Experimental investigation on two-phase air/high-viscosity-oil flow in a horizontal pipe

The flow of very-viscous-oil and air through a horizontal pipe (inner diameter 22 mm) is experimentally studied. We first build and analyze the flow pattern map; a comparison between the air–water and the air–oil flow pattern maps shows a strong influence of the fluid properties. The experimental flow maps are compared with empirical and theoretical ones – Baker (1954), Mandhane et al. (1974), and Petalas and Aziz (1998) – showing a poor agreement. Experimental pressure gradients are also reported and compared with theoretical model, but also in this case the agreement is not very satisfactory. Finally, the elongated bubble velocity and length are measured and compared to model present in the literature. We conclude that the high viscosity of the liquid phase has a strong influence on the results and that the current models are not able to predict the flow features satisfactorily.     

Quantifying sub-grid scale (SGS) turbulent dispersion force and its effect using one-equation SGS large eddy simulation (LES) model in a gas–liquid and a liquid–liquid system

The one-equation SGS LES model has shown promise in revealing flow details as compared to the Dynamic model, with the additional benefit of providing information on the modelled SGS-turbulent kinetic energy (Niceno et al., 2008). This information on SGS-turbulent kinetic energy (SGS-TKE) offers the possibility to more accurately model the physical phenomena at the sub-grid level, especially the modelling of the SGS-turbulent dispersion force (SGS-TDF). The use of SGS-TDF force has the potential to account for the dispersion of particles by sub-grid scale eddies in an LES framework, and through its use, one expects to overcome the conceptual drawback faced by Eulerian–Eulerian LES models. But, no work has ever been carried out to study this aspect. Niceno et al. (2008) could not study the impact of SGS-TDF effect as their grid size was comparable to the dispersed bubble diameter. A proper extension of research ahead would be to quantify the effect of sub-grid scale turbulent dispersion force for different particle systems, where the particle sizes would be smaller than filter-size. This work attempts to apply the concept developed by Lopez de Bertodano (1991) to approximate the turbulent diffusion of the particles by the sub-grid scale liquid eddies. This numerical experimentation has been done for a gas–liquid bubble column system (Tabib et al., 2008) and a liquid–liquid solvent extraction pump-mixer system ( [Tabib et al., 2010] and [28] ). In liquid–liquid extraction system, the organic droplet size is around 0.5 mm, and in bubble columns, the bubble size is around 3–5 mm. The simulations were run with mesh size coarser than droplet size in pump-mixer, and for bubble column, two simulations were run with mesh size finer and coarser than bubble diameter. The magnitude of SGS-TDF values in all the cases were compared with magnitude of other interfacial forces (like drag force, lift force, resolved turbulent dispersion force, force due to momentum advection and pressure). The results show that the relative magnitude of SGS-TDF as compared to other forces were higher for the pump-mixer than for the coarser and finer mesh bubble column simulations. This was because in the pump-mixer, the ratio of “dispersed phase particle diameter to the grid-size” was smaller than that for the bubble column runs. Also, the inclusion of SGS-TDF affected the radial hold-up, even though the magnitudes of these SGS-TDF forces appeared to be small. These results confirms that (a) the inclusion of SGS-TDF will have more pronounced effect for those Eulerian–Eulerian LES simulation where grid-size happens to be more than the particle size, and (b) that the SGS-TDF in combination with one-equation-SGS-TKE LES model serves as a tool to overcome a conceptual drawback of Eulerian–Eulerian LES model.     

Controlled peroxide-induced degradation of polypropylene in a twin-screw extruder: Change of molecular weight distribution under conditions controlled by micromixing

Controlled degradation of polypropylene (PP) by peroxide was carried out in a laboratory twin-screw extruder ZSK 18 and the change in Molecular Weight Distribution (MWD) was measured using Size Exclusion Chromatography–Differential Viscosimetry (SEC–DV). The MWD results were compared to MWD predictions from a kinetic model developed and validated in earlier work (Iedema et al., 2001) assuming ideal mixing. Clear deviations were observed – the measured MWD was broader – that could only be explained by unaccounted heterogeneity in the extruder. Incorporating the relatively narrow Residence Time Distribution (RTD) in the twin-screw extruder did not lead to MWD broadening. In contrast, the exponential RTD of a Continuously Stirred Tank Reactor (CSTR) yielded a MWD widening that was too extreme. A new micromixing model, based on the striation thinning model by Ottino (1980), was constructed partly based on Monte Carlo sampling using a monomer scission probability (Tobita, 1996). This model was adapted to the geometry of the extruder entrance and the peroxide feed practice consisting of introducing a few per thousand peroxide-rich PP particles among pure PP particles. This micromixing model indeed allowed obtaining very good matches between measured and modeled MWD. Under different experimental conditions with respect to initial PP quality and amount of peroxide added, with a constant value for the striation thinning parameter the errors between measured and predicted MWD were around 5%.     

Evaluation of realistic 95% confidence intervals for the activation energy calculated by the iterative linear integral isoconversional method

Cai and Chen have proposed a new iterative linear integral isoconversional method that is capable of providing more accurate values of the activation energy than the traditional linear isoconversional methods (Cai, Junmeng, Chen, Siyu, 2009. Journal of Computational Chemistry 30, 1986–1991). However, an analysis of the estimation of confidence intervals for the activation energy determined by this iterative linear integral isoconversional method is still missing. Therefore, this short communication focuses on estimating realistic confidence intervals for the activation energy calculated by the isoconversional method. For this purpose, a comparison of confidence intervals estimated using the Vyazovkin–Sbirrazzuoli corrected Student's percentiles (Vyazovkin, Sergey, Sbirrazzuoli, Nicolas, 1997. Analytica Chimica Acta 355, 175–180) and a nonparametric method has indicated that the use of the Vyazovkin–Sbirrazzuoli method tends to overestimate confidence intervals for three heating rate estimates. The new corrected Student's percentiles for realistic 95% confidence intervals ?_n–2,0.975 of 2.9, 2.5 and 2.3 for three, four and five heating rate estimates, respectively, can be used to obtain realistic confidence intervals for the activation energy computed by the iterative linear integral isoconversional method.     

Gas–liquid flows in medium and large vertical pipes

Gas–liquid bubbly flows with wide range of bubble sizes are commonly encountered in many industrial gas–liquid flow systems. To assess the performances of two population balance approaches – Average Bubble Number Density (ABND) and Inhomogeneous MUlti-SIze-Group (MUSIG) models – in tracking the changes of gas volume fraction and bubble size distribution under complex flow conditions, numerical studies have been performed to validate predictions from both models against experimental data of Lucas et al. (2005) and Prasser et al. (2007) measured in the Forschungszentrum Dresden-Rossendorf FZD facility. These experiments have been strategically chosen because of flow conditions yielding opposite trend of bubble size evolution, which provided the means of carrying out a thorough examination of existing bubble coalescence and break-up kernels. In general, predictions of both models were in good agreement with experimental data. The encouraging results demonstrated the capability of both models in capturing the dynamical changes of bubbles size due to bubble interactions and the transition from “wall peak” to “core peak” gas volume fraction profiles caused by the presence of small and large bubbles. Predictions of the inhomogeneous MUSIG model appeared marginally superior to those of ABND model. Nevertheless, through the comparison of axial gas volume fraction and Sauter mean bubble diameter profiles, ABND model may be considered an alternative approach for industrial applications of gas–liquid flow systems.     

Time scale analysis for fluidized bed melt granulation III: Binder solidification rate

In series I and II of this study ( [Chua et al., 2010a] and [Chua et al., 2010b] ), we discussed the time scale of granule–granule collision, droplet–granule collision and droplet spreading in Fluidized Bed Melt Granulation (FBMG). In this third one, we consider the rate at which binder solidifies. Simple analytical solution, based on classical formulation for conduction across a semi-infinite slab, was used to obtain a generalized equation for binder solidification time. A multi-physics simulation package (Comsol) was used to predict the binder solidification time for various operating conditions usually considered in FBMG. The simulation results were validated with experimental temperature data obtained with a high speed infrared camera during solidification of ‘macroscopic’ (mm scale) droplets. For the range of microscopic droplet size and operating conditions considered for a FBMG process, the binder solidification time was found to fall approximately between 10⁻³ and 10⁻¹ s. This is the slowest compared to the other three major FBMG microscopic events discussed in this series (granule–granule collision, granule–droplet collision and droplet spreading).     

Removal of molybdenum using silver nanoparticles from water samples: Particle swarm optimization–artificial neural network

In this study, a simple and fast method for preconcentration and determination of trace amount of molybdenum from water samples was developed by silver nanoparticles based solid-phase extraction method and UV–vis spectrophotometry. Hybrid of artificial neural network–particle swarm optimization (ANN–PSO) has been used to develop predictive models for simulation and optimization of solid phase extraction method. Under the optimum conditions, the detection limit and relative standard deviation were 11 μg L⁻¹ and <3.9%, respectively. The pre-concentration factor of this method was 50. The method was applied to preconcentration and determination of molybdenum from water samples.     

Enhanced Inter-helical Residue Contact Prediction in Transmembrane Proteins

In this paper, based on a recent work by McAllister and Floudas who developed a mathematical optimization model to predict the contacts in transmembrane alpha-helical proteins from a limited protein data set (McAllister and Floudas, 2008), we have enhanced this method by (1) building a more comprehensive data set for transmembrane alpha-helical proteins and this enhanced data set is then used to construct the probability sets, MIN-1N and MIN-2N, for residue contact prediction, (2) enhancing the mathematical model via modifications of several important physical constraints and (3) applying a new blind contact prediction scheme on different protein sets proposed from analyzing the contact prediction on 65 proteins from Fuchs et al. (2009). The blind contact prediction scheme has been tested on two different membrane protein sets. First, it is applied to five carefully selected proteins from the training set. The contact prediction of these five proteins uses probability sets built by excluding the target protein from the training set, and an average accuracy of 56% was obtained. Second, it is applied to six independent membrane proteins with complicated topologies, and the prediction accuracies are 73% for 2ZY9A, 21% for 3KCUA, 46% for 2W1PA, 64% for 3CN5A, 77% for 3IXZA and 83% for 3K3FA. The average prediction accuracy for the six proteins is 60.7%. The proposed approach is also compared with a support vector machine method (TMhit Lo et al., 2009) and it is shown that it exhibits better prediction accuracy.     

A multiscale decomposition method for the optimal planning and scheduling of multi-site continuous multiproduct plants

This paper addresses the solution of simultaneous scheduling and planning problems in a production–distribution network of continuous multiproduct plants that involves different temporal and spatial scales. Production planning results in medium and long-term decisions, whereas production scheduling determines the timing and sequence of operations in the short-term. The production–distribution network is made up of several production sites distributing to different markets. The planning and scheduling model has to include spatial scales that go from a single production unit within a site, to a geographically distributed network. We propose to use two decomposition methods to solve this type of problems. One method corresponds to the extension of the bi-level decomposition of Erdirik-Dogan and Grossmann (2008) to multi-site, multi-market networks. A second method is a novel hybrid decomposition method that combines bi-level and spatial Lagrangean decomposition methods. We present four case studies to study the performance of the full space planning and scheduling model, the bi-level decomposition, and the bi-level Lagrangean method in profit maximization problems. Numerical results indicate that in large-scale problems, decomposition methods outperform the full space solution and that as problem size increases the hybrid decomposition method becomes faster than the bi-level decomposition alone.     

Computational fluid dynamic simulations of chemical looping fuel reactors utilizing gaseous fuels

A computational fluid dynamic (CFD) model for the fuel reactor of chemical looping combustion technology has been developed, with special focus on accurately representing the heterogeneous chemical reactions. A continuum two-fluid model was used to describe both the gas and solid phases. Detailed sub-models to account for fluid–particle and particle–particle interaction forces were also incorporated. Two experimental cases were analyzed in this study (Son and Kim, 2006; Mattison et al., 2001). Simulations were carried out to test the capability of the CFD model to capture changes in outlet gas concentrations with changes in number of parameters such as superficial velocity, metal oxide concentration, reactor temperature, etc. For the experiments of Mattisson et al. (2001), detailed time varying outlet concentration values were compared, and it was found that CFD simulations provided a reasonable match with this data.     

Steam reforming of methanol over a CuO/ZnO/Al2O3 catalyst, part I: Kinetic modelling

A kinetic study of the methanol steam reforming reaction was performed over a commercial CuO/ZnO/Al₂O₃ catalyst (Süd-Chemie, G66 MR), in the temperature range of 200–300 °C. The reactions considered in this work were methanol steam reforming (MSR) and reverse water gas shift (rWGS). Several MSR kinetic rate models developed by different authors were compared and the one was determined that best fitted the experimental data. A kinetic Langmuir–Hinshelwood model was proposed based on the work by Peppley et al. (1999a) . The kinetic expressions that presented the best fit were used to simulate the packed bed reactor with a one-dimensional model. A good agreement between the mathematical model and the experimental data was observed.     

Hydrodynamic and mass transfer in inertial gas–liquid flow regimes through straight and meandering millimetric square channels

Heat-exchanger reactors are an important part of process intensification technology. For plate geometries, one solution for intensifying transfer and increasing residence times is to construct two-dimensional meandering channels. Supported by this scientific context, the present work aims at characterising gas–liquid mass transfer in the same square millimetric meandering channel, as in Anxionnaz (2009), this constituted the preliminary step required for performing exothermic gas–liquid reactions. Firstly, the gas–liquid hydrodynamics were characterised for a water/air system. When compared to a straight channel of identical compactness and sectional-area (2×2 mm²), the meandering channel induced (i) a delay in the transition from Taylor to annular-slug regimes, (ii) a rise of 10–20% in bubble lengths while conserving almost identical slug lengths, (iii) higher deformations of bubble nose and rear due to centrifugal forces (bends). Secondly, an original method for verifying the relevancy of the plug flow model and accurately determining k_la was used (measurements of concentrations in dissolved oxygen along the channel length). For the Taylor flow regime, k_la increased coherently when increasing j_g, and the meandering geometry had a small influence. On the contrary, this effect was found no more negligible for the slug-annular flow regime. Whatever the channels, the NTU_l remained low, thus showing that, even if millimetric channels allowed to intensify k_la, a special attention should be paid for generating sufficient residence times. At identical compactness, the meandering channel was found to be the most competitive. Finally, results on gas–liquid interfacial areas and mass transfer coefficients were confronted and discussed with respect to the predictions issued from the model developed by Van Baten and Krishna (2004).     

Application of PSO-artificial neural network and response surface methodology for removal of methylene blue using silver nanoparticles from water samples

In this study, a simple and fast method for preconcentration and determination of trace amount of methylene blue (MB) from water samples was developed by silver nanoparticles based solid-phase extraction method and UV–Vis spectrophotometry. Response surface methodology and hybrid of artificial neural network- particle swarm optimization (ANN-PSO) have been used to develop predictive models for simulation and optimization of solid phase extraction method. Under the optimum conditions, the detection limit and relative standard deviation were 15.0 μg L^?1 and <2.7%, respectively. The preconcentration factor was 83. The method was applied to preconcentration and determination of methylene blue from water samples.     

CFD simulation of a chemical-looping fuel reactor utilizing solid fuel

A computational fluid dynamic (CFD) study has been carried out for the fuel reactor for a new type of combustion technology called chemical-looping combustion (CLC). CLC involves combustion of fuels by heterogeneous chemical reactions with an oxygen carrier, usually a granular metal oxide, exchanged between two reactors. There have been extensive experimental studies on CLC, however CFD simulations of this concept are quite limited. In the present paper we have developed a CFD model for the fuel reactor of a chemical-looping combustor described in the literature, which utilized a Fe-based carrier (ilmenite) and coal. An Eulerian multiphase continuum model was used to describe both the gas and solid phases, with detailed sub-models to account for fluid–particle and particle–particle interaction forces. Global reaction models of fuel and carrier chemistry were utilized. The transient results obtained from the simulations were compared with detailed experimental time-varying outlet species concentrations (Leion et al., 2008) and provided a reasonable match with the reported experimental data.     

Investigations on hydrodynamics and mass transfer in gas–liquid stirred reactor using computational fluid dynamics

In this work, the hydrodynamics and mass transfer in a gas–liquid dual turbine stirred tank reactor are investigated using multiphase computational fluid dynamics coupled with population balance method (CFD–PBM). A steady state method of multiple frame of reference (MFR) approach is used to model the impeller and tank regions. The population balance for bubbles is considered using both homogeneous and inhomogeneous polydispersed flow (MUSIG) equations to account for bubble size distribution due to breakup and coalescence of bubbles. The gas–liquid mass transfer is implemented simultaneously along with the hydrodynamic simulation and the mass transfer coefficient is obtained theoretically using the equation based on the various approaches like penetration theory, slip velocity, eddy cell model and rigid based model. The CFD model predictions of local hydrodynamic parameters such as gas holdup, Sauter mean bubble diameter and interfacial area as well as averaged quantities of hydrodynamic and mass transfer parameters for different mass transfer theoretical models are compared with the reported experimental data of [Alves et al., 2002a] and [Alves et al., 2002b] . The predicted hydrodynamic and mass transfer parameters are in reasonable agreement with the experimental data.     

Combination of ACO-artificial neural network method for modeling of manganese and cobalt extraction onto nanometer SiO2 from water samples

In this study, modeling based on ant-colony optimization – artificial neural network have been employed to develop the model for simulation and optimization of nanometer SiO₂ for the extraction of manganese and cobalt from water samples. The pH, time, amount of SiO₂ nanoparticles and concentration of 1-(2-pyridylazo)-2-naphthol (PAN) were the input variables, while the extraction% of analytes was the output. Under the optimum conditions, the detection limits were 0.52 and 0.7 μg L^?1, for manganese and cobalt, respectively. The method was applied to the extraction of manganese and cobalt from water samples and one certified reference material.     

Heterogeneously doped polyethylene glycol as nano-composite soft matter electrolyte

We have applied the concept of heterogeneous doping [1] to prepare and examine composite electrolytes, consisting of silica particles, low molecular weight polyethylene glycol solvents and lithium perchlorate salt. These “soggy sand” electrolytes combine high ionic conductivities (on the order of mS cm⁻¹) and high Li transference numbers (typically 60–80%) with improved mechanical properties. They were characterized using differential scanning calorimetry, dc-polarization and ac-impedance spectroscopy, zeta potential measurements and viscosimetry. Oxide, size and concentration as well as solvent molecular weight were varied to better understand the influence of ceramic oxide fillers on the ion conduction in these systems. As regarding the filler content, we observe that both conductivity and transference number of Li⁺ start increasing already at low volume fractions of oxide particles, reach a maximum and subsequently decrease to low values. The percolating network is – after initial partial coarsening – found to be stable within the time periods of the measurements.     

Dynamics of bubble breakup in a microfluidic T-junction divergence

The aim of this work is to investigate experimentally the bubble breakup in a microfluidic T-junction divergence using a high-speed digital camera and a micro-Particle Image Velocimetry (micro-PIV) system. The breakup and non-breakup of N₂ bubbles in glycerol–water mixtures with several concentrations of sodium dodecyl sulphate (SDS) as surfactant were studied with capillary number ranging from 0.001 to 0.1. The cross section of PMMA square microchannel is 400 μm wide and 400 μm deep. Four various flow patterns were observed at the T-junction by changing gas and liquid flow rates. The dynamics of three various types of symmetric breakup of bubbles were investigated. The symmetric breakup of bubbles type I is mainly controlled by the augmented pressure in liquid phase. The symmetric breakup of bubbles type II is controlled by both the increased pressure and viscous forces. In the symmetric breakup of bubbles type III, a scaling law for the minimum bubble neck and the remaining time during bubble breaking process were found. The transitions between breakup and non-breakup of bubbles were investigated, and a power–law relationship between bubble extension and capillary number was proposed to predict the transitions between adjacent regimes. Our experimental results reveal that the bubble breakup in a microfluidic T-junction divergence is similar to the droplet behaviours in such a device ( [Jullien et al., 2009] , [Leshansky and Pismen, 2009] and [Link et al., 2004] ).     

Demonstration of NIR inline monitoring for hops extraction and micronization of benzoic acid in supercritical CO2

The use of supercritical CO₂ as solvent for separation processes and chemical reactions is widespread. Many industrial extraction processes using CO₂ consume a huge amount of energy and hence are very cost-intensive. In the past, the duration of extraction was often longer than required for an optimum result. Therefore, an inline monitoring device for terminating CO₂ extraction processes at the right time has been desirable. In collaboration between KIT and SITEC-Sieber Engineering, Switzerland, a mobile near infrared (NIR) inline monitoring device has been developed to close this gap and to offer an opportunity to implement it into industrial extractions processes using CO₂ and to use the data for process optimization. NIR spectroscopy with fiber optics adaption has been proven to be a very good choice, because the CO₂ bands are well separated from all other bands of interest caused by the extracts (organics and water). The NIR inline monitoring device can easily be implemented into industrial plants to visualize the extraction progress and to terminate the process at the right time in order to save energy and money. Measurements on customer's demand are available for extraction and reaction processes in supercritical CO₂.This paper will actually focus on two applications. Firstly, in collaboration with NATECO₂, Germany, the NIR inline monitoring device has been implemented into a plant for hops extraction with supercritical CO₂. Extractions have been performed and successfully monitored for the varieties Hallertauer Magnum, Hallertauer Herkules, and French Strisselspalter at 60 °C and 25 MPa, 28 MPa, and 50 MPa, respectively. The detectability was 0.1 wt% of hops in CO₂.Secondly, the applicability of this NIR inline monitoring method on processes for the production of submicron particles in supercritical CO₂ has been demonstrated in a feasibility study. For this purpose, a RESS (Rapid Expansion of Supercritical Solution) high pressure plant (160 ml, max. 35 MPa, max. 120 °C) was built and the NIR inline monitoring device integrated. Two syringe pumps were coupled for an almost pulsation-free-feeding. Benzoic acid was used as a reference solid. In this feasibility study, the focus has not been to perform an optimized RESS process, but rather to monitor the loading of the CO₂ phase with benzoic acid continuously, as this information is crucial for the optimization of a RESS process and has not been available up to the present. The experiments have been carried out at 55 °C and 25 MPa as reference conditions. The performed calibration resulted in a detection limit of 0.1 mg benzoic acid per g CO₂. The loading of the CO₂ phase has been successfully and continuously monitored and can now be applied for other systems.A side effect of these investigations has been the finding that this NIR inline monitoring device can also be used for very precise solubility measurements and to visualize the establishment of thermodynamic phase equilibrium as a function of time, especially in cases of low solubility of a substance in CO₂. The NIR inline monitoring device can also be used for the inline monitoring of reactions producing data for kinetic modeling and process optimization.     

Metastable states during dissociation of carbon dioxide hydrates below 273 K

In this study, the dissociation of isolated carbon dioxide hydrate particles of sizes in the range 0.25–2.5 mm was investigated. It was found that below the ice melting point, the hydrates dissociated into supercooled water (metastable liquid) and gas. The formation of the liquid phase during CO₂ hydrate dissociation was visually observed, and the pressures of the hydrate dissociation into supercooled water and gas were measured in the temperature range 249–273 K. These pressures agreed well with the calculated data for the supercooled water–hydrate–gas metastable equilibrium (Istomin et al., 2006). In the P–T area on the phase diagram bounded by the ice–hydrate–gas equilibrium curve and the supercooled water–hydrate–gas metastable equilibrium curve, hydrates could exist for a long time because the metastable phase and their stability are not connected to the self-preservation effect. The growth of the metastable CO₂ hydrate film on the surface of supercooled water droplets formed during the hydrate dissociation was observed at pressure above the three-phase supercooled water–hydrate–gas metastable equilibrium pressure but still below the three-phase ice–hydrate–gas equilibrium pressure. It was found that the growth rate of the metastable CO₂ hydrate film was higher by a factor of 25 and 50 than that for methane hydrate and propane hydrate, respectively.