arXiv subjects

Qingfei Fu

Publications and source records attributed to Qingfei Fu.

5 recordsLinked to original sources

arXiv2026

How Surface Viscoelasticity Eliminates Satellite Drops

Satellite drops form widely during the breakup of liquid threads and constitute deleterious byproducts across a broad range of industrial technologies, yet their complete suppression has remained a longstanding challenge. Here, we experimentally report that surface viscoelasticity introduced by a small amount of bovine serum albumin can fully eliminate satellite drops, via modulating the localized spatiotemporal topology near pinch-off singularity. During the late thinning stage, surface shear viscosity counterbalances the capillary and stably anchors the thinning neck at the midpoint between the two primary beads, fundamentally precluding satellite droplet formation. We further propose a scaling law to describe the unique self-similar thinning behaviors dictated by surface viscosity. These results shed light on the thinning dynamics of liquid threads with surface rheology and offer a promising strategy to eliminate satellite drops in practical applications.

physics.flu-dyn↗

arXiv2026

Electric modification of mode competition in viscous films with insoluble surfactants on vertical fibers

This study investigates the coupled effects of an insoluble surfactant and a radial electric field on the stability of a viscous liquid film flowing down a vertical fiber. Starting from the governing equations in two dimensions, a reduced model in one dimension is derived using the long wave approximation to describe the coupled evolution of the interface and surfactant transport. Linear stability analysis identifies two distinct unstable modes: the Rayleigh-Plateau mode, which dominates at lower values of the Marangoni number $Ma$, and the Marangoni mode, which becomes dominant at higher values of $Ma$. The influence of the radial electric field is determined by the position of the outer electrode $\beta$. When $\beta<\mathrm{e}$, the electric field enhances both instabilities and narrows the stable interval in $Ma$ between the two modes. When $\beta>\mathrm{e}$, the electric field suppresses both modes and can completely eliminate the unstable region associated with the Marangoni mode even at a relatively small electric Weber number $E_b$. Continuation of the traveling wave solutions further shows that, when $\beta<\mathrm{e}$, the magnitude of the relative interfacial motion $I_{RP}$, generally increases with $E_b$. By contrast, the intensity of Marangoni convection $I_{M}$ varies only weakly at smaller values of $E_b$ and increases appreciably only when the electric field becomes sufficiently strong. Analysis of the stream function and the relative interfacial velocity reveals that the electric stress primarily intensifies the recirculation beneath the wave crest and reshapes the spatial distribution of the relative interfacial velocity.

physics.flu-dyn↗

arXiv2026

Marangoni modulation of coupled Rayleigh-Taylor and Faraday instabilities in vertically oscillated liquid films

We investigate the Marangoni modulation of coupled Rayleigh-Taylor and Faraday instabilities in a vertically oscillated Newtonian liquid film carrying insoluble surfactants. Linear stability analysis using Floquet theory reveals that an increasing Marangoni number (Ma) selectively suppresses subharmonic modes, driving the system into a harmonic-dominated regime. The interfacial response is found to be highly frequency-dependent. At low forcing frequencies, increasing Ma causes adjacent harmonic tongues to merge into a novel surfactant mode that migrates towards long wavelengths, ultimately coalescing with the RTI branch and fragmenting the dynamically stable window. Conversely, at high frequencies, surfactants monotonically elevate the harmonic instability threshold, significantly widening the stable parameter space. To uncover the underlying mechanisms, a long-wave asymptotic analysis is performed, demonstrating that the critical forcing amplitude factorizes into a static capillary-gravity margin and a dynamic elasto-inertial modulation, yielding a scaling law for the critical mode balance. Finally, nonlinear simulations based on a rigorous weighted-residual reduced model are utilized to dissect the spatial work performed by individual forces, which shows that surfactants modulate stability through phase-controlled Marangoni transport. In the RTI regime, increasing Ma reverses the transport direction and drives fluid into the peaks, inducing a transition from stabilization to destabilization. In the Faraday instability (FI) regime, the response exhibits a strong frequency dependence, governed by Marangoni transport that redistributes fluid away from interfacial peaks at high frequencies but toward them at low frequencies, thereby suppressing or enhancing the instability accordingly.

physics.flu-dyn↗

arXiv2024

Compression-thinning behavior of bubble suspensions

Rheology of bubble suspensions is critical for the prediction and control of bubbly flows in a wide range of industrial processes. It is well-known that the bubble suspension exhibits a shear-thinning behavior due to the bubble shape deformation under pure shear, but how the shear rheology response to dilatation remains unexplored. Here, we report a compression-thinning behavior that the bubble suspension exhibits a decreasing shear viscosity upon compressing. This peculiar rheological behavior is microscopically due to that a shrinking bubble surface effectively weakens the flow resistance of the surrounding liquid. We theoretically propose a constitutive equation for dilute bubble suspensions considering both shear and dilatation effects, and demonstrate that the contribution of dilatation effect on the shear viscosity can be significant at a changing pressure.

physics.flu-dyn↗

arXiv2024

A data-driven sparse learning approach to reduce chemical reaction mechanisms

Reduction of detailed chemical reaction mechanisms is one of the key methods for mitigating the computational cost of reactive flow simulations. Exploitation of species and elementary reaction sparsity ensures the compactness of the reduced mechanisms. In this work, we propose a novel sparse statistical learning approach for chemical reaction mechanism reduction. Specifically, the reduced mechanism is learned to explicitly reproduce the dynamical evolution of detailed chemical kinetics, while constraining on the sparsity of the reduced reactions at the same time. Compact reduced mechanisms are be achieved as the collection of species that participate in the identified important reactions. We validate our approach by reducing oxidation mechanisms for $n$-heptane (194 species) and 1,3-butadiene (581 species). The results demonstrate that the reduced mechanisms show accurate predictions for the ignition delay times, laminar flame speeds, species mole fraction profiles and turbulence-chemistry interactions across a wide range of operating conditions. Comparative analysis with directed relation graph (DRG)-based methods and the state-of-the-art (SOTA) methods reveals that our sparse learning approach produces reduced mechanisms with fewer species while maintaining the same error limits. The advantages are particularly evident for detailed mechanisms with a larger number of species and reactions. The sparse learning strategy shows significant potential in achieving more substantial reductions in complex chemical reaction mechanisms.

physics.chem-ph↗