Cyrus K. Aidun

We hypothesize that combining extreme turbulence with a minute reduction in surface tension $σ$ (surface tension of the liquid) using surfactant provides a simple and scalable route for controlling micron scale bubble size in gas--liquid systems. To test this, we generate high-intensity turbulence using a multiphase pump [turbulent intensity $\ge 40\%$; Taylor Reynolds number $Re_λ=\mathcal{O}(10^3)$; bulk Reynolds number $Re=\mathcal{O}(10^5)$] feeding a straight duct, which produces a decaying turbulent flow where, without additives, bubble coalescence dominates and causes monotonic downstream growth in the mean diameter $d_\mathrm{avg}$ of the bubbles. This growth is governed by the turbulent dissipation rate $\varepsilon$. High-speed imaging, back-lit shadowgraph and particle shadow velocimetry (PSV) quantify bubble statistics ($d_\mathrm{avg}$, and the bubble-size distribution) and turbulence metrics (turbulent kinetic energy $k$, turbulence intensity $\mathcal{I}$, and dissipation rate $\varepsilon$). We then introduce a minute amount ($\sim 0.01\%$ critical micelle concentration) of additive that produces a slight reduction in $σ$, used here only as an interfacial tuning knob because the same change in surface tension can be achieved with non surface active agents. This small decrease in $σ$ enhances breakup, slightly suppresses coalescence, and makes smaller bubbles more breakup prone, resulting in reduced $d_\mathrm{avg}$ and a narrower bubble-size distribution. Turbulence statistics remain unchanged within experimental uncertainty, indicating that the effect arises entirely from interface rather than hydrodynamic changes. Overall, combining extreme turbulence with a minute reduction in surface tension offers a low complexity and tunable lever for setting bubble-size distributions and intensifying mass transfer in industrial multiphase flows.

We hypothesize that combining extreme turbulence with a minute reduction in surface tension $σ$ (surface tension of the liquid) using surfactant provides a simple and scalable route for controlling micron scale bubble size in gas--liquid systems. To test this, we generate high-intensity turbulence using a multiphase pump [turbulent intensity $\ge 40\%$; Taylor Reynolds number $Re_λ=\mathcal{O}(10^3)$; bulk Reynolds number $Re=\mathcal{O}(10^5)$] feeding a straight duct, which produces a decaying turbulent flow where, without additives, bubble coalescence dominates and causes monotonic downstream growth in the mean diameter $d_\mathrm{avg}$ of the bubbles. This growth is governed by the turbulent dissipation rate $\varepsilon$. High-speed imaging, back-lit shadowgraph and particle shadow velocimetry (PSV) quantify bubble statistics ($d_\mathrm{avg}$, and the bubble-size distribution) and turbulence metrics (turbulent kinetic energy $k$, turbulence intensity $\mathcal{I}$, and dissipation rate $\varepsilon$). We then introduce a minute amount ($\sim 0.01\%$ critical micelle concentration) of additive that produces a slight reduction in $σ$, used here only as an interfacial tuning knob because the same change in surface tension can be achieved with non surface active agents. This small decrease in $σ$ enhances breakup, slightly suppresses coalescence, and makes smaller bubbles more breakup prone, resulting in reduced $d_\mathrm{avg}$ and a narrower bubble-size distribution. Turbulence statistics remain unchanged within experimental uncertainty, indicating that the effect arises entirely from interface rather than hydrodynamic changes. Overall, combining extreme turbulence with a minute reduction in surface tension offers a low complexity and tunable lever for setting bubble-size distributions and intensifying mass transfer in industrial multiphase flows.

This study experimentally investigates bubble size evolution and void fraction redistribution in an unexplored, coalescence-dominated regime of a decaying turbulent bubbly flow. The flow is generated downstream of a regenerative pump in a duct, with bulk Reynolds number ( Re ) $\sim \mathcal{O}(10^5)$ , Taylor-scale Reynolds number ( Re $_\lambda$ ) $\sim \mathcal{O}(10^3)$ and void fraction ( $\phi$ ) $\sim \mathcal{O}(1\,\%)$ , where the inlet turbulence is extremely intense (turbulence intensity $\gt 30\,\%$ ) but decays rapidly along the duct. Shadowgraph imaging and particle shadow velocimetry are used for measurements. The experimentally obtained turbulent dissipation in the duct flow decays as $\varepsilon \sim \mathcal{L}^{-2}$ , where $\mathcal{L}$ is the axial position, in close agreement with the homogeneous isotropic turbulence prediction of $\varepsilon \sim \mathcal{L}^{-2.2}$ . High-speed imaging and statistical analysis reveal that bubble coalescence dominates over breakup across most of the domain, leading to monotonic growth in the Sauter mean diameter ( $d_{32}$ ) and progressive broadening of the bubble size distribution. The normalised extreme-to-mean diameter ratio ( $\mathcal{D}$ ) increases axially and asymptotically from ${\sim} 1.9$ (breakup regime) and saturates at ${\sim} 2.2$ (coalescence regime), indicating the emergence of a quasi-self-similar bubble size distribution. The probability density function of the bubble diameter exhibits a dual power-law tail with exponents $-10/3$ and $-3/2$ near the duct inlet. However, after a few hydraulic diameters, a single $-3/2$ power-law scaling emerges, indicating a regime of pure coalescence in which all bubbles are smaller than the Hinze scale. The cumulative distribution plotted against $d/d_{32}$ shows that the slope decreases and the distribution width increases with both axial position and void fraction $(\phi )$ . Although classical Hinze scaling gives $d_{\textit{H}} \propto \mathcal{L}^{0.9}$ , our theory for $d_{32

We present direct numerical simulations (DNS) of laminar to turbulent transition in Herschel-Bulkley (HB) yield-stress fluids flowing through pipes and rectangular channels. The simulations employ a Herschel-Bulkley formulation that captures the yield-stress-driven plug, its breakdown, and the emergence of near-wall turbulent structures, enabling direct resolution of the transition mechanisms. The DNS cover a broad range of generalized Reynolds numbers, Re_G = 378 to 5300, allowing us to resolve plug formation, transition onset, and fully turbulent regimes. In pipe flow, the simulations reproduce the characteristic transition sequence, which includes a strong plug and negligible turbulence at low Re_G, a sharp rise in turbulence intensity and u'rms within a narrow transitional window (Re_G ~ 2000 to 3000), and wall-dominated turbulence with a weakened core at higher Re_G. Transition occurs only when local Reynolds stresses exceed the yield stress. The resulting regime boundaries (Re_G < 1735 laminar, 1735 < Re_G < 2920 transitional, and Re_G > 2920 turbulent) align with trends reported for Carbopol fluids. This work provides the first DNS resolving the complete laminar to turbulent transition in HB fluids for both pipe and channel configurations, offering unified insight into plug breakdown, turbulence localization, and the role of yield stress in transition mechanisms. Experimental validation using a 3.6 m acrylic channel with particle image velocimetry (PIV) is planned to further assess the DNS predictions and quantify geometry-dependent transition thresholds.

We present direct numerical simulations (DNS) of laminar to turbulent transition in Herschel-Bulkley (HB) yield-stress fluids flowing through pipes and rectangular channels. The simulations employ a Herschel-Bulkley formulation that captures the yield-stress-driven plug, its breakdown, and the emergence of near-wall turbulent structures, enabling direct resolution of the transition mechanisms. The DNS cover a broad range of generalized Reynolds numbers, Re_G = 378 to 5300, allowing us to resolve plug formation, transition onset, and fully turbulent regimes. In pipe flow, the simulations reproduce the characteristic transition sequence, which includes a strong plug and negligible turbulence at low Re_G, a sharp rise in turbulence intensity and u'rms within a narrow transitional window (Re_G ~ 2000 to 3000), and wall-dominated turbulence with a weakened core at higher Re_G. Transition occurs only when local Reynolds stresses exceed the yield stress. The resulting regime boundaries (Re_G < 1735 laminar, 1735 < Re_G < 2920 transitional, and Re_G > 2920 turbulent) align with trends reported for Carbopol fluids. This work provides the first DNS resolving the complete laminar to turbulent transition in HB fluids for both pipe and channel configurations, offering unified insight into plug breakdown, turbulence localization, and the role of yield stress in transition mechanisms. Experimental validation using a 3.6 m acrylic channel with particle image velocimetry (PIV) is planned to further assess the DNS predictions and quantify geometry-dependent transition thresholds.

Understanding the three-dimensional motion of bubbles is essential for interpreting transport and mixing in multiphase flows, especially when bubbles deform under shear or move rapidly through the flow field. In many laboratory setups, only a single high-speed camera is available, which limits measurements to two dimensions. Traditional image-processing tools can identify bubbles only when they appear circular and isolated, but they struggle with irregularly shaped bubbles, shear-induced deformations, strong blurring, and partial overlaps. Multi-camera systems could overcome these issues, but require significant hardware additions and calibration effort. In this work, we introduce a new machine-learning framework that can detect bubbles and estimate their depth using only a single 20 kHz high-speed camera with 3 \textmu m resolution. The method first uses a large unlabeled dataset and clusters the bubbles with an unsupervised algorithm to reveal their underlying structure. These clusters provide pseudo labels, which are combined with a small set of true in-plane bubble labels to train a semi-supervised model that generalizes across different bubble appearances. These components produce a continuous depth-proxy score that indicates how close each bubble is to the imaging plane, even when bubbles are distorted or irregularly shaped. In parallel, we perform robust bubble identification using instance segmentation, which separates touching, overlapping, and elongated bubbles generated by high-velocity shear. Quantitatively, the in-plane segmentation baseline achieves strong held-out performance with Average Precision (AP) = 0.818, implying stable detection across thresholds, clutter, bubble detection Precision of 0.901, and a False-Positive Rate (FPR) near 6.1\%, hence low spurious bubbles and cleaner statistics under the tested acquisition conditions.

Understanding the three-dimensional motion of bubbles is essential for interpreting transport and mixing in multiphase flows, especially when bubbles deform under shear or move rapidly through the flow field. In many laboratory setups, only a single high-speed camera is available, which limits measurements to two dimensions. Traditional image-processing tools can identify bubbles only when they appear circular and isolated, but they struggle with irregularly shaped bubbles, shear-induced deformations, strong blurring, and partial overlaps. Multi-camera systems could overcome these issues, but require significant hardware additions and calibration effort. In this work, we introduce a new machine-learning framework that can detect bubbles and estimate their depth using only a single 20 kHz high-speed camera with 3 \textmu m resolution. The method first uses a large unlabeled dataset and clusters the bubbles with an unsupervised algorithm to reveal their underlying structure. These clusters provide pseudo labels, which are combined with a small set of true in-plane bubble labels to train a semi-supervised model that generalizes across different bubble appearances. These components produce a continuous depth-proxy score that indicates how close each bubble is to the imaging plane, even when bubbles are distorted or irregularly shaped. In parallel, we perform robust bubble identification using instance segmentation, which separates touching, overlapping, and elongated bubbles generated by high-velocity shear. Quantitatively, the in-plane segmentation baseline achieves strong held-out performance with Average Precision (AP) = 0.818, implying stable detection across thresholds, clutter, bubble detection Precision of 0.901, and a False-Positive Rate (FPR) near 6.1\%, hence low spurious bubbles and cleaner statistics under the tested acquisition conditions.

Large eddy simulations (LES) of a side channel pump are conducted at different operating conditions, including best efficiency point (BEP) and off-design conditions. To address the numerical challenges of this LES, a high-quality mesh consisting of 116 million cells is generated for the impeller and casing parts. These parts are connected by three mesh interfaces, allowing for mesh motion at 3,450 RPM. The impeller with 72 staggered blades embedded in the side channel cavity transfers momentum to the flows in flow rates in the range of Q/QBEP∈[0.8−1.2], where Q is the volumetric flow rate. The validation shows a 5.1% efficiency deviation at the off-design condition of 0.8QBEP, where the flow is more unsteady than at other flow rates. The results reveal the state of turbulence, the pressure fluctuations and the vortical structures at the impeller periodic frequencies. The turbulence intensity of about 40% increases exponentially as the flow progresses around the impeller, driven by the interaction between the impeller blades and the radial discharge from the casing. The study illustrates that the state of turbulence is homogeneous in circumferential locations as θ∈[π/2−3π/2] of the casing, while the inlet and outlet ports change the state of turbulence. The six large structures generated by the impeller are related to the pressure fluctuations. The pumped outflow illustrates a moderate level of swirl while retaining extreme turbulence intensity in all conditions. The highest level of outflow swirl and turbulence is reported in 0.8QBEP. The study provides a comprehensive understanding of the complex vortical patterns and recirculation zones, which contribute to potential design improvements for enhanced, pump performance.

In this work, the conformational dynamics of the von Willebrand Factor (vWF) are investigated as it encounters localized regions of high shear and extensional forces in a converging/diverging channel. Using direct numerical simulations that employ two-way coupling between a lattice Boltzmann fluid solver and a Langevin dynamics-based bead-spring model for vWF, we study how flow-induced forces influence the spatiotemporal evolution of molecular unfolding. Unlike studies that rely on statistical models or averaged behavior, our approach captures transient and configuration-specific unfolding events that arise from the interplay between molecular conformation and flow-field structure. In the simulations, the vWF passes through a straight section of pipe with subcritical shear rates before entering a converging/diverging section where shear and extension rates exceed the known critical threshold for vWF unfolding. Streamwise extension and conformational states are analyzed over time. Results show that while vWF may unfurl in the converging/diverging sections, the likelihood of such events is significantly influenced by the vWF's initial conformation upon entering these regions. Notably, increasing the flow rate to elevate shear and extension rates does not necessarily enhance unfolding likelihood in the converging/diverging section due to its greatly reduced residence time.

Abstract Large eddy simulation (LES) of a regenerative pump is carried out to insightfully analyse the vortical flow driven by the impeller. The driven mechanism yields high heads in circumferential travel of pumped fluid through the impeller’s blades and the annular open side channel. The Reynolds averaged Navier-Stokes (RANS) is employed to figure out a compromise among imperative geometrical parameters for an averaged uniform outflow. The symmetric side channel reduces the unsteadiness of the outflow in the streamlined outlet. On the other hand, the well-resolved LES result, which is validated against experimental measurement, elaborates the flow field characteristics such as coherent structures generated from the fluid axially entering the inter-blade channel close to the hub and being radially discharged from the channel. This recirculation decides about the mixing rate of pump, the turbulent intensity and the structure size which are of particular interests. The flow entering the side channel transfers the added angular momentum to the peripheral flow in the circumferential direction and into the following inter-blade channels. This repetitive (regenerative) helical path generates high heads at relatively low specific speeds in a single impeller stage.

In this work, a new solver, FPSolve, is developed to study fiber orientation kinetics using the Fokker–Planck (FP) equation. The solver employs the finite-volume method. The FP equation is discretized on unstructured cubed-sphere grids using the centered differencing scheme (CDS) or a blend of the CDS and the upwind differencing scheme. Time integration is performed using a second-order two-stage explicit Runge–Kutta scheme. Different shape factors and rotational diffusion coefficients are implemented to study suspensions in dilute to semiconcentrated regimes. The verification of the solver is performed for the fiber orientation in simple shear flow up to a Peclet number of 1 0 5 . Grid independence analysis is presented to show the second-order accuracy of FPSolve. It is demonstrated that the solver does not need stabilization by upwinding. Simulations for semiconcentrated suspensions are performed using the model of Ferec et al. (2014). Time-accurate solutions of the FP equation with explicit time stepping for this model are presented for the first time.

The production of blueberries for fresh and processed consumption is increasing globally and has more than doubled in the last decade. Blueberry is grown commercially across a variety of climates in over 30 countries. The major classes of plants utilized for the planting and breeding of new cultivars are highbush, lowbush, half-high, Rabbiteye, and Southern highbush. Plants can be propagated by cuttings or in vitro micropropagation techniques. In vitro propagation offers advantages for faster generation of a large number of disease-free plants independent of season. Labor costs for in vitro propagation can be reduced using new cultivation technology and automation. Here, we test and demonstrate successful culture conditions and medium compositions for in vitro initiation, multiplication, and rooting of the Southern highbush cultivar ‘Blue Suede™’ (Vaccinium hybrid).

Mixing of fluids in a coaxial jet is studied under four distinct viscosity ratios, $m=1$ , $10$ , $20$ and $40$ , using highly resolved large-eddy simulations (LES), particle image velocimetry and planar laser-induced fluorescence. The accuracy of predictions is tested against data obtained by the simultaneous experimental measurements of velocity and concentration fields. For the highest and lowest viscosity ratios, standard RANS models with unclosed terms pertaining to viscosity variations are employed. We show that the standard Reynolds-averaged Navier–Stokes (RANS) approach with no explicit modelling for variable-viscosity terms is not applicable whereas dynamic LES models provide high-quality agreement with the measurements. To identify the underlying mixing physics and sources of discrepancy in RANS predictions, two distinct mixing modes are defined based on the viscosity ratio. Then, for each mode, the evolution of mixing structures, momentum budget analysis with emphasis on variable-viscosity terms, analysis of the turbulent activity and decay of turbulence are investigated using highly resolved LES data. The mixing dynamics is found to be quite distinct in each mixing mode. Variable viscosity manifests multiple effects that are working against each other. Viscosity gradients induce additional instabilities while increasing overall viscosity decreases the effective Reynolds number leading to laminarization of the turbulent jet, explaining the lack of dispersion and turbulent diffusion. Momentum budget analysis reveals that variable-viscosity terms are significant to be neglected. The scaling of the energy spectrum cascade suggests that in the TLL mode the unsteady laminar shedding is responsible for the eddies observed.