1. Introduction
In turbulence, bubbles undergo a cascade-like fragmentation process in which large bubbles break into smaller ones until capillary stresses balance turbulent stresses (Chan et al. Reference Chan, Johnson and Moin2021). Together with coalescence, breakup therefore controls the bubble size distribution, which, in turn, determines the total interfacial area and directly impacts transport phenomena such as mass and heat transfer (Liao & Lucas Reference Liao and Lucas2009; Soligo, Roccon & Soldati Reference Soligo, Roccon and Soldati2019; Ni Reference Ni2024). The classical basis for describing the breakup of bubbles and droplets in turbulence was established by the seminal works of Kolmogorov (Reference Kolmogorov1949) and Hinze (Reference Hinze1955), commonly known as the Kolmogorov–Hinze framework. Although originally developed for neutrally buoyant droplets, the framework is commonly applied to bubbles, despite differences in density and viscosity ratios. In this picture, a bubble of diameter
$D$
is expected to break if the dynamic pressure difference induced by the surrounding flow,
$\rho \delta u^2$
, surpasses the surface tension stresses,
$\sigma /D$
. This balance defines the Weber number,
$\textit{We} = {\rho (\delta u)^2}/(\sigma /D)$
, where
$\rho$
is the carrier-phase density,
$\sigma$
is the interfacial tension and
$\delta u$
is the characteristic velocity increment. The latter is particularly important for fragmentation, as the instantaneous action of turbulence on a deforming bubble is set by local velocity increments acting on the interface (Lalanne et al. Reference Lalanne, Masbernat and Risso2019).
Within the Kolmogorov–Hinze framework, this velocity increment at the bubble scale is usually replaced by the inertial-range second-order moment estimate,
$(\delta u)^2 \approx C_2(\langle \epsilon \rangle D)^{2/3}$
, where
$\langle \epsilon \rangle$
is the mean energy dissipation rate and
$C_2$
is the Kolmogorov constant. This simplification, considered in many breakup models (Prince & Blanch Reference Prince and Blanch1990; Martínez-Bazán et al. Reference Martínez-Bazán, Montañés and Lasheras1999; Lehr et al. Reference Lehr, Millies and Mewes2002), leads to a breakup criterion based on mean turbulent statistics. This closure is useful for estimating a characteristic breakup scale, but it averages out the instantaneous and directional nature of the velocity increments and does not specify how these increments act on the deforming interface. Several studies have moved beyond this mean-field closure by relating droplet or bubble deformation to local flow quantities, interface kinematics, or time-resolved shape evolution (Perlekar et al. Reference Perlekar, Biferale, Sbragaglia, Srivastava and Toschi2012; Qi et al. Reference Qi, Tan, Corbitt, Urbanik, Salibindla and Ni2022, Reference Qi, Xu, Tan, Zhong, Wu and Ni2024; Xu et al. Reference Xu, Qi, Zhong, Tan, Wu and Ni2024). However, a kinematic description that connects local turbulent velocity increments to the bubble deformation leading to breakup remains missing.
As discussed by Qi et al. (Reference Qi, Xu, Tan, Zhong, Wu and Ni2024), bubble deformation is typically quantified using global measures such as interfacial area, aspect ratio or spherical-harmonic mode amplitudes (Stone et al. Reference Stone, Bentley and Leal1986; Ravelet et al. Reference Ravelet, Colin and Risso2011; Vejražka et al. Reference Vejražka, Zedníková and Stanovský2018; Masuk et al. Reference Masuk, Salibindla and Ni2021; Perrard et al. Reference Perrard, Rivière, Mostert and Deike2021; Rivière et al. Reference Rivière, Abahri and Perrard2024). Some of these studies describe turbulence-induced deformation more generally, whereas others focus on the last stages preceding breakup. While these quantities are useful for describing the state of the interface, they are not easily related to turbulent velocity increments. Recently, Xu et al. (Reference Xu, Qi, Zhong, Tan, Wu and Ni2024) moved in this direction by analysing the velocity of the most stretched tip of deforming bubbles and comparing its probability density function (p.d.f.) to those of Eulerian velocity increments. Here, we adopt similar ideas, but focus specifically on breakup events. Instead of the most stretched tip of the bubble, we use a two-point description of the deformation: the parent-bubble volume is partitioned into two subvolumes associated with the daughter bubbles to be formed, and the motion of these subvolumes’ centroids is tracked up to the breakup instant. This two-point construction serves as an analogue to particle pair dispersion theory, also providing a kinematic link to carrier-phase velocity increments. Testing this interpretation requires time-resolved three-dimensional (3-D) measurements of the deforming bubble shape and the surrounding turbulent velocity field. The experimental methods used to obtain these measurements are described next.
2. Methods
2.1. Experimental set-up
The experiments, involving air bubbles in water, were conducted in the jet-stirred turbulent water tank illustrated in figure 1(a). Turbulence was generated within the octagonal tank by two opposing jet arrays, each consisting of 12 jets that continuously injected water at 8
$\text{m s}^{-1}$
. The turbulence was nearly homogeneous and isotropic in the central region of the test section, where the measurement volume was located. The measurement volume was approximately
$4\times 5\times 4$
cm
$^3$
. Millimetre-sized air bubbles were injected below this central region through the bottom part of the tank. Further details of the experimental facility can be found from Beckedorff et al. (Reference Beckedorff, Caridi and Soldati2025).
Experimental set-up and measurement procedure. (a) Schematic of the jet-stirred turbulent water tank. (b) Arrangement of the five high-speed cameras and (c) photograph of the apparatus. Each camera has an opposing LED panel, not shown here. (d) Example of raw backlight images and corresponding segmented particle and bubble images. (e) Reconstructed bubble together with surrounding tracer-particle trajectories.

Figure 1. Long description
Panel A: A schematic diagram of a jet-stirred turbulent water tank. The tank has inflow and outflow points, with jet flow and bubble injection mechanisms. Panel B: A diagram showing the arrangement of five high-speed cameras around the water tank. The cameras are labeled Cam 1 through Cam 5 and are positioned to capture different views of the tank. Panel C: A photograph of the experimental apparatus, showing the water tank and the five high-speed cameras positioned around it. Each camera is labeled accordingly. Panel D: Examples of raw backlight images and corresponding segmented particle and bubble images. The raw images show particles and bubbles, while the segmented images highlight the particles and bubbles separately. Panel E: A reconstructed bubble with surrounding tracer-particle trajectories, illustrating the movement and interaction of particles around the bubble.
Flow images were recorded using five high-speed cameras (Phantom VEO 340L at 2000 f.p.s.) and a backlight illumination system. The camera arrangement is displayed in figures 1(b) and 1(c). The illumination system consisted of five white LED panels placed opposite to each camera (not displayed in figure 1), casting the shadows of bubbles and flow tracers (60
${\unicode{x03BC}}$
m polyamide particles) onto the cameras’ imaging planes. The raw images were preprocessed and segmented into particle images and binarised bubble images; an example is shown in figure 1(d). The segmented images were then used for two purposes: (i) 3-D reconstruction of the bubble topology and (ii) carrier-phase measurements using 3-D particle tracking velocimetry (3-D-PTV). Bubble reconstruction used the visual Hull (VH) technique (Baumgart Reference Baumgart1974; Laurentini Reference Laurentini1994; Masuk et al. Reference Masuk, Salibindla and Ni2019) with a voxel size of
$0.1^3$
mm
$^3$
– equivalent to less than
$1\,\%$
of the average bubble volume. For the carrier-phase measurements, we obtained particle trajectories using the shake-the-box (STB) technique (Schanz et al. Reference Schanz, Gesemann and Schröder2016). Between 8000 and 12 000 particles were successfully tracked at each time step, corresponding to an average particle concentration of 0.125 particles mm–
$^3$
. Figure 1(e) shows an example of a reconstructed bubble together with the surrounding flow trajectories. Image acquisition, segmentation and STB processing were carried out using LaVision DaVis 10.2.1. The velocity data obtained from STB were then used to characterise the turbulence in the measurement volume.
Turbulence characterisation and experimental scales. (a) Eulerian second-order structure function,
$S_2^E$
, and longitudinal component,
$D_{\textit{LL}}$
, with inertial-range scaling shown for reference. (b) Estimates of the mean energy dissipation rate from second- and third-order structure functions; the shaded region indicates the estimated extent of the inertial range. (c) Summary of the relevant experimental length and time scales. The grey histogram indicates the bubble size distribution.

We conducted the experiments at
$\textit{Re}_\lambda =635$
, where the Taylor-microscale Reynolds number is defined as
$\textit{Re}_\lambda = u^{\prime 2}\sqrt {15/(\nu \langle \epsilon \rangle )}$
. Here,
$\nu$
is the kinematic viscosity,
$u^\prime =[(u_x^{\prime 2}+u_y^{\prime 2}+u_z^{\prime 2})/3]^{1/2}=0.28$
m s–1 is the root-mean-square velocity fluctuation and
$\langle \epsilon \rangle = 0.29$
m
$^2$
s–
$^{3}$
is the mean energy dissipation rate. We estimated
$\langle \epsilon \rangle$
from the Eulerian second-order structure function,
$S^E_2 = \langle |\boldsymbol{u}(\boldsymbol{x}+r,t) - \boldsymbol{u}(\boldsymbol{x},t)|^2\rangle$
, computed from velocity increments between particle pairs separated by a distance
$r$
. Figure 2(a) presents
$S^E_2$
and its longitudinal component (
$D_{\textit{LL}}$
) as functions of
$r$
. The dashed line indicates the slope of the inertial-range scaling law,
$S^E_2 = (11/3)C_2(r\langle \epsilon \rangle )^{2/3}$
, where the Kolmogorov constant is
$C_2 = 2.13$
. Figure 2(b) shows the estimation of
$\langle \epsilon \rangle$
based on the second- and third-order structure functions. The shaded area in figure 2(b) indicates the inertial range, which spans from
$1.5$
to
$9.8$
mm (
$40 \lt r/\eta \lt 260$
). We considered the inertial range as the region where the compensated third-order longitudinal structure function,
$-D_{\textit{LLL}}/(r\langle \epsilon \rangle )$
, deviates by less than
$10\,\%$
from
$4/5$
, where
$D_{\textit{LLL}} = \langle \delta u_L^3\rangle$
. Based on
$\langle \epsilon \rangle$
, the Kolmogorov length and time scales were
$\eta = (\nu ^3/\langle \epsilon \rangle )^{1/4}=38$
${\unicode{x03BC}}$
m and
$\tau _\eta = (\nu /\langle \epsilon \rangle )^{1/2} = 1.7$
ms. The integral length scale, estimated from the longitudinal velocity autocorrelation, was
$L = 4.1$
cm, giving an integral time scale
$T_L \approx L/u^\prime = 146$
ms. Figure 2(c) summarises the relevant time and length scales from the experiments. We note that the VH voxel size is larger than
$\eta$
. This does not limit the present analysis, because the statistics considered here are evaluated at inertial-range scales comparable to the bubble size, rather than from small-scale interfacial quantities such as local curvature.
The dataset comprised 124 bubble breakup events. The parent-bubble equivalent diameters,
$D$
, ranged from 2.2 to 8.8 mm (
$55 \lt D/\eta \lt 245$
) with a mean of
$6.3$
mm. The diameters fell within the inertial range; the bubble size distribution is illustrated in figure 2(c). The Weber number,
$\textit{We}=\rho C_2 \langle \epsilon \rangle ^{2/3} D^{5/3}/\sigma$
, ranged from 0.4 to 6.2, with a mean value of
$\textit{We}=2.85$
. The quantities
$D/\eta$
and
$\textit{We}$
were computed using the dissipation rate estimated for each individual case. Breakup events were morphologically diverse: in our dataset, most events produced unequal daughter bubbles, consistent with the U-shaped daughter-size distributions measured by Rodríguez-Rodríguez et al. (Reference Rodríguez-Rodríguez, Martínez-Bazán and Montañés2003) and the predominance of uneven breakups reported by Qi et al. (Reference Qi, Masuk and Ni2020). The smallest daughter bubble detected had a diameter of approximately 0.8 mm, close to the practical reconstruction limit imposed by the VH voxel size.
(a) Reconstructed breakup event of a bubble with diameter
$D=4.3$
mm. The two daughter-associated subvolumes,
$\varOmega _1$
and
$\varOmega _2$
, are shown together with their centroids,
$\boldsymbol{X}_1$
and
$\boldsymbol{X}_2$
; red and grey lines indicate the corresponding centroid trajectories. (b) Evolution of the separation
$r(t)=|\boldsymbol{X}_2(t)-\boldsymbol{X}_1(t)|$
, coloured by the velocity-increment magnitude
$\delta u=|\boldsymbol{u}_2(t)-\boldsymbol{u}_1(t)|$
. Black and white markers indicate the onset of the inertial deformation stage and breakup, respectively. The inset shows the corresponding alignment angle
$\theta$
between
$\boldsymbol{r}$
and
$\delta \boldsymbol{u}$
.

Figure 3. Long description
Panel A: A 3-D plot shows the trajectories of two subvolumes of a deforming bubble. The subvolumes are labeled V1 and V2, with their centroids marked as X1(t) and X2(t). The trajectories are indicated by red and grey lines. The distance between the centroids, r(t), is also shown. Panel B: A line graph displays the evolution of the separation distance r(t) over time t, colored by the velocity-increment magnitude delta u. The graph includes markers for the onset of the inertial deformation stage and the breakup point. The inset shows the alignment angle theta between the separation distance and another reference direction.
2.2. Bubble subvolume definition and tracking
We analysed the bubble deformation by partitioning the parent-bubble volume into two main subvolumes and tracking the relative separation of their centroids. An example of a reconstructed breakup event is shown in figure 3(a), where the grey and red lines represent the trajectories associated with the two subvolumes. These subvolumes, denoted by
$\varOmega _1$
and
$\varOmega _2$
, were defined recursively backward in time based on the volumes of the two largest daughter bubbles formed after the breakup, whose volumes are
$V_1$
and
$V_2$
.
The subvolume identification was initialised at the last frame in which the parent bubble remained connected. The centroids of the two largest daughter bubbles in the subsequent frame were mapped onto the voxelised parent-bubble volume and used as reference points, from which the geodesic distances
$d_1(\boldsymbol{x})$
and
$d_2(\boldsymbol{x})$
to every voxel
$\boldsymbol{x}$
within the parent bubble were computed. Voxels were then assigned according to their relative proximity to these reference points and partitioned into
$\varOmega _1$
and
$\varOmega _2$
based on the daughter-volume ratio, with
$\varOmega _1$
containing the fraction
$V_1/(V_1+V_2)$
of voxels and
$\varOmega _2$
defined by the complement. In non-binary breakup events,
$\varOmega _2$
included a small residual volume associated with minor fragments. However, the influence of this residual was small, as non-binary breakups accounted for only 12 events in our dataset, with an average residual volume of
$1.3\,\%$
. The centroids of
$\varOmega _1$
and
$\varOmega _2$
were then used as reference points in the preceding frame and the same voxel-assignment procedure was applied recursively backward in time to define the evolution of the two daughter-associated subvolumes. This procedure is not intended as an exact material reconstruction, but rather as a temporally coherent partition of the parent bubble near breakup for kinematic analysis. Furthermore, the two-point construction is breakup-conditioned: the daughter bubbles are first identified after breakup, and their measured volumes and centroids are then used to define a deformation coordinate over the preceding connected frames. The approach is therefore not used to predict the breakup event or to determine the daughter bubbles before they are observed.
After defining the two subvolumes,
$\varOmega _1(t)$
and
$\varOmega _2(t)$
, we computed their centroids,
$\boldsymbol{X}_1(t)$
and
$\boldsymbol{X}_2(t)$
. The centroid trajectories were filtered using a second-order Savitzky–Golay filter with a 7-frame window (window length
$\approx 2\tau _\eta$
), from which we obtained the relative separation
$\boldsymbol{r}(t) = \boldsymbol{X}_2(t) - \boldsymbol{X}_1(t)$
and the corresponding velocity increment
$\delta \boldsymbol{u}(t) = \boldsymbol{u}_2(t)-\boldsymbol{u}_1(t)$
. The centroid velocities,
$\boldsymbol{u}_1(t)$
and
$\boldsymbol{u}_2(t)$
, were computed by differentiating the fitted second-order polynomials from the Savitzky–Golay procedure. Note that these velocities are integral observables of the parent-bubble deformation. By construction,
$\delta \boldsymbol{u} = \mathrm{d}\boldsymbol{r}/\mathrm{d}t$
and its projection onto the deformation axis gives the ‘stretching rate’ of the parent bubble,
$\delta \boldsymbol{u} \boldsymbol{\cdot }\boldsymbol{r}/r = \mathrm{d}r/\mathrm{d}t$
. These velocities should not be interpreted as pointwise gas-phase or carrier-phase velocities. Figure 3(a) illustrates the trajectories
$\boldsymbol{X}_i(t)$
, the subvolumes
$\varOmega _i$
, the daughter-bubble volumes
$V_i$
and the relative separation
$\boldsymbol{r}(t)$
, while figure 3(b) presents the evolution of the separation magnitude,
$r = |\boldsymbol{r}|$
, coloured by the velocity increment magnitude,
$\delta u = |\delta \boldsymbol{u}|$
, for the same breakup event. The inset of figure 3(b) reports
$\theta$
, the angle between the separation vector and the velocity increment, defined as
$\theta \equiv \arccos [\delta \boldsymbol{u}\boldsymbol{\cdot }\boldsymbol{r} / (r\, \delta u)]$
(Shnapp et al. Reference Shnapp, Brizzolara, Neamtu-Halic, Gambino and Holzner2023); this quantity is analysed in § 3.
This two-point description of the deformation is initially evaluated using an analogy with particle pair dispersion theory (Richardson Reference Richardson1926; Batchelor Reference Batchelor1950; Bourgoin et al. Reference Bourgoin, Ouellette, Xu, Berg and Bodenschatz2006). Building on this analogy, we analysed the deformation using the mean squared separation,
$\langle |\boldsymbol{r}(t) - \boldsymbol{r}_0|^2\rangle$
, relative to an initial separation
$\boldsymbol{r}_0$
. Since we focus on the kinematics preceding breakup,
$\boldsymbol{r}_0$
was defined at the onset of the inertial deformation stage, identified for each event as the start of the last sustained increase in the separation
$r(t)$
before breakup. The onset corresponding to
$r_0$
was identified with a standard change-point method (Lavielle Reference Lavielle2005; Killick et al. Reference Killick, Fearnhead and Eckley2012). The separation
$r(t)$
was first smoothed with a centred moving-median filter of width
$3\tau _\eta$
. The smoothed signal was then approximated by two straight lines from the start of the recording to the instant of maximum separation. The onset was taken as the time for which this two-line description fits best in the least-squares sense: the first line captures the waiting stage and the second the sustained growth towards breakup. The onset was further required to lie at least
$3\tau _\eta$
from breakup, a margin comparable to the capillary time scale estimated in § 3. The inertial deformation stage is highlighted in figure 3(b), where the black- and white-filled markers denote the deformation onset (
$r_0$
) and breakup.
We emphasise that this two-point approach describes the geometric evolution of the parent-bubble deformation; it is not intended as a material reconstruction, nor as a measurement of the gas velocity inside the bubble. The approach is most reliable during the stage where the two daughter-associated subvolumes define a coherent deformation axis. During the inertial deformation stage, the separation vector was mostly aligned with the bubble semi-major axis, indicating that
$\boldsymbol{r}$
captures the dominant elongation direction. At earlier times, farther from breakup, the connection between the reconstructed subvolumes and the eventual daughter bubbles becomes less reliable. For this reason, the main breakup-conditioned statistics are evaluated over the inertial deformation stage. Here, ‘breakup-conditioned’ means that only bubbles for which breakup is directly observed are included and that the statistics are evaluated over the corresponding pre-breakup deformation stage.
Lastly, we computed two-point statistics of tracer-particle pairs sampled over the same pre-breakup time interval, with initial separations in the range
$10\eta \leqslant r_0 \leqslant 300\eta$
. An example of surrounding trajectories is shown in figure 1(e). We emphasise that the bubble-pair separation is defined kinematically from the centroids of the two daughter-associated subvolumes, whereas the carrier-phase separation is obtained from tracer-particle pairs. These carrier-phase statistics therefore provide a reference for comparison with the bubble deformation, rather than a material counterpart to the bubble-pair construction. Hereafter, superscripts
$b$
and
$f$
denote quantities associated with the bubble deformation and with the carrier phase, respectively. Quantities without superscript denote definitions common to both cases.
(a) Normalised mean squared separation of deforming bubbles (blue markers) and particle pairs (red lines) as a function of
$t/t_0$
. From light to dark red, the particle-pair initial separations are
$r_0 = 10\eta$
,
$20\eta$
,
$30\eta$
,
$40\eta$
,
$50\eta$
,
$100\eta$
,
$200\eta$
and
$300\eta$
. The inset shows the mean bubble separation with all events aligned at breakup,
$(t-t_b)/\tau _\eta =0$
. (b) Mean alignment angle
$\theta$
between the separation vector and velocity increment for deforming bubbles and particle pairs. The inset shows the breakup-aligned evolution of
$\langle \theta ^b\rangle$
; shaded regions indicate the average duration of the inertial deformation stage and the estimated capillary time.

3. Results
We first examine whether the two-point description of bubble deformation can be interpreted as a relative-dispersion problem. Figure 4(a) compares the mean squared separation of the bubble-subvolume centroids with that of particle pairs in the surrounding flow. The separation is normalised by the second-order structure function at the initial separation,
$S_2(r_0) = \langle |\delta \boldsymbol{u}_0|^2 \rangle$
, while time is normalised by the corresponding eddy turnover time,
$t_0 = r_0^{2/3}\langle \epsilon \rangle ^{-1/3}$
. Using the mean onset separation,
$\langle r_0\rangle =122\eta$
, this gives a representative value
$\langle t_0 \rangle \approx 42$
ms, although the normalisation is applied event by event. For each breakup event, time is measured from the identified onset of the inertial deformation stage, so that
$t = 0$
corresponds to
$r=r_0$
. Ensemble averages are then computed in fixed, non-overlapping bins of normalised time. As different bubbles break at different instants, late-time bins contain progressively fewer events, so we truncate the curves when fewer than 25 % of the events remain. Because
$r_0$
varies between breakup events, the normalisation cannot be based on a single value of
$S_2(r_0)$
. We therefore group the events into five
$r_0$
-ranges, each containing approximately 25 breakup events, and compute
$S_2(r_0)$
per range. Each breakup event is then normalised using the corresponding range-averaged value. Throughout this paper, shaded areas and error bars indicate 95 % bootstrap confidence intervals (Efron & Tibshirani Reference Efron and Tibshirani1994).
We observe that bubble deformation exhibits ballistic growth at early times, closely resembling the behaviour of particle pairs. The dispersion in this ballistic regime is governed by a persistent initial velocity increment, leading to the well-known scaling
$\langle |\boldsymbol{r}(t) - \boldsymbol{r}_0|^2 \rangle = S_2(r_0)t^2$
(Batchelor Reference Batchelor1950; Bourgoin Reference Bourgoin2015). In canonical pair dispersion,
$t/t_0 \approx 1$
marks the transition from the initial ballistic regime to subsequent dispersion regimes, whose nature depends on the initial separation
$r_0$
and the initial velocity increment (Shnapp & Liberzon Reference Shnapp and Liberzon2018; Tan & Ni Reference Tan and Ni2022; Li et al. Reference Li, Wang, Qi and Coletti2024). Reference slopes for possible subsequent regimes are included in figure 4(a): the slope
$t^3$
indicates the Richardson superdiffusive regime, while the
$t$
slope indicates the diffusive regime. Here, most bubbles break before reaching one eddy turnover time, making the transition to a second regime unclear and leaving ballistic dispersion as the dominant observed regime. The fact that most breakup events occur within
$t/t_0 \lt 1$
indicates that the pre-breakup deformation develops over a time shorter than (or comparable to) the turnover time of an eddy at the initial separation scale. This observation is consistent with classical breakage-time models that estimate the deformation time from an eddy-turnover time, such as that of Coulaloglou & Tavlarides (Reference Coulaloglou and Tavlarides1977).
While figure 4(a) indicates that bubbles deform following the same ballistic trend as particle pairs, defining
$r_0$
at the onset of inertial deformation may select a subset of events with distinct dispersion properties. In particular, the conditioned bubble-deformation data likely probe flow regions that promote stronger separation than those sampled by unconditioned particle pairs. This tendency can be evaluated through the alignment angle between the velocity increment and the separation vector,
$\theta \equiv \arccos [\delta \boldsymbol{u}\boldsymbol{\cdot }\boldsymbol{r} / (r\, \delta u)]$
(Shnapp et al. Reference Shnapp, Brizzolara, Neamtu-Halic, Gambino and Holzner2023; Tan et al. Reference Tan, Zhong, Xu, Qi and Ni2025). Angles smaller than
$90 ^{\circ }$
indicate increasing separation, whereas angles larger than
$90 ^{\circ }$
indicate decreasing separation.
Figure 4(b) shows the evolution of the mean alignment angle for deforming bubbles and particle pairs. The particle-pair results (red lines) follow the behaviour reported by Shnapp et al. (Reference Shnapp, Brizzolara, Neamtu-Halic, Gambino and Holzner2023):
$\langle \theta ^f \rangle$
starts at
$90 ^{\circ }$
, indicating no preferential alignment, then decreases monotonically during the ballistic regime and approaches approximately
$59.3 ^{\circ }$
in the inertial range for
$t/t_0 \gtrsim 0.5$
. For deforming bubbles,
$\langle \theta ^b \rangle$
remains mostly below
$59.3 ^{\circ }$
in the inertial deformation stage. This indicates that the breakup-conditioned deformation is dominated by an extensional relative motion, with
$\delta \boldsymbol{u}^b$
preferentially aligned with
$\boldsymbol{r}$
. The inset of figure 4(b) presents the evolution of
$\langle \theta ^b \rangle$
with all events aligned in time by subtracting the breakup instant
$t_b$
, so that breakup occurs at
$(t-t_b)/\tau _\eta = 0$
. The inset of figure 4(a) uses the same temporal reference for the mean separation. The red-shaded region indicates the average duration of the inertial deformation stage. The inset shows that
$\langle \theta ^b\rangle$
is close to
$90 ^{\circ }$
at early times, before the onset of the inertial deformation stage. This value should not be interpreted in the same way as the early-time limit of
$\langle \theta ^f\rangle$
for particle pairs. In the latter,
$\langle \theta ^f\rangle \approx 90 ^{\circ }$
results from random sampling of particle pairs in an unconditioned ensemble. For the bubble deformation, instead, the two daughter-associated subvolumes remain constrained by the interface and surface tension before the inertial deformation stage, so
$\langle \theta ^b\rangle \approx 90 ^{\circ }$
reflects a preferential perpendicular alignment between
$\delta \boldsymbol{u}^b$
and
$\boldsymbol{r}$
, not random sampling. Approximately
$8\tau _\eta$
before breakup,
$\langle \theta ^b\rangle$
decreases sharply to approximately
$40 ^{\circ }$
, indicating the onset of an extensional event in which the relative velocity becomes aligned with the deformation direction. This behaviour is consistent with the trend in the main panel.
The subsequent increase of
$\langle \theta ^b\rangle$
close to breakup likely reflects the rapid retraction observed in some events during pinch-off, where capillary effects are significant. A characteristic capillary time scale can be estimated as
$\tau _c=\sqrt {\rho d^3/\sigma }/(2\sqrt {3})$
(Rivière et al. Reference Rivière, Ruth, Mostert, Deike and Perrard2022; Ruth et al. Reference Ruth, Aiyer, Rivière, Perrard and Deike2022; Qi et al. Reference Qi, Xu, Tan, Zhong, Wu and Ni2024), where
$d$
is the neck width at the onset of the capillary instability. Since
$d$
is not robustly available for all events, we approximate it by the mean diameter of the smaller daughter bubble,
$d\approx 2.6$
mm, which gives
$\tau _c\approx 2.65\tau _\eta$
. This estimate is shown by the green-shaded region in the inset and is comparable to the time interval over which
$\langle \theta ^b\rangle$
increases before breakup.
The preferential alignment observed in figure 4(b) suggests an enhanced longitudinal velocity increment. To quantify this effect, we compare the longitudinal velocity increment at scale
$r$
, denoted
$\delta _r u_L$
, with the inertial-range velocity scale,
$(r \langle \epsilon \rangle )^{1/3}$
. Figure 5(a) shows the p.d.f. of this normalised longitudinal increment for bubble-deformation data collected over the inertial deformation stage (blue markers) and for particle pairs (red markers). Particle pairs are selected in a narrow separation range (
$120\eta \leqslant r \leqslant 124\eta$
) centred on
$r=122\eta$
, which corresponds to the mean initial separation
$\langle r_0^b\rangle$
of the bubbles. The particle-pair distribution is slightly negatively skewed, consistent with the asymmetry associated with Kolmogorov’s
$4/5$
law. In comparison, the bubble-deformation distribution exhibits a clear shift from the
$\delta _r u^f_L$
distribution. The bubble-deformation p.d.f. is based on a much smaller sample than the carrier-phase p.d.f. and should be interpreted only qualitatively. We therefore do not draw conclusions from higher-order moments, tail shape or intermittency levels. The most robust feature of the bubble-deformation p.d.f. is the positive shift of its mean value, consistent with the alignment trend in figure 4(b). This indicates that, conditioned on breakup, the pre-breakup deformation preferentially samples extensional increments. We therefore interpret
$\langle \delta _r u_L^b \mid \mathrm{breakup}\rangle$
as a breakup-conditioned mean extensional increment and ask whether its magnitude is compatible with the positive tail of the carrier-phase distribution once a capillary threshold is imposed.
(a) P.d.f. of the normalised longitudinal velocity increment,
$\delta _r u_L/(r\langle \epsilon \rangle )^{1/3}$
, for bubble-deformation data during the inertial deformation stage (blue), particle pairs with
$r=122\eta \pm 2\eta$
(red) and the Chevillard model (Chevillard et al. Reference Chevillard, Castaing, Lévêque and Arneodo2006) (black). The grey region indicates positive increments satisfying
$\delta _r u_L^f\geqslant u_c$
. (b) Normalised mean bubble-deformation increments (blue markers) compared with the conditioned estimate from (3.2) (red line) and the inertial-range estimate (dash-dotted line). The inset shows the conditioned estimate as a function of
$D/D_H$
; the red-shaded region marks
$\textit{We}\gt 10$
.

To examine this interpretation, we define a local longitudinal Weber number based on carrier-phase velocity increments,
$\textit{We}_L = \rho (\delta _r u^f_L) ^2/(\sigma /D)$
. Assuming that only extensional increments can increase the separation between the daughter-associated subvolumes, the threshold must be applied to the signed velocity increments. If breakup requires
$\textit{We}_L$
to exceed a critical value, say
$\textit{We}_L \geqslant \textit{We}_c = \mathcal{O}(1)$
, the corresponding threshold is
\begin{equation} \delta _r u^f_L \geqslant u_c = \sqrt {\frac {\textit{We}_c\sigma }{\rho D}}. \end{equation}
This conditioning is illustrated in figure 5(a): the grey region indicates the positive carrier-phase longitudinal increments that satisfy the threshold in 3.1. We then ask whether the conditional mean over this region,
$\langle \delta _r u^f_L\mid \delta _ru^f_L \geqslant u_{c}\rangle$
, provides a reasonable estimate of the measured breakup-conditioned bubble increment,
$\langle \delta _ru_L^b \mid \mathrm{breakup}\rangle$
. Estimating this conditional mean directly from a finite set of coupled bubble-flow measurements would require sufficient carrier-phase samples to resolve the positive tail of the p.d.f. over several decades of probability, which is impractical here. Instead, we use a model to provide a smooth representation of the carrier-phase longitudinal-increment p.d.f., namely
$\mathcal{P}_{\delta _r u_L}(\delta _r u^f_L)$
. Specifically, we adopt the unified multifractal description proposed by Chevillard et al. (Reference Chevillard, Castaing, Lévêque and Arneodo2006) to estimate
$\mathcal{P}_{\delta _r u_L}(\delta _r u^f_L)$
. We refer the reader to Chevillard et al. (Reference Chevillard, Castaing, Lévêque and Arneodo2006) for details of the model; the parameters are set to
$\mathcal{R}^*=52$
,
$c_1=0.37$
and
$c_2=0.025$
, as defined by the authors. The solid line in figure 5(a) displays the resulting
$\mathcal{P}_{\delta _r u_L}(\delta _r u^f_L)$
for
$r = 122\eta$
. The model provides a close approximation to our measured distributions of
$\delta _r u^f_L$
in the range
$20\eta \leqslant r \leqslant 300\eta$
(not shown here). We then use this p.d.f. to evaluate the conditional mean over positive events selected by the local Weber criterion. The mean velocity increment conditioned on this criterion at scale
$r$
is computed as
\begin{equation} \langle \delta _r u^f_L \mid \delta _r u^f_L \geqslant u_{c} \rangle = \frac {\int _{u_{c}}^\infty \delta _r u^f_L \mathcal{P}_{\delta _r u_L}(\delta _r u^f_L) d(\delta _r u^f_L)} {\int _{u_{c}}^\infty \mathcal{P}_{\delta _r u_L}(\delta _r u^f_L) d(\delta _r u^f_L)}. \end{equation}
In summary, this characteristic velocity increment can be estimated in three steps: (i) for a bubble of diameter
$D$
in a flow of known
$\rho$
,
$\sigma$
and
$\langle \epsilon \rangle$
, and a specified
$\textit{We}_c$
, compute the capillary threshold
$u_c$
from (3.1); (ii) estimate the carrier-phase longitudinal-increment p.d.f. at scale
$r \approx D$
; (iii) compute the characteristic velocity increment as the mean of this p.d.f. above
$u_c$
, from (3.2). Any representation that reproduces the carrier-phase increment statistics at the relevant scales can be used for the p.d.f. in step (ii), including a directly measured distribution, when available. Here, we chose the Chevillard et al. (Reference Chevillard, Castaing, Lévêque and Arneodo2006) model because it provides a closed-form representation of the increment p.d.f., with universal constants taken from the original publication (no parameters were fitted to our data).
Figure 5(b) compares the longitudinal velocity increment of deforming bubbles (blue markers) with the conditioned estimate from (3.2) (red line). The markers are obtained by sorting the dataset into three
$D/\eta$
bins, each containing approximately
$41$
events, and averaging
$\delta _r u_L^b$
over the inertial deformation stage. Each marker is placed at the corresponding bin-averaged diameter,
$\langle D/\eta \rangle$
. Equation (3.2) is evaluated using
$r=\langle r^b \rangle = 0.97D$
, where
$\langle r^b \rangle$
is the mean separation of bubbles during the inertial deformation stage. For comparison, the unconditioned inertial-range velocity scale,
$\delta u_L \approx \sqrt {C_2}(\langle \epsilon \rangle D)^{1/3}$
, is shown by the dash-dotted line. All velocity increments are normalised by
$(\langle \epsilon \rangle D)^{1/3}$
. The conditioned estimate obtained with
$\textit{We}_c = C_2 (0.725)^{5/3}$
, corresponding to Hinze’s classical criterion (Hinze Reference Hinze1955), agrees reasonably well with the measured magnitude of the bubble deformation increment and captures its decrease with increasing
$D$
. By contrast, the unconditioned inertial-range estimate based on the mean energy dissipation rate underpredicts the measured increments and does not reproduce their dependence on
$D$
. This difference is consistent with the fact that, for the present bubble sizes, capillary stresses are not negligible: breakup therefore preferentially samples stronger-than-average extensional increments from the carrier-phase distribution.
For the bubble breakup cascade, similarly to the turbulence cascade, an intermediate bubble-size subrange may exist in which turbulent velocity fluctuations dominate over capillary stresses (Chan et al. Reference Chan, Johnson and Moin2021). This range is expected for
$D_H \ll D \ll L$
, where
$D_H$
is the Hinze scale,
$D_H=[\textit{We}_c\sigma /(\rho C_2\langle \epsilon \rangle ^{2/3})]^{3/5}$
. The bubble sizes in the present experiments are of the same order as
$D_H$
, so the data do not lie deeply within this intermediate bubble-size subrange. In this regime, capillary stresses remain important and strongly affect the threshold
$u_c$
, and therefore the conditioning in (3.2). This is illustrated in the inset of figure 5(b), where
$D$
is normalised by
$D_H$
. As
$D/D_H$
increases, the threshold decreases and
$\langle \delta _r u^f_L \mid \delta _r u^f_L \geqslant u_{c} \rangle$
approaches a finite value, indicating that capillary effects become progressively less restrictive. The red-shaded region marks
$\textit{We} \gt 10$
, computed from
$D/D_H = (We/\textit{We}_c)^{3/5}$
. At sufficiently large
$D/D_H$
, the inertial-range estimate is expected to become an adequate description of the characteristic velocity increment, as predicted by the Kolmogorov–Hinze framework. At smaller
$D/D_H$
, however, stronger positive deviations from the mean inertial-range scaling are required to overcome capillary stresses, so a closure based on the conditioned carrier-phase p.d.f.,
$\mathcal{P}_{\delta _r u_L}(\delta _r u_L^f)$
, is more appropriate than the unconditioned estimate. We note that the conditioned estimate in the inset is not expected to converge exactly to
$\sqrt {C_2}$
at large
$D/D_H$
. The dash-dotted line is based on the simplified estimate
$\delta _D u_L\approx \sqrt {C_2}(\langle \epsilon \rangle D)^{1/3}$
, whereas the corresponding second-order moment scaling is
$\langle (\delta _D u_L)^2\rangle =C_2(\langle \epsilon \rangle D)^{2/3}$
. We use the simplified estimate only as a reference velocity scale, because the present dataset is not large enough to evaluate a comparable second-order moment for the bubble-deformation increments. Finally, we emphasise that the present experiments cover a limited range of
$D/D_H$
. Further measurements over a broader range of bubble sizes and
$\textit{We}$
are needed to test whether (3.2) remains valid in other regimes.
4. Discussion
The role of the velocity increment can be further understood through the K62 refined similarity hypothesis (Kolmogorov Reference Kolmogorov1962; Oboukhov Reference Oboukhov1962). The longitudinal velocity increment may be written as
$\delta _r u^f_L = V_L (\epsilon _r r)^{1/3}$
(Sreenivasan & Antonia Reference Sreenivasan and Antonia1997), where
$V_L$
is a dimensionless stochastic variable and
$\epsilon _r$
is the local average of the energy dissipation rate over a volume of size
$r^3$
(Iyer et al. Reference Iyer, Sreenivasan and Yeung2017). Since
$\epsilon _r\gt 0$
, the sign of
$\delta _r u^f_L$
is entirely determined by
$V_L$
. Thus, large local dissipation can increase the magnitude of the forcing, but it does not guarantee breakup. The local velocity increment must also be sufficiently extensional to separate the daughter-associated subvolumes. This distinction suggests that deformation-conditioned events are better described by the distribution of local longitudinal increments, which contains both the fluctuations of
$\epsilon _r$
and the signed contribution of
$V_L$
. Connecting breakup with intermittency remains a direction for future work. For bubbles well below the Hinze scale, the threshold
$u_c$
lies deep in the positive tail of the longitudinal-increment distribution, so the breakup frequency should become sensitive to intermittency corrections to the tail of
$\mathcal{P}_{\delta _r u_L}$
.
In conclusion, bubble breakup in turbulence can be characterised as a ballistic relative-dispersion process, similar to the short-time separation of tracer-particle pairs. This analogy, however, does not imply that breakup samples ordinary turbulent motion. With
$\textit{We} = \mathcal{O}(1)$
, breakup is biased towards extensional events in which local velocity increments are sufficiently strong to separate the daughter-associated subvolumes. In this sense, the Kolmogorov–Hinze framework correctly identifies velocity increments as central to turbulent breakup; however, our results suggest that breakup models for bubbles near or below the Hinze scale should account for the signed probability distribution of longitudinal velocity increments and its conditioning by capillary stresses, rather than relying solely on the inertial-range second-order moment estimate.
Acknowledgements
The authors acknowledge TU Wien for financial support through its Open Access Funding Programme. We thank F. Sortini, V. Giurgiu and O.M.H. Rodriguez for inspiring discussions and suggestions.
Funding
The funding from the Faculty of Mechanical and Industrial Engineering, TU Wien, Sonderprojekt No. A230719_UP_E322 is gratefully acknowledged. A.S. gratefully acknowledges financial support from the European Union-NextGenerationEU PNRR M4.C2.1.1 - PRIN 2022, ‘The fluid dynamics of interfaces: mesoscale models for bubbles, droplets, and membranes and their coupling to large scale flows’ 2022R9B2MW - G53C24000810001.
Declaration of interests
The authors report no conflict of interest.



S2E
DLL
D=4.3
Ω1
Ω2
X1
X2
r(t)=|X2(t)−X1(t)|
δu=|u2(t)−u1(t)|
θ
r
δu
t/t0
r0=10η
20η
30η
40η
50η
100η
200η
300η
(t−tb)/τη=0
θ
⟨θb⟩
δruL/(r⟨ϵ⟩)1/3
r=122η±2η
δruLf⩾uc
D/DH
We>10