Simulated Moving Bed Reactor Research Articles

Enhanced simulated moving bed reactor performance for the synthesis of solketal by implementing the ModiCon strategy

The need to extend the range of potential uses for the Simulated Moving Bed Reactor (SMBR) leads the development of new operational strategies that enable the equipment to perform increasingly difficult reactions and separations. Solketal is the valorization product from the reaction between glycerol and acetone, a thermodynamic limited process that faces miscibility and selectivity issues. In this work, the ModiCon SMBR is proposed and optimized aiming to overcome the difficulties of solketal synthesis in the Conventional SMBR. The optimization is based on the “Reactive-Separation Volumes” methodology, a well-established procedure followed for optimizing numerous other SMBR processes. The results demonstrate that the new SMBR operating mode can produce solketal with a purity of 97%, reaching a productivity of over 9.69 kgSolkLAds-1day-1\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${\ ext{kg}}_{{{\ ext{Solk}}}} {\ ext{ L}}_{{{\ ext{Ads}}}}^{{ - {1}}} {\ ext{ day}}^{{ - {1}}}$$\\end{document}, 38% higher than the Multifeed, another non-conventional strategy proposed in the open literature for the synthesis of solketal. The desorbent consumption is 6.76 LDesorbentkgProd-1,\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${\ ext{L}}_{{{\ ext{Desorbent}}}} \\,{\ ext{kg}}_{{{\ ext{Prod}}}}^{ - 1} ,$$\\end{document} 35% higher than the Multifeed. The most impressive result is the decrease in the reactants consumption of 12%. Such results demonstrate that this strategy intensifies the process even more than other non-conventional operating strategies proposed in the literature, which makes it more appealing to be implemented in the large scale solketal production.

Theoretical Analysis of Simulated Moving Bed Reactor for Rapid Reversible Acetalization of Glycerol with Acetone to Synthesize Solketal

Theoretical Analysis of Simulated Moving Bed Reactor for Rapid Reversible Acetalization of Glycerol with Acetone to Synthesize Solketal

Novel Framework for Simulated Moving Bed Reactor Optimization Based on Deep Neural Network Models and Metaheuristic Optimizers: An Approach with Optimality Guarantee.

Model-based optimization of simulated moving bed reactors (SMBRs) requires efficient solvers and significant computational power. Over the past years, surrogate models have been considered for such computationally demanding optimization problems. In this sense, artificial neural networks-ANNs-have found applications for modeling the simulated moving bed (SMB) unit but not yet been reported for the reactive SMB (SMBR). Despite ANNs' high accuracy, it is essential to assess its capacity to represent the optimization landscape well. However, a consistent method for optimality assessment using surrogate models is still an open issue in the literature. As such, two main contributions can be highlighted: the SMBR optimization based on deep recurrent neural networks (DRNNs) and the characterization of the feasible operation region. This is done by recycling the data points from a metaheuristic technique-optimality assessment. The results demonstrate that the DRNN-based optimization can address such complex optimization while meeting optimality.

Improving the Performance of a Simulated Moving Bed Reactor for the Synthesis of Solketal by Implementing Multifeed Strategy

Improving the Performance of a Simulated Moving Bed Reactor for the Synthesis of Solketal by Implementing Multifeed Strategy

Continuous Valorization of Glycerol into Solketal: From the Fixed-Bed Adsorptive Reactor to the Simulated Moving-Bed Reactor

Continuous Valorization of Glycerol into Solketal: From the Fixed-Bed Adsorptive Reactor to the Simulated Moving-Bed Reactor

A Complete Heterogeneous Model for the Production of n-Propyl Propionate Using a Simulated Moving Bed Reactor

n-Propyl Propionate (ProPro) is a harmless biodegradable product employed in several fields for the production of drugs, inks, coating, food, and perfume. ProPro is synthesized in an equilibrium reaction for which its yield can be enhanced by constant withdraw of the products as the reaction takes place. Simulated Moving Bed Reactor (SMBR) is a candidate for the production of ProPro with high efficiency as it is a multifunction unit able to simultaneously run reaction and separation, hence shifting the equilibrium reaction toward products. This paper proposes a complete phenomenological model for the ProPro synthesis in a Simulated Moving Bed Reactor (SMBR) packed with the heterogeneous catalyst Amberlyst 46 resin. The operating conditions are defined by the Triangle Theory to design an SMBR unit to produce ProPro efficiently and a comprehensive parameter estimation procedure is employed to obtain more representative parameters. The validated phenomenological model was applied to design an SMBR unit to produce high purity (99.28%) ProPro.

Improving the performances of a simulated-moving-bed reactor for the synthesis of methyl acetate ester by using partial port-closing strategies

Simulated-moving-bed reactor (SMBR) is one of the trustworthy processes to achieve high levels of conversion, yield, and throughput for an equilibrium-limited reversible reaction. As one way of finding a practical method to significantly improve the performances of an SMBR, the applicability of a partial port-closing strategy and its potential impact on the SMBR performances were investigated for the first time in this study. To facilitate this work, the synthesis of methyl acetate (MeOAc) ester was employed as a model reaction system. There are two applicable modes for implementing the aforementioned strategy in the SMBR for MeOAc synthesis. The first one is a partial extract-closing (PEC) mode, in which an extract port (non-product port) remains closed during the time that MeOAc passes through two zones adjacent to the extract port. Such action occurs mostly during the beginning of each step. By contrast, the second one is a partial raffinate-closing (PRC) mode, in which a raffinate port (product port) remains closed during the time that unreacted and side-product components pass through two zones adjacent to the raffinate port, which happens mostly during the end of each step. A series of comprehensive optimizations for the considered SMBR revealed that both the PEC and PRC strategies were effective in making a significant improvement in reaction yield, throughput, and solvent usage. It was also found that the higher the required throughput, the more advantageous it was to use PEC rather than PRC mode. Finally, it was confirmed that the merit of PEC over PRC mode in the economic feasibility of the SMBR became greater as the target levels of reaction yield and throughput were set higher.

Multi-Objective Optimisation of Biodiesel Synthesis in Simulated Moving Bed Reactor

In this work, multi-objective optimisation study was performed to determine the performance improvement in a simulated moving bed reactor (SMBR) for biodiesel synthesis. The selection of the operating parameters such as switching time, liquid flow rates in various sections, as well as the length and number of columns is not straightforward in an SMBR. In most cases, conflicting requirements and constraints influence the optimal selection of the decision (operating or design) variables. A mathematical model that predicts single-column experimental results well was modified and verified experimentally for multiple-column SMBR system. In this article, a few multi-objective optimisation problems were carried out for both existing set-up as well as at the design stage. A non-dominated sorting genetic algorithm (NSGA) was used as the optimisation tool for the optimisation study. Due to conflicting effect of process parameters, the multi-objective optimisation study resulted in non-dominated Pareto optimal solutions. It was shown that significant increase in yield and purity of biodiesel in SMBR was possible both for operating and at design stage.

Abnormal Operation Tracking through Big-Data-Based Gram–Schmidt Orthogonalization: Production of n-Propyl Propionate in a Simulated Moving-Bed Reactor: A Case Study

Big Data Analytics plays a crucial role in Industry 4.0 by offering tools to improve the decision-making process. These tools comprise data management infrastructures and analytical methods. Among ...

Multi-Objective Optimizations of Non-Isothermal Simulated Moving Bed Reactor: Parametric Analyses

Simulated moving bed reactor (SMBR), a multicolumn multifunctional integrated reactor system, which can be exploited with on-site adsorptive separation to enhance conversion of equilibrium-limited reversible chemical reaction. In this article, for generality, a dimensionless SMBR model was developed and effects of five representative temperature distributions among different zones on the performance of an SMBR for reversible reaction in the general form of a reactant decomposed to two products were evaluated based on simultaneous maximization of unit throughput and product purity. Multipliers were applied to adjust some of the model parameters such that different operation modes can be compared under various conditions in the parametric space. The multiobjective optimization problems were solved using the non-dominated sorting genetic algorithm. All simulations were carried out using FORTRAN codes. The results showed that both kinetics and adsorptive separation play important roles in SMBR. When kinetics is fast or adsorptive potency of the reactant is higher than the desired product (B) but lower than byproduct (C), non-isothermal operation can significantly improve unit throughput. On the contrary, feed concentration and reaction enthalpy have minor effects on the optimal solutions. Decision variables based on flow rate ratios and internal concentration profiles were used to explain the trends of Pareto optimal solution.

Optimization of the Production of 1,1-Diethoxybutane by Simulated Moving Bed Reactor

Simulated moving bed technology is applied in the field of pharmaceutical, petrochemical and fine chemistry. It shows capability in separating multicomponent mixtures up to high purities. In this work, an attempt was made to optimize the production of 1,1-diethoxybutane (DEB), using the simulated moving bed technology. A fixed bed model is made with good agreement with experimental results. This fixed bed model was expanded to a simulated moving bed model. This model was used to determine the optimum conditions regarding the switching time and flowrates in each section. From this model, the optimum switching time was found to be 2.4 min, and the ratio of liquid flowrate over the solid flowrate in Section 1Section 2Section 3 and Section 4 of the SMBR was found to be 4.24, 1.77, 3.03 and 1.35, respectively. Under those conditions, the productivity was 19.8 kg DEB per liter of adsorbent per day, and the desorbent consumption was 6.1 L of ethanol per kg of DEB. The results were obtained with a minimum purity of the extract and raffinate of 97%.

Advanced Manufacturing and Processing in the Time of Covid‐19

The COVID-19 pandemic has exposed fragilities and reinforced the resiliency of different elements of our manufacturing and processing systems. Food processing, in particular meat packing, currently a very labor-intensive operation, experienced significant disruption and the car industry implemented shutdowns which will ripple through supply chains in the coming months. It became clear that packaging supply chains are bottlenecks as producers tried to divert food stuffs from restaurants to consumer stores, and shifts in demand for paper products caused persistent consumer outages. The basic chemicals and fuels industry did not see significant disruption, but wild price fluctuations did occur as reduced demands and an unfortunately timed production increase caused available storage capacity to be strained. Recycling industries saw, and will continue to experience, both ends of the disruption as their consuming industries reduced demand and their providers stockpiled material or diverted it to trash. The beverage industry has significant inventory in public venues that has expired. Boutique level hand sanitizer production has resulted as these beverage production systems have been reconfigured and the rules surrounding the grade of alcohol relaxed.[1] We are sure there are many of you who have worked long hours to innovate your manufacturing and processing systems to cope with the challenges of COVID-19 and we would welcome articles and commentaries on how advanced manufacturing can play a role in our collective response. In this issue of JAMP we share a commentary on the rapid manufacturing of vaccines as our contribution to understanding how our community might respond to COVID-19,[2] and we would like to encourage you to consider other ways in which our manufacturing systems will change in response to the pandemic. However, much as there is a need to address the short-term disruptions caused by a pandemic, and to understand how research can respond to create advanced manufacturing and processing systems with flexibility and resilience in the future, we also need to continue to push forward with efforts that provide new foundations for those features and we have curated articles that we hope fulfill that goal. Process intensification remains a key approach to advanced manufacturing enabling more nimble and responsive systems. This issue provides two examples tackling a variety of processes: the epoxidation of vegetable oils and the manufacturing of butyl acrylate. Rahim et al.[3] show that by using a mesoscale oscillating baffled reactor the process can be converted from a batch operation to a continuous one and in the process they estimate that the new reactor is approximately 144 times smaller than the batch reactor operating at the same production rate. The Simulated Moving Bed Reactor (SMBR) technology has been an example for process intensification for a couple of decades. Constantino et al.[4] have combined this technology with membrane pervaporation creating a Simulated Moving Bed Membrane Reactor which reduces the number of operation sections for the manufacturing of butyl acrylate while reducing the eluent consumption and improving the productivity. A complete analysis of all process metrics is given in this paper. The use of Artificial Intelligence (AI) in the chemical process industry is being used in new ways that are challenging the way this industry should consider the adoption and deployment of Industry 4.0 that has become ubiquitous in other business sectors. Colegrove[5] discusses the importance of protecting data as critical intellectual capital and how many in the AI vendor community do not understand the value of data to the process industry. The commentary offers insight on the need for chemical engineers and data scientists to work closely together to solve technical and operational problems that require analysis of data that is broader than process data and where fundamental models break down. This commentary takes on additional importance for resiliency in light of the social and economic impact of COVID-19.

Simulated moving bed reactor for p-xylene production: Modeling, simulation, and optimization

A Simulated Moving Bed Reactor (SMBR), comprising a homogeneous mixture of adsorbent and catalyst, can overcome the equilibrium constraints in the production of p-xylene (PX). In this proposal, toluene and benzene were respectively considered as desorbent in the process. The arrangement of columns and optimum operating conditions such as switching time and flow rates that lead to maximum p-xylene productivity and minimum desorbent consumption were determined. Several constraints, including maximum pressure drop per bed and purity, were considered. Additionally, the operating temperature was optimized for the first time taking into account the energy consumption within the associated distillation columns; the heat integration involving the distillation columns was also discussed. Finally, toluene showed better performance than benzene as desorbent. For the best case studied, the optimized temperature was 540 K. Moreover, an increase of about 25% in the recovery of PX, compared to the conventional Simulated Moving Bed, was obtained.

Multi-objective optimization of non-isothermal simulated moving bed reactor: Methyl acetate synthesis

Simulated moving bed reactor (SMBR) increases conversion of a reversible chemical reaction by introducing continuous counter-current in-situ adsorptive separation of reactants and/or products. Effects of temperature variance among different operating zones on the performance of a 4-column SMBR for reaction in the form of A↔B+C were evaluated based on multi-objective optimization. This article is focused on the model system of methyl acetate synthesis. A total of five representative cases with different temperature distributions in the range of 308–323 K were compared for six optimization problems with two or three objective functions along with practical constraints in terms of product purity, yield, unit throughput and solvent consumption. Pareto solutions were obtained for each problem. Under optimal conditions, a major fraction (over 85%) of the fed acid is converted in feed-section. For a given purity requirement, Cases 1 and 2 with 323 K in the feed section have similar unit throughput, higher than those of the other cases studied by about 10–40%. Compared with isothermally operated Case 1, Case 2 with a temperature gradient exhibited reduced solvent consumption (defined as the ratio of desorbent flowrate to maximum flowrate) by about 20% at 313 K. The superiority of non-isothermal operation resulting on reduced solvent consumption becomes more significant with decreased purity requirement and/or decreased unit throughput.

Transient analysis of true/simulated moving bed reactors: A case study on the synthesis of n-Propyl propionate

A potential improvement in the production route of the ester n-propyl-propionate can be done by the Simulated Moving Bed Reactor (SMBR). However, there is a need to address the complex dynamics of these systems providing a deeper understanding during the unit operation and control. Thus, this work proposes two SMBR units for the synthesis of n-propyl-propionate: the SMBR-4 with four columns and the SMBR-8 with eight columns. Their performance was compared to the True Moving Bed Reactor (TMBR). Two detailed analyses were performed to assess the system dynamic behavior of the three units: an orthogonalization based analysis and the process reaction curve. The first showed that the switching time and feed concentration influence the system the most, though at different extensions. The second highlighted that the SMBR/TMBR commonly used equivalence is not valid during transient conditions.

Pervaporation and Sorption Enhanced Reactive Cyclic Processes: The Butyl Acrylate Case Study

New process intensification strategies for butyl acrylate production are emerging as an alternative to the conventional multistage process, where high temperatures and homogeneous catalysts are used. In this work, a novel approach is presented focusing on process reintensification by combining pervaporation and sorption enhanced reactive processes, the simulated moving-bed membrane reactor (SMBR), also known as PermSMBR. Different configurations of membranes combined with the simulated moving-bed reactor (SMBR) were investigated: integrated, comprising membranes packed with the Amberlyst-15 ion-exchange resin, and coupled, consisting of several hydrophilic membranes each of which was followed by a fixed-bed adsorptive reactor. Mathematical models were implemented to predict the PermSMBR performance with the different configurations. To achieve this, different experimental runs were carried out to validate the mathematical model for the simulated moving-bed reactor. Then, fundamental pervaporation data were taken into account to investigate numerically the PermSMBR process. The maximum performance was achieved with the integrated PermSMBR configuration, which was the best strategy for BAc production, with a productivity of 8.00 (kgBAc (Lₐdₛ–¹·day–¹)), which is 33% higher than that obtained in the conventional SMBR. Moreover, this strategy leads to a significant reduction in the consumption of the eluent, 32%, relative to SMBR for the same conversion (≥99%) and purity criteria (≥99.5%). This is due to the more effective removal of water by favoring the solid regeneration step.

Design and Scheduling of Semibatch Chemical-Looping Reactors

Chemical-looping combustion is explored as a chemical reactor design problem. The continuous operation of fixed bed reactors using gaseous fuels for the purpose of power generation through integration with a combined cycle power plant is studied. The fixed bed reactors are assumed to operate in a semibatch mode composed of reactor modules that are integrated into module trains that comprise the chemical-looping combustion island of the power plant. The scheduling of each reactor train is cast as an optimization problem that maximizes thermodynamic efficiency subject to constraints imposed to each reactor and the entire island. It is shown that when the chemical-looping reactors are arranged cyclically, each feeding to or being fed from another reactor, in an operating scheme that mimics simulated moving bed reactors, the thermodynamic efficiency of the reactor island can be improved. Allowing the reversal of module order in the cyclically arranged reactor modules further improves the overall thermodynamic efficiency (to 84.7%, defined as the fraction of enthalpy sent to the gas turbine of a combined cycle power plant over the total energy output of the reactor), while satisfying constraints imposed for carbon capture, fuel conversion, power plant safety, and oxygen carrier stability.

Dynamics of a True Moving Bed Reactor: Synthesis of n-Propyl Propionate and an alternative optimization method

This work investigates a novel synthesis route of n-Propyl Propionate using a Simulated Moving Bed Reactor (SMBR) packed with Amberlyst 46 resin. Simultaneously, it is presented a novel method for SMBR units design and optimization. The results demonstrate that the unit is capable of producing the n-Propyl Propionate with high purity and conversion, over 99 %. Furthermore, the productivity associated with its low consumption of eluent and its operation at significantly lower temperature provides evidence that the SMBR may be an efficient and competitive route to produce n-Propyl Propionate. Moreover, the swarm optimization method here used showed to be a powerful optimization tool while simultaneously providing deep information about the SMBR process feasible operating region.

Process integration for simulated moving bed reactor for the production of glycol ether acetate

This work designs and optimizes a simulated moving bed reactor (SMBR) within an overall process that includes two downstream units. The extract and raffinate streams are processed to improve product purity, and recycle streams leaving the downstream units are returned to the SMBR to reduce solvent consumption. Three different operating schemes are evaluated–the standard, limited superstructure, and full superstructure configuration.The proposed process flowsheet is optimized in a deterministic, nonlinear dynamic optimization scheme. The productivity of the target product, propylene glycol methyl ether acetate (PMA), is maximized while the minimum conversion is maintained between 70% and 99%, and the ratio of excess (solvent) reactant to the product is from 1.2 to 8. In addition to the standard configuration of SMBR, we found novel operating schemes through a superstructure formulation which allows feeding the recycle stream from downstream separation units. This work offers a realistic understanding of SMBR for implementation in an overall process flowsheet for industrial applications.

Experimental evaluation of simulated moving bed reactor for transesterification reaction synthesis of glycol ether ester

This work presents an experimental evaluation of multi-column simulated moving bed reactor (SMBR) technology for transesterification of glycol ether ester for the first time. An industrially relevant solvent, propylene glycol methyl ether acetate (DOWANOL™ PMA) was produced using a laboratory-scale SMBR unit packed with a base catalyst. The catalyst selected in this study, a Type-II anion exchange resin, was found to be resistant to deactivation through our experimental runs. To design the SMBR process, single-column experiments were first carried out to develop a mathematical model and estimate model parameters. Using this model, the optimal SMBR process was found by a multi-objective optimization technique to maximize the productivity while achieving high conversions. The optimal operating conditions found in this manner were implemented in the lab-scale SMB unit, which achieved conversions ranging from 47.3 to 57.7%. Furthermore, using the experimental data obtained from these experimental runs, the prediction of the model was improved via Tikhonov regularization, which was successfully validated in an additional run at an even higher conversion of 74.6%.