A new X-ray computed tomography technique for the purpose of imaging fluidized beds is presented. It consists of an experimental set-up with three stationary X-ray source and flat panel detector pairs, a geometric calibration and data processing workflow, and an image reconstruction algorithm. The technique enables sparse-angular tomographic reconstruction in large 3D regions of fluidized beds at framerates up to 200 Hz, and therefore images bubbles along their whole trajectories through the volume. It allows for a unique analysis of bubble dynamics in fluidized beds, including bubble velocities, bubble transformations, i.e., time evolution of the bubble distributions in space, and bubble–bubble interactions. In this article, we first analyze the main limitation of the technique, the sparse angular resolution, through numerical simulations. We then test the experimental set-up through imaging a series of phantoms. Lastly, we demonstrate results from a Geldart B bubbling fluidized bed.

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This study reports the effect of N₂ and CO₂ bubbles on dilute to dense gas-liquid two-phase bubbly flow. A shadowgraph imaging technique captured bubble images at a high spatiotemporal resolution. The recordings of bubble images allow us to compute gas fraction distribution. It requires challenging segmentation and gas-liquid interface detection approaches in image processing. Hence a novel gas contour characterization technique has been introduced in this study that analyses light intensity per pixel for quantifying the effect of local gas volume fraction. The dominant gas structure and repetitive gas pattern have also been determined here using Fourier transform-based power spectral density and 2D cross-correlation functions, respectively. Gas-liquid flow regimes of dissolved CO₂ bubbles are found quite different than that of N₂ bubbles. The plausible reasons are that gas fraction distribution at the sparger region may inhibit bubble coalescence and the positive surface charge of CO₂ bubbles acts as a barrier to the interface deformation.

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This study focuses on the metabolic impacts of simultaneous glucose and oxygen concentration gradients on penicillin production in an industrial-scale fermentor, using the computational fluid dynamics-cellular reaction dynamics approach. Inclusion of oxygen-coupling considerably impacts the glucose uptake and resulting penicillin productivity. This is characterised by six metabolic regimes; lifeline data reconstructed from experimental results, recorded from the cellular perspective, indicates rapid dynamics in glucose and dissolved oxygen uptake by the microorganisms. The results are highly sensitive to variations in the oxygen-related model parameters, requiring accurate insight into the multiphase hydrodynamics and metabolic processes. Hypothetical scenarios with stronger glucose-oxygen limitations than tested experimentally were further explored. A precision scale-down (SD) simulator was designed based on the lifeline data, requiring considerable operational dynamics, with increasing system complexity and implementation difficulty. These insights may inspire further research into alternative SD configurations better suited to mimic the rapid dynamics of large-scale fermentation processes.

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Emulsions stabilized by nanoparticles, known as Pickering emulsions, exhibit remarkable stability, which enables applications ranging from encapsulation, to advanced materials, to chemical conversion. The layer of nanoparticles at the interface of Pickering droplets is a semi-permeable barrier between the two liquid phases, which can affect the rate of release of encapsulates, and the interfacial transfer of reactants and products in biphasic chemical conversion. A gap in our fundamental understanding of diffusion in multiphase systems with particle-laden interfaces currently limits the optimal development of these applications. To address this gap, we developed an experimental approach for in situ, real-time quantification of concentration fields in Pickering droplets in a Hele-Shaw geometry and investigated the effect of the layer of nanoparticles on diffusion of solute across a liquid–liquid interface. The experiments did not reveal a significant hindrance on the diffusion of solute across an interface densely covered by nanoparticles. We interpret this result using an unsteady diffusion model to predict the spatio-temporal evolution of the concentration of solute with a particle-laden interface. We find that the concentration field is only affected in the immediate vicinity of the layer of particles, where the area available for diffusion is affected by the particles. This defines a characteristic time scale for the problem, which is the time for diffusion across the layer of particles. The far-field concentration profile evolves towards that of a bare interface. This localized effect of the particle hindrance is not measurable in our experiments, which take place over a much longer time scale. Our model also predicts that the hindrance by particles can be more pronounced depending on the particle size and physicochemical properties of the liquids and can ultimately affect performance in applications.@en

In this work, the rise characteristics of a single H₂ bubble, in the ellipsoidal regime, in (i) water, (ii) single electrolyte (2 M, 4.5 M NaCl) solution and (iii) various concentrations of electrolyte mixture (up to 6.4 M of 1:5 weight fraction NaCl-NaClO₃), have been studied, at temperatures up to 80°C. Our results show that both individual and collective effects of the temperature and the electrolyte concentration on the rise velocity and the bubble shape are purely dependent on the changes in liquid properties (density, viscosity, and surface tension); the bubble motion can be described by known non-dimensional correlations for clean bubble rise in pure fluids.

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The dynamics of suspended sediment transport in horizontal open channel flow is analysed using point-particle one-way coupling Direct Numerical Simulations (DNS), with a virtual wall as a simple particle resuspension model. In sediment transport, the bed-load is dominated by the inter-particle interactions, but the suspended sediments are transported essentially in a one-way coupling situation. The validity of one-way coupling DNS with point-particle approach for the transport of suspended sediment is analysed, by comparing the simulations with existing well-designed experiments performed under very similar conditions. The range of the relevant non-dimensional parameters of the simulations is roughly the same as in actual sediment transport, except for the flow Reynolds number. Good agreement is observed between the simulations and the experiments; furthermore, the simulation results of the motion of the suspended sediment are insensitive to the position of the virtual wall, provided this wall is placed in a region where the fluid velocity fluctuation in the wall-normal direction is comparable to the particle settling velocity. Using the simulation results, the interplay between the different fluid–particle interaction forces is analysed, with and without gravity. In the absence of gravity, the dynamics is dominated by the balance between the stress-gradient force and the turbophoretic effects; as the particle-to-fluid density ratio for the sediment particles is on the order of one, the situation is quite different when compared to the dynamics with a density ratio on the order of 1000. When gravity is included, the dynamics is dominated by the interplay between the drag and gravitational forces, and they balance each other. Both with and without gravity, the lift and added-mass forces have only secondary effects and do not play an important role.

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Turbulence and its organization, long conceptualized in terms of "coherent structures,"has resisted clear description. A significant limitation has been the lack of tools to identify instantaneous, spatially finite structures, while unraveling their superposition. We present a framework of generalized correlations, which can be used to readily define a variety of correlation measures, aimed at identifying field patterns. Coupled with Helmholtz-decomposition, this provides a paradigm to identify and disentangle structures. We demonstrate the correlations using vortex-based canonical flows and then apply them to incompressible, homogeneous, isotropic turbulence. We find that high turbulence kinetic energy (Ek) regions form compact velocity-jets that are spatially exclusive from high enstrophy (ω 2) regions that form vorticity-jets surrounded by swirling velocity. The correlation fields reveal that the energetic structures in turbulence, being invariably jets, are distinct from those in vortex-based canonical flows, where they can be jet-like as well as swirling. A full Biot-Savart decomposition of the velocity field shows that the velocity-jets are neither self-induced, nor induced by the interaction of swirling, strong vorticity regions, and are almost entirely induced, non-locally, by the permeating intermediate range (rms level) vorticity. Velocity-swirls, instead, are a superposition of self-induced and background-induced velocity. Interestingly, it is the mild intermediate vorticity that dominantly induces the velocity-field everywhere. This suggests that turbulence organization could result from non-local and non-linear field interactions, leading to an emergent description unlike the notion of a strict structural hierarchy. Our correlation-decomposition framework lends itself readily to the study of generic vector and scalar fields associated with diverse phenomena.

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Swirl-based separators are widely used in the separation of two-phase flows with phases of different densities, e.g. in the oil and gas industry. The separation is based on centrifugal forces associated with the swirl motion, that splits the original mixture into a light-phase core and a heavy-phase annulus, captured by two separate outlets equipped with control valves. Due to the complex (unsteady) dynamics of the flow and variations in the mixture that reaches the separator, real-time controllers are required to keep the separation optimal. Traditionally, the control is based on pressure measurements at the boundaries of the separator. However, pressure is only indirectly related to the separation. A more direct (and potentially more effective) control variable is the distribution of phases inside the separator, which can be monitored using soft-field tomography. This idea is explored in this work using an air-water inline-swirl separator facility equipped with an Electrical Resistance Tomography (ERT) sensor, that determines the size of the air core in real-time using a newly developed fast ERT reconstruction algorithm. The dynamics of the system was studied for different valve actions and summarized into a Transfer Function of the process, which is used to design a PI controller. The approach was successful and the control strategy implemented kept the air core near the setpoint in the presence of disturbances in the air flow rate reaching the separator.

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The performance of multiphase flow processes is often determined by the distribution of phases inside the equipment. However, controllers in the field are typically implemented based on flow variables, which are simpler to measure, but indirectly connected to performance (e.g., pressure). Tomography has been used in the study of the distribution of phases of multiphase flows for decades, but only recently, the temporal resolution of the technique was sufficient for real-time reconstructions of the flow. Due to the strong connection between the performance and distribution of phases, it is expected that the introduction of tomography to the real-time control of multiphase flows will lead to substantial improvements in the system performance in relation to the current controllers in the field. This paper uses a gas–liquid inline swirl separator to analyze the possibilities and limitations of tomography-based real-time control of multiphase flow processes. Experiments were performed in the separator using a wire-mesh sensor (WMS) and a high-speed camera to show that multiphase flows have two components in their dynamics: one intrinsic to its nonlinear physics, occurring independent of external process disturbances, and one due to process disturbances (e.g., changes in the flow rates of the installation). Moreover, it is shown that the intrinsic dynamics propagate from upstream to inside the separator and can be used in predictive and feedforward control strategies. In addition to the WMS experiments, a proportional–integral feedback controller based on electrical resistance tomography (ERT) was implemented in the separator, with successful results in relation to the control of the distribution of phases and impact on the performance of the process: the capture of gas was increased from 76% to 93% of the total gas with the tomography-based controller. The results obtained with the inline swirl separator are extended in the perspective of the tomography-based control of quasi-1D multiphase flows.

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Electrical resistance tomography (ERT) has been used in the literature to monitor the gas–liquid separation. However, the image reconstruction algorithms used in the studies take a considerable amount of time to generate the tomograms, which is far above the time scales of the flow inside the inline separator and, as a consequence, the technique is not fast enough to capture all the relevant dynamics of the process, vital for control applications. This article proposes a new strategy based on the physics behind the measurement and simple logics to monitor the separation with a high temporal resolution by minimizing both the amount of data and the calculations required to reconstruct one frame of the flow. To demonstrate its potential, the electronics of an ERT system are used together with a high-speed camera to measure the flow inside an inline swirl separator. For the 16-electrode system used in this study, only 12 measurements are required to reconstruct the whole flow distribution with the proposed algorithm, 10× less than the minimum number of measurements of ERT (120). In terms of computational effort, the technique was shown to be 1000× faster than solving the inverse problem non-iteratively via the Gauss–Newton approach, one of the computationally cheapest techniques available. Therefore, this novel algorithm has the potential to achieve measurement speeds in the order of 10⁴ times the ERT speed in the context of inline swirl separation, pointing to flow measurements at around 10kHz while keeping the average estimation error below 6 mm in the worst-case scenario.

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Phase separation based centrifugal forces is effective, and thus widely explored by the process industry. In an inline swirl separator, a core of the light phase is formed in the center of the device and captured further downstream. Given the inlet conditions, this gas core created varies in shape and size. To predict the separation behavior and control the process in an optimal way, the gas core diameter should be measured with the minimum possible intrusiveness. Process tomography techniques such as electrical resistance tomography (ERT) allows us to measure the gas core diameter in a fast and non-intrusive way. Due to the soft-field nature and ill-posed problem in solving the inverse problem, especially in the area of low spatial resolution, the reconstructed images often overestimate the diameter of the object under consideration leading to unreliable measurements. To use ERT measurements as an input for the controller, the estimated diameters should be corrected based on secondary measurements, e.g., optical techniques such as high-speed cameras. In this context, image processing and image analysis techniques were adapted to compare the diameter calculated by an ERT system and a fast camera. In this paper, a correction method is introduced to correct the diameter obtained by ERT based on static measurements. The proposed method reduced the ERT error of dynamic measurements of the gas core size from over 300% to below 20%, making it a reliable sensing technique for controlled separation processes.

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This text structures the application of Wire-Mesh sensors and Electrical Resistance Tomography in the control of an Inline Swirl Separator. It introduces a mechanistic model of the two-phase flow inside the device, which is linearized around an ideal perfect operation, and implemented in a Model Predictive Controller. The whole text is structured aiming at a future real application of the controller, briefly introducing the setup that is going to be used, the sensors and their working principles. The results obtained show a stable controller, able to regulate the process relatively fast in relation to the time resolution of the sensors. The positive response of the approach stimulates further improvements in the model developed, and the implementation of more sophisticated techniques to handle the non-linearities of the process.

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Today's mechanical fluid separators in industry are mostly operated without any control to maintain efficient separation for varying inlet conditions. Controlling inline fluid separators, on the other hand, is challenging since the process is very fast and measurements in the multiphase stream are difficult as conventional sensors typically fail here. With recent improvement of process tomography sensors and increased processing power of smart computers, such sensors can now be potentially used in inline fluid separation. Concepts for tomography-controlled inline fluid separation were developed, comprising electrical tomography and wire-mesh sensors, fast and massive data processing and appropriate process control strategy. Solutions and ideas presented in this paper base on process models derived from theoretical investigation, numerical simulations and analysis of experimental data.

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We show experimentally, and explain theoretically, what velocity is needed to break an elongated droplet entering a microfluidic T-junction. Our experiments on short droplets confirm previous experimental and theoretical work that shows that the critical velocity for breakup scales with the inverse of the length of the droplet raised to the fifth power. For long elongated droplets that have a length about thrice the channel width, we reveal a drastically different scaling. Taking into account that a long droplet remains squeezed between the channel walls when it enters a T-junction, such that the gutters in the corners of the channel are the main route for the continuous phase to flow around the droplet, we developed a model that explains that the critical velocity for breakup is inversely proportional to the droplet length. This model for the transition between breaking and nonbreaking droplets is in excellent agreement with our experiments.

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In this work, the effect of an electrolyte (up to 2 M of NaCl dissolved in water) on a homogeneous dense bubbly flow, in an airlift bubble column, is studied using nonintrusive techniques. X-ray and high-speed imaging are used to investigate the bubble size distribution, the local and the global gas-fraction profiles. The major effect of the electrolyte is the bubble size distribution at the fine-pore sparger, which is a consequence of the bubble coalescence inhibition promoted by the electrolyte. The bubble plume widening, the increase in overall gas fraction, and the onset of bubble recirculation in the column can all be explained by the bubble size reduction at the fine-pore spargers. As a result of the bubble size reduction, the overall role of the electrolyte is in a reduction of the driving force for the liquid recirculation. Furthermore, an accumulation of the small bubbles causes a layer of foam at the free surface, which is dynamic in nature and induces additional bubble recirculation.

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Based on our earlier experimental work on the effect of surfactants on air-water flow in vertical pipes with internal diameters of 34 mm, 50 mm, and 80 mm, we create a mechanistic annular flow model for the pressure gradient. The major effect of the addition of surfactants is the formation of foam. We model the formation of foam and its impact on the flow. In the model we consider a gas core and a film at the wall, which consists of a layer of liquid at the wall and a layer of foam between the liquid layer and the gas core. We do not consider entrainment in the model. We developed four closure relations in order to solve the model: (i) for the density of the foam, (ii) for the viscosity of the foam, (iii) for the interfacial friction between the gas and the film, and (iv) for the thickness of the liquid layer at the wall. Subsequently, we solve for the film thickness that yields the imposed liquid flow rate. Comparing the experimental results for the pressure gradient to the results from the model, we observe that in most cases the model can predict the pressure gradient within 25%. Furthermore, the model is able to predict the onset of downwards flow in the film. Therefore, it can predict the transition between annular flow and churn flow. We show that the effect of five different surfactants on the flow is equal, apart from a scaling factor of the concentration, which means that the model can be applied for many different types of surfactants. The scaling factor is an input parameter to the model, which needs to be determined in a small scale experiment.

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We have developed and applied an Eulerian-Lagrangian model for the transport, formation, break-up, deposition and re-entrainment of particle agglomerates. In this paper, we focus on agglomeration and break-up. Simulations were carried out to investigate what changes in the turbulent flow are inflicted by the presence of the agglomerates. Also, the dependence of the properties of the agglomerates on the Reynolds number of the flow and on the strength of the bonds between the primary particles is studied. The presence of the agglomerates attenuates the turbulence and thereby lowers the Reynolds stresses. As a result, the flow rate increases at constant pressure drop when agglomerates are formed (up to a certain dimension). If the agglomerates surpass this dimension, long-distance viscosity effects become dominant and a flow rate decrease occurs. The characteristics of the agglomerates are largely insensitive to the Reynolds number, provided the flow is turbulent. The agglomerates have an open and porous structure, and a fractal dimension of 1.8-2.3. Their mean mass scales exponentially with the strength of the internal bonds. Contrary to assumptions that are typically made in engineering models in the literature, agglomerates do not preferentially break into two fragments of similar size.@en

In this work, we present results of flow visualisation, pressure gradient measurements, and liquid holdup measurements for air-water flow without and with surfactants in vertical pipes with diameters of 34 mm, 50 mm, and 80 mm. The surfactants cause the formation of foam. This foam has a larger volume and a smaller density than the liquid. The larger volume results in a larger pressure gradient at large gas flow rates. At small gas flow rates, the lower density of the foam causes the transition between the regular annular flow regime and the irregular churn flow regime to shift to lower gas flow rates. As a result foam reduces the pressure gradient and the liquid holdup at small gas flow rates. Surfactants are more reduce the pressure gradient more effectively for thinner liquid films at the wall; therefore, they are more effective for small pipe diameters and small liquid flow rates.@en

We present a model for the formation, break-up, deposition and re-entrainment of solid particle agglomerates in turbulent flows. The turbulent flow of the liquid carrier is represented through Direct Numerical or Large Eddy Simulations. The structure of the agglomerates, which are formed by inter-linked spherical primary particles, is explicitly taken into account in this model. While firstly still ignoring deposition and re-entrainment, we present results on the properties of the agglomerates formed both in channel flow, and in flow in a cylindrical pipe. The collision rate of the agglomerates is found to be under-predicted by the Saffman & Turner collision kernel by up to a factor of 10. We also present results on the modification of the turbulence due to the presence of the agglomerates. Furthermore, results on the deposition and re-entrainment rate of the agglomerates, as well as on the additional streamwise pressure drop induced by the deposition are presented. Ultimately, the results obtained this way are used to construct improved engineering models for predicting asphaltene deposition during crude oil production.This research was carried out in the context of the Integrated Systems Approach to Petroleum Production (ISAPP) Knowledge Center. ISAPP is a joint project of the Netherlands Organization for Applied Scientific Research (TNO) and Delft University of Technology, sponsored by ENI, Petrobras, and Statoil.@en