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With extreme weather events becoming more common, the risk posed by surface water flooding is ever increasing. In this work we propose a model, and associated Bayesian inference scheme, for generating probabilistic (high-resolution…

The wetting dynamics of liquid particles, from coated droplets to soft capsules, holds significant technological interest. Motivated by the need to simulate liquid metal droplet with an oxidize surface layer, in this work we introduce a…

Fluid Dynamics · Physics 2024-02-14 Francesca Pelusi , Fabio Guglietta , Marcello Sega , Othmane Aouane , Jens Harting

Accurate stochastic simulations of hourly precipitation are needed for impact studies at local spatial scales. Statistically, hourly precipitation data represent a difficult challenge. They are non-negative, skewed, heavy tailed, contain a…

Methodology · Statistics 2015-06-22 Erwan Koch , Philippe Naveau

Inference on the extremal behaviour of spatial aggregates of precipitation is important for quantifying river flood risk. There are two classes of previous approach, with one failing to ensure self-consistency in inference across different…

Methodology · Statistics 2022-06-22 Jordan Richards , Jonathan A. Tawn , Simon Brown

Coarsening of precipitates in coherent systems is influenced by the elastic fields of the precipitates and the interfacial curvature. It is also known that if precipitates are connected by dislocations, coarsening is affected by the elastic…

Materials Science · Physics 2024-01-10 Arjun Varma R , Prita Pant , M P Gururajan

We present a model treating the kinetics of adsorption of soluble surface-active molecules at the interface between an aqueous solution and another fluid phase. The model accounts for both the diffusive transport inside the solution and the…

Soft Condensed Matter · Physics 2007-05-23 H. Diamant , D. Andelman

Precipitation is one of the most important meteorological variables for defining the climate dynamics, but the spatial patterns of precipitation have not been fully investigated yet. The complex network theory, which provides a robust tool…

Atmospheric and Oceanic Physics · Physics 2013-08-22 Stefania Scarsoglio , Francesco Laio , Luca Ridolfi

Mineral precipitation and dissolution processes in a porous medium can alter the structure of the medium at the scale of pores. Such changes make numerical simulations a challenging task as the geometry of the pores changes in time in an…

Numerical Analysis · Mathematics 2020-07-13 Manuela Bastidas , Carina Bringedal , Iuliu Sorin Pop

A general phenomenological reaction-diffusion model for flow-induced phase transitions in complex fluids is presented. The model consists of an equation of motion for a nonconserved composition variable, coupled to a Newtonian stress…

Soft Condensed Matter · Physics 2009-11-07 J. L. Goveas , P. D. Olmsted

We introduce and solve a model of hardcore particles on a one dimensional periodic lattice which undergoes an active-absorbing state phase transition at finite density. In this model an occupied site is defined to be active if its left…

Statistical Mechanics · Physics 2009-07-28 Urna Basu , P. K. Mohanty

Even though the phenomenon of evaporation is omnipresent and has immense scientific and technological importance, the research effort to unveil its fundamentals remains inadequately low. As one particular consequence, the textbooks and…

Other Condensed Matter · Physics 2014-06-10 V. V. Semak

A recombination reaction model for high-temperature chemical kinetics is derived from ab initio simulations data. A kinetic recombination rate model is derived using a recently developed ab initio state-specific dissociation model and the…

Chemical Physics · Physics 2020-09-15 Narendra Singh , Thomas Schwartzentruber

The properties of the interface between solid and melt are key to solidification and melting, as the interfacial free energy introduces a kinetic barrier to phase transitions. This makes solidification happen below the melting temperature,…

Statistical Mechanics · Physics 2015-12-02 Bingqing Cheng , Gareth A. Tribello , Michele Ceriotti

Precipitation remains one of the most challenging climate variables to observe and predict accurately. Existing datasets face intricate trade-offs: gauge observations are relatively trustworthy but sparse, satellites provide global coverage…

Atmospheric and Oceanic Physics · Physics 2025-06-24 Sencan Sun , Congyi Nai , Baoxiang Pan , Wentao Li , Lu Li , Xin Li , Efi Foufoula-Georgiou , Yanluan Lin

We examine phase separation in aqueous mixtures due to preferential solvation with a low-density solute (hydrophilic ions or hydrophobic particles). For hydrophilic ions, preferential solvation can stabilize water domains enriched with…

Soft Condensed Matter · Physics 2015-05-20 Ryuichi Okamoto , Akira Onuki

Alkane mixtures are model systems where the influence of surface tension gradients during the spreading and the evaporation of wetting drops can be easily studied. The surface tension gradients are mainly induced by concentration gradients,…

Classical Physics · Physics 2016-08-16 Geoffroy Guéna , Christophe Poulard , Anne-Marie Cazabat

We consider a kinetic model, which describes the sedimentation of rod-like particles in dilute suspensions under the influence of gravity. This model has recently been derived by Helzel and Tzavaras in \cite{HT2015}. Here we restrict our…

Fluid Dynamics · Physics 2017-03-09 Christiane Helzel , Athanasios E. Tzavaras

Model calculations that include the effects of irreversible, environmental couplings on top of a coupled-channels dynamical description of the collision of two complex nuclei are presented. The Liouville-von Neumann equation for the…

Nuclear Theory · Physics 2009-11-13 Alexis Diaz-Torres , David Hinde , Mahananda Dasgupta , Gerard Milburn , Jeff Tostevin

We consider a family of models having an arbitrary positive amount of mass on each site and randomly exchanging an arbitrary amount of mass with nearest neighbor sites. We restrict to the case of diffusive models. We identify a class of…

Statistical Mechanics · Physics 2023-09-29 Monia Capanna , Davide Gabrielli , Dimitrios Tsagkarogiannis

Deep learning has emerged as a promising tool for precipitation downscaling. However, current models rely on likelihood-based loss functions to properly model the precipitation distribution, leading to spatially inconsistent projections…

Atmospheric and Oceanic Physics · Physics 2024-08-02 Jose González-Abad
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