Buchumschlag

New Interpretation for error propagation of data-driven Reynolds stress closures via global stability analysis

Fuente: arXiv

Gespeichert in:

Bibliographische Detailangaben
Hauptverfasser:	Shan, Xianglin, Cao, Wenbo, Zhang, Weiwei
Format:	Preprint
Veröffentlicht:	2024
Schlagworte:	Fluid Dynamics
Online-Zugang:	Acceder al recurso
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Ähnliche Einträge

An analysis and solution of ill-conditioning in physics-informed neural networks
von: Cao, Wenbo, et al.
Veröffentlicht: (2024)

Data-driven approach for modeling Reynolds stress tensor with invariance preservation
von: Fu, Xuepeng, et al.
Veröffentlicht: (2023)

Frozen propagation of Reynolds force vector from high-fidelity data into Reynolds-averaged simulations of secondary flows
von: Amarloo, Ali, et al.
Veröffentlicht: (2022)

Towards a Generalized SA Model: Symbolic Regression-Based Correction for Separated Flows
von: Sun, Xuxiang, et al.
Veröffentlicht: (2025)

A solver for subsonic flow around airfoils based on physics-informed neural networks and mesh transformation
von: Cao, Wenbo, et al.
Veröffentlicht: (2024)

A complete state-space solution model for inviscid flow around airfoils based on physics-informed neural networks
von: Cao, Wenbo, et al.
Veröffentlicht: (2024)

Solving compressible Navier-Stokes equations using the feature-enhanced neural network
von: Song, Jiahao, et al.
Veröffentlicht: (2026)

FENN: Feature-enhanced neural network for solving partial differential equations involving fluid mechanics
von: Song, Jiahao, et al.
Veröffentlicht: (2025)

A note on the error analysis of data-driven closure models for large eddy simulations of turbulence
von: Chakraborty, Dibyajyoti, et al.
Veröffentlicht: (2024)

Reynolds stress scaling in the near-wall region
von: Smits, Alexander J., et al.
Veröffentlicht: (2021)

Internal stresses in low-Reynolds-number fractal aggregates
von: Polimeno, Matteo, et al.
Veröffentlicht: (2024)

Progressive augmentation of Reynolds stress tensor models for secondary flow prediction by computational fluid dynamics driven surrogate optimisation
von: Rincón, M. J., et al.
Veröffentlicht: (2023)

A data-driven convergence booster for accelerating and stabilizing pseudo time-stepping
von: Wang, Xukun, et al.
Veröffentlicht: (2025)

Aerodynamic equilibria and flight stability of plates at intermediate Reynolds numbers
von: Pomerenk, Olivia, et al.
Veröffentlicht: (2024)

Projection-based reduced order modeling and data-driven artificial viscosity closures for incompressible fluid flows
von: Prakash, Aviral, et al.
Veröffentlicht: (2024)

Reynolds stress scaling in the near-wall region of wall-bounded flows
von: Smits, Alexander J., et al.
Veröffentlicht: (2021)

Implementation and verification of the resolved Reynolds stress transport equations in OpenFOAM
von: Rincón, Mario J., et al.
Veröffentlicht: (2025)

A matrix preconditioning framework for physics-informed neural networks based on adjoint method
von: Song, Jiahao, et al.
Veröffentlicht: (2025)

Solving all laminar flows around airfoils all-at-once using a parametric neural network solver
von: Cao, Wenbo, et al.
Veröffentlicht: (2025)

Optimization-Based Discovery of A Non-Attracting Flow State in An Oscillating-Cylinder Wake
von: Dong, Daiwei, et al.
Veröffentlicht: (2026)

Anomalous Reynolds stress and dynamic mechanisms in two-dimensional elasto-inertial turbulence of viscoelastic channel flow
von: Cheng, Haotian, et al.
Veröffentlicht: (2025)

A method for evaluating relations of turbulent normal-stresses by experimental data over a wide range of Reynolds numbers
von: Nagib, Hassan, et al.
Veröffentlicht: (2024)

Alfvén waves at low magnetic Reynolds number: Transitions between diffusion, dispersive Alfvén waves and nonlinear propagation
von: Lalloz, Samy, et al.
Veröffentlicht: (2024)

High Reynolds number trends of centerline mean velocity and normal stress in pipe flow
von: Nagib, Hassan, et al.
Veröffentlicht: (2025)

Physics informed data-driven near-wall modelling for lattice Boltzmann simulation of high Reynolds number turbulent flows
von: Xue, Xiao, et al.
Veröffentlicht: (2024)

Self-scaling tensor basis neural network for Reynolds stress modeling of wall-bounded turbulence
von: Yuan, Zelong, et al.
Veröffentlicht: (2026)

A symbolic regression-based implicit algebraic stress turbulence model: incorporating the production of non-dimensional Reynolds stress deviatoric tensor
von: Ji, Ziqi, et al.
Veröffentlicht: (2025)

Role of flow topology in wind-driven wildfire propagation
von: Viknesh, Siva, et al.
Veröffentlicht: (2024)

Goal-oriented Feature Extraction: a novel approach for enhancing data-driven surrogate model
von: Wang, Xu, et al.
Veröffentlicht: (2024)

Reynolds number required to accurately discriminate between proposed trends of skin friction and normal stress in wall turbulence
von: Nagib, Hassan, et al.
Veröffentlicht: (2023)

Wake dynamics of finite-aspect-ratio rotating circular cylinders at low Reynolds number
von: Zhang, Kai, et al.
Veröffentlicht: (2025)

Phase-based analysis and control of low Reynolds number aeroelastic flows
von: Sumanasiri, Chathura R., et al.
Veröffentlicht: (2025)

Interpretable data-driven turbulence modeling for separated flows using symbolic regression with unit constraints
von: Zhang, Boqian, et al.
Veröffentlicht: (2024)

The Reynolds-Averaged Vortex Force Map Method
von: Liguori, Matteo, et al.
Veröffentlicht: (2026)

Generalizable data-driven turbulence closure modeling on unstructured grids with differentiable physics
von: Kim, Hojin, et al.
Veröffentlicht: (2023)

Comparison of data-driven symmetry-preserving closure models for large-eddy simulation
von: Agdestein, Syver Døving, et al.
Veröffentlicht: (2026)

A total-shear-stress-conserved wall model for large-eddy simulation of high-Reynolds number wall turbulence
von: Liu, Huan-Cong, et al.
Veröffentlicht: (2024)

Turbulence at Low Reynolds Numbers
von: Yu, Ziyue, et al.
Veröffentlicht: (2025)

Mach and Reynolds Number Effects on Transonic Buffet on the XRF-1 Transport Aircraft Wing at Flight Reynolds Number
von: Waldmann, Andreas, et al.
Veröffentlicht: (2022)

Reynolds Number Effects on Lift Enhancement Mechanisms of Dragonfly Wings: Their Effective Ranges and Determination by Local Reynolds Numbers
von: Fujita, Yusuke, et al.
Veröffentlicht: (2025)