General & Applied Physics · Physics & Astronomy
Fluid Dynamics
The newest papers in Fluid Dynamics that ReadSearch has read, newest first. Each links to its own page, with its authors, date, where it was published and the original.
101 papers, from 7 September 2026 to 5 November 2026: 101 arXiv preprints.
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Newest papers, page 5
HGPTrans: Hierarchical Graph-Pooling Transolver for Automotive Aerodynamic Drag Coefficient Prediction
Accurate and rapid prediction of the aerodynamic drag coefficient ($C_D$) is essential for vehicle design, particularly during early-stage styling iterations where a large number of candidate…Underwater Navigation in Unsteady Flows Using Measurement Histories from a Single Sensing Unit
Spatial flow measurements support underwater navigation, but distributed sensing is constrained by robot size and sensor layout.Quantum many-body framework for passive-scalar turbulence
How spatial structures manifest in multi-time correlations is a fundamental question in turbulence.Semi-automated reconstruction of indoor geometry from 360-degree video for CFD-based airflow analysis in classrooms
Computational Fluid Dynamics (CFD) is widely used to evaluate ventilation and contaminant transport in occupied buildings, but deployment at scale is limited by three bottlenecks: acquiring room…Learning Stiffness Dependent Fluid Structure Dynamics from Coarse Flow Representations
This paper develops a data-driven framework for long-term prediction of fluid--structure interaction (FSI) dynamics, focusing on the flow-induced vibration (FIV) of a flexible plate.Periodic Neural Mapping for Unsteady Rotor-Blade Pressure and Aeroelastic Load Prediction
Accurate prediction of unsteady aerodynamic loads remains a major challenge in turbomachinery design.An improved periodic activation for PINNs reconstructing convective flows
Architectures with periodic activation functions have already been shown to be beneficial in comparison to monotonic counterparts for a wide range of applications of physics-informed neural networks.Well-posedness of neural turbulence closures and tangent dissipation
A neural turbulence closure defines a new boundary-value problem, $R(U)=N(U)+F(U)=0$, with a coupled Jacobian $J(U)=N'(U)+F'(U)$, where $N$ is the original mean-flow operator and $F$ the learned…How Does Distribution Shift Shape Pretraining Gains in Neural PDE Surrogates?
Pretraining a neural PDE surrogate can reduce the amount of new CFD data needed when geometry or modeled physics changes.Neural Field Ensembles for Aerodynamic Surface Prediction: Winning Solution to the ONERA CRM Wall Distribution 2025 Challenge
Machine-learning surrogate models offer a promising alternative to high-fidelity Computational Fluid Dynamics (CFD) simulations for aerodynamic analysis and design.Swim-and-Breach at Palm Scale: A Rudder-Steered Two-Propeller Underwater Robot Platform with Differential-Thrust Pitch Control
We present a palm-scale (65 mm, 34 g) swim-and-breach robot platform.Physics Informed Neural Network model for the dynamical study of Abdominal Aortic Aneurysm
We present the development and application of a three-dimensional Physics-Informed Neural Network (PINN) framework for the investigation of haemodynamic behaviour in the human aorta.Computer-assisted global regularity across nonlinear families of three-dimensional periodic Navier-Stokes flows
Numerical simulations reveal how vortices stretch and transfer energy, but establishing smooth evolution requires bounds that remain valid beyond the simulated resolution.Improving Reduced-Order Rotating Detonation Engine Models with Data Assimilation and Machine Learning
Rotating detonation engines (RDEs) exhibit strongly nonlinear, multiscale wave dynamics that set the observed thermal field.Autonomous Droplet Navigation via Model-Based Reinforcement Learning
Precise manipulation of liquid droplets underpins lab-on-a-chip platforms for diagnostics, chemical synthesis, and biological assays.Embracing Flow Unsteadiness: A High-Throughput Learning Platform Enables Vortex-Exploiting Bioinspired Propulsion
Biological swimmers and flyers exploit unsteady vortices for propulsion, whereas engineered vehicles usually suppress them as disturbances.A panoramic aerodynamic performance prediction method for turbomachinery cascades using transformer-enhanced neural operator
To enable flexible and rapid aerodynamic performance evaluation in turbomachinery design, this paper proposes a panoramic performance prediction framework.Attention Is All You Need (to Avoid Spurious Oscillations)
Can attention move a shock across several cells in one update without breaking it?ONE CYLinder: A Benchmark for Graph-Based Surrogate Modeling of Unsteady Bluff-Body Flows
Graph-based surrogate models offer a promising route to accelerate computational fluid dynamics (CFD) simulations on unstructured meshes.A Systematic Analysis of Automatic Differentiation versus Discretization-based Constraints for Physics-Informed PDE Solvers
Physics-informed neural networks (PINNs) represent a growing frontier in using artificial intelligence to solve partial differential equations (PDEs).
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