Special Issue "Chemical Process Design, Simulation and Optimization"

A special issue of Processes (ISSN 2227-9717). This special issue belongs to the section "Chemical Systems".

Deadline for manuscript submissions: 31 December 2020.

Special Issue Editors

Prof. Dr. Jean-Pierre Corriou
Website
Guest Editor
LRGP-CNRS-ENSIC, University of Lorraine, 1 rue Grandville BP 20451-54001, Nancy Cedex, France
Interests: process modelling, simulation, optimization and control; chemical processes; signal processing; numerical methods
Dr. Jean-Claude Assaf
Website1 Website2
Guest Editor
Department of Chemical Engineering, Lebanese University (UL), Saint Joseph University (USJ) and University of Balamand (UOB), Lebanon
Interests: process modelling, simulation, optimization and control, chemical processes, linear & non-linear processes

Special Issue Information

Dear Colleagues,

 Chemical Process Design, Simulation and Optimization constitute the core of the activity of chemical process engineers, process developers and designers, process economic evaluators, energy engineers and researchers implicated in chemical engineering.

This Special Issue explores the design and simulation of new and revamped chemical processes as well as the numerical modeling and optimization of existing plants/processes using proven software. Thus, it offers novel illustrative examples, prospective applications and solutions to improve chemical processes. The aim of this issue is to combine theoretical principles with examples modeled by commonly-used simulation software (AspenPlus, AspenHysys, Pro/II, Prosim, CHEMCAD, Scilab, Matlab and others) employing steady-state or dynamic process simulation. Furthermore, applying numerical methods and optimization at both the theoretical and practical levels are within the scope of this issue. Original research papers and reviews covering a wide range of processes such as chemical industries, refining, oil and gas and engineering processes will be considered for publication.

Topics include, but are not limited to applications in the following areas:

  • Design and simulation of a novel or revamped chemical process
  • Optimization of the processing capacity and operating conditions of a current chemical process
  • Improvement of equipment design and the performance of a specific chemical process
  • Monitoring safety and operational issues in chemical plants
  • Identification of energy savings opportunities, material integration and economic evaluation to realize savings in the process design
  • Development of efficient numerical and optimization methods with applications in chemical and energy engineering
Prof. Dr. Jean-Pierre Corriou
Dr. Jean-Claude Assaf
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Processes is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1500 CHF (Swiss Francs). Please note that for papers submitted after 31 December 2020 an APC of 2000 CHF applies. Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • process modelling
  • simulation
  • optimization and control
  • chemical processes
  • linear and non-linear processes

Published Papers (16 papers)

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Research

Open AccessArticle
Investigation of Plume Offset Characteristics in Bubble Columns by Euler–Euler Simulation
Processes 2020, 8(7), 795; https://doi.org/10.3390/pr8070795 - 07 Jul 2020
Abstract
Based on low-cost and easy to enlarge, the bubble column device has been widely concerned in chemical industry. This paper focuses on bubble plumes in laboratory-scale three-dimensional rectangular air-water columns. Static behavior has been investigated in many experiments and simulations, and our present [...] Read more.
Based on low-cost and easy to enlarge, the bubble column device has been widely concerned in chemical industry. This paper focuses on bubble plumes in laboratory-scale three-dimensional rectangular air-water columns. Static behavior has been investigated in many experiments and simulations, and our present investigations consider the dynamic behavior of bubble plume offset in three dimensions. The investigations are conducted with a set of closure models by the Euler–Euler approach, and subsequently, literature data for rectangular bubble columns are analyzed for comparison purposes. Moreover, the transient evolution characteristics of the bubble plume in the bubble column and the gas phase distribution in sections are introduced, and the offset characteristics and the oscillation period of the plume are analyzed. In addition, the distributions of the vector diagram of velocity and vortex intensity in the domain are given. The effects of different fluxes and column aspect ratios on bubble plumes are studied, and the offset and plume oscillation period (POP) characteristics of bubbles are examined. The investigations reveal quantitative correlations of operating conditions (gas volume flux) and aspect ratios that have not been reported so far, and the simulated and experimental POP results agree well. An interesting phenomenon is that POP does not occur under conditions of a high flux and aspect ratio, and the corresponding prediction values for the conditions with and without POP are given as well. The results reported in this paper may open up a new way for further study of the mass transfer of bubble plumes and development of chemical equipment. Full article
(This article belongs to the Special Issue Chemical Process Design, Simulation and Optimization)
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Open AccessArticle
Inside–Out Method for Simulating a Reactive Distillation Process
Processes 2020, 8(5), 604; https://doi.org/10.3390/pr8050604 - 19 May 2020
Abstract
Reactive distillation is a technical procedure that promotes material strengthening and its simulation plays an important role in the design, research, and optimization of reactive distillation. The solution to the equilibrium mathematical model of the reactive distillation process involves the calculation of a [...] Read more.
Reactive distillation is a technical procedure that promotes material strengthening and its simulation plays an important role in the design, research, and optimization of reactive distillation. The solution to the equilibrium mathematical model of the reactive distillation process involves the calculation of a set of nonlinear equations. In view of the mutual influence between reaction and distillation, the nonlinear enhancement of the mathematical model and the iterative calculation process are prone to fluctuations. In this study, an improved Inside–Out method was proposed to solve the reaction distillation process. The improved Inside–Out methods mainly involved—(1) the derivation of a new calculation method for the K value of the approximate thermodynamic model from the molar fraction summation equation and simplifying the calculation process of the K value, as a result; and (2) proposal for an initial value estimation method suitable for the reactive distillation process. The algorithm was divided into two loop iterations—the outer loop updated the relevant parameters and the inside loop solved the equations, by taking the isopropyl acetate reactive distillation column as an example for verifying the improved algorithm. The simulation results presented a great agreement with the reference, and only the relative deviation of the reboiler heat duty reached 2.57%. The results showed that the calculation results were accurate and reliable, and the convergence process was more stable. Full article
(This article belongs to the Special Issue Chemical Process Design, Simulation and Optimization)
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Open AccessFeature PaperArticle
Comparison of Exergy and Advanced Exergy Analysis in Three Different Organic Rankine Cycles
Processes 2020, 8(5), 586; https://doi.org/10.3390/pr8050586 - 14 May 2020
Abstract
Three types of organic Rankine cycles (ORCs): basic ORC (BORC), ORC with single regeneration (SRORC) and ORC with double regeneration (DRORC) under the same heat source have been simulated in this study. In the following, the energy and exergy analysis and the advanced [...] Read more.
Three types of organic Rankine cycles (ORCs): basic ORC (BORC), ORC with single regeneration (SRORC) and ORC with double regeneration (DRORC) under the same heat source have been simulated in this study. In the following, the energy and exergy analysis and the advanced exergy analysis of these three cycles have been performed and compared. With a conventional exergy analysis, researchers can just evaluate the performance of components separately to find the one with the highest amount of exergy destruction. Advanced analysis divides the exergy destruction rate into unavoidable and avoidable, as well as endogenous and exogenous, parts. This helps designers find more data about the effect of each component on other components and the real potential of each component to improve its efficiency. The results of the advanced exergy analysis illustrate that regenerative ORCs have high potential for reducing irreversibilities compared with BORC. Total exergy destruction rates of 4.13 kW (47%) and 5.25 kW (45%) happen in avoidable/endogenous parts for SRORC and DRORC, respectively. Additionally, from an advanced exergy analysis viewpoint, the priority of improvement for system components is given to turbines, evaporators, condensers and feed-water heaters, respectively. Full article
(This article belongs to the Special Issue Chemical Process Design, Simulation and Optimization)
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Open AccessArticle
Performance Comparison of Industrially Produced Formaldehyde Using Two Different Catalysts
Processes 2020, 8(5), 571; https://doi.org/10.3390/pr8050571 - 12 May 2020
Abstract
Formaldehyde is an important industrial chemical that is a strong-smelling and colorless gas. It is used in a number of processes such as making household products and building materials, glues and adhesives, resins, certain insulation materials, etc. Formaldehyde can be produced industrially using [...] Read more.
Formaldehyde is an important industrial chemical that is a strong-smelling and colorless gas. It is used in a number of processes such as making household products and building materials, glues and adhesives, resins, certain insulation materials, etc. Formaldehyde can be produced industrially using air and methanol as raw materials in the presence of metal oxide catalyst or silver-based catalyst. The operating conditions and requirements of the process depend on the type of catalyst used. Therefore, a comparative study of both processes was conducted, and the results were compared. It was observed that the silver-based catalyst process has a compact plant size since the amount of air required is halved as compared to the metal oxide process. Thus, it appears that the silver-based catalyst process is more suitable for small-scale production due to its compact size and reduced utility cost. Full article
(This article belongs to the Special Issue Chemical Process Design, Simulation and Optimization)
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Open AccessArticle
Integrated Method of Monitoring and Optimization of Steam Methane Reformer Process
Processes 2020, 8(4), 408; https://doi.org/10.3390/pr8040408 - 31 Mar 2020
Abstract
Reforming of natural gas with steam represents the most energy-intensive part of ammonia production. An integrated numerical model for calculating composition of primary reforming products with cross-checking of outlet methane molar concentration, heat duty, maximum tube wall temperature, tube pressure drops, and approach [...] Read more.
Reforming of natural gas with steam represents the most energy-intensive part of ammonia production. An integrated numerical model for calculating composition of primary reforming products with cross-checking of outlet methane molar concentration, heat duty, maximum tube wall temperature, tube pressure drops, and approach to equilibrium was set up involving production parameters. In particular, the model was used for continuous monitoring and optimization of a steam methane reformer (SMR) catalyst in ammonia production. The calculations involve the solution of material and energy balance equations along with reaction kinetic expressions. Open source code based on Matlab file was used for modelling and calculation of various physical properties of the reacting gases. One of the main contributions is development of the rapid integrated method for data exchange between any distributed control system (DCS) and the model to accomplish continuous monitoring and optimization of SMR catalyst and reformer tubes. Integrated memory block was proposed for rapid synchronization between commercial DCS with the model solver. The developed model was verified with the industrial top-fired SMR unit in ammonia production located in Petrokemija, Croatia. Practical application of proposed solution can ensure overall energy savings of up to 3% in ammonia production. Full article
(This article belongs to the Special Issue Chemical Process Design, Simulation and Optimization)
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Open AccessFeature PaperArticle
Numerical Simulation of a Flow Field in a Turbo Air Classifier and Optimization of the Process Parameters
Processes 2020, 8(2), 237; https://doi.org/10.3390/pr8020237 - 19 Feb 2020
Abstract
Due to the rapid development of powder technology around the world, powder materials are being widely used in various fields, including metallurgy, the chemical industry, and petroleum. The turbo air classifier, as a powder production equipment, is one of the most important mechanical [...] Read more.
Due to the rapid development of powder technology around the world, powder materials are being widely used in various fields, including metallurgy, the chemical industry, and petroleum. The turbo air classifier, as a powder production equipment, is one of the most important mechanical facilities in the industry today. In order to investigate the production efficiency of ultrafine powder and improve the classification performance in a turbo air classifier, two process parameters were optimized by analyzing the influence of the rotor cage speed and air velocity on the flow field. Numerical simulations using the ANSYS-Fluent Software, as well as material classification experiments, were implemented to verify the optimal process parameters. The simulation results provide many optimal process parameters. Several sets of the optimal process parameters were selected, and the product particle size distribution was used as the inspection index to conduct a material grading experiment. The experimental results demonstrate that the process parameters of the turbo air classifier with better classification efficiency for the products of barite and iron-ore powder were an 1800 rpm rotor cage speed and 8 m/s air inlet velocity. This research study provides theoretical guidance and engineering application value for air classifiers. Full article
(This article belongs to the Special Issue Chemical Process Design, Simulation and Optimization)
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Open AccessArticle
A Hybrid Inverse Problem Approach to Model-Based Fault Diagnosis of a Distillation Column
Processes 2020, 8(1), 55; https://doi.org/10.3390/pr8010055 - 02 Jan 2020
Abstract
Early-stage fault detection and diagnosis of distillation has been considered an essential technique in the chemical industry. In this paper, fault diagnosis of a distillation column is formulated as an inverse problem. The nonlinear least squares algorithm is used to evaluate fault parameters [...] Read more.
Early-stage fault detection and diagnosis of distillation has been considered an essential technique in the chemical industry. In this paper, fault diagnosis of a distillation column is formulated as an inverse problem. The nonlinear least squares algorithm is used to evaluate fault parameters embedded in a nonlinear dynamic model of distillation once abnormal symptoms are detected. A partial least squares regression model is built based on fault parameter history to explicitly predict the development of fault parameters. With the stripper of Tennessee Eastman process as example, this novel approach is tested for step- and random-type faults and several factors affecting its efficiency are discussed. The application result shows that the hybrid inverse problem approach gives the correct change of fault parameter at a speed far faster than the base approach with only a nonlinear model. Full article
(This article belongs to the Special Issue Chemical Process Design, Simulation and Optimization)
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Open AccessArticle
Process of Natural Gas Explosion in Linked Vessels with Three Structures Obtained Using Numerical Simulation
Processes 2020, 8(1), 52; https://doi.org/10.3390/pr8010052 - 02 Jan 2020
Cited by 1
Abstract
Combinations of spherical vessels and pipes are frequently employed in industries. Scholars have primarily studied gas explosions in closed vessels and pipes. However, knowledge of combined spherical vessel and pipe systems is limited. Therefore, a flame acceleration simulator was implemented with computational fluid [...] Read more.
Combinations of spherical vessels and pipes are frequently employed in industries. Scholars have primarily studied gas explosions in closed vessels and pipes. However, knowledge of combined spherical vessel and pipe systems is limited. Therefore, a flame acceleration simulator was implemented with computational fluid dynamics software and was employed to conduct natural gas explosions in three structures, including a single spherical vessel, a single spherical vessel with a pipe connected to it, and a big spherical vessel connected to a small spherical vessel with a pipe. These simulations reflected physical experiments conducted by at Nanjing Tech University. By changing the sizes of vessels, lengths of pipes, and ignition positions in linked vessels, we obtained relevant laws for the time, pressure, temperature, and concentrations of combustion products. Moreover, the processes of natural gas explosions in different structures were obtained from simulation results. Simulation results agreed strongly with corresponding experimental data, validating the reliability of simulation. Full article
(This article belongs to the Special Issue Chemical Process Design, Simulation and Optimization)
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Open AccessArticle
Modeling and Economic Optimization of the Membrane Module for Ultrafiltration of Protein Solution Using a Genetic Algorithm
Processes 2020, 8(1), 4; https://doi.org/10.3390/pr8010004 - 18 Dec 2019
Cited by 1
Abstract
The performance of cross-flow ultrafiltration is greatly influenced by permeate flux behavior, which depends on many factors, including solution properties, membrane characteristics, and operating conditions. Currently, most research focuses on improving membrane performance, both in terms of permeability and selectivity. Only a few [...] Read more.
The performance of cross-flow ultrafiltration is greatly influenced by permeate flux behavior, which depends on many factors, including solution properties, membrane characteristics, and operating conditions. Currently, most research focuses on improving membrane performance, both in terms of permeability and selectivity. Only a few studies have paid attention to how the membrane module is configured and operated. In this study, the geometric design and operating conditions of a membrane module are considered as multivariable optimization variables. The objective function is the annual cost. The cost consists of a capital investment depending on the plant scale and an operating expense associated with energy consumption. In the optimization problem, the channel dimensions (width × length × height), and operating conditions (the inlet pressure and recirculation flow rate) were considered as decision variables. The operating configuration of the membrane plant is assumed to be feed and bleed mode, and a model including the pressure drop is introduced. The model is used to simulate the membrane plant and calculate the membrane area and energy usage, which are directly related to the total cost. The genetic algorithm is used for the optimization. The effect of individual parameters on the total cost is discussed. Full article
(This article belongs to the Special Issue Chemical Process Design, Simulation and Optimization)
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Open AccessArticle
Production of Butyric Anhydride Using Single Reactive Distillation Column with Internal Material Circulation
Processes 2020, 8(1), 1; https://doi.org/10.3390/pr8010001 - 18 Dec 2019
Abstract
The traditional two-column reactive distillation (RD) process is used for the production of butyric anhydride, which is synthesized with butyric acid and acetic anhydride via a reversible reaction. In this work, a novel process with a single RD column (SRDC) is designed for [...] Read more.
The traditional two-column reactive distillation (RD) process is used for the production of butyric anhydride, which is synthesized with butyric acid and acetic anhydride via a reversible reaction. In this work, a novel process with a single RD column (SRDC) is designed for the production of butyric anhydride, where the second distillation column for separating excess reactant is removed based on the boiling point profile of the reaction system. Two applications of the proposed SRDC process, namely SRDC with excess butyric acid or acetic anhydride circulating internally, are economically optimized, and the results show that both SRDC processes have a lower total annual cost (TAC) than the traditional two-column process. Furthermore, from the perspective of TAC, the application with an excess feed of butyric acid is better than the application with excess acetic anhydride. The developed technique may also be applied to retrofit other traditional two-column RD processes, where the overhead and bottom products are the lightest and heaviest components of the reaction system, respectively, and no azeotrope is involved in the RD column. Full article
(This article belongs to the Special Issue Chemical Process Design, Simulation and Optimization)
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Open AccessArticle
Sustainable Synthesis Processes for Carbon Dots through Response Surface Methodology and Artificial Neural Network
Processes 2019, 7(10), 704; https://doi.org/10.3390/pr7100704 - 05 Oct 2019
Cited by 1
Abstract
Nowadays, to ensure sustainability of smart materials, it is imperative to eliminate or reduce carbon footprint related to nano material production. The concept of design of experiment to provide an optimal synthesis process, with a desired yield, is indispensable. It is the researcher’s [...] Read more.
Nowadays, to ensure sustainability of smart materials, it is imperative to eliminate or reduce carbon footprint related to nano material production. The concept of design of experiment to provide an optimal synthesis process, with a desired yield, is indispensable. It is the researcher’s goal to get optimum value for experiments that requires multiple runs and multiple inputs. Herein, is a reliable approach of utilizing design of experiment (DOE) for response surface methodology (RSM). Thus, to optimize a facile and effective synthesis process for fluorescent carbon dots (CDs) derived from tapioca that is in line with green chemistry principles for sustainable synthesis. The predictions for fluorescent CDs synthesis from RSM were in excellent agreement with the artificial neural network (ANN) model prediction by the Levenberg–Marquardt back propagation (LMBP) algorithm. Considering R2, root mean square error (RMSE) and mean absolute error (MAE) have all revealed a positive hidden layer size. The best hidden layer of neurons were discovered at point 4-8, to confirm the validity of carbon dots, characterization of surface morphology and particles sizes of CDs were conducted with favorable confirmations of the unique characteristics and attributes of synthesized CDs by hydrothermal route. Full article
(This article belongs to the Special Issue Chemical Process Design, Simulation and Optimization)
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Open AccessFeature PaperArticle
Simulation and Experimental Study of a Single Fixed-Bed Model of Nitrogen Gas Generator Working by Pressure Swing Adsorption
Processes 2019, 7(10), 654; https://doi.org/10.3390/pr7100654 - 25 Sep 2019
Cited by 1
Abstract
Nitrogen is an inert gas available in the air and is widely used in industry and food storage technology. Commonly, it is separated by air refrigerant liquefaction and fractional distillation techniques based on different boiling temperatures of components in the mixed air. Currently, [...] Read more.
Nitrogen is an inert gas available in the air and is widely used in industry and food storage technology. Commonly, it is separated by air refrigerant liquefaction and fractional distillation techniques based on different boiling temperatures of components in the mixed air. Currently, selective adsorption techniques by molecular sieve materials are studied and applied to separate gases based on their molecular size. In this paper, we simulate and investigate the effect parameters in a single fixed-bed model of a nitrogen gas generator using carbon molecular sieves, following pressure swing adsorption. This study aims to identify the effect of changing parameters so as to select the optimal working conditions of a single fixed-bed model, used as a basis for equipment optimization. This equipment was designed, manufactured, and installed at the Institute of Technology, General Department of Defense Industry, Vietnam to investigate, simulate, and optimize the industrial scale-up. Full article
(This article belongs to the Special Issue Chemical Process Design, Simulation and Optimization)
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Open AccessArticle
Numerical Simulation Study of Heavy Oil Production by Using In-Situ Combustion
Processes 2019, 7(9), 621; https://doi.org/10.3390/pr7090621 - 14 Sep 2019
Abstract
An in-situ combustion method is an effective method to enhance oil recovery with high economic recovery rate, low risk, fast promotion and application speed. Currently, in-situ combustion technique is regarded as the last feasible thermal recovery technology to replace steam injection in the [...] Read more.
An in-situ combustion method is an effective method to enhance oil recovery with high economic recovery rate, low risk, fast promotion and application speed. Currently, in-situ combustion technique is regarded as the last feasible thermal recovery technology to replace steam injection in the exploitation of bitumen sands and heavy oil reservoirs. However, the oil-discharging mechanism during the in-situ combustion process is still not clearly understood. In this paper, the in-situ combustion process has been numerically simulated based on the Du 66 block. The effect of production parameters (huff and puff rounds, air injection speed, and air injection temperature) and geological parameters (bottom water thickness, stratigraphic layering, permeability ratio, and formation thickness) on the heavy oil recovery have been comprehensively analyzed. Results show that the flooding efficiency is positively correlated with the thickness of the bottom water, and negatively correlated with the formation heterogeneity. There exist optimum values for the oil layer thickness, huff and puff rounds, and air injection speed. And the effect of air injection temperature is not significant. The results of this paper can contribute to the understanding of mechanisms during in-situ combustion and the better production design for heavy oil reservoirs. Full article
(This article belongs to the Special Issue Chemical Process Design, Simulation and Optimization)
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Open AccessArticle
Assessment of the Total Volume Membrane Charge Density through Mathematical Modeling for Separation of Succinic Acid Aqueous Solutions on Ceramic Nanofiltration Membrane
Processes 2019, 7(9), 559; https://doi.org/10.3390/pr7090559 - 23 Aug 2019
Abstract
Nanofiltration of aqueous solutions of succinic acid with the addition of sodium hydroxide or magnesium hydroxycarbonate has been investigated experimentally and modeled with the comprehensively described Donnan–Steric partitioning model. The experimental retentions of acid at the same pH varied between 16% and 78%, [...] Read more.
Nanofiltration of aqueous solutions of succinic acid with the addition of sodium hydroxide or magnesium hydroxycarbonate has been investigated experimentally and modeled with the comprehensively described Donnan–Steric partitioning model. The experimental retentions of acid at the same pH varied between 16% and 78%, while the estimated total volume membrane charge densities were in the range of −35.73 and +875.69 mol/m3. This work presents a novel insight into the modeling of nanofiltration and investigates the relations between the estimated total volume membrane charge densities, ionic strength, and component concentration on the performance of ceramic membrane. In addition, this study takes into consideration other parameters such as pH regulation and viscosities of solutions. Full article
(This article belongs to the Special Issue Chemical Process Design, Simulation and Optimization)
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Open AccessArticle
Application of Transformation Matrices to the Solution of Population Balance Equations
Processes 2019, 7(8), 535; https://doi.org/10.3390/pr7080535 - 14 Aug 2019
Cited by 1
Abstract
The development of algorithms and methods for modelling flowsheets in the field of granular materials has a number of challenges. The difficulties are mainly related to the inhomogeneity of solid materials, requiring a description of granular materials using distributed parameters. To overcome some [...] Read more.
The development of algorithms and methods for modelling flowsheets in the field of granular materials has a number of challenges. The difficulties are mainly related to the inhomogeneity of solid materials, requiring a description of granular materials using distributed parameters. To overcome some of these problems, an approach with transformation matrices can be used. This allows one to quantitatively describe the material transitions between different classes in a multidimensional distributed set of parameters, making it possible to properly handle dependent distributions. This contribution proposes a new method for formulating transformation matrices using population balance equations (PBE) for agglomeration and milling processes. The finite volume method for spatial discretization and the second-order Runge–Kutta method were used to obtain the complete discretized form of the PBE and to calculate the transformation matrices. The proposed method was implemented in the flowsheet modelling framework Dyssol to demonstrate and prove its applicability. Hence, it was revealed that this new approach allows the modelling of complex processes involving materials described by several interconnected distributed parameters, correctly taking into consideration their interdependency. Full article
(This article belongs to the Special Issue Chemical Process Design, Simulation and Optimization)
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Open AccessArticle
A Numerical Approach to Solve Volume-Based Batch Crystallization Model with Fines Dissolution Unit
Processes 2019, 7(7), 453; https://doi.org/10.3390/pr7070453 - 15 Jul 2019
Abstract
In this article, a numerical study of a one-dimensional, volume-based batch crystallization model (PBM) is presented that is used in numerous industries and chemical engineering sciences. A numerical approximation of the underlying model is discussed by using an alternative Quadrature Method of Moments [...] Read more.
In this article, a numerical study of a one-dimensional, volume-based batch crystallization model (PBM) is presented that is used in numerous industries and chemical engineering sciences. A numerical approximation of the underlying model is discussed by using an alternative Quadrature Method of Moments (QMOM). Fines dissolution term is also incorporated in the governing equation for improvement of product quality and removal of undesirable particles. The moment-generating function is introduced in order to apply the QMOM. To find the quadrature abscissas, an orthogonal polynomial of degree three is derived. To verify the efficiency and accuracy of the proposed technique, two test problems are discussed. The numerical results obtained by the proposed scheme are plotted versus the analytical solutions. Thus, these findings line up well with the analytical findings. Full article
(This article belongs to the Special Issue Chemical Process Design, Simulation and Optimization)
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