Application of in situ adaptive tabulation to CFD simulation of nano-particle formation by reactive precipitation

Reactive precipitation involves four fundamental processes: mixing-limited reaction, nucleation, growth, and aggregation. A novel algorithm, in situ adaptive tabulation (ISAT), has been implemented in a code for micromixing simulations, which is often applied together with computational fluid dynamics (CFD), using full probability density function (PDF) methods to incorporate these fundamental processes in the formation of nano-particles by reactive precipitation in a plug-flow reactor. The quadrature method of moments is applied to solve population balance equations for turbulent aggregation of the growing particles. The various performance issues (error control, accuracy, number of records, speed-up) for ISAT are discussed. Based on a large number of simulations, an error tolerance of 10⁻⁴-10⁻⁵ is found to be satisfactory for carrying out time-evolving full PDF simulations of nano-particle formation by reactive precipitation. Our results show that CFD simulation of reactive precipitation requires a much smaller computational effort when the ISAT algorithm is implemented than when direct integration is used. Finally, the effects of initial species concentrations, micromixing time, and turbulent shear rate on the reactive precipitation of barium sulfate are studied.     

Multi-scale product property model of polypropylene produced in a FBR: From chemical process engineering to product engineering

A multi-scale product model has been built to characterize the polypropylene (PP) formation dynamics in a catalytic FBR. For the first time, the gas–solid flow field, the morphological and molecular properties of particles, as well as their dynamics can be simultaneously obtained by solving the unique model that couples a CFD model, a population balance model (PBM) and moment equations. The quantitative relationships between the operating conditions and the multi-scale particle properties have been further established. The results demonstrate that the product model can be used to guide a multi-scale generalization of the polymer product from chemical process to product engineering.     

Pervaporation of emulsion droplets for the templated assembly of spherical particles: A population balance model

The emulsion droplet solvent evaporation method is used in the preparation of spherical particles, which form due to processes such as the clustering of nanocrystals or precipitation of polymers as the volume of solvent in the droplets decreases. A population balance model is presented to describe this transport of solvent from nanocrystal‐ or polymer‐laden droplets in an emulsion that flows through a pervaporation unit. The solvent transport and lateral migration of droplets was simulated using a high‐resolution finite‐volume algorithm, which provided a smooth solution with second‐order accuracy. Concentration gradients in the continuous phase become prominent when the resistance to solvent transport in the continuous phase dominates that in the membrane. In contrast, with the membrane resistance controlling the overall transport rate, a lumped capacitance assumption can be made and a simpler plug flow model would be sufficient. The simulations also indicate that the particle‐size distributions are generally bimodal, and are broader for low dispersed‐phase volume fractions and very low‐solvent solubilities. Furthermore, the distributions show that radial diffusion of the particles occurs to a significant degree. Such simulations offer insight into how the solvent is removed from emulsion droplets as they flow down a pervaporation fiber and should be useful in the design of pervaporation systems for that purpose. © 2013 American Institute of Chemical Engineers AIChE J, 59: 3975–3985, 2013     

油包水乳化体系的配方设计及生产工艺研究(续前)

论述了影响油包水乳化体系稳定性的因素、油包水的配方设计原则以及油包水的生产工艺的控制和调整,并介绍了有利凯玛公司的油包水乳化剂。     

Two state estimators for the barium sulfate precipitation in a semi-batch reactor

The on-line determination of particle property distributions by direct measurements is often difficult, because the measurement equations are not invertible or because the inverse problem is ill-posed. If the process is observable, one can use state estimation techniques in order to reconstruct unmeasurable internal states of the process. This is discussed here for a semi-batch precipitation reactor. A square root unscented Kalman filter and state estimation by online minimisation are studied for the case of a measurable average particle size. Both estimators use a one-dimensional population balance model. The two approaches are compared in simulations.     

The film-boiling densification process for C/C composite fabrication: From local scale to overall optimization

The film-boiling densification process is an alternative of chemical vapor infiltration involving a strong thermal gradient. It allows to fabricate composite materials starting from a fibrous preform lying in a boiling hydrocarbon precursor, the cracking of which results in a solid deposit constituting the matrix of the carbon/carbon composite. A modelling approach is presented and validated with respect to experimental data. Then, the sensitivity of the process is studied with respect to various parameters. Optimization guidelines are proposed, in conjunction with a discussion on the densification front that characterizes the process. It is thus possible to evaluate the minimal amount of power required, while maintaining the quality of the produced material, i.e., its bulk density and homogeneity.     

Development of new concepts for the control of polymerization processes: Multiobjective optimization and decision engineering. I. Application to emulsion homopolymerization of styrene

This article deals with the development of a multicriteria analysis, and its application to the optimization of batch emulsion polymerization processes. This new approach in the domain of polymer reaction engineering illustrates how a multiobjective optimization aided by a genetic algorithm and using the Pareto concept of domination is useful. In this process (emulsion homopolymerization of styrene), several objectives were simultaneously required, e.g., a high quality of the resulting products together with a high productivity. The aim of this study was to find the optimal experimental conditions to obtain simultaneously the minimum reaction time and designed values for both average molecular weights and particles size. To do that, an adapted mathematical model, able to describe all the process physicochemical phenomena, was been first elaborated. The multicriteria analysis then gave a set of nondominated points with conflicting criteria. A decision support system was then developed and applied to rank the Pareto solutions set and to propose some good solutions by taking into account the decision maker's preferences. © 2003 Wiley Periodicals, Inc. J Appl Polym Sci 87: 2383–2396, 2003     

Multiscale modeling of methane catalytic partial oxidation: From the mesopore to the full‐scale reactor operation

A multiscale methodology combining three different reactor length‐scales is presented to investigate the role of the catalyst internal pore structure and metal loading and dispersion on the catalyst layer and full‐scale reactor performances. At the catalyst level, the methodology involves pore‐scale simulations in the three‐dimensional mesopore and macropore space. The information gathered at the catalyst level is delivered to the full‐scale reactor model. The methodology is applied to a honeycomb reactor performing methane partial oxidation considering reaction kinetics described through a detailed multistep reaction mechanism. Realistic mesopore and macropore structures were reconstructed and combined to form specific bidisperse porous washcoat layers. The study shows that species effective diffusivities vary significantly but not in the same proportion for different structures. For structures featuring poor transport characteristics, the integral methane conversion and hydrogen selectivity are strongly affected while the reactor temperatures increase substantially. © 2017 American Institute of Chemical Engineers AIChE J, 64: 578–594, 2018     

From pore scale to wellbore scale: Impact of geometry on wormhole growth in carbonate acidization

Acid injection in carbonate reservoir is commonly used in the oil industry to improve, or at least recover, its productivity. The aim of this stimulation technique is to create empty channels called wormholes which, if successful, would bypass the damaged area near the wellbore. During production, wormholes become pathways for the reservoir oil to reach the well. This technique increases near-wellbore permeability, and therefore improves oil production. The interaction between the transport of acid, chemical reaction, and heterogeneities encountered at different scales, controls the unstable behaviour of wormholing and, thus, the success of the treatment. Most of the experimental and numerical studies done on this subject in the past have been limited in their observations because they only considered the dissolution process at a small scale (from pore scale to core scale). The purpose of this work is to study how the geometry of the domain can constrain wormhole competition, and influence wormholing dynamics in a core submitted to acidizing.After a short review of the literature on wormholing to see how the geometry effect could have influenced previous experiments, we study specifically the question of wormhole density. We emphasize that two mechanisms are involved in wormhole competition, with one of them being effective only at small scale. Thus we conclude that wormholing is not a full-scale independent process. We describe differences in the wormhole growth dynamics between “confined” and “unconfined” domains for different dissolution regimes. We focus on optimum conditions and their transition from “confined” to “unconfined” domain to realize that the flow rate in the dominant wormhole does not depend on geometric effects. We conclude by a comparison between 2D and 3D simulations, in both linear and radial flow, and observe changes in the wormholing process. All our results serve as a discussion about definitions of optimum conditions in the literature.     

Development of new concepts for the control of polymerization processes: Multiobjective optimization and decision engineering. II. Application of a Choquet integral to an emulsion copolymerization process

In polymer industry, engineers seek to obtain polymers with prescribed end‐use properties, high productivities, and low cost. Thus, the optimization of a manufacturing process with all those goals and constraints belongs to a problem domain that aims to achieve the best trade‐off possible. This article concerns the optimization of the batch emulsion polymerization of styrene and α‐methylstyrene. An accurate model was developed to describe the complete patterns of the emulsion polymerization. Key parameters of the model were identified on the basis of batch experimental data. The model was then used to simulate, under several operating conditions, the polymerization rate, the overall conversion of monomers, and the number and weight‐average molecular weights. Amulticriteria optimization approach based on an evolutionary algorithm and the concept of dominance from the Pareto frontier theory was used. Last, a decision aid system based on the Choquet integral was proposed to determine the optimal operating conditions with the preferences of the decision maker taken into account. © 2011 Wiley Periodicals, Inc. J Appl Polym Sci, 2011     

Advanced modelling and optimal operating strategy in emulsion copolymerization: Application to styrene/MMA system

A model-based framework for advanced optimal operation of copolymerization processes was developed and tested experimentally in conjunction with a distributed control system (DCS) suitable for industrial application. A test case of emulsion copolymerization of styrene (Sty) and methyl-methacrylate (MMA) was investigated for predicting and optimizing key product properties including molecular weight distribution (MWD), particle size distribution (PSD), copolymer composition and conversion. The model equations include diffusion-controlled kinetics at high monomer conversions, where transition from a ‘zero-one’ to a ‘pseudo-bulk’ regime occurs. The reactor mass and energy balances describe the system transients for batch and semi-batch operations. Population balance equations, describe the particle evolution and comprise sets of integro-partial differential and nonlinear algebraic equations. The models were solved using an efficient numerical scheme suitable for on-line monitoring and control. The model predictions were found to be in good agreement with experimental results for measurements carried out with variable monomer feed rates, variable temperature and variable composition of styrene-MMA, from 25/75 to 75/25 proportions. The manipulation of these variables was found to affect the PSD significantly. The experimental results confirmed the accuracy of our optimization scheme for the desired conversion, MWD and PSD.     

Dissolution of olivine in the presence of oxalate, citrate, and CO2 at 90 °C and 120 °C

In this article, we report the results from a study of olivine dissolution kinetics under operating conditions suitable for ex situ aqueous mineral carbonation for CO₂ storage. We studied the effect of oxalate and citrate ions on the dissolution of gem-quality San Carlos olivine (Mg_1.82Fe_0.18SiO₄). Flow-through experiments were performed at 90 °C and 120 °C, at f_CO2 between 4 and 81 bar, with a solution containing either sodium oxalate or sodium citrate in a molality range between 10⁻³ and 10⁻¹. The pH was varied between 2 and 7 by adding HCl, LiOH, and adjusting f_CO2. At all investigated temperatures and for pH values in a broad range, both sodium oxalate and sodium citrate increased dissolution rate with the strongest effect up to one order of magnitude in presence of 0.1 m of oxalate, at 120 °C, and above pH 5. The enhancement effect was primarily ascribed to the oxalate or citrate ions that are the dominant species in this pH range. The overall dissolution process was described using the population balance equation (PBE) coupled with a mass balance equation to account for the evolution of the particle size distribution (PSD) of olivine. Far from equilibrium conditions for dissolution were established in all the experiments in order to achieve a surface-reaction controlled mechanism. We described the reaction with a surface complexation model, which assumes adsorption of a proton and of an oxalate (citrate) ions (proton and oxalate) on adjacent sites in order to enhance dissolution, and we derived a dissolution rate equation in presence of oxalate:where r^? is the specific dissolution rate commonly used in absence of organic compounds, and K_H, K_X, and β are thermodynamic and kinetic parameters. The values of these parameters have been estimated from the experimental data and the agreement between the model results and the experiments is very good.     

Factorial experimental design approach in semicontinuous emulsion polymerization of methyl methacrylate to study the effect of process variables

This article describes the effect of various process variables in the semicontinuous emulsion polymerization of methyl methacrylate. A series of poly(methyl methacrylate) (PMMA) emulsions were prepared using ammonium persulphate as initiator in absence and presence of Dowfax 2AI as surfactant. The effect of process variables such as initiator concentration, monomer concentration (solid content), surfactant concentration, reaction temperature, monomer feeding time, and holding time were systematically studied on monomer conversion, particle size, gel content, and molecular weight using a two‐level fractional factorial experimental method. Analysis of fractional factorial design revealed that surfactant concentration, monomer concentration, initiator concentration, and monomer feeding time affect all the properties. However, the surfactant concentration and the interaction effect of initiator and monomer feeding time are the key variables influencing the properties of PMMA latex. © 2009 Wiley Periodicals, Inc. J Appl Polym Sci, 2009     

Role of silane grafting in the development of a superhydrophobic clay-alumina composite membrane for separation of water in oil emulsion

Hydrophobic composite kaolin-coated clay-alumina membranes are unique choices for water in oil emulsion separation. In this work, a membrane fabrication approach is presented using kaolin clay coating in the clay-alumina tubular composite support tube and subsequently grafting by different concentrations of fluoroalkyl silane (FAS: 1H, 1H, 2H, 2H, -Perfluorooctyltriethoxysilane) on the membrane surface. Different concentrations of fluoroalkyl silane formed distinctive hierarchical structures which exhibited hydrophobicity of the membrane surface. The pore property, surface roughness properties, and thermogravimetric properties can be suitably tailored by tuning the silane concentration in the grafting solution. The surfaces of comparatively higher silane content grafted (M50 and M100) composite membranes were found to be superhydrophobic. Comparably, our optimal composite membrane (M100) displayed a moderate steady flux rate of 80-100LMH (Lm^?2h ^?1) and excellent water rejection (>99%) properties during the separation of water in hexane and toluene emulsion at a cross-flow transmembrane pressure of 1 bar. The role of silane concentration on permeated hexane and toluene flux rate, water rejection rate, surface wettability, microstructure, and hydrophobic stability reveals new distinguishing insights into the hydrophobic clay-alumina composite membrane fabrication.     

From dynamic response surface models to the identification of the reaction stoichiometry in a complex pharmaceutical case study

The dynamic response surface methodology (DRSM) (Klebanov and Georgakis, Ind Eng Chem Res. 2016;55(14):4022–4034) was proposed as a generalization of the classical response surface methodology (RSM). The power of DRSM is evaluated here in a blind test against a complex pharmaceutical process containing 10 observed species involved in eight reactions. The obtained DRSM models, one for each species, accurately represented the time-varying concentrations of 8 of the 10 species. The DRSMs for two intermediate species suffered a bit from oscillatory behavior toward the end of the batch, due to their small concentration values and the polynomial-based model. These DRSM models greatly facilitated the application of target factor analysis (Bonvin and Rippin, Chem Eng Sci. 1990; 45(12): 3417–3426) correctly identifying six of the eight true reaction stoichiometries, whereas all six false reactions were rejected. In addition, the ability to distinguish true and false reaction stoichiometries was not affected by a less informative design of experiments (DoEs) than the original center composite design (CCD). © 2018 American Institute of Chemical Engineers AIChE J, 65: 1173–1185, 2019     

Using the discrete element method to predict collision-scale behavior: A sensitivity analysis

Discrete element method (DEM) simulations have recently been used to investigate collision-scale measurements such as collision frequency and impact velocity distributions. These simulations are typically validated against particle velocity fields using experimental techniques such as particle image velocimetry or positron emission particle tracking. An important question that has not been addressed is whether validation of a macroscopic velocity field or solid fraction field also implies a validation of collision-scale measurements such as collision frequency. In this study, DEM measurements of solid fraction, shear rate, collision frequency, and impact velocity are made in a small region just beneath the free surface in a rotating drum. The effects of periodic drum length, particle stiffness, coefficient of restitution, and particle size are investigated. The solid fraction and shear rate do not vary with particle stiffness or coefficient of restitution over the range of values studied. However, the collision rate increases with increasing particle stiffness and coefficient of restitution. In addition, the average collision speed decreases as particles become stiffer or less elastic. The shear rate varies with particle size, but the average collision velocity remains constant. These findings indicate that validation against particle velocity and solid fraction fields does not necessarily imply validation of collision frequency and impact velocity. Indeed, the velocity and solid fraction fields were found to be relatively insensitive to a range of DEM contact stiffnesses and coefficients of restitution while the collision distributions were sensitive.     

Kinetic modeling formulation of the methanol to olefin process: Parameter estimation

Detailed kinetic models at the elementary step level were developed for the methanol to olefins (MTO) process over SAPO-34 catalyst. Starting from believable mechanisms, forming primary products was modeled rigorously by the Hougen–Watson formalism. Discrimination of kinetic equations and calculation of the parameters of best fit were performed by solving the mass conservation equations of the main products of the kinetic scheme. For rate constants, preexponential factors and apparent activation energies were then calculated according to the Arrhenius equation. For thermodynamic constants, the difference between apparent activation energies of forward and reverse reaction was considered. The kinetic model fits well the experimental data, which is obtained in a fixed bed reactor. The results showed that rising space-time is favorable for olefin yields while an optimum temperature might produce the maximum olefin.     

Microkinetic model for the pyrolysis of methyl esters: From model compound to industrial biodiesel

A tool for the generation of decomposition schemes of large molecules has been developed. These decomposition schemes contain radicals which can be eliminated from the model equations if both the μ‐hypothesis and the pseudosteady‐state approximation are valid. The reaction rate coefficients and thermodynamic parameters have been calculated by incorporating a comprehensive group additive framework. A microkinetic model for the pyrolysis of methyl esters with a carbon number of up to 19 has been generated using this tool. It is validated by comparing calculated and experimental yields of the pyrolysis of methyl decanoate and novel rapeseed methyl ester pyrolysis data in the temperature range from 800 to 1100 K and methyl ester partial pressure range from 1 × 10^?3 to 1 × 10^?2 MPa. This modeling frame work allows to not only assess the use of methyl ester mixtures as potential feedstock for olefin production but also their effect as blend‐in or trace impurity. © 2015 American Institute of Chemical Engineers AIChE J, 61: 4309–4322, 2015     

Part IV: Dynamic evolution of the particle size distribution in particulate processes. A comparative study between Monte Carlo and the generalized method of moments

The present work provides a comparative study on the numerical solution of the dynamic population balance equation (PBE) for batch particulate processes undergoing simultaneous particle aggregation, growth and nucleation. The general PBE was numerically solved using three different techniques namely, the Galerkin on finite elements method (GFEM), the generalized method of moments (GMOM) and the stochastic Monte Carlo (MC) method. Numerical simulations were carried out over a wide range of variation of particle aggregation and growth rate models. The performance of the selected techniques was assessed in terms of their numerical accuracy and computational requirements. The numerical results revealed that, in general, the GFEM provides more accurate predictions of the particle size distribution (PSD) than the other two methods, however, at the expense of more computational effort and time. On the other hand, the GMOM yields very accurate predictions of selected moments of the distribution and has minimal computational requirements. However, its main disadvantage is related to its inherent difficulty in reconstructing the original distribution using a finite set of calculated moments. Finally, stochastic MC simulations can provide very accurate predictions of both PSD and its corresponding moments while the MC computational requirements are, in general, lower than those required for the GFEM.