Andreev

We present a stochastic mean-reverting jump-diffusion model to simulate rainfall time series and validate it using long-term half-hourly rain fall data from the North-East region of India. The model captures the intermittent and…

Statistical Mechanics · Physics 2026-04-10 Joya GhoshDastider , D. Pal , Pankaj Kumar Mishra

Diffusion models have revolutionized various application domains, including computer vision and audio generation. Despite the state-of-the-art performance, diffusion models are known for their slow sample generation due to the extensive…

Machine Learning · Computer Science 2024-06-25 Zehao Dou , Minshuo Chen , Mengdi Wang , Zhuoran Yang

The growth of homogeneously nucleated droplets in water vapor at the fixed temperatures T=273, 283, 293, 303, 313, 323, 333, 343, 353, 363 and 373 K (the pressure $p=1$ atm.) is investigated on the basis of the coarse-grained molecular…

Soft Condensed Matter · Physics 2012-12-06 Anatolii V. Mokshin , Bulat N. Galimzyanov

Water droplets coalesce into larger ones in atmospheric clouds to form rain. But droplets on collision courses do not always coalesce due to the cushioning effects of the air between them. The extent to which these so-called hydrodynamic…

Fluid Dynamics · Physics 2022-04-19 R. V. Kearney , G. P. Bewley

Droplet coalescence is ubiquitous in nature and the same time key to various technologies, such as inkjet printing. Here, we report on the coalescence of polymer droplets with different chain lengths coalescing on substrates of different…

Soft Condensed Matter · Physics 2023-09-21 Soheil Arbabi , Panagiotis E. Theodorakis

In order to understand the origin of observed molecular cloud properties, it is critical to understand how clouds interact with their environments during their formation, growth, and collapse. It has been suggested that accretion-driven…

Astrophysics of Galaxies · Physics 2018-12-21 Juan C. Ibáñez-Mejía , Mordecai-Mark Mac Low , Ralf S. Klessen , Christian Baczynski

We discuss a thin film evolution equation for a wetting evaporating liquid on a smooth solid substrate. The model is valid for slowly evaporating small sessile droplets when thermal effects are insignificant, while wettability and…

Soft Condensed Matter · Physics 2012-04-11 Desislava Todorova , Uwe Thiele , Len M. Pismen

Consistency models imitate the multi-step sampling of score-based diffusion in a single forward pass of a neural network. They can be learned in two ways: consistency distillation and consistency training. The former relies on the true…

Machine Learning · Computer Science 2025-07-03 Thibaut Issenhuth , Sangchul Lee , Ludovic Dos Santos , Jean-Yves Franceschi , Chansoo Kim , Alain Rakotomamonjy