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Current hydrological modeling methods combine data-driven Machine Learning (ML) algorithms and traditional physics-based models to address their respective limitations incorrect parameter estimates from rigid physics-based models and the…

Machine Learning · Computer Science 2024-02-22 Mostafa Esmaeilzadeh , Melika Amirzadeh

We present an immersed interface method for the vorticity-velocity form of the 2D Navier Stokes equations that directly addresses challenges posed by multiply connected domains, nonconvex obstacles, and the calculation of force…

Fluid Dynamics · Physics 2022-07-13 James Gabbard , Thomas Gillis , Philippe Chatelain , Wim M. van Rees

In this work we propose a novel Hybrid High-Order method for the incompressible Navier--Stokes equations based on a formulation of the convective term including Temam's device for stability. The proposed method has several advantageous…

Numerical Analysis · Mathematics 2018-10-11 Lorenzo Botti , Daniele Di Pietro , Jérôme Droniou

In the theory of the Navier-Stokes equations, the viscous fluid in incompressible flow is modelled as a homogeneous and dense assemblage of constituent "fluid particles" with viscous stress proportional to rate of strain. The crucial…

Fluid Dynamics · Physics 2022-08-23 Wennan Zou

Density functional theory (DFT) is a fundamental method for simulating quantum chemical properties, but it remains expensive due to the iterative self-consistent field (SCF) process required to solve the Kohn-Sham equations. Recently, deep…

Computational Physics · Physics 2025-10-23 Seongsu Kim , Nayoung Kim , Dongwoo Kim , Sungsoo Ahn

The presented research paper illustrates the development of a new methodology to solve 2-dimensional (2D) Navier-Stoke equations, which Pukhnachev proposed through introducing unknown functions in the stream and pressure functions of fluid…

Fluid Dynamics · Physics 2022-09-07 Mohit Kumar Srivastava , Love Trivedi , Rakshit Kaushik

The paper is devoted to the simulation of maritime two-phase flows of air and water. Emphasis is put on an extension of the classical Volume-of-Fluid (VoF) method by a diffusive contribution derived from a Cahn-Hilliard (CH) model and its…

Computational Physics · Physics 2020-03-24 Niklas Kühl , Michael Hinze , Thomas Rung

In this article, we present a cut finite element method for two-phase Navier-Stokes flows. The main feature of the method is the formulation of a unified continuous interior penalty stabilisation approach for, on the one hand, stabilising…

Numerical Analysis · Computer Science 2019-05-01 Susanne Claus , Pierre Kerfriden

Weakly-compressible particle-based discretization methods, utilized for the solution of the subsonic Navier-Stokes equation, are gaining increasing popularity in the fluid dynamics community. One of the most popular among these methods is…

Fluid Dynamics · Physics 2021-08-18 Max Okraschevski , Niklas Buerkle , Rainer Koch , Hans-Joerg Bauer

We consider surface finite elements and a semi-implicit time stepping scheme to simulate fluid deformable surfaces. Such surfaces are modeled by incompressible surface Navier-Stokes equations with bending forces. Here, we consider closed…

Numerical Analysis · Mathematics 2023-05-03 Veit Krause , Axel Voigt

Computational fluid dynamics is both a thriving research field and a key tool for advanced industry applications. The central challenge is to simulate turbulent flows in complex geometries, a compute-power intensive task due to the large…

In this work, we design and analyze semi/fully-discrete virtual element approximations for the time-dependent Navier--Stokes-Cahn--Hilliard equations, modeling the dynamics of two-phase incompressible fluid flows with diffuse interfaces. A…

Numerical Analysis · Mathematics 2026-01-27 Alberth Silgado , Giuseppe Vacca

The simulation of large open water surface is challenging using a uniform volumetric discretization of the Navier-Stokes equations. Simulating water splashes near moving objects, which height field methods for water waves cannot capture,…

Graphics · Computer Science 2021-09-21 Libo Huang , Ziyin Qu , Xun Tan , Xinxin Zhang , Dominik L. Michels , Chenfanfu Jiang

Understanding turbulence is the key to our comprehension of many natural and technological flow processes. At the heart of this phenomenon lies its intricate multi-scale nature, describing the coupling between different-sized eddies in…

We apply a continuous data assimilation method to the Navier-Stokes-Fourier system governing the evolution of a compressible, rotating and thermally driven fluid. A rigorous proof of the tracking property is given in the asymptotic regime…

Analysis of PDEs · Mathematics 2025-10-24 Eduard Feireisl , Wladimir Neves

Drawing inspiration from the lateral lines of fish, the inference of flow characteristics via surface-based data has drawn considerable attention. The current approaches often rely on analytical methods tailored exclusively for potential…

Fluid Dynamics · Physics 2023-11-03 Colin Rodwell , Kumar Sourav , Phanindra Tallapragada

We propose a fourth order Navier-Stokes solver based on the immersed interface method (IIM), for flow problems with stationary and one-way coupled moving boundaries and interfaces. Our algorithm employs a Runge-Kutta-based projection method…

Fluid Dynamics · Physics 2025-08-22 Xinjie Ji , Changxiao Nigel Shen , Wim M. van Rees

We introduce a continuous data assimilation (downscaling) algorithm for the two-dimensional Navier-Stokes equations employing coarse mesh measurements of only one component of the velocity field. This algorithm can be implemented with a…

Analysis of PDEs · Mathematics 2016-03-23 Aseel Farhat , Evelyn Lunasin , Edriss S. Titi

This article focusses on the analysis of a conforming finite element method for the time-dependent incompressible Navier-Stokes equations. For divergence-free approximations, in a semi-discrete formulation, we prove error estimates for the…

Numerical Analysis · Mathematics 2018-03-20 Philipp W. Schroeder , Gert Lube

A hybrid physics-machine learning modeling framework is proposed for the surface vehicles' maneuvering motions to address the modeling capability and stability in the presence of environmental disturbances. From a deep learning perspective,…

Robotics · Computer Science 2025-03-27 Zihao Wang , Jian Cheng , Liang Xu , Lizhu Hao , Yan Peng
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