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The interaction between turbulence and surface tension is studied numerically using the one-dimensional-turbulence (ODT) model. ODT is a stochastic model simulating turbulent flow evolution along a notional one-dimensional line of sight by…

Fluid Dynamics · Physics 2024-04-16 A. Movaghar , R. Chiodi , M. Oevermann , O. Desjardins , A. R. Kerstein

We study laminar, transitional and turbulent flow in wavy pipes using direct numerical simulations for bulk Reynolds numbers between 1-5300. Flow behaviors are analyzed in terms of the friction factor f and mean velocity statistics for…

Fluid Dynamics · Physics 2026-04-21 Ismail El Mellas , Juan J. Hidalgo , Marco Dentz

The two-dimensional flows around a cylinder between two parallel walls at Re=40 and Re=100 are simulated with computational fluid dynamics (CFD). The governing equations are Navier-Stokes equations. They are discretized with finite volume…

Fluid Dynamics · Physics 2019-02-13 Hua-Shu Dou , An-Qing Ben

The stratified inclined duct (SID) flow provides a canonical model for sustained, buoyancy-driven exchange between two reservoirs of different density, and emerges as a new paradigm in geophysical fluid dynamics. Yet, the flow dynamics…

Fluid Dynamics · Physics 2026-03-18 Rundong Zhou , Adrien Lefauve , Roberto Verzicco , Detlef Lohse

The lattice Boltzmann method with enhanced collisions and rest particles is used to calculate the flow in a two-dimensional lid-driven cavity. The abilitity of this method to compute the velocity and the pressure of an incompressible fluid…

comp-gas · Physics 2009-10-22 W. Miller

Dust explosions are among the most hazardous accidents affecting industrial facilities processing particulate solids. Describing the severity parameters of dust clouds is critical to the safety management and risk assessment of dust…

Wall pressure fluctuations beneath the turbulent boundary layer of high-speed underwater vehicles are crucial for hydro-acoustics and acoustic stealth. However, a comprehensive understanding remains limited due to a lack of high-quality…

Fluid Dynamics · Physics 2025-12-30 Peng Jiang , Haoyu Zhang , Yi Dai , Tao Peng , Bin Xie , Shijun Liao

We present the new code ALCAR developed to model multidimensional, multi energy-group neutrino transport in the context of supernovae and neutron-star mergers. The algorithm solves the evolution equations of the 0th- and 1st-order angular…

High Energy Astrophysical Phenomena · Physics 2015-09-09 Oliver Just , Martin Obergaulinger , H. -Thomas Janka

Flow topology optimization (ToOpt) based on Darcy's source term is widely used in the field of ToOpt. It has a high degree of freedom and requires no initial configuration, making it suitable for conceptual aerodynamic design. Two problems…

Fluid Dynamics · Physics 2024-07-02 Chenyu Wu , Yufei Zhang

A physics-informed convolutional neural network is proposed to simulate two phase flow in porous media with time-varying well controls. While most of PICNNs in existing literatures worked on parameter-to-state mapping, our proposed network…

Machine Learning · Computer Science 2024-10-24 Jungang Chen , Eduardo Gildin , John E. Killough

In turbulence research and flow applications, turbulence models like RaNS (Reynolds averaged Navier-Stokes) models and LES (Large Eddy Simulation) are used. Both models filter the governing flow equations. Thus a scale separation approach…

Fluid Dynamics · Physics 2015-06-17 Christoph Glawe , Heiko Schmidt , Alan R. Kerstein , Rupert Klein

We study dynamic network flows with uncertain input data under a robust optimization perspective. In the dynamic maximum flow problem, the goal is to maximize the flow reaching the sink within a given time horizon $T$, while flow requires a…

Discrete Mathematics · Computer Science 2018-05-07 Corinna Gottschalk , Arie M. C. A. Koster , Frauke Liers , Britta Peis , Daniel Schmand , Andreas Wierz

We investigate Taylor-Couette flow with realistic no-slip boundary conditions at all surfaces through direct numerical simulations (DNS) and theoretical analysis. Imposing physically consistent end-wall conditions at the top and bottom lids…

In this article we examine channel flow subject to spatially varying viscosity in the streamwise direction. The Reynolds number is imposed locally with three different ramps. The setup is reminiscent of transient channel flow, but with a…

Fluid Dynamics · Physics 2020-06-11 Victor Coppo Leite , Elia Merzari

We investigate eddy-viscosity distributions in pressure-driven wall turbulence for three canonical configurations: plane closed-channel flow, open-channel flow with a free-slip surface, and pipe flow. Using direct numerical simulation (DNS)…

Fluid Dynamics · Physics 2026-04-13 Ben-Rui Xu , Ao Xu

A new scheme that tightly couples kinetic turbulence codes across a spatial interface is introduced. This scheme evolves from considerations of competing strategies and down-selection. It is found that the use of a composite kinetic…

Lattice Boltzmann Method (LBM) simulations for turbulent flows over a fractal and non-fractal obstacles are presented. The wake hydrodynamics are compared and discussed in terms of flow relaxation, Strouhal numbers and wake length for…

Fluid Dynamics · Physics 2019-06-26 N. M. Sangtani Lakhwani , F. C. G. A Nicolleau , W. Brevis

In this work we show the application of Sailfish to the study of fluid dynamics in porous media. Sailfish is an open-source software based on the lattice-Boltzmann method. This application of computational fluid dynamics is of particular…

Fluid Dynamics · Physics 2017-11-27 Rodrigo C. V. Coelho , Rodrigo F. Neumann

The hydrodynamics of viscoelastic materials (for example polymer melts and solutions) presents interesting and complex phenomena, for example instabilities and turbulent flow at very low Reynolds numbers due to normal stress effects and the…

Soft Condensed Matter · Physics 2007-05-23 Ellak Somfai , Alexander N. Morozov , Wim van Saarloos

High-fidelity modeling of turbulent flows requires capturing complex spatiotemporal dynamics and multi-scale intermittency, posing a fundamental challenge for traditional knowledge-based systems. While deep generative models, such as…

Machine Learning · Computer Science 2026-04-08 Li Kunpeng , Wan Chenguang , Qu Zhisong , Lim Kyungtak , Virginie Grandgirard , Xavier Garbet , Yu Hua , Ong Yew Soon
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