QUANTIFICATION OF UNCERTAINTY IN COMPUTATIONAL FLUID DYNAMICS

1997/01/01 by P. J. Roache, Patrick J. Roache · 2,276 citations
Engineering · Mathematics · #Advanced Numerical Methods in Computational Mathematics #Algorithm #Applied mathematics #Computational Fluid Dynamics and Aerodynamics #Computational fluid dynamics #Computer science #Convergence (economics) #Dynamics (music) #Estimation #Estimator #Fluid Dynamics and Turbulent Flows #Fluid dynamics #Machine learning #Mathematical optimization #Mathematics #Mechanics #Nonlinear system #Physics #Statistics #Uncertainty quantification

paper · doi:10.1146/annurev.fluid.29.1.123

published in Annual Review of Fluid Mechanics 29(1), 123-160 (Annual Reviews)

openalex publication_date 1997/01/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/06

Abstract

▪ Abstract This review covers Verification, Validation, Confirmation and related subjects for computational fluid dynamics (CFD), including error taxonomies, error estimation and banding, convergence rates, surrogate estimators, nonlinear dynamics, and error estimation for grid adaptation vs Quantification of Uncertainty.

Cited by

• A Unified Pore-Scale Multiphysics Model for the Integrated Soot Transport-Deposition-Oxidation in Catalytic Diesel Particulate Filters
• 3-Dimensional Adaptive Unstructured Tessellated Look-up Tables for the Approximation of Compton Form Factors
• Experimental Methods for Membrane Applications in Desalination and Water Treatment
• Identifying and optimizing the aeroacoustic source regions of a slot air diffuser
• From patch to channel scale: The evolution of emergent vegetation in a channel
• Modeling environmental contamination in hospital single- and four-bed rooms
• Uncertainty in marine weather routing
• Handling obstacles in pedestrian simulations: Models and optimization
• Numerical Investigation of Coaxial GCH4/LOx Combustion at Supercritical Pressures
• Numerical simulations of an effective two-dimensional model for flows with a transverse magnetic field
• Disjoining Pressure Driven Transpiration of Water in a Simulated Tree

Related

• An Uncertainty-Quantification Framework for Assessing Accuracy, Sensitivity, and Robustness in Computational Fluid Dynamics
• Uncertainty Quantification in Computational Fluid Dynamics: Physics and Machine Learning Based Approaches
• Physics Based & Machine Learning Methods For Uncertainty Estimation In Turbulence Modeling
• Uncertainty Quantification for Multi-fidelity Simulations
• A Validation and Uncertainty Quantification Framework for Eulerian-Eulerian Two-Fluid Model based Multiphase-CFD Solver. Part I: Methodology