Quantification of uncertainty in computational fluid dynamics

PJ Roache - Annual review of fluid Mechanics, 1997 - annualreviews.org
▪ Abstract This review covers Verification, Validation, Confirmation and related subjects for
computational fluid dynamics (CFD), including error taxonomies, error estimation and …

Verification and validation in computational fluid dynamics

WL Oberkampf, TG Trucano - Progress in aerospace sciences, 2002 - Elsevier
Verification and validation (V&V) are the primary means to assess accuracy and reliability in
computational simulations. This paper presents an extensive review of the literature in V&V …

NSFnets (Navier-Stokes flow nets): Physics-informed neural networks for the incompressible Navier-Stokes equations

X Jin, S Cai, H Li, GE Karniadakis - Journal of Computational Physics, 2021 - Elsevier
In the last 50 years there has been a tremendous progress in solving numerically the Navier-
Stokes equations using finite differences, finite elements, spectral, and even meshless …

Dense velocity reconstruction from particle image velocimetry/particle tracking velocimetry using a physics-informed neural network

H Wang, Y Liu, S Wang - Physics of fluids, 2022 - pubs.aip.org
The velocities measured by particle image velocimetry (PIV) and particle tracking
velocimetry (PTV) commonly provide sparse information on flow motions. A dense velocity …

[图书][B] Finite element methods for incompressible flow problems

V John - 2016 - Springer
Incompressible flow problems appear in many models of physical processes and
applications. Their numerical simulation requires in particular a spatial discretization. Finite …

[图书][B] Mathematical aspects of discontinuous Galerkin methods

DA Di Pietro, A Ern - 2011 - books.google.com
This book introduces the basic ideas to build discontinuous Galerkin methods and, at the
same time, incorporates several recent mathematical developments. The presentation is to a …

Separable physics-informed neural networks

J Cho, S Nam, H Yang, SB Yun… - Advances in Neural …, 2024 - proceedings.neurips.cc
Physics-informed neural networks (PINNs) have recently emerged as promising data-driven
PDE solvers showing encouraging results on various PDEs. However, there is a …

Code verification by the method of manufactured solutions

PJ Roache - J. Fluids Eng., 2002 - asmedigitalcollection.asme.org
Verification of Calculations involves error estimation, whereas Verification of Codes involves
error evaluation, from known benchmark solutions. The best benchmarks are exact …

A review of droplet bouncing behaviors on superhydrophobic surfaces: Theory, methods, and applications

H Wang, H Lu, W Zhao - Physics of Fluids, 2023 - pubs.aip.org
The phenomenon of droplet bouncing on superhydrophobic surfaces has received
extensive attention in the academic and industrial fields, as it is critical for various …

[图书][B] Scientific Computation

P Joly, A Quarteroni, J Rappaz - 2005 - Springer
Two decades ago when we wrote Spectral Methods in Fluid Dynamics (1988), the subject
was still fairly novel. Motivated by the many favorable comments we have received and the …