Image de couverture de livre

Deep Reinforcement Learning for Active Flow Control around a Three-Dimensional Flow-Separated Wing at Re = 1,000

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Montalà, R., Font, B., Suárez, P., Rabault, J., Lehmkuhl, O., Vinuesa, R., Rodriguez, I.
Format:	Preprint
Publié:	2025
Sujets:	Computational Engineering, Finance, and Science
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Discovering Flow Separation Control Strategies in 3D Wings via Deep Reinforcement Learning
par: Montalà, R., et autres
Publié: (2025)

Towards Active Flow Control Strategies Through Deep Reinforcement Learning
par: Montalà, Ricard, et autres
Publié: (2024)

High-lift Wing Separation Control via Bayesian Optimization and Deep Reinforcement Learning
par: Montalà, Ricard, et autres
Publié: (2026)

An Embedded Boundary Scheme for Three-Dimensional Flow Over Terrain on a Staggered Mesh
par: Kang, Soonpil, et autres
Publié: (2026)

OptiWing3D: A Diverse Dataset of Optimized Wing Designs
par: Diniz, Cashen, et autres
Publié: (2025)

Hybrid DeepONet Surrogates for Multiphase Flow in Porous Media
par: Santos, Ezequiel S., et autres
Publié: (2025)

Gaussian Field Representations for Turbulent Flow: Compression, Scale Separation, and Physical Fidelity
par: Shenoy, Dhanush Vittal, et autres
Publié: (2026)

$μ$-FlowNet: A Deep Learning Approach for Mapping Flow Fields in Irregular Microchannels Using an Attention-based U-Net Encoder-Decoder Architecture
par: Meshram, Ganesh Sahadeo, et autres
Publié: (2026)

D-Flow: Multi-modality Flow Matching for D-peptide Design
par: Wu, Fang, et autres
Publié: (2024)

Scalable High-Dimensional Bayesian Field Reconstruction with Finite Elements: Application to 3D Porous Media Flow
par: Nitzler, Jonas, et autres
Publié: (2026)

Active flow control for drag reduction through multi-agent reinforcement learning on a turbulent cylinder at $Re_D=3900$
par: Suárez, P., et autres
Publié: (2024)

LineageFlow: Flow Matching for High-Fidelity Family-Aware Protein Sequence Generation
par: Liang, Langzhang, et autres
Publié: (2026)

Flow control of three-dimensional cylinders transitioning to turbulence via multi-agent reinforcement learning
par: Suárez, P., et autres
Publié: (2024)

Nonlinear Flexibility Effects on Flight Dynamics of High-Aspect-Ratio Wings
par: Tantaroudas, Nikolaos D., et autres
Publié: (2026)

ParetoFlow: Guided Flows in Multi-Objective Optimization
par: Yuan, Ye, et autres
Publié: (2024)

International Trade Flow Prediction with Bilateral Trade Provisions
par: Pan, Zijie, et autres
Publié: (2024)

Evaluation of Deep Reinforcement Learning Algorithms for Portfolio Optimisation
par: Lu, Chung I
Publié: (2023)

Advances in Particle Flow Filters with Taylor Expansion Series
par: Servadio, Simone
Publié: (2025)

Tight MIP Formulation for Pipeline Gas Flow with Linepack
par: Klatzer, T., et autres
Publié: (2024)

Flow Field Reconstruction with Sensor Placement Policy Learning
par: Li, Ruoyan, et autres
Publié: (2026)

Dynamical Update Maps for Particle Flow with Differential Algebra
par: Servadio, Simone
Publié: (2025)

Designing Mechanical Meta-Materials by Learning Equivariant Flows
par: Mirramezani, Mehran, et autres
Publié: (2024)

History-Matching of Imbibition Flow in Multiscale Fractured Porous Media Using Physics-Informed Neural Networks (PINNs)
par: Abbasi, Jassem, et autres
Publié: (2024)

A GPU-Accelerated Three-Dimensional Crack Element Method for Transient Dynamic Fracture Simulation
par: Xie, Yuxi, et autres
Publié: (2025)

Deep Reinforcement Learning Algorithms for Option Hedging
par: Neagu, Andrei, et autres
Publié: (2025)

Zero-Shot Forecasting of Network Dynamics through Weight Flow Matching
par: Zhou, Shihe, et autres
Publié: (2025)

Bilateral Trade Flow Prediction by Gravity-informed Graph Auto-encoder
par: Minakawa, Naoto, et autres
Publié: (2024)

Bayesian Model Selection for Complex Flows of Yield Stress Fluids
par: Rinkens, Aricia, et autres
Publié: (2026)

Navigation in a simplified Urban Flow through Deep Reinforcement Learning
par: Tonti, Federica, et autres
Publié: (2024)

Physics-Guided Reinforcement Learning System for Realistic Vehicle Active Suspension Control
par: Nhu, Anh N., et autres
Publié: (2024)

WeightFlow: Learning Stochastic Dynamics via Evolving Weight of Neural Network
par: Li, Ruikun, et autres
Publié: (2025)

MolFORM: Preference-Aligned Multimodal Flow Matching for Structure-Based Drug Design
par: Zhang, Daiheng, et autres
Publié: (2025)

An Impulse-formed Navier-Stokes Solver based on Long-range Particle Flow Maps
par: Li, Zhiqi, et autres
Publié: (2026)

equilibrium-c: A Lightweight Modern Equilibrium Chemistry Calculator for Hypersonic Flow Applications
par: Gibbons, Nicholas N.
Publié: (2024)

Multi-Objective Loss Balancing in Physics-Informed Neural Networks for Fluid Flow Applications
par: Farea, Afrah, et autres
Publié: (2025)

A Multi-physics Model of Flow from Coronary Angiography: Insights to Microvascular Function
par: Yang, Haizhou, et autres
Publié: (2024)

Flow of Knowledge: Federated Fine-Tuning of LLMs in Healthcare under Non-IID Conditions
par: Chen, Zeyu, et autres
Publié: (2025)

Agentic AI for Particle-Based Simulation: Automating SPH Workflows for Debris Flow Modeling
par: Zhang, Danrong, et autres
Publié: (2026)

Dflow-SUR: Enhancing Generative Aerodynamic Inverse Design using Differentiation Throughout Flow Matching
par: Yang, Aobo, et autres
Publié: (2025)

Private Order Flows and Builder Bidding Dynamics: The Road to Monopoly in Ethereum's Block Building Market
par: Wang, Shuzheng, et autres
Publié: (2024)