Copertina

Toward ultra-efficient high-fidelity prediction of bed morphodynamics of large-scale meandering rivers using a novel LES-trained machine learning approach

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Zhang, Zexia, Anjiraki, Mehrshad Gholami, Seyedzadeh, Hossein, Sotiropoulos, Fotis, Khosronejad, Ali
Natura:	Preprint
Pubblicazione:	2024
Soggetti:	Fluid Dynamics
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Wind farm layout optimization using a novel machine learning approach
di: Anjiraki, Mehrshad Gholami, et al.
Pubblicazione: (2025)

Toward ultra-efficient high fidelity predictions of wind turbine wakes: Augmenting the accuracy of engineering models via LES-trained machine learning
di: Santoni, Christian, et al.
Pubblicazione: (2024)

On the interaction of fish and marine hydrokinetic turbines: Insights gained through experimental and computational observations
di: Seyedzadeh, Hossein, et al.
Pubblicazione: (2025)

Large eddy simulation of a utility-scale vertical-axis marine hydrokinetic turbine under live-bed conditions
di: Anjiraki, Mehrshad Gholami, et al.
Pubblicazione: (2025)

Computational study of vertical-axis MHK turbines using a coupled flow-sediment-turbine modeling approach
di: Anjiraki, Mehrshad Gholami, et al.
Pubblicazione: (2025)

From lab to landscape-scale experiments for the morphodynamics of sand dunes
di: Claudin, P., et al.
Pubblicazione: (2024)

The characteristics of the meandering effect in a stratified wake
di: Huang, Xinyi, et al.
Pubblicazione: (2023)

Cost-effective multi-fidelity strategy for the optimization of high-Reynolds number turbine flows guided by LES
di: Matar, Camille, et al.
Pubblicazione: (2025)

Neural-ISAM: A hybrid in-situ machine learning approach for complex manifold-based combustion models in LES of turbulent flames
di: Fush, S. Trevor, et al.
Pubblicazione: (2026)

CaLES: A GPU-accelerated solver for large-eddy simulation of wall-bounded flows
di: Xiao, Maochao, et al.
Pubblicazione: (2024)

Application of a dispersive wave hydro-sediment-morphodynamic model in the Ria Formosa lagoon
di: Kazhyken, Kazbek, et al.
Pubblicazione: (2022)

Data-driven prediction of reversal of large-scale circulation in turbulent convection
di: Katsumi, Daigaku, et al.
Pubblicazione: (2025)

A novel Cercignani-Lampis boundary model for discrete velocity methods in predicting rarefied and multi-scale flows
di: Chen, Jianfeng, et al.
Pubblicazione: (2024)

Prograde and meandering wall modes in rotating Rayleigh-Bénard convection with conducting walls
di: Ravichandran, S., et al.
Pubblicazione: (2023)

Analysis of soot formation in a lab-scale Rich-Quench-Lean combustor using LES with tabulated chemistry
di: Pachano, Leonardo, et al.
Pubblicazione: (2024)

Data-driven prediction of large-scale spatiotemporal chaos with distributed low-dimensional models
di: Constante-Amores, C. Ricardo, et al.
Pubblicazione: (2024)

Scale invariance of intermittency in LES turbulence
di: Magacho, B., et al.
Pubblicazione: (2025)

Persistence of large scale coherent structures in a turbulent pipe flow through an improved lattice Boltzmann approach
di: Magacho, B., et al.
Pubblicazione: (2024)

A high-fidelity and efficient framework for point-particle direct numerical simulation based on multi-block overset grids
di: Wang, Taiyang, et al.
Pubblicazione: (2025)

Dynamic subgrid-scale LES model for turbulent non-Newtonian flows: A priori and a posteriori analyses of Burgers turbulence
di: Amani, E., et al.
Pubblicazione: (2025)

A Kernel-based Resource-efficient Neural Surrogate for Multi-fidelity Prediction of Aerodynamic Field
di: Sarker, Apurba, et al.
Pubblicazione: (2025)

High-efficient machine learning projection method for incompressible Navier-Stokes equations
di: Chen, Ruilin
Pubblicazione: (2025)

On the feasibility of a component-based approach to predict aerodynamic noise from high-speed train bogies
di: Iglesias, Eduardo Latorre, et al.
Pubblicazione: (2024)

Fast buffet onset prediction and optimization method based on a pre-trained flowfield prediction model
di: Yang, Yunjia, et al.
Pubblicazione: (2024)

Empirical large-scale extension of Yakhot's model of strong turbulence
di: Renner, Christoph
Pubblicazione: (2024)

Temporal large-scale intermittency and its impact on the statistics of turbulence
di: Bentkamp, Lukas, et al.
Pubblicazione: (2023)

A CNN-based particle tracking method for large-scale fluid simulations with Lagrangian-Eulerian approaches
di: Luo, Xuan, et al.
Pubblicazione: (2024)

Modal analysis of high-fidelity simulations in turbomachinery
di: Morsbach, Christian, et al.
Pubblicazione: (2024)

A novel simulation approach for concentration-driven evaporation in capillaries
di: Namesnik, Phil, et al.
Pubblicazione: (2025)

A Comparison of LES Inlet Boundary Conditions for Supersonic Jet Flows
di: Abreu, Diego F., et al.
Pubblicazione: (2025)

A Moving Surface Drag Model for LES of Wind over Waves
di: Ayala, Manuel, et al.
Pubblicazione: (2024)

LES of Droplet Impingement: Application to Clean and Laser-Scanned Ice Shapes
di: Zabaleta, Federico, et al.
Pubblicazione: (2026)

Stochastic Backscatter for Grey-Area Mitigation in Hybrid RANS-LES Simulations
di: Passariello, Angelo, et al.
Pubblicazione: (2025)

Anisotropy of emergent large-scale dynamics in forced stratified shear flows
di: Vieweg, Philipp P, et al.
Pubblicazione: (2025)

Analysis of anisotropic subgrid-scale stress for coarse large-eddy simulation
di: Inagaki, Kazuhiro, et al.
Pubblicazione: (2023)

Particle chirality does not matter in the large-scale features of strong turbulence
di: Piumini, Giulia, et al.
Pubblicazione: (2024)

Subharmonic instability of large-scale wavy structures in two-dimensional channels
di: Han, An-Xiao, et al.
Pubblicazione: (2026)

TripNet: Learning Large-scale High-fidelity 3D Car Aerodynamics with Triplane Networks
di: Chen, Qian, et al.
Pubblicazione: (2025)

High-fidelity Modeling of Full-scale Pressurized Water Reactor Flow Fields for Machine Learning Applications
di: Burnett, Logan A., et al.
Pubblicazione: (2026)

Benchmarking machine learning models for predicting aerofoil performance
di: Summerell, Oliver, et al.
Pubblicazione: (2025)