Band 6, Heft 1

The present work aims at finding the best distillation sequence in terms of control properties for the separation of a ternary mixture of n-pentane, n-hexane and n-heptane. The study has been carried out using ASPEN PLUS. The different sequences have been compared for regulatory problem (step change in feed concentration and feed flow rate) and servo problem (step change in product composition). PI controller has been used to control level and composition in the various configurations studied. Auto tuning of the controller has been carried out using relay feedback test. Ziegler–Nichols method was used to calculate controller gain (KI) and integral time (τI) of PI controller. Controller parameters have been fine tuned using these tuning maps.

The main aim of this paper is to establish a reliable model of a process behavior under the normal operating conditions. The use of this model should reflect the true behavior of the process in the whole way and thus distinguish a normal mode from the abnormal modes. In order to obtain a reliable model for the process dynamics, the black-box identification by means of a NARMAX model has been chosen in this paper. It is based on the neural networks approach. The main advantage of the proposed approach consists in the natural ability of neural networks in modeling non-linear dynamics in a fast and simple way and in the possibility to address the process to be modeled as an input-output black-box, with little or no mathematical information on the system. This paper will show the choice and the performance of the neural network in the training and the test phases. A study is related to the number of inputs, and of hidden neurons used and their influence on the behavior of the neural predictor. Three statistical criterions, Aikeke’s information criterion (AIC), Rissanen’s Minimum Description Length (MDL), and Bayesian information criteria (BIC), are used for the validation of the experimental data. In order to illustrate the ideas proposed concerning the dynamics modelling, a heat exchanger is used. The outlet temperature is modeled according to the inlet temperature. The model is implemented by training a Multilayer Perceptron artificial neural network with input-output experimental data. Satisfactory agreement between identified and experimental data is found and results show that the model successfully predicts the evolution of the outlet temperature of the process.

Discrete, or Distinct, element modelling, DEM, is used to investigate the effect of particle shape on hopper flowrate. Firstly, simulation results using a model based on spherical particles are validated against solid discharge rates predicted by the modified Beverloo equation. The validated model is then used to investigate the shape effects on discharge rate from a flat bottomed rectangular hopper. Two regular rounded polyhedral particles are studied. The discharge rate varies significantly with particle shape. A reduction on flowrate of up to 49% and 41% is observed for tetrahedral and octahedral particles, respectively. The effects of friction, cohesion, and damping on flowrate are also investigated with DEM.

In the present study dealing with nanodrug delivery, nanofluid flow in a microchannel is considered. The nanofluid considered is a solid (aluminum oxide) - liquid (water) mixture. A transient 3-D problem of controlled nanodrug delivery has been numerically solved. The study has been carried out using ANSYS CFX Version 11.0. The velocity profile and dimensionless nanodrug concentration profile for different Reynolds number ratios were obtained at different axial stations along the length of the microchannel (z = 0.5, 5, and 10mm). Effect of particle size on drug uniformity has been investigated.

Membrane reactor is a process intensified equipment that carries out both the reaction and separation in a single vessel. The equilibrium limited water gas shift reaction is an ideal reaction to be carried out in a membrane reactor as it improves the conversion of the reaction and reduces the space requirement for the reactor. Computational fluid dynamics offers a virtual prototyping of the reactor and helps in design, optimization, and scale-up of the reactor. To obtain pure hydrogen from the membrane reactor, the pressure of the reactor needs to be optimized. Hence the water gas shift membrane reactor is subjected to computational fluid dynamic analysis to understand the role played by pressure on the performance of the reactor using three different gas mixtures. The CO conversion and H2 recovery for the different operating pressures are simulated and the effects of pressure are discussed in this paper.

In this paper, an industrial linear low density polyethylene (LLDPE) production process including two serried fluidized bed reactors (FBR) and other process equipment was completely simulated in steady state mode. Both of FBRs were considered like two serried continuous stirred tank reactors (CSTR). In this simulation, a kinetic model that is based on a multiple active site heterogeneous Ziegler-Natta catalyst was used for simulation of reactions in two FBRs. Simulator by using this model is able to predict the important attributes of LLDPE like melt flow index (MFI), density (ρ), polydispersity (PDI), numerical and weight average molecular weight (Mn, Mw) and co-polymer molar fraction (SFRAC). On the other hand, this simulator can be applied in wide range of changing in inlet operating conditions. The results of the simulation are compared with industrial data of LLDPE plant. A good agreement is observed between the simulator predictions and actual plant data. Finally, by using of the simulator, the steady state operating conditions for producing different grades of polyethylene are obtained.

Wet gas metering by differential pressure flow meters is gaining prominence in the oil and gas industry, owing to their simple construction. Slotted orifice, a modified version of the standard orifice meter has been found promising by many researchers. This novel flow meter is shown to be insensitive to the upstream flow profile with lower head loss and faster pressure recovery compared to the standard orifice. In the present work, the effect of geometry of slots and pressure on the performance of the slotted orifice has been studied by CFD modeling of the wet gas flow. The performance of slotted orifice with rectangular perforations (1.5 ≤ l/w ≤ 3.0) and circular perforations has been compared with that of the standard orifice having same β-ratio of 0.40. Simulation results reveal that the shape of perforation of the slotted orifice has no effect on the differential pressure. However, the pressure recovery with the rectangular slots is found to increase with increasing aspect ratio. Moreover, at low pressure, slotted orifice is found to be more sensitive to liquid presence than the standard orifice. The relatively higher over reading values obtained in this work is consistent with the results of Geng et al (2006) that for slotted orifice, a low beta ratio is more sensitive to the liquid presence in the stream and hence is preferable for wet gas metering. Homogeneous model, Steven’s and De Leeuw’s correlations, are found to be better than orifice correlations for wet gas mass flow prediction.

In this study, the performance of a fixed–bed tubular reactor for the production of phthalic anhydride is mathematically analyzed. The conversion degree and reactor temperature values are compared with the measured one in a tubular reactor applied in Farabi petrochemical unit in Iran as well as reported data in the literature for a pilot plate. The comparisons are satisfactory. The effects of some operating parameters including reactor length, feed temperature, reactor pressure, and existence of an inert in the catalytic bed are investigated. The optimum value of each parameter is determined on the basis of the corresponding operating conditions.

One-hidden-layer artificial neural networks (ANNs) using a back-propagation structure have been trained on different sets of experimental data to identify and evaluate the degradation of different azo dyes (Reactive Yellow 84, Reactive Blue 19, Direct Red 23, Direct Red 28, and Acid Blue 193) by photo-Fenton process and combined ozonation and ultrasonolysis processes. Different input variables such as pH, initial concentrations of dyes and ozone, reaction time, ultrasonic power density, and initial concentrations of hydrogen peroxide and ferrous in aqueous solution were employed to model the degradation rates of azo dyes based on the decolorization efficiency and the removal rate using chemical oxygen demand (COD) and total organic carbon (TOC). A new model expression is developed to find the effect of individual parameters and their interactions on the efficiency of organic degradation by advanced oxidation processes.

The capability of Computational Fluid Dynamics (CFD) alternates the interest of researcher from the empirical models into the numerical approaches for studying hydrocyclones. This paper presents a comprehensive survey on the influences of turbulence model options in the 3D simulation of the hydrocyclone flow pattern. The required grid resolution was selected through a grid independency study. Four categories of turbulence models involving models based on the Boussinesq hypothesis, the Reynolds Stress Model (RSM), the Large Eddy Simulation (LES) model, and the Detached Eddy Simulation (DES) model were investigated for prediction of velocity components within the hydrocyclone. The methodology was validated by experimental data. The results confirm that both RSM and LES models are efficient turbulent model choices for the simulation of swirling flow of hydrocyclones.

Considering that there are many factors having highly nonlinear effect on the Murphree efficiency of column in petrochemical industry and that the obtained accurate value of the Murphree efficiency plays an important role in the performance of the column model, a novel hybrid model method which combines mechanism with least square support vector machine (LS-SVM) is proposed to model solvent dehydratic distillation column (SDDC). In the hybrid model, the mechanism method is used to develop the whole model of SDDC, and LS-SVM is employed to describe the relationship between the factors and the Murphree efficiency due to the nonlinear representing ability of LS-SVM. Further, the correlation between the factors and the Murphree efficiency is analyzed to select the input variables of LS-SVM, and leave-one-out cross-validation method is employed to demonstrate the performance of LS-SVM. The simulation result shows that the hybrid model has robust and good predicting performance and can simulate different conditions of SDDC.

The main factors that influence the adsorption process were studied by means of numerical simulation, based on experimental data of the rupture curve of an adsorption column employed in the purification of clavulanic acid with Amberlite IRA-400 ion-exchange resin. Starting from a heterogeneous model that describes fixed bed adsorption, three important process parameters were determined and evaluated: the degradation constant inside the pores of the resin, the global mass transfer coefficient, and the axial dispersion coefficient. The model was adjusted to the experimental data of an absorption column operating with clavulanic acid feed concentrations of 100.0; 114.0 and 122.0 mg/L, pH 6.2, at a temperature of 10°C. The results confirmed the good adjustment of the numerical simulation to the experimental data.

Many biological phenomena of interest occur on a time scale that is too great to be studied by atomistic simulations. The use of coarse-graining methods to represent a system can alleviate this restriction by reducing the number of degrees of freedom thus extending the time and length scale in molecular modeling. Coarse-grained molecular dynamics (CGMD) technique was employed to simulate diffusion of water in the nanopores of lysozyme protein crystals. Good agreement was obtained between the atomistic and CG simulations in view of the stability of the protein crystal structure and water transport properties. Our simulations demonstrate that the CG method is a suitable technique for simulation the solvent diffusion process in the lysozyme protein crystal and also can be a good technique to predict the behavior of solvent and solutes in the biological systems at longer length and time scales.

Compacted bentonite is the main candidate for buffer material in several plans for spent nuclear fuel repositories. One of its important properties is high swelling capacity, which is caused by interaction between water molecules and exchangeable cations. This interaction makes bentonite behave differently from capillary materials. In this article, a model for thermo-hydro-mechanical state of partially water saturated bentonite is presented. It couples the water retention and swelling properties with introduction of the swelling factor in effective strain. The Helmholz energy density determines the state with a relatively small set of independent parameters: swelling pressure, swelling factor, maximum confined water content and the reference state. The model parameters are determined from experimental data for FEBEX bentonite, and as a simple consistency check, confined suction curves are calculated and compared to test results. Consistency of the model with observations on nano- and microscale of bentonite is also discussed.

This paper presents a new adaptive control scheme based on feedback linearization technique for single-input, single-output (SISO) processes with nonlinear time-varying dynamic characteristics. The proposed scheme utilizes a modified growing and pruning radial basis function (MGAP-RBF) neural network (NN) to adaptively identify two self-generating RBF neural networks for online realization of a well-known affine model structure. An extended Kalman filter (EKF) learning algorithm is developed for parameter adaptation of the MGAP-RBF neural networks. The MGAP-RBF growing and pruning criteria have been endeavored to enhance its performance for online dynamic model identification purposes. A stability analysis has been provided to ensure the asymptotic convergence of the proposed adaptive control scheme using Lyapunov criterion. Capabilities of the adaptive feedback linearization control scheme is evaluated on two nonlinear CSTR benchmark processes, demonstrating good performances for both set-point tracking and disturbance rejection objectives.

This work deals with the study of thermodynamical models for the solid-liquid equilibrium (SLE) and comparing its performance with experimental data. The xylose solubility in the xylose-water and xylose-water-ethanol systems has been measured using a variant of the isothermal method. A total of 12 experiments were performed in a 100 mL glass jacketed crystallizer with helix-type agitator by changing the temperature from 0 to 60°C. The solution was mixed during 72 h with an IKA Labortechnic, RW 20.n agitator at 450 rpm. Later, the experimental and reported results were fitted using the prediction models based on the vapor-liquid-equilibrium (UNIFAC (Universal Functional Activity Coefficient), ASOG (Analytical Solutions of Groups) and GSP (Group Solubility Parameter); semi-empirical models based on the vapor-liquid-equilibrium (VLE) (UNIQUAC (Universal Quasi Chemical), Wilson and NRTL (Non Randon Two Liquid)) on the solid-liquid-equilibrium, and empirical model with fitted parameters (Nývlt, λh, Margules with 1 and 2 parameters). The results showed that the UNIQUAC model with fitted parameters can describe the SLE with reasonable accuracy (1.28 and 3.36% for binary and ternary systems, respectively). The average deviation was the arithmetic mean of the deviations. On the other hand, the other methods resulted in poor agreement with the system’s behavior presenting systematic deviations from the experimental data.

The existence of sulfur in crude oil and petroleum fractions imposes plenty of harmful effects to the environment and process equipment. Therefore, elimination of these compounds from petroleum cuts has extensively been studied. In this research, the process of hydrodesulfurization of dibenzothiophene as one of the most stable sulfur components has been discussed and nonisothermal heterogeneous modeling and simulation of the three-stage trickle bed reactor has been performed. The catalyst, used in this operation, is CoMo/Al2O3. A kinetic equation, based on the Langmuir-Hingshelwood method of rate determination was incorporated into the model. The feed of the reactor was assumed to be gas oil and reactor inlet temperature and pressure were 354°C and of 70barg, respectively. The presence of stagnant liquid pockets between catalyst particles and the heat production due to highly exothermic HDS reactions have been considered in this model. The simulation results showed sulfur conversion of 99% in the final product and good agreement between the simulation results and the experimental data were achieved. In addition, two-dimensional modeling of the first bed of the reactor was conducted. The results indicated that maximum conversion rate occurred at the central axis of the reactor. The model has the ability of determining the position of the hot spots inside the reactor.

A growing number of studies indicated that human exposure to traffic-emitted ultrafine particles (UFP) was associated with adverse health effects. In this study, we estimated the UFP concentrations and the intake fraction (iF) in Corpus Christi, Texas. The UFP concentrations were predicted at the census block level by modifying the CALINE4 Gaussian dispersion model using distance-dependant scaling functions specifically for UFPs. The scaling functions for daytime and nighttime are expressed as 0.12+1.60exp(-0.0067x) with an R2 of 0.78 and 2.58+1.17exp(-0.010x) with an R2 of 0.89, respectively, where x represents the downwind distance of the receptor from the road in meters. The scaling function was derived from the ratio of measured UFP concentrations to estimated UFP concentrations using the unmodified CALINE4 model near four freeways and was applicable for the roads with light duty vehicle fraction ranging 65-95 percent, winds near-perpendicular to the roads with speed < 3.5 m/s, 50-90 percent relative humidity, and 15-30°C temperature. In the Corpus Christi urban area, the average daily UFP concentrations were estimated 5.6×103 #/cm3 (STD: 3.1×103 #/cm3) and 6.4×103 #/cm3 (STD: 7.3×103 #/cm3) in January and July of 2006, respectively. In the downtown area with busy traffic, the average estimated UFP concentration was 7.7×103 - 9.3×103 #/cm3. The traffic-emitted UFP iFs in Corpus Christi were estimated being 5.9 per million and 7.7 per million in January and July, respectively. Despite the limitations of the input data, our results can be helpful in modeling vehicular UFP concentrations near roadways.

The bark extracts of various commercially important trees contain polyphenolics, which in the form of tannins can form condensation products with formaldehyde to produce wood adhesives. In the present work, aqueous acetone and aqueous ethanol were used as solvents to extract tannin from Pinus caribaea bark. The Stiasny number was determined as well as the amount of sugar co-extracted. Batch experiments were performed at different extraction times (30-180 min), extraction temperature (35-60°C for aqueous acetone; 35-80°C for aqueous ethanol), solvent concentration (10-100 percent), stage extraction (1-6) and liquid-solid ratio (10-50). A mathematical model was proposed to identify the effects of the individual interactions of these variables on the extraction of tannin using the two different solvents. The results have been modeled using response surface methodology. The response surface method was developed using five levels (-2, -1, 0, +1, +2) with the above mentioned factors except the stage extraction factor. The second order quadratic regression model fitted the experimental data with Prob > F to be < 0.0001 for the aqueous ethanol extraction and Prob > F to be < 0.006 for the aqueous acetone extraction. The experimental values were found to be in good agreement with the predicted values, with a satisfactory correlation coefficient of R2 = 0.82 in the case of aqueous ethanol extraction and R2 = 0.45 in the case of aqueous acetone extraction. The maximum predicted tannin yield of 20.68 percent was obtained under the optimum extraction conditions of 71.46°C extraction temperature, 79.2 min extraction time, 21.9 percent ethanol concentration, and 26.4:1 liquid-solid ratio. The amount of total sugars and the Stiasny number predicted under these conditions were 4.94 percent and 80.47 percent, respectively.

Drying kinetics of microwave, convective and microwave assisted convective drying of thin layer Nendran banana was investigated on a modified microwave oven. The drying characteristics through the operating parameters of the drying process, such as power output, air temperature, slice thickness and sample mass in terms of drying rate equation, were analyzed. An appropriate empirical model to represent the drying process was established by analyzing the available literature models with current experimental data. The statistical analysis for the selected model was performed, parameters like Mean Bias Error, Root Mean Square Error, reduced chi square and t-stat were estimated to examine the consistency of the model to represent the present experimental results. Higher rates and shorter drying times were achieved at a higher temperature and microwave heating power and lesser sample thickness and load. Microwave drying resulted in a substantial decrease in the drying time with better quality product when dried at higher power (300 W) level compared to other processes.

In this work, a structured mathematical model of the VERvet Origin (VERO) cell metabolism in a fixed-bed bioreactor is developed. Mass balance equations for the extra- and intracellular species are written considering the main pathways of the animal cell metabolism. From the model equations, an undetermined set of equations relating the consumption or production velocities of the extracellular species and the velocities of the metabolic reactions can be developed. The monitoring of a reference cell culture enables to transform this undetermined set of equations in a determined one. The resolution of this determined set of equations enables to analyze and characterize the cell metabolism. From the model and the cell metabolism characterization, a monitoring tool is developed to simulate the time evolution of the species concentrations when the time evolution of the cell concentration is known. This simulation tool is used to simulate five experimental cell cultures. The comparison of the experimentally determined and computed time evolutions of the species concentrations enables to validate the developed monitoring tool. The validated monitoring tool can be used to optimize the operating conditions of the culture, as the medium feeding rate, the range of the species concentrations.

In this study, Maxwell-Stefan (M-S) formulation was used to describe the behavior of diffusion in steady state of light (gaseous) hydrocarbons in nanostructure MFI zeolite membranes. Also, ideal adsorbed solution theory (IAST) and dual site Langmuir (DSL) for evaluating sorbate loading were used. A new solution method was used to calculate fluxes through zeolite membranes. For a mixture of methane, ethane, propane and n-butane, the proposed method was used and showed the same behavior as predicted in the literature using single site Langmuir adsorption theory. Then, for a binary mixture of methane and propane, this method showed that the predicted permeation selectivity of gaseous hydrocarbons through nanostructure MFI zeolite membranes has better agreement with literature experimental data compared to that of the models presented in the literature.

In this work, a mathematical model of a fixed-bed bioreactor for the animal cell culture is developed to study the optimization and the scale-up of this bioreactor. Several cell populations are considered: the cells in suspension in the medium at the beginning of the process and the adhering cells to the fixed-bed. The model includes a capture rate kinetic of the cells in suspension by the fixed-bed and a spatial distribution of the nutrient and by-product concentrations in the fixed-bed. Therefore, the model reports the potential gradients of the cell concentrations in the fixed-bed. Some model parameters are experimentally identified and the model is validated using experimental data obtained with two pilot bioreactors. The model is used as a simulation tool to study the influence of the bioreactor design or the velocity field of the culture medium on the cell concentration gradients in the fixed-bed bioreactor and to optimize the operating conditions, the design, and the scale-up of this bioreactor.

The cellulase production by Trichoderma viride was optimized using artificial intelligence-based techniques under solid state fermentation. In this study, a back propagation network was designed with Levenberg-Marquardt training algorithm, and the tangent sigmoid and pure linear functions were used as the transfer functions in the hidden and output layers of the ANN, respectively. An artificial neural network coupling genetic algorithms was used to optimize the process parameters, which include the mass ratio of wheat straw to wheat bran, moisture content and fermentation time. The ultimate process parameters of optimization were mass ration of wheat straw to wheat bran 2.9, moisture content 69.6 percent, and fermentation time 123.3h. Further test experiment showed that the final cellulase activity can reach to 11.62 U/g, which was the highest value among all the experimental results. This result indicates that the genetic algorithm based on a neural network model is a better optimization method for cellulase production in solid state fermentation. To improve the cellulase production, a mixed culture system of Trichoderma viride and Aspergillus niger was also developed. The cellulase activity increased by 7.40 percent with the addition of Aspergillus niger at 72h.

The insertion of an axially positioned non-porous and porous draft tube into the conventional spouted bed has shown potential advantages in stability and flexibility of the system and controlling particle trajectory history. In this work with computational fluid dynamics (CFD), important information on the flow field within three types of spouted bed has been provided and influences of using internal tube on spouted beds hydrodynamics were investigated. The simulation used the multi-fluid Eulerian-Eulerian approach based on kinetic theory of granular flows (KTGF), incorporating a kinetic-frictional constitutive model for dense assemblies of particulate solids and Gidaspow’s drag model for the interaction between gas and particles. Finally, the modeling results were compared with the experimental data from literature.

Briquetted urea is commonly used in wet agricultural soils since it has potential to reduce loss of urea occuring in the fields by various mechanisms. In the present study, commercially available uncoated urea briquettes were subjected to release in wet loam and wet silty clay soils, both maintained at 40% moisture, measured on dry basis. Adapted semi infinite model and developed shrinking core model predictions were compared with the experimentally determined concentration profiles and unreleased quantity of urea, respectively. Semi infinite model developed with the assumption of unchanging briquette size did not match well with experimental results. However, shrinking core model predicted the unreleased urea contents in briquettes reasonably well.

In this study, Taguchi method was used to identify the several factors that may affect the percentage degradation of phenol and p-chlorophenol in wastewater in a UV/H2O2/TiO2 system. The percentage degradation of phenol and p-chlorophenol was greatly influenced by factors such as pH, cycle time and initial concentration of the organic pollutant. By using orthogonal experimental design and analysis technique, the UV/H2O2/TiO2 system performance can be analyzed with more objective conclusion through only a small number of simulation experiments. Analysis of variance (ANOVA) was carried out to identify the significant factors affecting the response and the best possible factor level combination was determined through. Finally, a regression model for percentage degradation of phenol and p-chlorophenol has been developed, as a function of system parameters. It was found that a UV/H2O2/TiO2 system decomposition of the organic pollutant were highly dependent on cycle time followed by pH of aqueous solution. The optimal settings of highest percentage degradation of phenol and p-chlorophenol in wastewater were also determined.

In this work, flow patterns within an annular chemical reactor were characterized. The reactor was modeled by a cascade of communicating Continuous Stirred Tank Reactors (CSTRs) exchanging flow rates of variable intensities. Mixing time and Residence Time Distribution measurements were used as basis for flow modeling. A Matlab computer code has been developed to predict the exchanged flow rates through the minimization of an objective function. This paper describes the parameter estimation technique which is based on the Gauss-Newton method with a linear search algorithm. Only two opposite flow rates between reactor compartments were assumed and were identified for various mixing conditions. For the studied cases, the predicted responses were close to the experimental measurements.

Carbon dioxide (CO2) gas solubilities are predicted via quantum chemical calculations, which only requires molecular structure as initial information. The quantum chemical based Conductor like Screening Model for Real Solvents (COSMO-RS) has been adopted for this purpose. Predictions of gas solubility at temperatures ranging from (283.15 to 323.15 K) at 0.1 MPa were done for the IL:[EMIM][TFI]. The relative absolute deviation of around 30% shows that the quality of predictions is highly dependent on the infinite dilution activity coefficient of CO2 in [EMIM][TFI].Additionally thermodynamic parameters such as Gibb’s Energy of solvation, enthalpies and entropies have also been predicted and compared for the IL:[BMIM][BF4]. In addition, the carbon dioxide solubility in 16 ionic liquids comprising of imidazolium and pyridinium based cations was validated with reported values. The Root Mean Square Deviation (RMSD) obtained was: 3.09% [TFI], 6.5% [TFO] and 12% [PF6], respectively. Finally, the Henry’s constants of CO2 in 286 ionic liquids comprising of newer cations such as pyrrolidinium, piperidinium and morpholium were predicted at T=298.15 K. The saturated aromatic ring structure of pyrrolidinium, morpholinium and piperidinium based ionic liquids possessed low Henry’s constant values which indicates high solubility of CO2 in ionic liquids.

During a cell culture in a bioreactor, the cells are exposed to the shear stresses mainly generated in the culture medium by the mixing device. Beyond a critical shear stress, this exposition induces cell damages. Therefore, the limitation of the shear stress is an important criterion for the design of bioreactors. An accurate modeling of the flow and the induced shear stresses in the medium is a tool to achieve an effective design of a bioreactor. In this work, a new design of a mixing device is considered. The aims of this work are to develop a methodology to study the flow and the induced shear stresses in the device, to study and to model the relation between the flow, the induced shear stresses and the cell viability, to use the developed model as an optimization tool, and to study the design of the bioreactor mixing device and its scale-up. In a first step, the flow and the induced shear stresses in the device are simulated by Computational Fluid Dynamics. In a second step, the model of the influence of the flow and the induced shear stresses on the cell viability is established by a comparison between the computed flow and the induced shear stresses and experimental measurements of cellular viabilities for different impeller rotation speeds. Finally, the influence of another design of the mixing device on the cell viability is studied.

The flow pattern and mixing in an industrial Peirce-Smith converter (PSC) has been experimentally and numerically studied using cold model simulations. The effects of air volumetric flow rate and presence of overlaying slag phase on matte on the flow structure and mixing were investigated. The 2-D and 3-D simulations of the three phase system were carried out using volume of fluid (VOF) and realizable k - ɛ turbulence model to account for the multiphase and turbulence nature of the flow respectively. These models were implemented using commercial Computational Fluid Dynamics (CFD) numerical code FLUENT. The cold model for physical simulations was a 1:5 horizontal cylindrical container made of Perspex with seven tuyeres on one side of the cylinder typifying a Peirce-Smith converter. Compressed air was blown into the cylinder through the tuyeres, simulating air or oxygen enriched air injection into the PSC. The matte and slag phases were simulated with water and kerosene respectively in this study. The influence of varying blowing conditions and simulated slag quantities on the bulk mixing was studied with five different air volumetric flow rates and five levels of simulated slag thickness. Mixing time results were evaluated in terms of total specific mixing power and two mixing time correlations were proposed for estimating mixing times in the model of PSC for low slag and high slag volumes. Both numerical and experimental simulations were in good agreement to predict the variation characteristics of the system in relation to global flow field variables set up in the converter through mathematical calculation of relevant integrated quantities of turbulence, Volume Fraction (VF) and velocity magnitudes. The findings revealed that both air volumetric flow rate and presence of the overlaying slag layer have profound effects on the mixing efficiency of the converter.

A project team was given the task of evaluating various technology options for design of a small-scale gas-to-liquids (GTL) process operated remotely at or near an individual gas source. For this study, small-scale plants were considered those producing between 100 and 500 barrels per day of liquid fuels. In addition, being remote enforced limitations on utility sources available to the plant site such as water and grid power. A secondary goal was development of a dynamic model of the plant to use in operator training. To accomplish these objectives, the authors investigated the suitability of a process-simulation application. The conceptual design of the GTL unit included many different possibilities, such as front-end design, back-end design, heat integration, and recycling of materials. Complications associated with plant start-up and shutdown, utilities, process reliability, and economics were included in the decision-making process. The authors present selective results from a steady-state model and sensitivity studies. Considerations for the development of the dynamic model included both a fully rigorous dynamic model and a pseudo-dynamic steady-state-based model; results of the latter model are provided. The study concluded that an industrial steady-state simulation tool provided sufficient flexibility to complete the material and energy-balance calculations, sensitivity analyses, and pseudo-dynamic modeling. This study yielded significant insights into the importance of model assumptions and their impact on the overall process viability. The pseudo-dynamic model also provided insight for improving the process control design. During the work completed the authors determined that the object-oriented structure adopted for the model enabled an efficient, rapid model development.

This study proposes a model for the fast pyrolysis of biomass. A reaction scheme of a set of three parallel reactions followed by a set of two parallel reactions has been used to describe the primary and secondary reactions of biomass pyrolysis in a stationary bed reactor. A simple first-order kinetic approach has been applied to predict the product yields. The bed hydrodynamics, the mass transfer between phases and the reaction kinetics have been mathematically formulated. The effects of the operating parameters on the biomass pyrolysis product yield were simulated; the results show that the reaction temperature and nitrogen flow rate plays an important role in the yield of bio-oil. Good agreement between the predicted and measured results was obtained.

A pressure swing adsorption air separation process in a commercial aircraft using 13X zeolite with a more complex cycle than the classic Skarstrom was simulated via a predictive dynamic model to evaluate and optimize oxygen generation system. The coupled mass, energy, and momentum differential equations were discretized using the implicit central finite-difference technique and the obtained equations were solved by Newton-Raphson method. The validated model in conjunction with an optimization procedure (Successive Quadratic Programming) was utilized to investigate the oxygen separation efficiency as a function of β (ratio between the bed time constant and the particle diffusion time constant), Cfp (purge orifice coefficient), θcycle (cycle time), Cff (feed valve), Cfe (exhaust valve) and pH* (high pressure operation). A set of optimum values (β=150, Cfp=0.7, θcycle=1.5, Cff=31, Cfe=52 and pH*=3.8) was obtained and recommended to achieve maximum recovery (0.26) at 98% purity.

The temperature control and the composition control for the production process was used to evaluated a method to control the quality of methyl ester production in a reactive distillation column. The optimum condition at steady state was selected as the base case condition for the control study by using Aspen Dynamic Simulation. In this work, two controller settings for PID controller of each control loop were based on the Zeigler-Nichol and the Tyreus-Luyben tuning formulae. The controllability and performance of both control structures were compared. The result shows that the control loop using the Ziegler-Nichols setting gave better control performance than the other using the Tyreus-Luyben setting. It also found that the control structure based on temperature control gives the same control performance as the other based on composition control, but less expensive and less complicated to implement.

This paper presents a numerical study to predict the particle separation performance of a dust-settling hopper using computational fluid dynamics. The Euler-Lagrange approach was employed to analyze the particle separation efficiency and the outflow particle concentration of the dust-settling hopper under different inlet airflow velocities. The calculation results obtained reveal that the overall particle separation efficiency and the outflow particle concentration decrease with the increase of the inlet airflow velocity, and the particle grade efficiency increases with particle size. Since there is a paradox between the particle separation performance and the particle removal performance for a street vacuum sweeper, it is necessary to counter-balance the effects of the inlet airflow velocity on them. According to the simulation analysis, an appropriate inlet airflow velocity is provided for the design of the dust-settling hopper.

Soft sensors have proved themselves as valuable alternatives to the traditional means for the acquisition of critical process variables, process monitoring and other tasks relating to process control. Most of the present day soft sensors for complex chemical processes are designed from actual industrial data because of the various difficulties associated with developing first principle models such as poor process understanding, impossible or difficult to determine model parameters and mathematical complexity of the models. This paper discusses characteristics of the process industry data which are critical for the design and development of data driven soft sensors. The focus of this paper is on the different shortcomings of the raw process data collected from the historical database and a review of different techniques available for processing of the raw data so as to make the data suitable for design of data driven soft sensors.

Inorganic membranes for gas separation and purification have attracted great research interest. One application utilizing these materials is for H2 production from the water-gas shift reactions (WGS). The exothermic, reversible WGS reaction is controlled by thermodynamic equilibrium and exhibits decreased conversion with increasing temperatures. It is envisaged that the reaction conversion will surpass the equilibrium value if the reaction is conducted in a hydrogen-permselective membrane reactor, where the hydrogen product can be continuously removed from the reactor to shift the reaction equilibrium. In this article, the most recent development on material synthesis and fabrication of microporous ceramic membranes and dense palladium-based metal membranes are firstly reviewed according to their performance for H2 permeance and permselectivity over slightly larger molecules. The modification methods for improving membrane structure integrity, hydrophobicity, and stability at high temperature operation are also discussed. Subsequently, inorganic membrane reactors for the WGS reaction are evaluated in terms of CO conversion, hydrogen purity and operation parameters. Finally, modeling on gas transport through inorganic membranes and simulation of membrane reactors are discussed. By comparing the performance of various membranes, future prospective and improvement on membrane preparation and membrane reactor design are proposed.

A double temperature-cascade control strategy for controlling distillate composition is proposed. The control structure is based on two secondary loops that are designed for tracking the temperature of one tray in the rectifying and stripping section by manipulation of the reflux rate and reboiler heat input, respectively. Simulation results show that when saturations are imposed on controller outputs (reflux rate and heat input) both cascade controllers can act in a switching-like scheme without interaction problems. It is also shown that an adequate setting of a saturation parameter allows a low energy regulation of distillate composition under disturbances in feed composition.