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This paper presents an analysis approach to finite-time attraction in probability concerns with nonlinear systems described by nonlinear random differential equations (RDE). RDE provide meticulous physical interpreted models for some…

Systems and Control · Computer Science 2016-06-15 Sina Sanjari , Mahdieh Tahmasebi

This text describes a method to simultaneously reconstruct flow states and determine particle properties from Lagrangian particle tracking (LPT) data. LPT is a popular measurement strategy for fluids in which particles in a flow are…

Fluid Dynamics · Physics 2023-11-16 Ke Zhou , Samuel J. Grauer

Algorithms based on normalizing flows are emerging as promising machine learning approaches to sampling complicated probability distributions in a way that can be made asymptotically exact. In the context of lattice field theory,…

A numerical analysis for the fully discrete approximation of an operator Lyapunov equation related to linear SPDEs (stochastic partial differential equations) driven by multiplicative noise is considered. The discretization of the Lyapunov…

Numerical Analysis · Mathematics 2022-05-04 Adam Andersson , Annika Lang , Andreas Petersson , Leander Schroer

High-order CFD is gathering a broadening interest as a future industrial tool, with one such approach being Flux Reconstruction (FR). However, due to the need to mesh complex geometries if FR is to displace current, lower order methods, FR…

Numerical Analysis · Mathematics 2018-11-27 Will Trojak , Rob Watson , Paul G. Tucker

We discuss the irreversibility, nonlocality, and fluctuations, as well as the Lyapunov and hydrodynamic instabilities characterizing atomistic, smooth-particle, and finite-difference solutions of the two-dimensional Rayleigh-B\'enard…

Statistical Mechanics · Physics 2012-05-22 Wm. G. Hoover , Carol G. Hoover

Based on machine learning techniques, we propose a novel method to estimate flow fields using only floating sensor locations. This method does not require either ground-truth velocity fields or governing equations for fluid flows, which is…

Fluid Dynamics · Physics 2026-04-07 Tomoya Oura , Reno Miura , Koji Fukagata

Extracting information on fluid motion directly from images is challenging. Fluid flow represents a complex dynamic system governed by the Navier-Stokes equations. General optical flow methods are typically designed for rigid body motion,…

Machine Learning · Computer Science 2022-06-23 Mingrui Zhang , Jianhong Wang , James Tlhomole , Matthew D. Piggott

We present a new implicit higher-order finite element (FE) approach to efficiently model compressible multicomponent fluid flow on unstructured grids and in fractured porous subsurface formations. The scheme is sequential implicit:…

Computational Physics · Physics 2016-08-25 Joachim Moortgat , Mohammad Amin Amooie , Mohamad Reza Soltanian

We introduce an FFT-based solver for the combinatorial continuous maximum flow discretization applied to computing the minimum cut through heterogeneous microstructures. Recently, computational methods were introduced for computing the…

Computational Engineering, Finance, and Science · Computer Science 2021-09-30 Felix Ernesti , Matti Schneider

In multi-phase fluid flow, fluid-structure interaction, and other applications, partial differential equations (PDEs) often arise with discontinuous coefficients and singular sources (e.g., Dirac delta functions). These complexities arise…

Numerical Analysis · Mathematics 2019-07-24 Chung-Nan Tzou , Samuel Stechmann

Flow field segmentation and classification help researchers to understand vortex structure and thus turbulent flow. Existing deep learning methods mainly based on global information and focused on 2D circumstance. Based on flow field…

Computer Vision and Pattern Recognition · Computer Science 2023-06-16 Xiaorui Bai , Wenyong Wang , Jun Zhang , Yueqing Wang , Yu Xiang

A phase-field method for unstructured grids that is accurate, conservative, and robust is proposed in this work. The proposed method also results in bounded transport of volume fraction, and the interface thickness adapts automatically to…

Fluid Dynamics · Physics 2023-10-18 Hanul Hwang , Suhas S. Jain

The problem of natural convection in a laterally heated three-dimensional cubic cavity under the action of an externally imposed magnetic field is revisited. Flows at the Rayleigh number Ra=10^6 and the Hartmann number Ha=100, and three…

Fluid Dynamics · Physics 2018-05-15 A. Gelfgat , O. Zikanov

Fluid deformation and strain history are central to wide range of fluid mechanical phenomena ranging from fluid mixing and particle transport to stress development in complex fluids and the formation of Lagrangian coherent structures…

Fluid Dynamics · Physics 2025-10-03 Daniel R. Lester , Marco Dentz , Tanguy Le Borgne , Felipe P. J. de Barros

The fractional Laplacian $(-\Delta)^{\alpha/2}$ is the prototypical non-local elliptic operator. While analytical theory has been advanced and understood for some time, there remain many open problems in the numerical analysis of the…

Numerical Analysis · Mathematics 2016-11-02 Yanghong Huang , Adam Oberman

In many applications, the two-dimensional trajectories of fluid particles are available, but little is known about the underlying flow. Oceanic floats are a clear example. To extract quantitative information from such data, one can measure…

Chaotic Dynamics · Physics 2010-04-07 Jean-Luc Thiffeault

A novel pressure-free two-fluid model formulation is proposed for the simulation of one-dimensional incompressible multiphase flow in pipelines and channels. The model is obtained by simultaneously eliminating the volume constraint and the…

Fluid Dynamics · Physics 2020-10-27 B. Sanderse , J. F. H. Buist , R. A. W. M. Henkes

In this paper, a new formalism for the filtered density function (FDF) approach is developed for the treatment of turbulent polydispersed two-phase flows in LES simulations. Contrary to the FDF used for turbulent reactive single-phase…

Fluid Dynamics · Physics 2012-02-07 Sergio Chibbaro , jean-Pierre Minier

Inverse parallel schemes remain indispensable tools for computing the roots of nonlinear systems, yet their dynamical behavior can be unexpectedly rich, ranging from strong contraction to oscillatory or chaotic transients depending on the…

Numerical Analysis · Mathematics 2026-01-21 Mudassir Shams , Andrei Velichko , Bruno Carpentieri
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