Search arXivSearch

arXiv · 0907.5154

Generation and Breakup of Worthington Jets After Cavity Collapse

Abstract

Helped by the careful analysis of their experimental data, Worthington (1897) described roughly the mechanism underlying the formation of high-speed jets ejected after the impact of an axisymmetric solid on a liquid-air interface. In this work we combine detailed boundary-integral simulations with analytical modeling to describe the formation and break-up of such Worthington jets in two common physical systems: the impact of a circular disc on a liquid surface and the release of air bubbles from an underwater nozzle. We first show that the jet base dynamics can be predicted for both systems using our earlier model in Gekle, Gordillo, van der Meer and Lohse. Phys. Rev. Lett. 102 (2009). Nevertheless, our main point here is to present a model which allows us to accurately predict the shape of the entire jet. Good agreement with numerics and some experimental data is found. Moreover, we find that, contrarily to the capillary breakup of liquid cylinders in vacuum studied by Rayleigh, the breakup of stretched liquid jets at high values of both Weber and Reynolds numbers is not triggered by the growth of perturbations coming from an external source of noise. Instead, the jet breaks up due to the capillary deceleration of the liquid at the tip which produces a corrugation to the jet shape. This perturbation, which is self-induced by the flow, will grow in time promoted by a capillary mechanism. We are able to predict the exact shape evolution of Worthington jets ejected after the impact of a solid object - including the size of small droplets ejected from the tip due to a surface-tension driven instability - using as the single input parameters the minimum radius of the cavity and the flow field before the jet emerges.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Stephan Gekle, J. M. Gordillo. 2009-07-29. Generation and Breakup of Worthington Jets After Cavity Collapse. https://doi.org/10.1017/s0022112010003526

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

Bayesian neural network correction of RANS turbulence models with uncertainty quantification in separated flows

Data-driven correction of turbulence models offers a promising route for improving Reynolds-averaged Navier-Stokes (RANS) predictions, but quantifying uncertainty in such corrections and ensuring generalization across flows remain key challenges. This work presents a Bayesian neural network (BNN) framework for uncertainty-aware correction of RANS models. The BNN represents both epistemic and input-dependent aleatoric uncertainty, interpreted here as irreducible scatter in the feature-to-correction relationship, with the latter propagated as spatially correlated fields through the RANS solver. The framework is trained exclusively on a periodic-hill configuration and evaluated without retraining on five unseen separated-flow configurations. The learned corrections improve the training-flow prediction, but the strong momentum-field benefit obtained from the anisotropy correction does not transfer consistently to the unseen flows. Out-of-distribution under-coverage is already present at the correction-field level, indicating that the loss of calibration is already present in transfer of the learned correction rather than being introduced primarily by CFD propagation. Overall, the framework enables joint propagation of epistemic and aleatoric uncertainty while exposing the present limitations of uncertainty calibration under distribution shift.

physics.flu-dyn

Direct numerical simulation of particle-laden flow in a linear compressor cascade: Unsteady boundary-layer effects on particle-blade interactions

We perform point-particle direct numerical simulations (PP-DNS) of particle-laden flow through a linear compressor cascade subjected to synthetic free-stream turbulence. Monodisperse particles are advanced in a one-way coupled Eulerian-Lagrangian framework with drag-only dynamics. We use PP-DNS collision statistics together with empirical deposition and erosion models to estimate particle deposition and blade erosion. Collision hotspots and regions of predicted deposition are identified near the leading edge and over the pressure side. On the pressure side, for the intermediate Stokes number, the onset of frequent collisions and predicted deposition is spatially associated with elevated boundary-layer intermittency during bypass transition. Nevertheless, for the largest particles, impacts occur farther upstream. On the suction side, sparse collisions and predicted deposition events appear only for the smallest particles and are phase-modulated by separation-induced vortex shedding. Joint distributions of impact velocity and angle show that leading-edge impacts are faster and span wider angles than pressure-side impacts. For the two larger particle sizes, the higher normal impact velocities near the leading edge result in a greater likelihood of rebound than on the pressure side. Therefore, appreciable erosion is predicted primarily near the leading edge under the present conditions. The present results highlight the role of unsteady boundary-layer dynamics in affecting particle-blade interactions in compressor cascades.

physics.flu-dyn

Diffusion Enhancement and Directional Suppression Induced by Reciprocal Flows

Reciprocal flows repeatedly return fluid elements to their initial positions, producing no net advective transport on time average. Nevertheless, their interplay with diffusion gives rise to nontrivial transport. To describe this phenomenon, we develop a general theory of effective diffusion under two-dimensional linear flows with arbitrary time dependence. By analyzing the advection-diffusion equation, we derive exact expressions for the mean square displacement and the effective diffusion coefficients for extensional, simple shear, and rotational flows within a single framework. We show that the reciprocal flows universally induce diffusion enhancement. The diffusion tensor exhibits pronounced anisotropy, which can result in directional diffusion suppression in spite of the direction-averaged diffusion enhancement. Our results provide a general framework for diffusion control by time-dependent flows and can provide new strategies for transport manipulation in microfluidic and biological systems.

physics.flu-dyn