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Large-eddy simulations of incompressible Newtonian fluid flows with approximate deconvolution models based on the van Cittert method are reported. The Legendre spectral element method is used for the spatial discretization to solve the…

This paper introduces a new approach to Large-Eddy Simulation (LES) where subgrid-scale (SGS) dissipation is applied proportionally to the degree of local spectral broadening, hence mitigated or deactivated in regions dominated by…

Computational Engineering, Finance, and Science · Computer Science 2018-02-14 Jean-Baptiste Chapelier , Bono Wasistho , Carlo Scalo

Structure-based coarse graining of molecular systems offers a systematic route to reproduce the many-body potential of mean force. Unfortunately, common strategies are inherently limited by the molecular mechanics force field employed.…

Soft Condensed Matter · Physics 2018-12-27 Tristan Bereau , Joseph F. Rudzinski

Computing the electric eddy currents in non-linear materials, such as superconductors, is \E{not straightforward}. The design of superconducting magnets and power applications needs electromagnetic computer modeling, being in many cases a…

Superconductivity · Physics 2017-06-02 Enric Pardo , Milan Kapolka

Turbulent concentric coaxial pipe flows are numerically investigated as canonical problem addressing spanwise curvature effects on heat and momentum transfer that are encountered in various engineering applications. It is demonstrated that…

Fluid Dynamics · Physics 2026-02-04 Marten Klein , Pei-Yun Tsai , Heiko Schmidt

The predictive accuracy of wall-modeled large eddy simulation is studied by systematic simulation campaigns of turbulent channel flow. The effect of wall model, grid resolution and anisotropy, numerical convective scheme and subgrid-scale…

Fluid Dynamics · Physics 2019-04-01 Saleh Rezaeiravesh , Timofey Mukha , Mattias Liefvendahl

A multigrid scheme is proposed for the pressure equation of the incompressible unsteady fluid flow equations, allowing efficient implementation on clusters of modern CPUs, many integrated core devices (MICs), and graphics processing units…

Numerical Analysis · Mathematics 2014-08-19 György Tegze , Gyula I. Tóth

Efficient sampling of the Boltzmann distribution of molecular systems is a long-standing challenge. Recently, instead of generating long molecular dynamics simulations, generative machine learning methods such as normalizing flows have been…

Machine Learning · Computer Science 2024-08-06 Henrik Schopmans , Pascal Friederich

Climate change necessitates rapid expansion of renewable energy, with wind energy offering a scalable and low-impact solution. However, accurate prediction of wind loads and power generation remains challenging due to uncertainties in wind…

Fluid Dynamics · Physics 2026-04-30 Omar Sallam , Mirjam Fürth

We present results from extensive 3-d molecular dynamics (MD) simulations of phase separation kinetics in fluids. A coarse-graining procedure is used to obtain state-of-the-art MD results. We observe an extended period of temporally linear…

Statistical Mechanics · Physics 2015-05-19 Shaista Ahmad , Subir K. Das , Sanjay Puri

Coarse-graining has become an area of tremendous importance within many different research fields. For molecular simulation, coarse-graining bears the promise of finding simplified models such that long-time simulations of large-scale…

Chemical Physics · Physics 2019-09-04 Feliks Nüske , Lorenzo Boninsegna , Cecilia Clementi

This Letter introduces unexpected diffusion properties in dense granular flows, and shows that they result from the development of partially jammed clusters of grains, or granular vortices. Transverse diffusion coefficients $D$ and average…

Soft Condensed Matter · Physics 2017-10-25 Prashidha Kharel , Pierre Rognon

The complex interactions existing between turbulence and mixing in a bluff-body stabilised flame configuration is investigated by means of a wavelet cross-correlation analysis on Large Eddy Simulations. The combined approach allows to…

Fluid Dynamics · Physics 2007-05-23 Stefano Sello , Jacopo Bellazzini

Traditional frameworks for dynamic graphs have relied on processing only the stream of edges added into or deleted from an evolving graph, but not any additional related information such as the degrees or neighbor lists of nodes incident to…

Social and Information Networks · Computer Science 2018-03-01 Guyue Han , Harish Sethu

Cytoplasmic streaming, the coherent flow of cytoplasm, plays a critical role in transport and mixing over large scales in eukaryotic cells. In many large cells, this process is driven by active forces at the cell boundary, such as cortical…

Biological Physics · Physics 2025-02-18 Pyae Hein Htet , Eric Lauga

We investigate the behavior of colloidal suspensions with different volume fractions confined between parallel walls under a range of steady shears. We model the particles using molecular dynamics (MD) with full hydrodynamic interactions…

Soft Condensed Matter · Physics 2014-09-18 Frances E. Mackay , Kyle Pastor , Mikko Karttunen , Colin Denniston

The series expansion of the residual-mean eddy streamfunction and the quasi-Stokes streamfunction are compared up to third order in buoyancy perturbation, both formally and by using several idealised eddy-permitting zonal channel model…

Atmospheric and Oceanic Physics · Physics 2016-05-03 Jan Viebahn , Carsten Eden

We live in an age in which high-performance computing is transforming the way we do science. Previously intractable problems are now becoming accessible by means of increasingly realistic numerical simulations. One of the most enduring and…

Simulating turbulence is critical for many societally important applications in aerospace engineering, environmental science, the energy industry, and biomedicine. Large eddy simulation (LES) has been widely used as an alternative to direct…

Fluid Dynamics · Physics 2023-12-13 Shengyu Chen , Tianshu Bao , Peyman Givi , Can Zheng , Xiaowei Jia

Over the last years, supervised learning (SL) has established itself as the state-of-the-art for data-driven turbulence modeling. In the SL paradigm, models are trained based on a dataset, which is typically computed a priori from a…

Fluid Dynamics · Physics 2022-12-23 Marius Kurz , Philipp Offenhäuser , Andrea Beck
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