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Related papers: Low-rank Linear Fluid-structure Interaction Discre…

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The macroscopic properties of materials that we observe and exploit in engineering application result from complex interactions between physics at multiple length and time scales: electronic, atomistic, defects, domains etc. Multiscale…

When a multicomponent liquid composed of particles with random interactions is slowly cooled below the freezing temperature, the fluid reorganises in order to increase (decrease) the number of strong (weak) attractive interactions and…

Soft Condensed Matter · Physics 2019-07-24 Kulveer Singh , Yitzhak Rabin

We employ three numerical methods to explore the motion of low Reynolds number swimmers, modeling the hydrodynamic interactions by means of the Oseen tensor approximation, lattice Boltzmann simulations and multiparticle collision dynamics.…

Soft Condensed Matter · Physics 2007-05-23 David J. Earl , C. M. Pooley , J. F. Ryder , Irene Bredberg , J. M. Yeomans

The electrostatic interaction in ionic fluids is well-known to give rise to a characteristic phase behavior and structure. Sometimes its long range is proposed to single out the electrostatic potential over other interactions with shorter…

Soft Condensed Matter · Physics 2015-05-05 Hendrik Bartsch , Oliver Dannenmann , Markus Bier

Flexible slender structures such as rods, ribbons, plates, and shells exhibit extreme nonlinear responses bending, twisting, buckling, wrinkling, and self contact, that defy conventional simulation frameworks. Discrete Differential Geometry…

Multi-fluid flows are found in various industrial processes, including metal injection molding and 3D printing. The accuracy of multi-fluid flow modeling is determined by how well interfaces and capillary forces are represented. In this…

Numerical Analysis · Mathematics 2024-05-10 Michel Nohra , Steven Dufour

Moderate deviation principles for empirical measure processes associated with weakly interacting Markov processes are established. Two families of models are considered: the first corresponds to a system of interacting diffusions whereas…

Probability · Mathematics 2015-10-09 Amarjit Budhiraja , Ruoyu Wu

In this paper, we present a generic approach of a dynamical data-driven model order reduction technique for three-dimensional fluid-structure interaction problems. A low-order continuous linear differential system is identified from…

Computational Engineering, Finance, and Science · Computer Science 2023-01-25 Claire Dupont , Florian De Vuyst , Anne-Virginie Salsac

Simulating fluid flows in different virtual scenarios is of key importance in engineering applications. However, high-fidelity, full-order models relying, e.g., on the finite element method, are unaffordable whenever fluid flows must be…

Fluid Dynamics · Physics 2021-11-24 Stefania Fresca , Andrea Manzoni

Fluid-structure interactions are a widespread phenomenon in nature. Although their numerical modeling have come a long way, the application of numerical design tools to these multiphysics problems is still lagging behind. Gradient-based…

Numerical Analysis · Mathematics 2021-09-27 Mohamed Abdelhamid , Aleksander Czekanski

Trajectories of a buoyant spherical solid particle in a linear shear flow were investigated at low Reynolds numbers. A two-dimensional CFD analysis was performed to simulate the solid-fluid flows. Our numerical model, the discrete phase…

Fluid Dynamics · Physics 2019-02-14 Nima Fathi , Seyed Sobhan Aleyasin , Peter Vorobieff , Goodarz Ahmadi

We use molecular dynamics simulations to test integral equation theory predictions for the structure of fluids of spherical particles with eight different piecewise-constant pair interaction forms comprising a hard core and a combination of…

Soft Condensed Matter · Physics 2015-05-01 Kyle B. Hollingshead , Thomas M. Truskett

A nonlinear dynamical system model that approximates a microscopic Gibbs field model for the yielding of a viscoplastic material subjected to varying external stress recently reported in [1] is presented. The predictions of the model are in…

Soft Condensed Matter · Physics 2016-10-04 Sainudiin Raazesh , Moyers-Gonzalez Miguel , Burghelea Teodor

Plastic deformation of heterogeneous solid structures is often characterized by random intermittent local plastic events. On the mesoscale this feature can be represented by a spatially fluctuating local yield threshold. Here we study the…

Statistical Mechanics · Physics 2023-02-16 Dénes Berta , Gábor Péterffy , Péter Dusán Ispánovity

Interfacial fluctuations in a two-phase binary fluid mixture reveal signatures of underlying physical processes that occur within each phase and on a range of spatial and temporal scales. In this study, we investigate a model binary fluid…

Fluid Dynamics · Physics 2026-03-04 Samuel Z Khiangte , Triparna Sanyal , Sumantra Sarkar , Nairita Pal

Thin liquid films on surfaces are part of our everyday life, they serve e.g. as coatings or lubricants. The stability of a thin layer is governed by interfacial forces, described by the effective interface potential, and has been subject of…

Soft Condensed Matter · Physics 2015-06-04 Oliver Bäumchen , Renate Fetzer , Mischa Klos , Matthias Lessel , Ludovic Marquant , Hendrik Hähl , Karin Jacobs

The challenging problem of conducting fully Bayesian inference for the reaction rate constants governing stochastic kinetic models (SKMs) is considered. Given the challenges underlying this problem, the Markov jump process representation is…

Computation · Statistics 2019-01-10 Andrew Golightly , Emma Bradley , Tom Lowe , Colin S. Gillespie

We study the joint variability of structural information in a hard sphere fluid biased to avoid crystallisation and form fivefold symmetric geometric motifs. We show that the structural covariance matrix approach, originally proposed for…

Disordered Systems and Neural Networks · Physics 2018-07-04 Benjamin M. G. D. Carter , Francesco Turci , Pierre Ronceray , C. Patrick Royall

The influence-matrix formalism provides an alternative route to the classical simulation of quantum dynamics. Because influence matrices retain information only about the effective bath seen by local observables, they are expected to be…

Quantum Physics · Physics 2026-05-14 Cathy Li , Bruno Bertini , Katja Klobas , Tianci Zhou

This paper focuses on the identification of dynamical systems with tailor-made model structures, where neural networks are used to approximate uncertain components and domain knowledge is retained, if available. These model structures are…

Machine Learning · Computer Science 2021-10-29 Marco Forgione , Dario Piga