Latest Research in Fluid Dynamics
18 research papers · 2026 median publication year
Top Research Topics in Fluid Dynamics
- Fluid Dynamics — 5 papers
- Machine Learning — 4 papers
- Model Reduction and Neural Networks — 3 papers
- Fluid Dynamics and Turbulent Flows — 1 papers
- Computational Physics — 1 papers
- Wave and Wind Energy Systems — 1 papers
- Numerical Analysis — 1 papers
- Computational Fluid Dynamics and Aerodynamics — 1 papers
- Machine Learning — 1 papers
Highest-Cited Papers
- Radius-dependent looseness of the far-field Calderón–Zygmund bound in turbulent vortex stretching
- PosteriorBench: From Point Estimates to Posterior Matching in Evaluating Generative Inverse Solvers
- How Does Distribution Shift Shape Pretraining Gains in Neural PDE Surrogates?
- A Cummins-equation-based physics-informed neural network for response prediction and system identification of wave energy converters
- Comparison of generative learning methods as turbulence surrogates
- Geometric Vorticity Control ver.3 with Supplementary Material ver.2
- Deep Koopman Sensing
- Physics-Guided Conditional Flow Matching with Energy Regularization for Robust PDE Inverse Problems
- Task-preserving neural segmentation of overlapping shocks and vortex cores in compressible flows
- Two-Scale Localized PCA-Net: Coarse-Global and Local-Residual Representations for Artifact-Reduced PDE Operator Learning
- Prediction of Hydrogen Mixing and Velocity Fields Behind a Strut Injector with Multi-Lobe Nozzles at scramjet engine using POD+LSTM technique
- Multivariate Scientific Data Compression with Learned Cross-Variable Latent Decorrelation and Autoregressive Entropy Modeling
- How well can Diffusion Models learn Lagrangian-Tracer Statistics in Non-reciprocal Turbulence?
- SnapPINN: Pressure and Energy Dissipation Reconstruction from a Sparse and Noisy Velocity Snapshot
- TRACE: Retrospective Streaming Generation of Physical Fields under Sparse Structured Sensing
- DAW: Dynamics-Aware Weighting for Deep Learning Forecasts of Chaotic Systems
- A Compensated Koopman Neural Operator with Selective State-Space Dynamics for Unsteady Flows
- Interpretable discovery of anisotropic dissipation limiters for hypersonic flows via flow-aligned spatiotemporal graph attention and symbolic distillation