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 2
CFD-driven symbolic regression of RANS transition models
Laminar-turbulent transition governs skin friction, heat transfer and losses in turbomachinery, yet Reynolds-averaged Navier-Stokes (RANS) transition models rely on empirical correlations and…Physics-Informed Identification of Tensegrity Prestress across Taut-Slack Transitions
Prestress governs the stability, stiffness, and dynamic behavior of tensegrity structures, but it is not directly observable from sparse structural measurements, and it may decrease during service…Variational learning of energy-stable macroscopic flow equations from microscopic laws
We present a generalized variational approach for constructing energy-stable macroscopic partial differential equations (PDEs) directly from microscopic physical laws.Pore-scale mechanisms of capillary imbibition in cement-based materials revealed by direct numerical simulations in a realistic FIB-SEM microstructure
Moisture transport in cement-based materials involves transient multiphase flow through highly irregular pore networks, where evolving air--water interfaces strongly influence liquid invasion and…Quantum HHL Algorithm for Solving 1D Linear Advection Equation Using Explicit and Implicit Finite Difference Schemes
This study develops and implements a Harrow-Hassidim-Lloyd (HHL) quantum algorithm for solving a one-dimensional linear advection equation with periodic boundary conditions.Learned Surrogates of Three-Dimensional Magnetohydrodynamic Turbulence
Three-dimensional magnetohydrodynamic (MHD) turbulence, the flow of astrophysical and fusion plasmas, is costly to simulate.ART of PIV: Agentic Real-Time Particle Image Velocimetry for Active Flow Control
Particle image velocimetry (PIV) measures fluid motion from images of tracer particles, but its accuracy depends on choices throughout the estimation pipeline, including image preprocessing, flow…Feature-preserving interface reconstruction using piecewise circles and cusps
We present a geometric interface reconstruction method for Volume-of-Fluid (VOF) simulations that captures both curved interfaces and sharp features using only volume fraction data.As a matter of reconstruction -- varying the magnetic Prandtl number in implicit large eddy simulations
The magnetic Prandtl number ($\mathrm{Pm}$), the ratio of viscosity to magnetic diffusivity, spans many orders of magnitude in astrophysical plasmas.Hard Constraint Projection in a Physics Informed Neural Network (Burgers)
Physics informed machine learning provides a framework to study and simulate fluid dynamics, potentially at a fraction of the computational cost of traditional numerical methods, with the goal of…OPINE: Orthogonal Projection in Invertible Nonlinear Embeddings for Turbulent Flows
Proper orthogonal decomposition (POD) represents physical fields with orthogonal modes ordered by variance, so that one decomposition gives reduced coordinates in every dimension, but it needs many…Optimization of curved vortex generator geometry for enhanced thermal performance in water-to-air finned-tube heat exchanger
In the study, the geometry of curved rectangular vortex generators (RVG) has been optimized to enhance heat transfer and overall performance of the analyzed water-to-air finned-tube heat exchanger…Wave Turbulence of Capillary Waves in Finite Systems
We consider classical problem of turbulence of capillary waves.FLUCS: a modular GPU-native framework for fluid and plasma turbulence
We present FLUCS, an open-source framework for solving systems of partial differential equations efficiently on graphics processing units (GPUs), targeting models of fluid and plasma turbulence.Benchmarking One-Dimensional Quantum Lattice Boltzmann Methods on Quantum Hardware
Classical computational fluid dynamics (CFD) methods encounter significant computational bottlenecks in large systems and at high Reynolds number flows due to the rapid increase in degrees of…Frozen in Time: How a Physics Foundation Model Forgets Under Sim-to-Real Adaptation
Scientific foundation models (SciFMs) have achieved remarkable performance on a wide range of PDEs, including the ability to efficiently adapt to unseen data distributions with additional finetuning.Differentiable Schwarz-Coupled Solvers for Thin Boundary Layer Transport: Inverse Modeling via Agentic AI Optimization
High-Péclet-number transport problems give rise to thin boundary layers with steep near-wall gradients whose accurate solution requires high-resolution meshes and could challenge inverse modeling.Dual Area-Volume-of-Fluid (DAVOF): co-advecting volume and face-area fractions for a closed-form, cell-local interface normal and position on unstructured meshes
Geometric Volume-of-Fluid (VOF) on unstructured polyhedral meshes reconstructs the interface orientation from the volume fractions of a stencil of neighbours; on irregular cells and in the presence…Agentic AI Reasoning and Learned Sampling for Task-Aware Projection Selection in Sparse-View CT: Predicting Hemodynamics
Sparse-view computed tomography (CT) reduces the number of acquired projections, but conventional sampling strategies are designed primarily for image reconstruction rather than for downstream…High-Fidelity Aerostructural Dataset of Transonic Wings in Cruise Conditions
Recent advances in machine learning (ML) have the potential to substantially accelerate aircraft wing design, a process that has traditionally required extensive high-fidelity simulation and design…
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