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Spatially-periodic channels are increasingly attracting attention as an efficient alternative to packed columns for a number of analytical and engineering processes. In incompressible flows, the periodic geometry allows to compute the flow…

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 develop a $ P $-multigrid solver to simulate locally preconditioned unsteady compressible Navier-Stokes equations at low Mach numbers with implicit high-order methods. Specifically, the high-order flux reconstruction/correction procedure…

Computational Physics · Physics 2019-08-13 Lai Wang , Meilin Yu

Solving high-dimensional PDE-governed inverse problems is often challenging due to complex non-Gaussian posterior distributions, expensive forward model evaluations, and misspecified prior information. To address these issues, we propose a…

Machine Learning · Computer Science 2026-05-29 Yueyang Wang , Xili Wang , Kejun Tang , Xiaoliang Wan , Tao Zhou , Chao Yang

Simulating the interaction of fluids with immersed moving solids is playing an important role for gaining a better quantitative understanding of how fluid dynamics is altered by the presence of obstacles and which forces are exerted on the…

Accurate simulation of fluid flow in porous media is challenging due to complex pore-space geometries and the computational cost of solving the Navier-Stokes equations. This difficulty is particularly important when repeated simulations are…

Machine Learning · Computer Science 2026-05-21 Rafał Topolnicki , Paweł Dłotko , Maciej Matyka

We prove the existence and uniqueness of strong solutions to the steady isentropic compressible Navier-Stokes equations with inflow boundary conditions for density and mixed boundary conditions for the velocity around a shear flow. In…

Analysis of PDEs · Mathematics 2022-04-19 Wen-Gang Yang

Immersed methods discretize boundary conditions for complex geometries on background Cartesian grids. This makes such methods especially suitable for two-way coupled flow-body problems, where the body mechanics are partially driven by…

Fluid Dynamics · Physics 2025-04-01 Xinjie Ji , James Gabbard , Wim M. van Rees

We construct a class of spatially polynomial velocity fields that are exact solutions of the planar unsteady Navier-Stokes equation. These solutions can be used as simple benchmarks for testing numerical methods or verifying the feasibility…

Fluid Dynamics · Physics 2020-05-20 Tiemo Pedergnana , David Oettinger , Gabriel Provencher-Langlois , George Haller

The Navier-Stokes-$\alpha$ equations belong to the family of LES (Large Eddy Simulation) models whose fundamental idea is to capture the influence of the small scales on the large ones without computing all the whole range present in the…

Analysis of PDEs · Mathematics 2014-01-27 Juan Vicente Gutiérrez-Santacreu , Marko Antonio Rojas-Medar

We investigate the reconstruction of a turbulent flow field in the atmospheric boundary layer from a time series of lidar measurements, using Large-Eddy Simulations (LES) and a 4D-Var data assimilation algorithm. This leads to an…

Fluid Dynamics · Physics 2020-11-17 Pieter Bauweraerts , Johan Meyers

We show the existence and the regularity properties of the weak solutions to the two-dimensional stationary incompressible inhomogeneous Navier-Stokes equations with variable viscosity coefficient, by analyzing a fourth-order nonlinear…

Analysis of PDEs · Mathematics 2022-05-09 Zihui He , Xian Liao

In this work, we propose a new analysis strategy to establish an a priori estimate of the weak solutions to the coupled steady-state dual-porosity-Navier-Stokes fluid flow model with the Beavers-Joseph-Saffman interface condition. The most…

Analysis of PDEs · Mathematics 2022-01-03 Di Yang , Yinnian He , Luling Cao

We derive an efficient stochastic algorithm for inverse problems that present an unknown linear forcing term and a set of nonlinear parameters to be recovered. It is assumed that the data is noisy and that the linear part of the problem is…

Numerical Analysis · Mathematics 2019-09-17 Darko Volkov

We study Bayesian data assimilation (filtering) for time-evolution PDEs, for which the underlying forward problem may be very unstable or ill-posed. Such PDEs, which include the Navier-Stokes equations of fluid dynamics, are characterized…

Analysis of PDEs · Mathematics 2022-07-27 Samuel Lanthaler , Siddhartha Mishra , Franziska Weber

In this paper, a novel immersed boundary method is developed, validated, and applied. Through devising a second-order three-step flow reconstruction scheme, the proposed method is able to enforce the Dirichlet, Neumann, Robin, and Cauchy…

Fluid Dynamics · Physics 2018-09-10 Huangrui Mo , Fue-Sang Lien , Fan Zhang , Duane S. Cronin

Gravity inversion is a commonly applied data analysis technique in the field of geophysics. While machine learning methods have previously been explored for the problem of gravity inversion, these are deterministic approaches returning a…

We develop a semi-implicit algorithm for time-accurate simulation of the compressible Navier-Stokes equations, with special reference to wall-bounded flows. The method is based on linearization of the partial convective fluxes associated…

Fluid Dynamics · Physics 2016-08-31 Davide Modesti , Sergio Pirozzoli

Inverse problems, i.e., estimating parameters of physical models from experimental data, are ubiquitous in science and engineering. The Bayesian formulation is the gold standard because it alleviates ill-posedness issues and quantifies…

Machine Learning · Statistics 2024-05-28 Sharmila Karumuri , Ilias Bilionis

Computational Fluid Dynamics (CFD) simulation by the numerical solution of the Navier-Stokes equations is an essential tool in a wide range of applications from engineering design to climate modeling. However, the computational cost and…

Computational Physics · Physics 2021-11-29 Mateus Dias Ribeiro , Abdul Rehman , Sheraz Ahmed , Andreas Dengel