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In-cylinder flow structures and turbulence characteristics are investigated using direct numerical simulations (DNS) in a laboratory-scale engine at technically relevant engine speeds (1500 and 2500 rpm at full load). The data is computed…

流体动力学 · 物理学 2025-06-05 Bogdan A. Danciu , George K. Giannakopoulos , Mathis Bode , Christos E. Frouzakis

The term `history effect' refers to the contribution of any past mass transfer events between a gas bubble and its liquid surroundings towards the current diffusion-driven growth or dissolution dynamics of that same bubble. The history…

When very small particles are suspended in a fluid in motion, they tend to follow the flow. How such tracer particles are mixed, transported, and dispersed by turbulent flow has been successfully described by statistical models. Heavy…

流体动力学 · 物理学 2023-12-21 J. Bec , K. Gustavsson , B. Mehlig

The swimming of an assembly of rigid spheres immersed in a viscous fluid of infinite extent is studied in low Reynolds number hydrodynamics. The instantaneous swimming velocity and rate of dissipation are expressed in terms of the…

流体动力学 · 物理学 2015-05-25 B. U. Felderhof

Particle-laden flows are simulated at various scales using numerical techniques that range from particle-resolved Direct Numerical Simulations (pr-DNS) for small-scale systems to Lagrange point-particle methods for laboratory-scale…

流体动力学 · 物理学 2025-07-29 Alexander Metelkin , Sam Jacob Jacob , Bernhard Vowinckel

Hydrodynamic memory force or Basset force is known since the 19th-century. Its influence on Brownian motion remains, however, mostly unexplored. Here, we investigate its role in nonlinear transport and diffusion within a paradigmatic model…

统计力学 · 物理学 2020-07-22 Igor Goychuk , Thorsten Pöschel

Our experiments on a sphere falling under gravity in Stokes flow show significant history effects. We observe an algebraic, not exponential, relaxation rate to the terminal velocity, validating the solution to the Basset-Boussinesq-Oseen…

流体动力学 · 物理学 2025-06-18 Tomek Jaroslawski , Divya Jaganathan , Rama Govindarajan , Beverley McKeon

Dissipative particle dynamics is a widely used mesoscale technique for the simulation of hydrodynamics (as well as immersed particles) utilizing coarse-grained molecular dynamics. While the method is capable of describing any fluid, the…

计算物理 · 物理学 2019-10-22 Ryan C. Krafnick , Angel E. Garcia

Numerical simulation of fluids plays an essential role in modeling many physical phenomena, such as weather, climate, aerodynamics and plasma physics. Fluids are well described by the Navier-Stokes equations, but solving these equations at…

流体动力学 · 物理学 2022-04-27 Dmitrii Kochkov , Jamie A. Smith , Ayya Alieva , Qing Wang , Michael P. Brenner , Stephan Hoyer

A popular method of forcing the fluid in Direct Numerical Simulations of turbulence is to take the body force proportional to the projection of the velocity of the fluid onto its lowest Fourier modes, while keeping the injected external…

流体动力学 · 物理学 2007-05-23 Charles R. Doering , Nikola P. Petrov

We propose a physics-constrained machine learning method-based on reservoir computing- to time-accurately predict extreme events and long-term velocity statistics in a model of turbulent shear flow. The method leverages the strengths of two…

流体动力学 · 物理学 2021-04-14 Nguyen Anh Khoa Doan , Wolfgang Polifke , Luca Magri

In this work, based on the moving-least-squares immersed boundary method, we proposed a new technique to improve the calculation of the volume force representing the body boundary. For boundary with simple geometry, we theoretically analyse…

数值分析 · 数学 2021-10-27 Wenyuan Chen , Shufan Zou , Qingdong Cai , Yantao Yang

Three-dimensional miscible Rayleigh--Taylor (RT) turbulence at small Atwood number and at Prandtl number one is investigated by means of high resolution direct numerical simulations of the Boussinesq equations. RT turbulence is a…

混沌动力学 · 物理学 2015-05-19 G. Boffetta , A. Mazzino , S. Musacchio , L. Vozella

The impact of turbulent fluctuations on the forces exerted by a fluid on a towed spherical particle is investigated by means of high-resolution direct numerical simulations. The measurements are carried out using a novel scheme to integrate…

流体动力学 · 物理学 2016-11-21 Holger Homann , Jérémie Bec , Rainer Grauer

We propose a particle-based method to simulate thin-film fluid that jointly facilitates aggressive surface deformation and vigorous tangential flows. We build our dynamics model from the surface tension driven Navier-Stokes equation with…

流体动力学 · 物理学 2021-05-18 Mengdi Wang , Yitong Deng , Xiangxin Kong , Aditya H. Prasad , Shiying Xiong , Bo Zhu

We report a high-resolution numerical study of two-dimensional (2D) miscible Rayleigh-Taylor (RT) incompressible turbulence with the Boussinesq approximation. An ensemble of 100 independent realizations were performed at small Atwood number…

流体动力学 · 物理学 2015-06-16 Quan Zhou

Consider the dynamics of a gas bubble in an inviscid, compressible liquid with surface tension. Kinematic and dynamic boundary conditions couple the bubble surface deformation dynamics with the dynamics of waves in the fluid. This system…

偏微分方程分析 · 数学 2015-03-14 A. M. Shapiro , M. I. Weinstein

Particle methods play an important role in computational fluid dynamics, but they are among the most difficult to implement and solve. The most common method is smoothed particle hydrodynamics, which is suitable for problem settings that…

流体动力学 · 物理学 2025-08-26 Masato Shibukawa , Naoya Ozaki , Maximilien Berthet

The piece-wise parabolic method (PPM) is applied to simulations of forced isotropic turbulence with Mach numbers $\sim 0.1... 1$. The equation of state is dominated by the Fermi pressure of an electron-degenerate fluid. The dissipation in…

天体物理学 · 物理学 2007-05-23 W. Schmidt , W. Hillebrandt , J. C. Niemeyer

In particle-laden turbulent wall flows, lift forces can influence the near-wall turbulence. This has been recently observed in particle-resolved simulations, which, however, are too expensive to be used in upscaled models. Instead,…

流体动力学 · 物理学 2024-07-29 Wei Gao , Pengyu Shi , Matteo Parsani , Pedro Costa