SIMULATION OF A REACTIVE GAS-LIQUID SYSTEM WITH QUADRATURE-BASED MOMENTS METHOD

The description of the interaction between fluid dynamics and fast chemical reactions in gas-liquid systems is complicated by the fact that the gas phase is poly-dispersed, namely it is constituted by bubbles characterized by a distribution of velocity, size and composition values. Phase coupling can be successfully described only if the modeling approach acknowledges the existence of this distribution, whose evolution in space and time is governed by the so-called Generalized Population Balance Equation (GPBE). A computationally efficient approach for solving the GPBE is represented by the Quadrature-Based Moment Methods (QBMM), where the evolution of the entire bubble population is recovered by tracking some specific moments of the distribution. In the present work, one of these methods, the Conditional Quadrature Method of Moments (CQMOM) has been implemented in the OpenFOAM two-fluid solver compressibleTwoPhaseEulerFoam , to simulate a chemically reacting gas-liquid system. To reduce the computational time and increase stability, a second-order operator-splitting technique for the solution of the chemically reacting species was also implemented, allowing to solve the different processes involved with their own time-scale. This modeling approach is here validated by comparing predictions with experiments, for the chemical absorption of CO 2 in NaOH solution, performed in a rectangular bubble column

Application of dissipative particle dynamics to interfacial systems: Parameterization and scaling

Dissipative Particle Dynamics (DPD) is a stochastic particle model that is able to simulate larger systems over longer time scales than atomistic modeling approaches by including the concept of coarse-graining. Whether standard DPD can cover the whole mesoscale by changing the level of coarse-graining is still an open issue. A scaling scheme originally developed by Füchslin et al. (2009) was here applied to interfacial systems as one of the most successful uses of the classical DPD method. In particular, equilibrium properties such as the interfacial tension were analyzed at different levels of coarse-graining for planar oil–water interfaces with and without surfactant. A scaling factor for the interfacial tension was found due to the combined effect of the scaling scheme and the coarse-graining parameterization. Although the level of molecular description was largely decreased, promising results showed that it is possible to conserve the interfacial tension trend at increasing surfactant concentrations, remarkably reducing modeling complexity. The same approach was also employed to simulate a droplet configuration. Both planar and droplet conformations were maintained, showing that typical domain formations of multi-component systems can be performed in DPD by means of the scaling procedure. Therefore, we explored the possibility of describing oil–water and oil–water–surfactant systems in standard DPD using a scaling scheme with the aim of highlighting its advantages and limitations

IMPACT OF TURBULENCE MODELING ON FLUID/SOLID HEAT TRANSFER INSIDE INDUSTRIAL AUTOCLAVES

This work is centred on the analysis of the impact of different turbulence modeling approaches on the fluid/solid heat exchange inside a commercial size autoclave. This project proposes itself to be a first step towards the optimization of the turbulent flow inside this kind of machinery to improve the curing treatment of Carbon-Fiber Reinforced Plastics (CFRP). The setup of the CFD simulations includes the presence of a metallic sample object inside the autoclave, where air will be recirculated with velocity, pressure and temperature typically adopted for this type of treatments. The analysis takes advantage of parallel CFD simulations, conducted by using the open-source software openFOAM v2106. Two turbulence models have been adopted: one is the well-known Reynolds-Average Navier-Stokes approach (RANS), which is currently used to model the turbulence inside this type of machinery. The second one is the Delayed Detached Eddy Simulations (DDES), which allows the full resolution of the majority of turbulent scales around the sample object. First, we propose the difference between the local heat flux distribution at the air/solid interface computed by using RANS and DDES, next we analyse the overall heat flux entering the sample object: the resolution of the turbulent scales does not influence the local heat flux only, but also the overall heat flux entering the object; an average increase of 35% is reported when the velocity fluctuations are neglected. Future steps of the research foresee the analysis of the heat flux and temperature distributions on the surface of realistic shapes and common-use CFRP. Afterwards, the autoclave design will be optimized by adding multiple inlets and aerodynamic devices to guarantee a more homogeneous heat flux distribution on the surface of realistic shapes of actual CFRP

Molecular modeling of the interface of an egg yolk protein-based emulsion

Many food emulsions are stabilized by functional egg yolk biomolecules, which act as surfactants at the oil/water interface. Detailed experimental studies on egg yolk emulsifying properties have been largely hindered due to the difficulty in isolating individual chemical species. Therefore, this work presents a molecular model of an oil/water interfacial system where the emulsifier is one of the most surface-active proteins from the egg yolk low-density lipoproteins (LDL), the so-called Apovitellenin I. Dissipative particle dynamics (DPD) was here adopted in order to simulate large systems over long time scales, when compared with full-atom molecular dynamics (MD). Instead of a manual assignment of the DPD simulation parameters, a fully automated coarse-graining procedure was employed. The molecular interactions used in the DPD system were determined by means of a parameter calibration based on matching structural data from atomistic MD simulations. Despite the little availability of experimental data, the model was designed to test the most relevant physical properties of the protein investigated. Protein structural and dynamics properties obtained via MD and DPD were compared highlighting advantages and limits of each molecular technique. Promising results were achieved from DPD simulations of the oil/water interface. The proposed model was able to properly describe the protein surfactant behavior in terms of interfacial tension decrease at increasing protein surface concentration. Moreover, the adsorption time of a free protein molecule was estimated and, finally, an LDL-like particle adsorption mechanism was qualitatively reproduced

Multiscale simulation of a high-shear mixer for food emulsion production

Food emulsions, such as mayonnaise, are made of a continuous water phase, a dispersed phase with a high content of oil, and a surfactant (i.e. the egg yolk for mayonnaise) that stabilizes the oil drops. The droplet size distribution (DSD) is the most important property of the emulsion since the structure, stability, taste, and color of the final product depend on the DSD. The DSD in turn depends on the emulsion composition, the type of process, and the operating conditions in which the production process operates. The production of emulsions is based on mixing the ingredients and applying enough mechanical energy to the emulsion, to reach the desired DSD. In particular, for the food emulsion investigated in this work, i.e. the mayonnaise, a typical mixing process is composed of two steps (Figure 1). First, the ingredients (mainly egg yolk, vinegar, oil, water, salt) are mixed together in large stirred vessels at a moderate rotational speed. Then, this premixed emulsion is finally fluxed into a high-shear device, commonly a cone mill mixer, where the oil droplets undergo breakage until the final size distribution is reached. This last step is crucial to fine-tune the DSD, in order to determine the properties of the final product. A typical cone mill is constituted of a solid conical frustum rotor inside a slightly larger stator of the same shape, forming a small gap in which the emulsion flows and experiences high shear stresses, due to the high rotational speed of the rotor. Within the multiscale framework, different time- and space- scales are investigated to describe the modeling approach for the macro-scale (cone mill) and the molecular scale (oil-water interface). Computational fluid dynamics (CFD) simulations are employed to properly describe the non-Newtonian dynamics of the emulsion, investigate the role of the pre- and post-mixing zones and clarify the importance of the type of flow, namely pure-shear versus elongational. In order to describe the evolution of the droplet size distribution, the Population Balance Modelling (PBM) is employed, in which coalescence and breakage of oil droplets are taken into account by appropriate kernels, which depend on local flow conditions. During the emulsification process, the interfacial properties between dispersed and continuous phases have an essential role in the formation and stabilization of the oil droplets. Once the chemical composition of mayonnaise is determined, especially the biomolecules acting as surfactants, the interfacial tension between the two phases is directly computed with the help of atomistic techniques, such as Molecular Dynamics (MD) and Dissipative Particle Dynamics (DPD). This mesoscale approach also provides the surfactant adsorption kinetics and its molecular conformation at the interface, paving the way for a better understanding of the breakage and coalescence events of the oil droplets occurring in the production process. This information can be eventually transferred to the CFD-PBM simulations thus achieving a complete, general, and multi-scale model of the food emulsion production process. This effort is carried out in the context of the VIMMP project (www.vimmp.eu), where the entire workflow will serve to devise a marketplace for generic multiscale and multiphysics simulations. The VIMMP project has received funding from the European Union’s Horizon 2020 Research Innovation Programme under Grant Agreement n. 760907

FBR for Polyolefin Production in Gas Phase: Validation of a Two-phase Compartmentalized Model by Comparison with CFD

Two different modeling approaches are applied in this work to the simulation of fluidized bed reactors containing solid particles of Geldart A-B type and operated at conditions typically used for polyolefins production. On one side, a fully detailed computational fluid dynamics (CFD) model is developed, considering a 2D planar geometry and a multi-fluid description with kinetic theory of granular flows. On the other, a conventional three-phase, 1D compartmentalized model (SCM) is also developed, implementing the fluid dynamic description based on popular, semi-empirical relationships available in the literature. Given the huge difference of computational effort associated with the corresponding numerical solutions, our aim is to confirm the reliability of the simplified model by comparison with the results of the detailed CFD model. The comparison is carried out considering the fluidization of a bed of solid particles without reaction and solid injection or withdrawal, thus focusing on the steady-state fluid dynamic behavior of the expanded bed. Three different gas velocities and different monodisperse and polydisperse particle populations are analyzed. The results show that the oversimplified compartmentalized approach is capable to predict the solid mixing features established inside the reactor operated in bubbling fluidization regime with good reliability for non-reactive polyethylene particles. Average solid volume fractions are particularly close to the values predicted by the CFD model when monodisperse particles are considered inside the examined range of gas velocity values. A generally good agreement is also found when solids with broad size distribution are analyzed. Overall, these comparisons provide a meaningful validation of the simplified compartmentalized models: given their negligible computational demand and general versatility (complex kinetic schemes and single particle models are easily accounted for), they still represent an effective tool of industrial process design

Comparison between detailed (CFD) and simplified models for the prediction of solid particle size distribution in fluidized bed reactors

This work is aimed at developing a simplified model suitable to effectively describe the fluidization behavior within fluidized beds with minimal computational efforts. The simplified model was validated through detailed CFD Euler-Euler simulations showing a good agreement in the case of large particles (about 450 micron) at all the gas velocities considered (20, 40, 61 cm/s). Slightly less accurate outcomes were observed for smaller particles (about 220 micron). This was due to the underestimation of the particle size effect on the fluidization behavior by the simplified approach