Chemical Process Modelling and Simulation

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

Deadline for manuscript submissions: closed (30 April 2024) | Viewed by 38917

Special Issue Editor


E-Mail Website
Guest Editor
Department of Process Engineering, University of Pannonia, H-8200 Veszprém, Hungary
Interests: process modeling and simulation; process optimization; safety analysis; reactor runaway indication; kinetic model development

Special Issue Information

Dear Colleagues,

Modeling is a tool for understanding reality. We should never forget that the model is always just a projection of the real system so the reliability of the model should be quantified before it is applied in a practical problem solution. In modern chemical industry processes, modeling and simulation are a crucial pillar of day-to-day operations from design to maintenance and control of chemical process technologies. Today, the modeling task in the chemical industry often requires dynamic process modeling and simulation to follow the transient behavior of the system. Next to this, to obtain more information about the real system, we need more complex models than earlier, which makes it possible to identify that hidden capacity in process units which can improve the performance of the whole system. As model complexity is increasing, the numerical solution methods should be improved in order to solve models with sufficient precision.

All work related to chemical process modeling and simulation is welcome in this Special Issue to offer insight to the future readers into the current state of this wide topic.

Dr. Tamás Varga
Guest Editor

Manuscript Submission Information

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Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). 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

  • model identification
  • process analysis
  • process design
  • process control
  • model reliability
  • numerical solution

Published Papers (17 papers)

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Research

18 pages, 7041 KiB  
Article
Effect of Obstacle Gradient on the Deflagration Characteristics of Hydrogen/Air Premixed Flame in a Closed Chamber
by Yufei Wang and Shengjun Zhong
Processes 2024, 12(5), 962; https://doi.org/10.3390/pr12050962 - 9 May 2024
Viewed by 429
Abstract
In this paper, computational fluid dynamics (CFD) numerical simulation is employed to analyze and discuss the effect of obstacle gradient on the flame propagation characteristics of premixed hydrogen/air in a closed chamber. With a constant overall volume of obstacles, the obstacle blocking rate [...] Read more.
In this paper, computational fluid dynamics (CFD) numerical simulation is employed to analyze and discuss the effect of obstacle gradient on the flame propagation characteristics of premixed hydrogen/air in a closed chamber. With a constant overall volume of obstacles, the obstacle blocking rate gradient is set at +0.125, 0, and −0.125, respectively. The study focuses on the evolution of the flame structure, propagation speed, the dynamic process of overpressure, and the coupled flame–flow field. The results demonstrate that the flame front consistently maintains a jet flame as the obstacle gradient increases, with the wrinkles on the flame front becoming increasingly pronounced. When the blocking rate gradients are +0.125, 0, and −0.125, the corresponding maximum flame propagation speeds are measured at 412 m/s, 344 m/s, and 372 m/s, respectively, indicating that the obstacle gradient indeed increases the flame propagation speed. Moreover, the distribution of pressure is closely related to changes in the flame structure, with the overpressure decreasing in the obstacle channel as the obstacle gradient increases. Furthermore, the velocity vector and vortex distribution in the flow field are revealed and compared. It is found that the obstacle tail vortex is the main factor inducing flame evolution and flow field changes in a closed chamber. The effect of the blocking rate gradient on flow velocity is also quantified, with instances of deceleration occurring when the blocking rate gradient is −0.125. Full article
(This article belongs to the Special Issue Chemical Process Modelling and Simulation)
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25 pages, 4979 KiB  
Article
Artificial Intelligence for Hybrid Modeling in Fluid Catalytic Cracking (FCC)
by Jansen Gabriel Acosta-López and Hugo de Lasa
Processes 2024, 12(1), 61; https://doi.org/10.3390/pr12010061 - 27 Dec 2023
Viewed by 1168
Abstract
This study reports a novel hybrid model for the prediction of six critical process variables of importance in an industrial-scale FCC (fluid catalytic cracking) riser reactor: vacuum gas oil (VGO) conversion, outlet riser temperature, light cycle oil (LCO), gasoline, light gases, and coke [...] Read more.
This study reports a novel hybrid model for the prediction of six critical process variables of importance in an industrial-scale FCC (fluid catalytic cracking) riser reactor: vacuum gas oil (VGO) conversion, outlet riser temperature, light cycle oil (LCO), gasoline, light gases, and coke yields. The proposed model is developed via the integration of a computational particle-fluid dynamics (CPFD) methodology with artificial intelligence (AI). The adopted methodology solves the first principle model (FPM) equations numerically using the CPFD Barracuda Virtual Reactor 22.0® software. Based on 216 of these CPFD simulations, the performance of an industrial-scale FCC riser reactor unit was assessed using VGO catalytic cracking kinetics developed at CREC-UWO. The dataset obtained with CPFD is employed for the training and testing of a machine learning (ML) algorithm. This algorithm is based on a multiple output feedforward neural network (FNN) selected to allow one to establish correlations between the riser reactor feeding conditions and its outcoming parameters, with a 0.83 averaged regression coefficient and an overall RMSE of 1.93 being obtained. This research underscores the value of integrating CPFD simulations with ML to optimize industrial processes and enhance their predictive accuracy, offering significant advancements in FCC riser reactor unit operations. Full article
(This article belongs to the Special Issue Chemical Process Modelling and Simulation)
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20 pages, 6932 KiB  
Article
Significance of Pressure Drop, Changing Molar Flow, and Formation of Steam in the Accurate Modeling of a Multi-Tubular Fischer–Tropsch Reactor with Cobalt as Catalyst
by Andreas Jess and Christoph Kern
Processes 2023, 11(12), 3281; https://doi.org/10.3390/pr11123281 - 23 Nov 2023
Cited by 1 | Viewed by 778
Abstract
A Fischer–Tropsch (FT) fixed-bed reactor was simulated with reactor models of different complexities to elucidate the impact of a pressure drop, a change in the total molar volume rate (induced by the reaction) along the tubes, and a change in the axial variation [...] Read more.
A Fischer–Tropsch (FT) fixed-bed reactor was simulated with reactor models of different complexities to elucidate the impact of a pressure drop, a change in the total molar volume rate (induced by the reaction) along the tubes, and a change in the axial variation of the external radial heat transfer coefficient (external tube wall to cooling medium, here, boiling water) compared to disregarding these aspects. The reaction kinetics of CO conversion for cobalt as a catalyst were utilized, and the influence of inhibition of syngas (CO, H2) conversion reaction rate by steam, inevitably formed during FT synthesis, was also investigated. The analysis of the behavior of the reactor (axial/radial temperature profiles, productivity regarding the hydrocarbons formed, and syngas conversion) clearly shows that, for accurate reactor modeling, the decline in the total molar flow from the reaction and the pressure drop should be considered; both effects change the gas velocity along the tubes and, thus, the residence time and syngas conversion compared to disregarding these aspects. Only in rare cases do both opposing effects cancel each other out. The inhibition of the reaction rate by steam should also be considered for cobalt as a catalyst if the final partial pressure of steam in the tubes exceeds about 5 bar. In contrast, the impact of an axially changing heat transfer coefficient is almost negligible compared to disregarding this effect. Full article
(This article belongs to the Special Issue Chemical Process Modelling and Simulation)
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22 pages, 19405 KiB  
Article
Separation of Ternary System 1,2-Ethanediol + 1,3-Propanediol + 1,4-Butanediol by Liquid-Only Transfer Dividing Wall Column
by Yan-Yang Wu, Zhong-Wen Song, Jia-Bo Rao, Yu-Xian Yao, Bin Wu, Kui Chen and Li-Jun Ji
Processes 2023, 11(11), 3150; https://doi.org/10.3390/pr11113150 - 4 Nov 2023
Viewed by 961
Abstract
This study focuses on separating a mixture consisting of 1,2-ethanediol (1,2-ED), 1,3-propanediol (1,3-PD), and 1,4-butanediol (1,4-BD). Vapor–liquid equilibrium (VLE) data for 1,2-ED + 1,4-BD and 1,3-PD + 1,4-BD are determined at 101.3 kPa using a modified Rose equilibrium still. The consistency of the [...] Read more.
This study focuses on separating a mixture consisting of 1,2-ethanediol (1,2-ED), 1,3-propanediol (1,3-PD), and 1,4-butanediol (1,4-BD). Vapor–liquid equilibrium (VLE) data for 1,2-ED + 1,4-BD and 1,3-PD + 1,4-BD are determined at 101.3 kPa using a modified Rose equilibrium still. The consistency of the VLE data is checked with both Redlich–Kister and Fredenslund tests. The VLE data are fitted by the Wilson, NRTL, and UNIQUAC activity coefficient models. All three models can effectively correlate the VLE data. Then, the separation of the mixture is designed with the NRTL model and its correlated binary interaction parameters. A liquid-only transfer dividing wall column (LDWC) is investigated on the basis of a direct conventional distillation sequence (DCDS). For a fair comparison, both DCDS and LDWC are optimized to minimize total annual cost using sequential iterative optimization procedures. After optimization, LDWC exhibits a 16.87% reduction in total annual cost, while cooling and heating utility consumptions are reduced by 28.40% and 19.24% compared to DCDS. Full article
(This article belongs to the Special Issue Chemical Process Modelling and Simulation)
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25 pages, 2902 KiB  
Article
Online Dynamic Optimization of Multi-Rate Processes with the Case of a Fluid Catalytic Cracking Unit
by Jianfei Zhang, Jiajiang Lin, Feng Xu and Xionglin Luo
Processes 2023, 11(11), 3088; https://doi.org/10.3390/pr11113088 - 27 Oct 2023
Viewed by 709
Abstract
Due to operational limitations in the industrial field, the operating variables of fluid catalytic cracking units (FCCU) are of multiple operating frequencies, which are CO combustion promoter amount, recycle slurry flow rate, combustion air flow rate, heat escape, and reaction temperature, from low [...] Read more.
Due to operational limitations in the industrial field, the operating variables of fluid catalytic cracking units (FCCU) are of multiple operating frequencies, which are CO combustion promoter amount, recycle slurry flow rate, combustion air flow rate, heat escape, and reaction temperature, from low frequency to high frequency. There are usually two schemes for operation optimization of FCCU. The former is called single-rate, single-window optimization, whose operating variables are optimized only once in the whole operation cycle, which is easy to achieve, but the optimization effect is poor. The latter is called single-rate multi-window optimization, whose operating variables are optimized repeatedly and whose operation cycle is discretized into multiple optimization periods with the same frequency, which costs a heavy calculation burden and cannot adapt to the optimization variables with multiple operating frequencies. So, a multi-rate, variable-window online dynamic optimization method is proposed. In an operation cycle, the high-frequency operating variable is optimized in a short optimization period, and the low-frequency operating variable is optimized in a long optimization period; each optimization period has integer multiples to the minimum optimization period. Each optimized result for each optimization period is put into use online immediately. The optimization model involves the time domain differential equations, integral cost objective function, and measured disturbances. The experimental results show that compared with the single-rate, single-window optimization method and single-rate multi-window optimization method, the optimization effect of multi-rate, variable-window online dynamic optimization is better than single-rate, single-window optimization but worse than single-rate multi-window optimization. However, the optimization results are consistent with the operation frequency of each optimization variable, which can be implemented in complex chemical processes and increase certain economic benefits. Full article
(This article belongs to the Special Issue Chemical Process Modelling and Simulation)
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14 pages, 1612 KiB  
Article
Multi-Phase Equilibrium Model of Oxygen-Enriched Lead Oxidation Smelting Process Based on Chemical Equilibrium Constant Method
by Xinzhou Chen, Mingzhou Li, Fupeng Liu, Jindi Huang and Minghao Yang
Processes 2023, 11(10), 3043; https://doi.org/10.3390/pr11103043 - 23 Oct 2023
Viewed by 961
Abstract
With the increasingly complicated sources of lead smelting materials, it is becoming more difficult to optimize process parameters during the bottom-blowing lead oxidation smelting process. Building a bottom-blowing lead smelting thermodynamic model has significant importance for the green production of the lead smelting [...] Read more.
With the increasingly complicated sources of lead smelting materials, it is becoming more difficult to optimize process parameters during the bottom-blowing lead oxidation smelting process. Building a bottom-blowing lead smelting thermodynamic model has significant importance for the green production of the lead smelting process. In this study, we built a multi-phase equilibrium thermodynamic model and simulation system for the oxygen-enriched bottom-blowing lead oxidation smelting process using the MetCal software platform (MetCal v7.81) according to the chemical equilibrium constant method. The equilibrium products composition and important technical indicators were calculated under factory operating conditions. Compared with the industrial data, the calculation results demonstrated that the average relative error of the calculation value of the mass fraction in the crude lead, lead-rich slag, and dust was 3.76%. The average relative error of important technical indicators, including dust rate, crude lead yield, lead-rich slag temperature, slag iron–silica ratio (RFe/SiO2), and slag calcium–silica ratio (RCaO/SiO2), was 6.39%. As a result, the developed modeling and simulation system was able to reflect the current state of the oxygen-enriched bottom-blowing lead smelting. It also demonstrated the potential to enhance the smelting process and optimize the process parameters. Therefore, it is expected to provide a useful tool for thermodynamic analysis. Full article
(This article belongs to the Special Issue Chemical Process Modelling and Simulation)
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15 pages, 4515 KiB  
Article
A Simple Strategy for the Simultaneous Determination of Dopamine, Uric Acid, L-Tryptophan and Theophylline Based on a Carbon Nano-Onions Modified Electrode
by Rui An, Wenzhu Kuang, Zijian Li, Tiancheng Mu and Hongxia Luo
Processes 2023, 11(9), 2547; https://doi.org/10.3390/pr11092547 - 25 Aug 2023
Cited by 1 | Viewed by 804
Abstract
In this work, carbon nano-onions (CNOs) with particle sizes of 5–10 nm were prepared by the multi-potential step method. High-resolution transmission electron microscopy, infrared spectroscopy and Raman spectroscopy characterize the effective synthesis of CNOs. CNOs/GCEs were prepared by depositing the prepared CNOs onto [...] Read more.
In this work, carbon nano-onions (CNOs) with particle sizes of 5–10 nm were prepared by the multi-potential step method. High-resolution transmission electron microscopy, infrared spectroscopy and Raman spectroscopy characterize the effective synthesis of CNOs. CNOs/GCEs were prepared by depositing the prepared CNOs onto glassy carbon electrodes (GCEs) by a drop-coating method. Examination of the electrocatalytic activity of the CNOs/GCE sensor by simultaneously detecting dopamine (DA), uric acid (UA), L-tryptophan (Trp) and theophylline (TP) using a differential pulse voltammetry technique. The results showed that the linear ranges of DA, UA, Trp and TP were DA 0.01–38.16 μM, UA 0.06–68.16 μM, Trp 1.00–108.25 μM, and TP 8.16–108.25 μM, and the detection limits (S/N = 3) were 0.0039 μM, 0.0087 μM, 0.18 μM and 0.35 μM, respectively. The CNOS/GCE sensor had good stability and could be used for the detection of actual samples. Full article
(This article belongs to the Special Issue Chemical Process Modelling and Simulation)
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26 pages, 8965 KiB  
Article
Optimization of Flow and Mixing in a Venturi Tube Mixer with a Two-Step Method Using Numerical Simulation
by Zhenxin Tang, Fenglei Huang, Zixiong Yao, Ziqi Cai, Xin Ma, Zhipeng Li and Zhengming Gao
Processes 2023, 11(4), 1083; https://doi.org/10.3390/pr11041083 - 3 Apr 2023
Cited by 1 | Viewed by 2269
Abstract
To achieve efficient mixing in a Venturi tube mixer (VTM), an optimization with a two-step method for this mixing device based on a Venturi tube (VT) was carried out using numerical simulation. Firstly, the effects of the structural parameters on the flow in [...] Read more.
To achieve efficient mixing in a Venturi tube mixer (VTM), an optimization with a two-step method for this mixing device based on a Venturi tube (VT) was carried out using numerical simulation. Firstly, the effects of the structural parameters on the flow in VT were revealed, and the optimized configuration was determined for the following VTM. Subsequently, by introducing a jetting tube, the suction capacity, energy consumption and mixing quality were used to evaluate the performance of VTM under various configurations and operating conditions. According to the effects of the structural parameters on the mixing quality of VTM, an empirical formula for mixing quality with structural parameters was proposed. Finally, an optimized VTM was proposed. This work can provide a valid suggestion for the design and optimization of such a mixing device. Full article
(This article belongs to the Special Issue Chemical Process Modelling and Simulation)
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18 pages, 14386 KiB  
Article
Device Testing: High-Efficiency and High-Uniformity Microwave Water Treatment System Based on Horn Antennas
by Renxuan Tan, Yuanyuan Wu, Fengming Yang, Yang Yang, Junqing Lan and Huacheng Zhu
Processes 2023, 11(3), 826; https://doi.org/10.3390/pr11030826 - 9 Mar 2023
Viewed by 1679
Abstract
Microwave heating has excellent potential for applications in wastewater treatment. This study proposes a highly efficient continuous liquid-phase microwave heating system to overcome the problems of low treatment capacity, low dynamic range of loads, and insufficient heating uniformity of the existing equipment. First, [...] Read more.
Microwave heating has excellent potential for applications in wastewater treatment. This study proposes a highly efficient continuous liquid-phase microwave heating system to overcome the problems of low treatment capacity, low dynamic range of loads, and insufficient heating uniformity of the existing equipment. First, a quarter-wavelength impedance-matching layer improves heating efficiency, and the heating uniformity has been enhanced by horn antennas. Second, an experimental system is developed. The simulation and experimental results are consistent, with the microwave system achieving over 90% energy utilization for different thicknesses and concentrations of salt water. Finally, simulations are performed to analyze microwave efficiency and heating uniformity at different flow rates, salinities, dielectric properties, and sawtooth structures. The system can efficiently heat loads with a wide range of dielectric properties, including saline water. Generally, when the permittivity varies from 10 to 80, and the loss tangent varies dynamically from 0.15 to 0.6, more than 90% of microwave efficiency and excellent temperature distribution (The coefficient of temperature variation COV < 0.5) can be achieved. The system’s modular design enables scaling up to further boost processing capacity. Overall, the system provides high-throughput, high-efficiency, high-uniformity, and large-dynamic-range microwave water treatment, which has promising applications in industrial water treatment. Full article
(This article belongs to the Special Issue Chemical Process Modelling and Simulation)
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18 pages, 4963 KiB  
Article
Thermodynamic and Economic Evaluation of a Novel Green Methanol Poly-Generation System
by Qiliang Ye, Yipeng Bao, Hui Pan, Yulan Liu and Peiqing Yuan
Processes 2023, 11(1), 206; https://doi.org/10.3390/pr11010206 - 9 Jan 2023
Cited by 2 | Viewed by 1949
Abstract
Methanol is considered a sustainable alternative energy source due to its ease of storage and high-octane rating. However, the conventional methanol production process is accompanied by resource consumption and significant greenhouse gas emissions. The electrochemical reaction of electrochemically reacted hydrogen (H2) [...] Read more.
Methanol is considered a sustainable alternative energy source due to its ease of storage and high-octane rating. However, the conventional methanol production process is accompanied by resource consumption and significant greenhouse gas emissions. The electrochemical reaction of electrochemically reacted hydrogen (H2) with captured carbon dioxide (CO2) offers an alternative route to methanol production. This paper presents a new green poly-generation system consisting of a parabolic trough solar collector (PTC) unit, an organic Rankine cycle (ORC) unit, a CO2 capture unit, an alkaline electrolysis unit, a green methanol synthesis and distillation unit, and a double-effect lithium bromide absorption refrigeration (ARC) unit. The system mainly produced 147.4 kmol/h of methanol at 99.9% purity, 283,500 kmol/h of domestic hot water, and a cooling load of 1341 kW. A total 361.34 MW of thermal energy was supplied to the ORC by the PTC. The alkaline electrolysis unit generated 464.2 kmol/h of H2 and 230.6 kmol/h of oxygen (O2) while providing H2 for methanol synthesis. Thermodynamic and economic analysis of the system was carried out. The energy and exergy efficiency of the whole system could reach 76% and 22.8%, respectively. The internal rate of return (IRR) for the system without subsidies was 11.394%. The analysis for the methanol price showed that the system was economically viable when the methanol price exceedsed$363.34/ton. This new proposed poly-generation system offers more options for efficiently green methanol production. Full article
(This article belongs to the Special Issue Chemical Process Modelling and Simulation)
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30 pages, 5784 KiB  
Article
Failure Risk Assessment of Coal Gasifier Based on the Integration of Bayesian Network and Trapezoidal Intuitionistic Fuzzy Number-Based Similarity Aggregation Method (TpIFN-SAM)
by Yunpeng Liu, Shen Wang, Qian Liu, Dongpeng Liu, Yang Yang, Yong Dan and Wei Wu
Processes 2022, 10(9), 1863; https://doi.org/10.3390/pr10091863 - 15 Sep 2022
Cited by 3 | Viewed by 1459
Abstract
The coal gasifier is the core unit of the coal gasification system. Due to its exposure to high temperatures, high pressures, and aggressive media, it is highly susceptible to serious accidents in the event of failure. Therefore, it is important for the gasifier [...] Read more.
The coal gasifier is the core unit of the coal gasification system. Due to its exposure to high temperatures, high pressures, and aggressive media, it is highly susceptible to serious accidents in the event of failure. Therefore, it is important for the gasifier to perform failure-risk assessment to understand its safety status and provide safety measures. Bayesian networks (BNs) for risk analysis of process systems has received a lot of attention due to its powerful inference capability and its ability to reflect complex relationships between risk factors. However, the acquisition of basic probability data in a Bayesian network is always a great challenge. In this study, an improved Bayesian network integrated with a trapezoidal intuitionistic fuzzy number-based similarity aggregation method (TpIFN-SAM) is proposed for the failure-risk assessment of process systems. This approach used the TpIFN-SAM to collect and aggregate experts’ opinions for obtaining the prior probabilities of the root events in the BN. In the TpIFN-SAM, the intuitionistic fuzzy analytic-hierarchy-process method (IF-AHP) was adopted to assign the expert weights for reducing subjectivity or the bias caused by individual differences. To clarify the suitability of the proposed method, a case study of a coal gasifier was demonstrated, and both prediction and diagnosis analyses of the BN were performed; finally, the weak links of the gasifier were identified. Full article
(This article belongs to the Special Issue Chemical Process Modelling and Simulation)
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15 pages, 1680 KiB  
Article
Plant-Wide Modeling and Economic Analysis of Monoethylene Glycol Production
by Md Emdadul Haque, Namit Tripathi, Srinivas Palanki, Qiang Xu and Krishna D. P. Nigam
Processes 2022, 10(9), 1755; https://doi.org/10.3390/pr10091755 - 2 Sep 2022
Cited by 5 | Viewed by 6819
Abstract
Monoethylene glycol (MEG) is used to produce polyester fibers and polyethylene terephthalate resins. It is also utilized in antifreeze, pharmaceuticals, and cosmetics applications. In this research, we consider the development of a novel process plant that produces MEG from ethylene. The proposed ethylene-to-ethylene [...] Read more.
Monoethylene glycol (MEG) is used to produce polyester fibers and polyethylene terephthalate resins. It is also utilized in antifreeze, pharmaceuticals, and cosmetics applications. In this research, we consider the development of a novel process plant that produces MEG from ethylene. The proposed ethylene-to-ethylene oxide (EO) plant is integrated with an EO-to-MEG plant to reduce utility costs and recover high-value products. Energy-saving opportunities are analyzed via heat integration tools. Furthermore, a multitube glycol reactor is used in conjunction with a novel MTO catalyst in the ethylene-to-EO reactor. Our results demonstrate that the integrated EO/EG plant produces ethylene glycols with that same purity and product recovery as conventional designs. A comparative economic assessment based on a 200,000 t/y plant indicates that process integration techniques can reduce costs significantly. Full article
(This article belongs to the Special Issue Chemical Process Modelling and Simulation)
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24 pages, 3180 KiB  
Article
CFD Modelling of Calcination in a Rotary Lime Kiln
by Jarod Ryan, Markus Bussmann and Nikolai DeMartini
Processes 2022, 10(8), 1516; https://doi.org/10.3390/pr10081516 - 1 Aug 2022
Cited by 8 | Viewed by 3701
Abstract
A 2D axisymmetric computational fluid dynamics (CFD) model, coupled to a 1D bed model, has been developed to capture the key processes that occur within rotary lime kilns. The model simulates the calcination reaction using a shrinking core model, and predicts the start [...] Read more.
A 2D axisymmetric computational fluid dynamics (CFD) model, coupled to a 1D bed model, has been developed to capture the key processes that occur within rotary lime kilns. The model simulates the calcination reaction using a shrinking core model, and predicts the start of calcination and the degree of calcination at the end of the kiln. The model simulates heat transfer due to radiation, convection and conduction between the gas, wall, chains, and bed. The 2D gas and 1D bed models are coupled by mass and heat sinks to simulate heat transfer, evaporation, and the calcination reaction. The model is used to simulate two industrial kilns, one wet and one dry. The steady-state simulation results are compared to mill data, and good agreement is found. A sensitivity analysis is also presented, to obtain insight on how operating conditions and model variables impact the calcination location and degree of calcination. Full article
(This article belongs to the Special Issue Chemical Process Modelling and Simulation)
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20 pages, 6639 KiB  
Article
Computational Fluid Dynamics Study of a Pharmaceutical Full-Scale Hydrogenation Reactor
by David Fernandes del Pozo, Mairtin Mc Namara, Bernardo J. Vitória Pessanha, Peter Baldwin, Jeroen Lauwaert, Joris W. Thybaut and Ingmar Nopens
Processes 2022, 10(6), 1163; https://doi.org/10.3390/pr10061163 - 9 Jun 2022
Viewed by 2229
Abstract
The pharmaceutical industry has been quite successful in developing new hydrogenation processes, and the chemistry of hydrogenation is currently well understood. However, it is a complex process to scale and optimize due to its high exothermicity, use of expensive catalysts and solvents, and [...] Read more.
The pharmaceutical industry has been quite successful in developing new hydrogenation processes, and the chemistry of hydrogenation is currently well understood. However, it is a complex process to scale and optimize due to its high exothermicity, use of expensive catalysts and solvents, and its mass transfer requirements. Therefore, the aim of this work is to develop a CFD model to be able to describe the mass transfer, hydrodynamics, and mixing with respect to changes in rotational speed for a full-scale pharmaceutical hydrogenation reactor. In the first stage, a simple CFD model is used to predict the development of the surface vortex, and it is validated against literature data. In the second stage, the CFD model is tested on a full-scale configuration equipped with a Rushton turbine and a bottom kicker to study the formation of the surface vortex. Simulation results show the ability to predict the development of the surface vortex. These results are used to estimate the liquid height and mixing time as a function of several rotational speeds, allowing us to propose novel process correlations for this particular configuration. Although modelling the complete hydrogenation process would be challenging, this work is seen as a first step towards developing models that demonstrate the use of CFD at such large reactor scales. Full article
(This article belongs to the Special Issue Chemical Process Modelling and Simulation)
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20 pages, 35336 KiB  
Article
A Method to Derive the Characteristic and Kinetic Parameters of 1,1-Bis(tert-butylperoxy)cyclohexane from DSC Measurements
by Tung Chang, Kuang-Hua Hsueh, Cheng-Chang Liu, Chen-Rui Cao and Chi-Min Shu
Processes 2022, 10(5), 1026; https://doi.org/10.3390/pr10051026 - 20 May 2022
Cited by 1 | Viewed by 2969
Abstract
A differential scanning calorimetry (DSC) experiment was carried out to determine the thermal characteristics of harmful substances. Most experimenters only use the results of measurement and rarely conduct in-depth research on the variety of information behind the measurement. This study used Wolfram’s Mathematica [...] Read more.
A differential scanning calorimetry (DSC) experiment was carried out to determine the thermal characteristics of harmful substances. Most experimenters only use the results of measurement and rarely conduct in-depth research on the variety of information behind the measurement. This study used Wolfram’s Mathematica as a DSC measurement research tool to plot the peak curve and derive the characteristic parameters graphically for 1,1-Bis(tert-butylperoxy)cyclohexane. The research steps included raw data cleansing, peak curve normalization, characteristic parameter derivation, and total reaction heat calculation. The kinetic parameters of individual data were derived through the Borchardt and Daniels method, and the autocatalytic model was also verified. We applied the derived characteristic parameters to simulate the peak curve through the Gaussian curve model, which can be used for estimating the peak curve of other heating rates. The derived kinetic parameters were used to observe the effects on the peak curve. The simulation can be used to plan the test results at other rates in a similar temperature range and can also be used to explore the influence of different kinetic parameters on the configuration of the shape of the peak curve and a preliminary model test of materials for materials DSC research. Full article
(This article belongs to the Special Issue Chemical Process Modelling and Simulation)
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20 pages, 3078 KiB  
Article
Characterization of Stressing Conditions in a High Energy Ball Mill by Discrete Element Simulations
by Christine Friederike Burmeister, Moritz Hofer, Palanivel Molaiyan, Peter Michalowski and Arno Kwade
Processes 2022, 10(4), 692; https://doi.org/10.3390/pr10040692 - 1 Apr 2022
Cited by 8 | Viewed by 2900
Abstract
The synthesis of sulfide solid electrolytes in ball mills by mechanochemical routes not only is efficient but also can enable the upscaling of material synthesis as required for the commercialization of solid-state battery materials. On a laboratory scale, the Emax high energy ball [...] Read more.
The synthesis of sulfide solid electrolytes in ball mills by mechanochemical routes not only is efficient but also can enable the upscaling of material synthesis as required for the commercialization of solid-state battery materials. On a laboratory scale, the Emax high energy ball mill accounts for high stresses and power densities, as well as for temperature control, to prevent damage to the material and equipment even for long process times. To overcome the merely phenomenological treatment, we characterized the milling process in an Emax by DEM simulations, using the sulfide solid electrolyte LPS as a model material for the calibration of input parameters to the DEM, and compared it to a planetary ball mill for a selected parameter set. We derived mechanistic model equations for the stressing conditions depending on the operation parameters of rotational speed, media size and filling ratio. The stressing conditions are of importance as they determine the outcome of the mechanochemical milling process, thus forming the basis for evaluating and interpreting experiments and for establishing scaling rules for the process transfer to larger mills. Full article
(This article belongs to the Special Issue Chemical Process Modelling and Simulation)
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11 pages, 2008 KiB  
Article
Kinetic Studies of Esterification of Rosin and Pentaerythritol
by Meiga Putri Wahyu Hardhianti, Rochmadi and Muhammad Mufti Azis
Processes 2022, 10(1), 39; https://doi.org/10.3390/pr10010039 - 25 Dec 2021
Cited by 6 | Viewed by 4118
Abstract
Esterification of rosin with pentaerythritol produces rosin pentaerythritol ester (RPE) which is widely used in paint, coating, and pressure-sensitive and hot-melt adhesive industries. Although RPE has excellent valuable applications and has been industrially produced, studies on the reaction kinetics have not been widely [...] Read more.
Esterification of rosin with pentaerythritol produces rosin pentaerythritol ester (RPE) which is widely used in paint, coating, and pressure-sensitive and hot-melt adhesive industries. Although RPE has excellent valuable applications and has been industrially produced, studies on the reaction kinetics have not been widely reported in the present literature. This work proposed a kinetic study of RPE synthesis by including a series of consecutive reactions forming mono-, di-, tri-, and tetra-ester with decarboxylation of rosin as a side reaction in the kinetics model. For esterification, the reaction rates were determined by the second-order kinetic model. The first-order kinetic order was proposed for decarboxylation. Kinetic experiments were performed at a temperature range of 260 °C to 290 °C. The initial molar ratio of pentaerythritol to rosin (in the mole of OH/COOH) used was between 0.8 and 1.2. A small amount of samples were withdrawn in certain time interval. The sample was analyzed to evaluate their acid and saponification number. Afterward, those experimental data were used to simulate and validate the proposed kinetic model. In general, the proposed model could capture the experimental data well. The resulting activation energies ranged from 65.81 to 129.13 kJ mol−1 for esterification and 233.00 kJ mol−1 for decarboxylation. This model also offers a new insight that correlates well with tetra-ester formation and the softening point. Full article
(This article belongs to the Special Issue Chemical Process Modelling and Simulation)
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