967 papers
Fluid dynamics explores how liquids and gases move, shaping everything from weather patterns to the flow of blood through our veins. This field bridges the gap between abstract mathematical equations and the tangible forces that drive our physical world, offering insights into turbulence, aerodynamics, and fluid behavior in complex environments.
On Gist.Science, we process every new preprint in this category directly from arXiv to make cutting-edge research accessible to everyone. Each paper is transformed into a clear, plain-language overview alongside a detailed technical summary, ensuring both students and experts can grasp the latest findings without getting lost in dense jargon.
Below, you will find the most recent studies in fluid dynamics, curated and explained for a broader audience.
This study utilizes high-fidelity direct numerical simulation to characterize the near-field combustion-noise dynamics of a supersonic reacting hydrogen-air temporal mixing layer, revealing that broadband pressure fluctuations are modulated by combustion intermittency and exhibit weak, low-frequency coherence with heat release rather than collapsing onto a single dominant mode.
This study utilizes direct numerical simulation of a supersonic reacting hydrogen-air temporal mixing layer to demonstrate that compression-chemistry coupling is best understood through an event-level framework, where intermittent compression events organize exothermic heat release and scalar-gradient amplification via specific population characteristics, spatial overlap, proximity, and temporal lags rather than through whole-field averages.
This paper investigates the energy spectrum of a quantum vortex ring in a flowing fluid within a cylindrical pipe, demonstrating the existence of states with negative and large effective masses, proposing a mechanism for turbulence formation based on coupled vortex pairs, and offering a new method to determine the critical Reynolds number in quantum turbulence.
This study demonstrates that linear resolvent analysis based on mean flow data from a large-eddy simulation can effectively characterize the transitional dynamics in an axisymmetric stenosis, successfully reconstructing turbulent kinetic energy and wall shear stress fluctuations through low-rank, axisymmetric coherent structures.
This paper presents a hybrid quantum-classical Markov chain Monte Carlo method that utilizes parametric quantum circuits to efficiently sample turbulent acceleration vectors and model Lagrangian tracer dispersion in shear flows, demonstrating superior spectral gaps and reliable performance with a limited number of qubits compared to classical approaches.
This paper presents a fully quantum algorithm for the one-dimensional linear Lattice Boltzmann method that eliminates intermediate measurements to require only a single final readout, demonstrating its performance on a simulator and a 133-qubit quantum system while analyzing the impact of decoherence noise on the results.
This paper introduces a geometry-conditioned latent surrogate model that achieves a speed-up over high-fidelity CFD simulations by encoding adaptive mesh refinement cell-density fields as a compact proxy to accurately reconstruct transient two-phase spray breakup dynamics for efficient nozzle design.
This paper introduces a rigorously validated, reproducible pipeline using a cumulant-based Lattice Boltzmann solver to generate a high-resolution dataset of 3D turbulent obstructed channel flows, establishing a standardized benchmark for evaluating and comparing neural operator surrogates in turbulence modeling.
This paper presents numerical simulations using Nek5000 and EllipSys to analyze the transition and long-term flow response of an FFA-W3 airfoil at low Reynolds numbers, validating the EllipSys code's ability to capture Kelvin-Helmholtz instabilities and identifying a slow, periodic modulation of the normal-force coefficient linked to low-frequency oscillations and potential bubble bursting.
This perspective paper argues that while machine learning offers transformative potential for rarefied gas transport modeling across various levels, its reliable deployment requires shifting focus from solver-based demonstrations to establishing trustworthy, auditable standards that address physical fidelity, uncertainty, and extrapolation capabilities.