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A kinetic-fluid model describing the evolutions of disperse two-phase flows is considered. The model consists of the Vlasov-Fokker-Planck equation for the particles (disperse phase) coupled with the compressible Navier-Stokes equations for…

Analysis of PDEs · Mathematics 2017-04-06 Fucai Li , Yanmin Mu , Dehua Wang

We present a derivation of a stochastic model of Navier Stokes equations that relies on a decomposition of the velocity fields into a differentiable drift component and a time uncorrelated uncertainty random term. This type of decomposition…

Fluid Dynamics · Physics 2015-06-15 Etienne Mémin

This work focuses on the development and analysis of a partitioned numerical method for moving domain, fluid-structure interaction problems. We model the fluid using incompressible Navier-Stokes equations, and the structure using linear…

Numerical Analysis · Mathematics 2020-07-03 Anyastassia Seboldt , Martina Bukač

This thesis deals with the investigation of a H(div)-conforming hybrid discontinuous Galerkin discretization for incompressible turbulent flows. The discretization method provides many physical and solving-oriented properties, which may be…

Computational Engineering, Finance, and Science · Computer Science 2020-09-25 Xaver Mooslechner

Coherent structures/motions in turbulence inherently give rise to intermittent signals with sharp peaks, heavy-skirt, and skewed distributions of velocity increments, highlighting the non-Gaussian nature of turbulence. That suggests that…

Computational Engineering, Finance, and Science · Computer Science 2019-09-24 Mehdi Samiee , Ali Akhavan-Safaei , Mohsen Zayernouri

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…

Fluid Dynamics · Physics 2021-05-18 Mengdi Wang , Yitong Deng , Xiangxin Kong , Aditya H. Prasad , Shiying Xiong , Bo Zhu

Finding the distribution of the velocities and pressures of a fluid by solving the Navier-Stokes equations is a principal task in the chemical, energy, and pharmaceutical industries, as well as in mechanical engineering and the design of…

Machine Learning · Computer Science 2024-07-16 Alexandr Sedykh , Maninadh Podapaka , Asel Sagingalieva , Karan Pinto , Markus Pflitsch , Alexey Melnikov

Numerical simulations of turbulence provide non-intrusive access to all the resolved scales, although they often invoke idealizations that can compromise realism. In contrast, experimental measurements probe the true flow with lesser…

Fluid Dynamics · Physics 2021-09-22 Tamer A. Zaki , Mengze Wang

In recent literature several derivations of incompressible Navier-Stokes type equations that model the dynamics of an evolving fluidic surface have been presented. These derivations differ in the physical principles used in the modeling…

Mathematical Physics · Physics 2021-10-28 Philip Brandner , Arnold Reusken , Paul Schwering

This article analyses the assumptions regarding the influence of pressure forces during the calculation of the motion of a Newtonian fluid. The purpose of the analysis is to determine the reasonableness of the assumptions and their impact…

Fluid Dynamics · Physics 2013-01-29 V. A. Budarin

Using Stokesian dynamics simulations, we examine the flow of a monodisperse, neutrally buoyant, homogeneous suspension of non-Brownian solid spheres in simple shear, starting from a large number of independent hard-sphere distributions and…

Materials Science · Physics 2019-06-19 M. Marchioro , A. Acrivos

Learning and predicting the dynamics of physical systems requires a profound understanding of the underlying physical laws. Recent works on learning physical laws involve generalizing the equation discovery frameworks to the discovery of…

Machine Learning · Statistics 2023-10-11 Tapas Tripura , Souvik Chakraborty

Physics-informed deep learning has been developed as a novel paradigm for learning physical dynamics recently. While general physics-informed deep learning methods have shown early promise in learning fluid dynamics, they are difficult to…

Fluid Dynamics · Physics 2024-06-07 Jing Qiu , Jiancheng Huang , Xiangdong Zhang , Zeng Lin , Minglei Pan , Zengding Liu , Fen Miao

This article introduces, and reviews recent work using, a simple optimisation technique for analysing the nonlinear stability of a state in a dynamical system. The technique can be used to identify the most efficient way to disturb a system…

Fluid Dynamics · Physics 2014-08-18 R. R. Kerswell , C. C. T. Pringle , A. P. Willis

Discovering the underlying dynamics of complex systems from data is an important practical topic. Constrained optimization algorithms are widely utilized and lead to many successes. Yet, such purely data-driven methods may bring about…

Dynamical Systems · Mathematics 2023-05-17 Nan Chen , Yinling Zhang

Harnessing data to discover the underlying governing laws or equations that describe the behavior of complex physical systems can significantly advance our modeling, simulation and understanding of such systems in various science and…

Machine Learning · Computer Science 2021-11-17 Zhao Chen , Yang Liu , Hao Sun

A constructive numerical approximation of the two-dimensional unsteady stochastic Navier-Stokes equations of an incompressible fluid is proposed via a pseudo-compressibility technique involving a parameter $\epsilon$. Space and time are…

Numerical Analysis · Mathematics 2022-05-02 Jad Doghman

Over the centuries mathematicians have been challenged by the partial differential equations (PDEs) that describe the motion of fluids in many physical contexts. Important and beautiful results were obtained in the past one hundred years,…

Analysis of PDEs · Mathematics 2023-07-05 Alexey Cheskidov , Mimi Dai , Susan Friedlander

The article provides an analytical solution of the Navier-Stokes equations for the case of the steady flow of an incompressible fluid between two uniformly co-rotating disks. The solution is derived from the asymptotical evolution of…

Fluid Dynamics · Physics 2007-05-23 Milan Batista

The statistical nature of discrete fluid molecules with random thermal motion so far has not been considered in mainstream fluid mechanics based on Navier-Stokes equations, wherein fluids have been treated as a continuum breaking into many…

Fluid Dynamics · Physics 2023-07-17 Haibing Peng
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