Volume 19, Issue 2 - Special Issue in Honor of Professor Faïçal Larachi; Guest Editor: Professor Safia Hamoudi

We study positively buoyant miscible jets through high-speed imaging and planar laser-induced fluorescence methods, and we rely on supervised machine learning techniques to predict jet characteristics. These include, in particular, predictions to the laminar length and spread angle, over a wide range of Reynolds and Archimedes numbers. To make these predictions, we use linear regression, support vector regression, random forests, K-nearest neighbour, and artificial neural network algorithms. We evaluate the performance of the aforementioned models using various standard metrics, finding that the random forest algorithm is the best for predicting our jet characteristics. We also discover that this algorithm outperforms a recent empirical correlation, resulting in a significant increase in accuracy, especially for predicting the laminar length.

Bubble formation in a square microchannel having a converging shape merging junction has been studied using the Coupled Level-Set and Volume-of-Fluid (CLSVOF) method. The influence of variations in merging junction angles, fluid properties, and operating conditions on the bubble length and pressure drop has been analyzed. The results show a direct relationship between surface tension, gas-liquid flow ratio, and the inverse relation of continuous phase viscosity with the bubble length. Moreover, opposite variations of these parameters are observed for pressure drop. This work reveals a discerning influence of the angle variations of merging junction on the interplay between inertial, viscous, and surface tension forces in the bubble formation mechanism. We envisage that this numerical work will be of significant interest for the process intensification in various industries that deal with gas-liquid microfluidic systems.

Two-phase flows in feed pipes of thermal separation columns have complex flow patterns and are difficult to predict during sizing and design for geometries with non-straight pipes. Numerical simulation codes have only been validated for very few pipe geometries. This work benchmarks the state-of-the-art Volume-of-Fluid model (VoF) and the Algebraic Interfacial Area Density model (AIAD) for the simulation of two-phase flows with the Eulerian/Eulerian CFD approach for straight pipes and horizontal bends as well as for different pipe diameters and flow rates. Both models are compared and shortcomings of the predicted velocity fields from AIAD in the vicinity of horizontal bends are highlighted. While phase dynamics, e.g., for wavy or disperse flows, are not well reproduced by either model, the phase distribution patterns in straight tubes and bends agree reasonably well with experimental data. Regardless of the geometry, better void fraction prediction is obtained for higher flow velocities and the larger pipe diameter. From the numerical results, recommendations for the selection of feed inlet devices are derived.

Sandwich packings represent new separation column internals, with a potential to intensify mass transfer. They comprise two conventional structured packings with different specific geometrical surface areas. In this work, the complex fluid dynamics in sandwich packings is modeled using a novel approach based on a one-dimensional, steady momentum balance of the liquid and gas phases. The interactions between the three present phases (gas, liquid, and solid) are considered by closures incorporated into the momentum balance. The formulation of these closures is derived from two fluid-dynamic analogies for the film and froth flow patterns. The adjustable parameters in the closures are regressed for the film flow using dry pressure drop measurements and liquid hold-up data in trickle flow conditions. For the froth flow, the tuning parameters are fitted to overall pressure drop measurements and local liquid hold-up data acquired from ultra-fast X-ray tomography (UFXCT). The model predicts liquid hold-up and pressure drop data with an average relative deviation of 16.4 % and 19 %, respectively. Compared to previous fluid dynamic models for sandwich packings, the number of adjustable parameters could be reduced while maintaining comparable accuracy.

The flow generated in a gas-liquid stirred tank reactor highly depends on the design of the impeller and sparger. To better understand the contact between the phases and the mass and heat transfer rates, especially when the mass transfer is the limiting step, it is crucial to investigate the hydrodynamics generated by the impellers and its impact on the bubble size and their distribution, and gas volume fraction. In this work, experimental and numerical studies are performed with a novel mixed impeller in a pilot scale ( T  = 0.486 m) gas-liquid stirred tank reactor. The Sauter mean diameter, mean bubble diameter and bubble size distribution is determined at the different radial and axial regions by using high-speed imaging technique. Further, Euler-Euler simulations are performed to find the detailed flow field of novel mixed impeller used in the current study. Finally, the gassed power to impeller swept volume ratio is determined from the CFD and correlated with the Sauter mean diameter measured in the experiment in the impeller discharge region. It is found that the novel mixed impeller used in current work shows the similar behavior as the Rushton impeller in the impeller discharge region and it also provide good axial mixing.

QSPR is a powerful tool for elucidating the correlation between chemical structure and property for both natural and synthesized compounds. In the present work, the half-wave reduction potential for a set of aziridinylquinones (Anticancer Agents [AA]) is modelled using a quantitative structure-electrochemistry relationship (QSER) based on multilinear regression (MLR) and artificial neural network (ANN). Molecular descriptors introduced in this work were computed using the Dragon software (V5). Before the model’s generation, using the Kennard and Stone algorithm, the data set of 84 aziridinylquinones was divided into training and prediction sets consisting of 70 % and 30 % of data points. Quantitative Structure Electrochemistry Relationship (QSER) models were developed using the Genetic Algorithm Multiple Linear Regressions (GA-MLR) and an Artificial Neural Network (ANN). The coefficient of determination ( R 2 ) and Root Mean Squared Error of prediction (RMSE) were mentioned to demonstrate the QSER model’s prediction abilities. Calculated R 2 and RMSE val values for the MLR model were 0.858 and 0.054, respectively. The R 2 and RMSE val values for the ANN training set were calculated to be 0.914 and 0.050, respectively. Findings show that GA is a powerful tool for selecting variables in QSER analysis. Comparing the two employed regression methods showed that ANN is superior to MLR in predictive ability.

Increasing environmental concerns have led to the development of alternative methods for the desulfurization of petroleum crude oil and liquid fuels. Phosphonium-based ionic liquids (PILs) have recently demonstrated promising potential for effective extractive desulfurization (EDS). The present study focuses on the synthesis and application of trihexyl tetradecyl phosphonium bis(2-ethylhexyl) phosphate [THTDP][D2EHP] for EDS of synthetic model fuels and real crude oils. The molecular confirmation and thermal stability of [THTDP][D2EHP] were investigated using FTIR and TGA analyses. In addition, the conductivity, solubility, and viscosity of the synthesized ionic liquid (IL) were analyzed. The impact of reaction time, temperature, and sulfur compounds, such as thiophene, benzothiophene, and dibenzothiophene (DBT), on the desulfurization efficiency from synthetic fuels was also investigated. The results indicated up to 63 and 57 % sulfur removal from DBT-based model fuels and Iranian crude oil, respectively. The optimum extraction conditions were found as 1:1 IL/fuel mass ratio, 35 °C, and 30 min. The findings of this study provide valuable insights into the synthesis and utilization of PILs as promising solvents for extractive desulfurization of crude oil and liquid fuels.

Contraction-expansion (CE) static mixers can enable solid-liquid and liquid-liquid dispersion with low energy dissipation, low risk of obstruction, and without moving parts. In this work, the influence of CE elements of different geometries on the imposed turbulence of a flowing liquid has been assessed by a two-dimensional computational fluid dynamic (2D-CFD) simulation. The effect of CE on the dispersion of droplets of an immiscible liquid has also been analysed from simulations, using the volume of fluid (VOF) approach. Direct numerical simulation (DNS) performed by the open-source Gerris Flow Solver software was used to get the velocity fields and turbulence characteristics. Different ratios of CE diameters and lengths were analysed for liquid Reynolds numbers from 500 to 20,000. From simulations, the CE geometry that maximised the average root mean square velocity, as an indicator of turbulence, was determined for different liquid flow rates. It was found that the average RMS had a maximum for a wide range of liquid flow rates when the CE diameter ratio was between 0.55 and 0.59 and the length ratio was between 0.2 and 0.3. Then, a device with seven CE elements with geometrical features within this range was built and used for preparing an oil-in-water emulsion. The test system contained water and sunflower oil (5 % v/v) with the further addition of TritonX100 (0.5 % in volume of the solution) as surfactant. The stability of the emulsions was assessed by measuring the time evolution of turbidity (absorbance at 860 nm), to get the initial separation velocities. The emulsions prepared using the CE device showed initial phase separation rates lower than the one obtained in a stirred flask, evidencing the feasibility of using CE static mixers for preparing emulsions with relatively low energy consumption. Moreover, the emulsions obtained with the CE device, although dependent on the flow rate, showed similar features when obtained with 10, 100 and 250 passes through the CE static mixer.

Currently, microchannels are widely used in liquid-liquid heterogeneous mass transfer systems due to its excellent mass transfer performance. However, because of the passive mixing principle of traditional microchannels, the improvement of mass transfer performance has a bottleneck. This work proposes a novel rotating millimeter channel reactor (RMCR), capable of achieving liquid-liquid heterogeneous mass transfer enhance by centrifugal force. Three typical flow patterns of slug flow, parallel-droplet flow, and parallel flow in the RMCR were observed by high-speed photography technology. The volumetric mass transfer coefficient ( K O a ) of the RMCR increased with the increase of the total volumetric flow rate and rotational speed ( N ) increased. Compared with N  = 0 r/min, the K O a of the RMCR increases by 61.5 % at 200 r/min, ranging from 0.013 to 0.021 s −1 . The RMCR proposed in this work is expected to be applied to the liquid-liquid heterogeneous mass transfer system with high processing capacity and easy plugging.

Algerian Eucalyptus Leaves (AEL), a natural biodegradable adsorbent abundantly available, was used for the removal of methylene blue (MB) dye. The AEL properties for the removal of MB were investigated under different conditions by varying the AEL amount, MB concentration, pH of the solution and the reaction temperature. Scanning electron microscopy (SEM) and infrared spectroscopy (FTIR) techniques have been used to characterize AEL biosorbent. Experimental results showed that the adsorption of MB dye at the concentration of 50 mg L −1 reached to 91 % at pH 10 with a stirring speed of 200 rpm and after 180 min of reaction time. The experimental data were analyzed using the linear forms of different kinetic models (pseudo-first order kinetic model, pseudo-second order kinetic model, and intra-particle diffusion models). The results demonstrated that the adsorption kinetics of MB was consistent with the pseudo-second order model with R 2 value of 0.9969. The isotherm models Langmuir, Freundlich, Dubinin, Elovich, Brunaut Emmet Teller and Temkin models were also investigated to describe the adsorption equilibrium. The results show that the AEL adsorption is in accordance with Temkin isotherm. The thermodynamic study revealed that the adsorption is spontaneous and exothermic. Therefore, as a cheap green adsorbent with high MB adsorption performance, AEL is expected to become one of the best candidate materials for future industrial wastewater treatment.