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In this study, we present a novel computational framework that integrates the finite volume method with graph neural networks to address the challenges in Physics-Informed Neural Networks(PINNs). Our approach leverages the flexibility of…

Fluid Dynamics · Physics 2024-05-08 Tianyu Li , Yiye Zou , Shufan Zou , Xinghua Chang , Laiping Zhang , Xiaogang Deng

Kinetic approaches, i.e., methods based on the lattice Boltzmann equations, have long been recognized as an appealing alternative for solving incompressible Navier-Stokes equations in computational fluid dynamics. However, such approaches…

Graphics · Computer Science 2018-07-09 Wei Li , Kai Bai , Xiaopei Liu

In this paper, we explore the evolution of plane curves and surfaces governed by the hyperbolic mean curvature flow. We propose a mesh-free approach based on the physics-informed neural networks (PINNs), which eliminates the need for…

Mathematical Physics · Physics 2026-01-19 Shuangshuang Duan , Chunlei He , Shoujun Huang , Dexing Kong

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…

Fluid Dynamics · Physics 2022-04-27 Dmitrii Kochkov , Jamie A. Smith , Ayya Alieva , Qing Wang , Michael P. Brenner , Stephan Hoyer

In this work, we detail the GPU-porting of an in-house pseudo-spectral solver tailored towards large-scale simulations of interface-resolved simulation of drop- and bubble-laden turbulent flows. The code relies on direct numerical…

Fluid Dynamics · Physics 2024-06-04 Alessio Roccon

Incompressible flow solvers based on strong-form meshfree methods represent arbitrary geometries without the need for a global mesh system. However, their local evaluations make it difficult to satisfy incompressibility at the discrete…

Numerical Analysis · Mathematics 2026-05-05 Takeharu Matsuda , Satoshi Ii

Physics-informed neural networks (PINNs) have emerged as a powerful tool for solving inverse problems, especially in cases where no complete information about the system is known and scatter measurements are available. This is especially…

Computational Engineering, Finance, and Science · Computer Science 2023-08-03 Jeremias Garay , Jocelyn Dunstan , Sergio Uribe , Francisco Sahli Costabal

Physics-Informed Neural Networks (PINNs) show significant potential for solving inverse problems, especially when observations are limited and sparse, provided that the relevant physical equations are known. We use PINNs to estimate smooth…

Numerical Analysis · Mathematics 2025-08-06 Moises Sierpe , Ernesto Castillo , Hernan Mella , Felipe Galarce

We present an exponentially convergent semi-implicit meshless algorithm for the solution of Navier-Stokes equations in complex domains. The algorithm discretizes partial derivatives at scattered points using radial basis functions as…

Numerical Analysis · Mathematics 2021-06-15 Shantanu Shahane , Surya Pratap Vanka

Numerical simulation is indispensable in industrial design processes. It can replace expensive experiments and even reduce the need for prototypes. While products designed with the aid of numerical simulation undergo continuous improvement,…

Numerical Analysis · Mathematics 2020-06-04 Henning Wessels , Christian Weißenfels , Peter Wriggers

This paper presents a robust, adaptive numerical scheme for simulating high density ratio and high shear multiphase flows on locally refined Cartesian grids that adapt to the evolving interfaces and track regions of high vorticity. The…

Computational Physics · Physics 2019-09-04 Nishant Nangia , Boyce E. Griffith , Neelesh A. Patankar , Amneet Pal Singh Bhalla

We describe a Physics-Informed Neural Network (PINN) that simulates the flow induced by the astronomical tide in a synthetic port channel, with dimensions based on the Santos - S\~ao Vicente - Bertioga Estuarine System. PINN models aim to…

This communication is devoted to the presentation of our recent results regarding the asymptotic analysis of a viscous flow in a tube with elastic walls. This study can be applied, for example, to the blood flow in an artery. With this aim,…

Analysis of PDEs · Mathematics 2017-03-14 G. Castiñeira , J. M. Rodríguez

We present a novel framework inspired by the Immersed Boundary Method for predicting the fluid-structure interaction of complex structures immersed in flows with moderate to high Reynolds numbers. The main novelties of the proposed…

In this paper, we present a mathematical and numerical model for blood solidification and its rupture in stenosed arteries. The interaction between the blood flow and an existing stenosis in the arterial wall is modeled as a three…

Numerical Analysis · Mathematics 2020-05-15 Fatima Abbas , Ayman Mourad

Fluid flows are omnipresent in nature and engineering disciplines. The reliable computation of fluids has been a long-lasting challenge due to nonlinear interactions over multiple spatio-temporal scales. The compressible Navier-Stokes…

Fluid Dynamics · Physics 2021-12-10 Deniz A. Bezgin , Aaron B. Buhendwa , Nikolaus A. Adams

Mathematical models and numerical simulations offer a non-invasive way to explore cardiovascular phenomena, providing access to quantities that cannot be measured directly. In this study, we start with a one-dimensional multiscale blood…

Machine Learning · Computer Science 2026-04-09 Giulia Bertaglia , Raffaella Fiamma Cabini

This work presents the development, performance analysis and subsequent optimization of a GPU-based spectral hyperviscosity solver for turbulent flows described by the three dimensional incompressible Navier-Stokes equations. The method…

Fluid Dynamics · Physics 2024-04-23 Tobias Rohner , Siddhartha Mishra

We present a new model and a novel loosely coupled partitioned numerical scheme modeling fluid-structure interaction (FSI) in blood flow allowing non-zero longitudinal displacement. Arterial walls are modeled by a {linearly viscoelastic,…

Numerical Analysis · Mathematics 2015-06-05 Martina Bukac , Suncica Canic , Roland Glowinski , Josip Tambaca , Annalisa Quaini

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
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