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Computational studies of crystal nucleation can be impacted by finite size effects, primarily due to unphysical interactions between crystalline nuclei and their periodic images. It is, however, not always feasible to systematically…

Statistical Mechanics · Physics 2021-01-29 Sarwar Hussain , Amir Haji-Akbari

An efficient technique to simulate turbulent particle-laden flow at high mass loadings within the four-way coupled simulation regime is presented. The technique implements large eddy simulation, discrete phase simulation, a deterministic…

Fluid Dynamics · Physics 2017-09-13 Derrick O. Njobuenwu , Michael Fairweather

In this paper we propose a new modeling framework for large eddy simulations (LES) of particle-laden turbulent flows that captures the interaction between the particle and fluid phase on both the resolved and subgrid-scales. Unlike the vast…

Fluid Dynamics · Physics 2023-10-26 Max Hausmann , Fabien Evrard , Berend van Wachem

A set of interpolating functions of the type f(v)={(sin[v pi/2])/(v pi/2)}^n is analyzed in the context of the smoothed-particle hydrodynamics (SPH) technique. The behaviour of these kernels for several values of the parameter n has been…

Astrophysics · Physics 2011-08-31 Ruben M. Cabezon , Domingo Garcia-Senz , Antonio Relaño

The study of interactions between biomimetic membranes and micron-sized particles is crucial for understanding various biological processes. Here, we control microparticle spontaneous engulfment by giant lipid vesicles by tuning particle…

Soft Condensed Matter · Physics 2025-01-22 Clément Marque , Gaetano D'Avino , Domenico Larobina , Aude Michel , Ali Abou-Hassan , Antonio Stocco

In non-ideal plasmas, the dielectric function has to be treated beyond the random phase approximation. Correlations and well as collisions have to be included. These corrections are known as (dynamical) local field corrections. With the…

Plasma Physics · Physics 2008-12-22 August Wierling

In this article we present a modification of classical Radial Basis Function (RBF) interpolation techniques aimed at reducing oscillations near discontinuities in one and two dimensions. Our approach introduces an adaptive mechanism by…

Numerical Analysis · Mathematics 2026-03-25 José Kuruc , David Levin , Pep Mulet , Juan Ruiz-Álvarez , Dionisio F. Yáñez

Long, shallow microchannels embedded in thick soft materials are widely used in microfluidic devices for lab-on-a-chip applications. However, the bulging effect caused by fluid--structure interactions between the internal viscous flow and…

Fluid Dynamics · Physics 2019-12-03 Xiaojia Wang , Ivan C. Christov

Meshless methods are commonly used to determine numerical solutions to partial differential equations (PDEs) for problems involving free surfaces and/or complex geometries, approximating spatial derivatives at collocation points via local…

Numerical Analysis · Mathematics 2025-10-24 H. Broadley , J. R. C. King , S. J. Lind

Reduced quasilinear (QL) and nonlinear (gradient-driven) models with scale separations, commonly used to interpret experiments and to forecast turbulent transport levels in magnetised plasmas are tested against nonlinear models without…

Diffusion of particles through an heterogenous obstacle line is modeled as a two-dimensional diffusion problem with a one--directional nonlinear convective drift and is examined using two-scale asymptotic analysis. At the scale where the…

Analysis of PDEs · Mathematics 2018-04-24 Emilio N. M. Cirillo , Ida de Bonis , Adrian Muntean , Omar Richardson

Nano-particle agglomeration plays an important role in processes such as spray drying and particle flame synthesis. These processes have in common that nano-particles collide at low concentrations and get irreversibly linked at the point of…

Soft Condensed Matter · Physics 2014-05-01 Gizem Inci , Axel Arnold , Andreas Kronenburg , Rudolf Weeber

The behavior of microgels near surfaces and their adsorption is studied by simple scaling theory. Two different types of microgels can be studied, i.e., fractal type microgels and randomly crosslinked polymer chains. In the first case the…

Soft Condensed Matter · Physics 2009-10-31 Thomas A. Vilgis , Michael Stapper

Coarsening of bicontinuous microstructures is observed in a variety of systems, such as nanoporous metals and mixtures that have undergone spinodal decomposition. To better understand the morphological evolution of these structures during…

Soft Condensed Matter · Physics 2020-10-28 W. Beck Andrews , Kate L. M. Elder , Peter W. Voorhees , Katsuyo Thornton

Polymer particle size constitutes a crucial characteristic of product quality in polymerization. Raman spectroscopy is an established and reliable process analytical technology for in-line concentration monitoring. Recent approaches and…

Machine Learning · Computer Science 2024-03-14 Eleni D. Koronaki , Luise F. Kaven , Johannes M. M. Faust , Ioannis G. Kevrekidis , Alexander Mitsos

The generalization ability of kernel interpolation in large dimensions (i.e., $n \asymp d^{\gamma}$ for some $\gamma>0$) might be one of the most interesting problems in the recent renaissance of kernel regression, since it may help us…

Machine Learning · Computer Science 2024-04-22 Haobo Zhang , Weihao Lu , Qian Lin

The paper deals with two fundamental types of trigonometric polynomials and splines on uniform grids, which allow us to construct interpolation approximations that depend linearly on the values of the interpolated function. Fundamental on…

Numerical Analysis · Mathematics 2019-12-05 V. P. Denysiuk

Given the widespread availability of grids of models for stellar atmospheres, it is necessary to recover intermediate atmospheric models by means of accurate techniques that go beyond simple linear interpolation and capture the intricacies…

Instrumentation and Methods for Astrophysics · Physics 2023-07-26 C. Westendorp Plaza , A. Asensio Ramos , C. Allende Prieto

The use of kernels for nonlinear prediction is widespread in machine learning. They have been popularized in support vector machines and used in kernel ridge regression, amongst others. Kernel methods share three aspects. First, instead of…

Machine Learning · Statistics 2025-08-25 Patrick J. F. Groenen , Michael Greenacre

We discuss the expansion of interaction kernels between anisotropic rigid molecules. The expansion decouples the correlated orientational variables so that it can be utilized to derive macroscopic models. Symmetries of two types are…

Mathematical Physics · Physics 2022-11-09 Jie Xu
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