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In Search of Data-Driven Improvements to RANS Models Applied to Separated Flows

https://doi.org/10.2514/6.2022-0937
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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1007/s10494-019-00011-5openalex-snapshot
Zonal Eddy Viscosity Models Based on Machine Learning
inferredcites →https://doi.org/10.1007/s10494-019-00089-xopenalex-snapshot
Discovery of Algebraic Reynolds-Stress Models Using Sparse Symbolic Regression
inferredcites →https://doi.org/10.1016/j.compfluid.2020.104431openalex-snapshot
Flows over periodic hills of parameterized geometries: A dataset for data-driven turbulence modeling from direct simulations
inferredcites →https://doi.org/10.1016/j.compfluid.2020.104497openalex-snapshot
Data-driven modelling of the Reynolds stress tensor using random forests with invariance
inferredcites →https://doi.org/10.1016/j.ijheatfluidflow.2017.09.017openalex-snapshot
The development of algebraic stress models using a novel evolutionary algorithm
inferredcites →https://doi.org/10.1016/j.jcp.2020.109413openalex-snapshot
RANS turbulence model development using CFD-driven machine learning
inferredcites →https://doi.org/10.1017/jfm.2016.615openalex-snapshot
Reynolds averaged turbulence modelling using deep neural networks with embedded invariance
inferredcites →https://doi.org/10.1017/jfm.2018.257openalex-snapshot
Numerical study of turbulent separation bubbles with varying pressure gradient and Reynolds number
inferredcites →https://doi.org/10.1063/1.4927765openalex-snapshot
Evaluation of machine learning algorithms for prediction of regions of high Reynolds averaged Navier Stokes uncertainty
inferredcites →https://doi.org/10.1103/physrevfluids.3.074602openalex-snapshot
Physics-informed machine learning approach for augmenting turbulence models: A comprehensive framework
inferredcites →https://doi.org/10.1103/physrevfluids.6.050504openalex-snapshot
Perspectives on machine learning-augmented Reynolds-averaged and large eddy simulation models of turbulence
inferredcites →https://doi.org/10.1103/physrevfluids.6.064607openalex-snapshot
Machine learning-augmented turbulence modeling for RANS simulations of massively separated flows
inferredcites →https://doi.org/10.1103/physrevfluids.6.124602openalex-snapshot
Generalizable physics-constrained modeling using learning and inference assisted by feature-space engineering
inferredcites →https://doi.org/10.1115/fedsm2016-7573openalex-snapshot
Adjoint-Based Aerodynamic Design of Complex Aerospace Configurations
inferredcites →https://doi.org/10.1146/annurev-fluid-010518-040547openalex-snapshot
Turbulence Modeling in the Age of Data
inferredcites →https://doi.org/10.1146/annurev-fluid-010719-060214openalex-snapshot
Machine Learning for Fluid Mechanics
inferredcites →https://doi.org/10.2514/1.j055595openalex-snapshot
Machine-Learning-Augmented Predictive Modeling of Turbulent Separated Flows over Airfoils
inferredcites →https://doi.org/10.2514/1.j056587openalex-snapshot
High-Fidelity Multidisciplinary Sensitivity Analysis and Design Optimization for Rotorcraft Applications
inferredcites →https://doi.org/10.2514/6.2019-1699openalex-snapshot
High-Fidelity Multidisciplinary Sensitivity Analysis Framework for Multipoint Rotorcraft Optimization
inferredcites →https://doi.org/10.2514/6.2019-1884openalex-snapshot
Towards Integrated Field Inversion and Machine Learning With Embedded Neural Networks for RANS Modeling
inferredcites →https://doi.org/10.2514/6.2021-1017openalex-snapshot
Machine learning enhancement of Spalart-Allmaras Turbulence Model using Convolutional Neural Network
inferredcites →https://doi.org/10.2514/6.2021-2903openalex-snapshot
Field Inversion and Machine Learning for turbulence modelling applied to three-dimensional separated flows

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

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Probabilistic Machine Learning to Improve Generalisation of Data-Driven Turbulence Modelling
inferred← citeshttps://doi.org/10.1007/s10494-023-00457-8openalex-snapshot
Modification of the SSG/LRR-Omega Model for Turbulent Boundary Layer Flows in an Adverse Pressure Gradient
inferred← citeshttps://doi.org/10.1007/s10494-024-00595-7openalex-snapshot
Generalization Limits of Data-Driven Turbulence Models
inferred← citeshttps://doi.org/10.1016/j.ast.2022.107843openalex-snapshot
Gradient-Based Shape Optimization for Unsteady Turbulent Simulations Using Field Inversion and Machine Learning
inferred← citeshttps://doi.org/10.1016/j.ast.2025.111194openalex-snapshot
An effective local feature-augmented machine-learning optimization method for enhancing the compressible RANS model in simulating complex flows from transonic to hypersonic regimes
inferred← citeshttps://doi.org/10.1016/j.ijmecsci.2025.110305openalex-snapshot
Gray area mitigation in grid-adaptive simulation for wall-bounded turbulent flows
inferred← citeshttps://doi.org/10.1016/j.jcp.2025.113793openalex-snapshot
Space-dependent aggregation of stochastic data-driven turbulence models
inferred← citeshttps://doi.org/10.1017/jfm.2026.11647openalex-snapshot
The role of the law of the wall in cross-scenario generalisation of data-driven models
inferred← citeshttps://doi.org/10.1063/5.0095592openalex-snapshot
Minimal error partially resolving simulation methods for turbulent flows: A dynamic machine learning approach
inferred← citeshttps://doi.org/10.1063/5.0136420openalex-snapshot
A unified method of data assimilation and turbulence modeling for separated flows at high Reynolds numbers
inferred← citeshttps://doi.org/10.1063/5.0208025openalex-snapshot
A field inversion and symbolic regression enhanced Spalart–Allmaras model for airfoil stall prediction
inferred← citeshttps://doi.org/10.1063/5.0211608openalex-snapshot
An innovative modification to the Menter shear-stress transport turbulence model employing the symbolic regression approach
inferred← citeshttps://doi.org/10.1088/2632-2153/ad7d60openalex-snapshot
Development and deployment of data-driven turbulence model for three-dimensional complex configurations
inferred← citeshttps://doi.org/10.1108/hff-11-2023-0710openalex-snapshot
Data-driven wall modeling for LES involving non-equilibrium boundary layer effects
inferred← citeshttps://doi.org/10.1115/1.4066642openalex-snapshot
Data-Guided Low-Reynolds-Number Corrections for Two-Equation Models
inferred← citeshttps://doi.org/10.1615/thmt-25.100openalex-snapshot
Machine learning for separated turbulent flow simulations: Classical versus dynamic methods
inferred← citeshttps://doi.org/10.2514/1.j062711openalex-snapshot
Turbulence Modeling via Data Assimilation and Machine Learning for Separated Flows over Airfoils
inferred← citeshttps://doi.org/10.2514/1.j062870openalex-snapshot
Data-Enabled Recalibration of the Spalart–Allmaras Model
inferred← citeshttps://doi.org/10.2514/1.j065567openalex-snapshot
Data-Driven Turbulence Modeling for Separated Flows Considering Nonlocal Effect
inferred← citeshttps://doi.org/10.2514/6.2023-1804openalex-snapshot
Patch-wise Training to Improve Convolutional Neural Network Synthetic Upscaling of Computational Fluid Dynamics Simulations
inferred← citeshttps://doi.org/10.2514/6.2024-1572openalex-snapshot
Adapting Reynolds-averaged Navier Stokes Models while Preserving the Basic Calibrations
inferred← citeshttps://doi.org/10.2514/6.2024-2520openalex-snapshot
On Generalizably Improving RANS Predictions of Flow Separation and Reattachment
inferred← citeshttps://doi.org/10.2514/6.2026-1334openalex-snapshot
A Data-Driven k-Equation-Based Framework for Modeling Turbulence Using Sparse Regression
inferred← citeshttps://doi.org/10.2514/6.2026-4397openalex-snapshot
Modification of Turbulence Model for High-Angles-of-Attack Flow Around Aircraft Configuration Using Equation Inference Technique
inferred← citeshttps://doi.org/10.3390/e26121044openalex-snapshot
Physically Consistent Resolving Simulations of Turbulent Flows
inferred← citeshttps://doi.org/10.3390/fluids9120278openalex-snapshot
The Potential of Machine Learning Methods for Separated Turbulent Flow Simulations: Classical Versus Dynamic Methods
inferred← citeshttps://doi.org/10.3390/math11143199openalex-snapshot
A Mathematical Solution to the Computational Fluid Dynamics (CFD) Dilemma
inferred← citeshttps://doi.org/10.55037/lxlaser.20th.17openalex-snapshot
Creating Data-Driven Turbulence Models Using PIV
inferred← citeshttps://doi.org/10.70675/38a58e45zad6az471fz97c7z52c39719e0acopenalex-snapshot
Turbulence closure for the compressible RANS equations assisted by field-inversion and machine-learning
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