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Advancements in computational fluid mechanics have largely relied on Newtonian frameworks, particularly through the direct simulation of Navier-Stokes equations. In this work, we propose an alternative computational framework that employs…

Fluid Dynamics · Physics 2024-12-10 H. Sababha , A. Elmaradny , H. Taha , M. Daqaq

We provide a new algebraic technique to solve the sequential flow problem in polynomial space. The task is to maximise the flow through a graph where edge capacities can be changed over time by choosing a sequence of capacity labelings from…

Optimization and Control · Mathematics 2026-02-09 Hugo Gimbert , Corto Mascle , Patrick Totzke

There is a Computational fluid dynamics (CFD) method of incorporating the DNN inference to reduce the computational cost. The reduction is realized by replacing some calculations by DNN inference. The cost reduction depends on the…

Despite its numerical challenges, finite element method is used to compute viscous fluid flow. A consensus on the cause of numerical problems has been reached; however, general algorithms---allowing a robust and accurate simulation for any…

Computational Engineering, Finance, and Science · Computer Science 2019-02-05 Bilen Emek Abali

Computational fluid dynamics (CFD) is a cornerstone of classical scientific computing, and there is growing interest in whether quantum computers can accelerate such simulations. To date, the existing proposals for fault-tolerant quantum…

Many problems in science and engineering can be represented by a set of partial differential equations (PDEs) through mathematical modeling. Mechanism-based computation following PDEs has long been an essential paradigm for studying topics…

Machine Learning · Computer Science 2022-11-21 Shudong Huang , Wentao Feng , Chenwei Tang , Jiancheng Lv

Physics-Informed Neural Networks have emerged as a promising methodology for solving PDEs, gaining significant attention in computer science and various physics-related fields. Despite being demonstrated the ability to incorporate the…

Machine Learning · Computer Science 2025-05-01 Yao-Hsuan Tsai , Hsiao-Tung Juan , Pao-Hsiung Chiu , Chao-An Lin

Deep Learning methods have seen a wide range of successful applications across different industries. Up until now, applications to physical simulations such as CFD (Computational Fluid Dynamics), have been limited to simple test-cases of…

Machine Learning · Computer Science 2024-05-20 Giuseppe Bruni , Sepehr Maleki , Senthil K. Krishnababu

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

In this article, we analyze a two-level finite element method for the equations of motion arising in the flow of 2D Oldroyd model with non-smooth initial data. It involves solving the non-linear problem on a coarse grid of mesh-size $H$ and…

Numerical Analysis · Mathematics 2012-11-26 Deepjyoti Goswami

A part of non-Newtonian fluids are yield stress fluids. They require a minimum stress to flow. Below this minimum value, yield stress fluids remain solid. To date, 1D and 2D numerical models have been used predominantly to study free…

Fluid Dynamics · Physics 2018-08-03 N Schaer , J. Vazquez , M. Dufresne , G Isenmann , J. Wertel

Driven by the advancement of GPUs and AI, the field of Computational Fluid Dynamics (CFD) is undergoing significant transformations. This paper bridges the gap between the machine learning and CFD communities by deconstructing…

Fluid Dynamics · Physics 2025-11-26 Neil Ashton , Johannes Brandstetter , Siddhartha Mishra

CFD-DEM is used to simulate solid-fluid systems. DEM models the motion of discrete particles while CFD models the fluid phase. Coupling both necessitates the calculation of the void fraction and the solid-fluid forces resulting in a…

Fluid Dynamics · Physics 2023-01-06 Toni El Geitani , Shahab Golshan , Bruno Blais

The finite element method is used to approximately solve boundary value problems for differential equations. The method discretises the parameter space and finds an approximate solution by solving a large system of linear equations. Here we…

Quantum Physics · Physics 2016-03-23 Ashley Montanaro , Sam Pallister

A very simple and accurate numerical method which is applicable to systems of differentio-integral equations with quite general boundary conditions has been devised. Although the basic idea of this method stems from the Keller Box method,…

Fluid Dynamics · Physics 2014-09-30 Jian-Jun Shu , Graham Wilks

Data-driven methods demonstrate considerable potential for accelerating the inherently expensive computational fluid dynamics (CFD) solvers. Nevertheless, pure machine-learning surrogate models face challenges in ensuring physical…

Fluid Dynamics · Physics 2024-09-12 Clément Caron , Philippe Lauret , Alain Bastide

Application of nonlinearity continuation method to numerical solution of steady-state groundwater flow in variably saturated conditions is presented. In order to solve the system of nonlinear equations obtained by finite volume…

Numerical Analysis · Mathematics 2020-08-04 Denis Anuprienko , Ivan Kapyrin

In this paper, we consider the finite difference method for the generalized two-dimensional (2D) multi-term time-fractional Oldroyd-B fluid model, which is a subclass of non-Newtonian fluids. Different from the general multi-term time…

Numerical Analysis · Mathematics 2019-03-20 Yanqin Liu , Fawang Liu , Libo Feng , Baogui Xin

This paper presents a new finite difference method, called {\varphi}-FD, inspired by the {\phi}-FEM approach for solving elliptic partial differential equations (PDEs) on general geometries. The proposed method uses Cartesian grids,…

Numerical Analysis · Mathematics 2025-05-28 Michel Duprez , Vanessa Lleras , Alexei Lozinski , Vincent Vigon , Killian Vuillemot

The design of microfluidic devices is a cumbersome and tedious process that can be significantly improved by simulation. Methods based on Computational Fluid Dynamics (CFD) are considered state-of-the-art, but require extensive compute time…

Computational Engineering, Finance, and Science · Computer Science 2024-01-17 Michel Takken , Robert Wille