Optimization Of Simulated Moving Bed Research Articles

Optimization of a simulated-moving-bed process for continuous separation of racemic and meso-2,3-butanediol using an efficient optimization tool based on nonlinear standing-wave-design method

The feasibility of using a simulated-moving-bed (SMB) process for continuous-mode separation of biotechnologically produced 2,3-butanediol (BD) into racemic-BD and meso-BD has been verified recently. One of the important tasks for facilitating the industrial application of such a BD-isomer separation SMB is to make a substantial improvement in its production rate and/or productivity while meeting the requirements on BD-isomer purities and pressure drop. To address this issue, the comprehensive optimization for a BD-isomer separation SMB was attempted in this study. First, an efficient SMB optimization tool based on a Langmuir isotherm standing-wave-design method was prepared and then applied to comprehensively optimizing the operation and system parameters of the considered SMB. The results revealed that the production rate (Prate), under a given column length, could reach its maximum when feed concentration (Cfeed,BD) was selected at the one where the negative effect of nonlinearity increase on Prate could be balanced with the positive effect of Cfeed,BD increase on Prate. The Prate could be improved further by modulating column length (Lc) to be a little lager than the Lc leading to a maximum in feed flow rate (Qfeed), which was effective in increasing Cfeed,BD high enough to outweigh the resultant decrease of Qfeed. It was also found that the productivity (Prod) could be enhanced by adopting the Lc smaller than that for a maximum in Qfeed, which could allow a sufficiently large savings of adsorbent to outweigh the resultant decrease of Qfeed and Cfeed,BD. Finally, it was confirmed that the comprehensively optimized SMB in this study could lead to more than 17 times the Prate and Prod, compared to the previously reported BD-isomer separation SMB.

Optimization of production rate, productivity, and product concentration for a simulated moving bed process aimed atfucose separation using standing-wave-design and genetic algorithm

The effectiveness of a simulated moving bed (SMB) technology in the continuous separation of fucose from a multi-component monosugar mixture, which stemmed from defatted microalgae, has recently been identified. To guarantee high economical efficiency of such fucose-production method, the comprehensive optimization of the relevant fucose-separation SMB process needs to be accomplished such that its production rate (Prate) and/or productivity (Prod) can be maximized while meeting the requirements on fucose product concentration (Cprod,F) and pressure drop (ΔPSMB). To resolve this issue, the SMB optimization program based on standing-wave-design method and genetic algorithm was prepared and then applied to the fucose-separation SMB optimization. It was found that the Prate, under a given particle size, could reach its maximum when the column length was selected to create a balance between the effects of the two limiting factors related to Cprod,F and ΔPSMB. It was also found that the Prate was governed by fucose yield, if the SMB would be in need of a relatively high Cprod,F; otherwise, the Prate was governed by feed flow rate. If the particle size of the SMB adsorbent was fixed at one of the commercially available ones, the SMB conditions leading to the highest Prate and the highest Prod coincided with each other. By contrast, if the particle size was included as one of optimization variables, the Prate and Prod represented a trade-off relationship. Finally, it was confirmed from the simultaneous optimization for Prate and Prod that the increase of particle size improved Prate at the cost of Prod, thereby causing the maximum Prod to be always attained at a smaller particle size than the maximum Prate regardless of the target Cprod,F level.

Standing wave design and optimization of a simulated moving bed chromatography for separation of xylobiose and xylose under the constraints on product concentration and pressure drop

The feasibility of a simulated moving bed (SMB) technology for the continuous separation of high-purity xylobiose (X2) from the output of a β-xylosidase X1→X2 reaction has recently been confirmed. To ensure high economical efficiency of the X2 production method based on the use of xylose (X1) as a starting material, it is essential to accomplish the comprehensive optimization of the X2-separation SMB process in such a way that its X2 productivity can be maximized while maintaining the X2 product concentration from the SMB as high as possible in consideration of a subsequent lyophilization step. To address this issue, a suitable SMB optimization tool for the aforementioned task was prepared based on standing wave design theory. The prepared tool was then used to optimize the SMB operation parameters, column configuration, total column number, adsorbent particle size, and X2 yield while meeting the constraints on X2 purity, X2 product concentration, and pressure drop. The results showed that the use of a larger particle size caused the productivity to be limited by the constraint on X2 product concentration, and a maximum productivity was attained by choosing the particle size such that the effect of the X2-concentration limiting factor could be balanced with that of pressure-drop limiting factor. If the target level of X2 product concentration was elevated, higher productivity could be achieved by decreasing particle size, raising the level of X2 yield, and increasing the column number in the zones containing the front and rear of X2 solute band.

General optimization strategy of simulated moving bed units through design of experiments and response surface methodologies

Abstract The optimization of simulated moving bed (SMB) units is often performed through detailed phenomenological models and require extensive computation time. Hence several optimization methods like the Triangle Theory, and the concept of separation volume have been proposed. However, they do not provide accurate results, when mass transfer limitations are significant, or require a large number of simulations. In this work, a combined Design of Experiments and Response Surface Methodology (DoE-RSM) approach is proposed for SMB optimization, aimed at providing good results with simplicity and reduced number of simulations. The separation of trans-stilbene oxide enantiomers is selected as case study in order to compare DoE-RSM with previous approaches. In the whole, accurate results are obtained with a few number of simulations, allowing for purities above 99.60% for both enantiomers, and productivity of 65.41 kg/(m3adsorbent day). The versatility of DoE-RSM tool is also discussed, emphasising their advantages and general applicability.

Development of a non-triangular separation region for improving the performance of a three-zone simulated moving bed chromatography for binary separation with linear isotherms

For a three-zone simulated moving bed (SMB) chromatography with linear isotherms, the feasible set of operating parameters for complete separation is known to exist within a triangular region of the triangle theory that is formed in the operating parameter plane spanned by the flow-rate-ratios in the separation zones (II and III), which are commonly denoted as m2 and m3. Such an operating region for complete separation region, however, has been established only in the first quadrant (m2, m3) plane, where m2>0 and m3>0, until now. In this study, a new complete-separation region was developed in the third quadrant (m2, m3) plane, where m2<0 and m3<0, regarding a three-zone SMB process for the first time. The results showed that the new separation region created in the third quadrant (m2, m3) plane took a non-triangular shape. The operating parameters within such a non-triangular separation region were capable of guaranteeing complete separation for an ideal system with no mass-transfer effects. For a non-ideal system with considerable mass-transfer effects, the operating parameters that were selected with a sufficient margin from the boundaries of the non-triangular separation region led to high purities. One of the noteworthy features in the pattern of solute migration for such case was that both low-affinity and high-affinity solutes reached their corresponding product ports after taking a turn around the SMB bed once. Finally, it was confirmed from the results of SMB optimization based on genetic algorithm and detailed model that the operating parameters in the third quadrant (m2, m3) plane, if chosen properly, could ensure higher purities or higher throughput than the optimal operating parameters in the first quadrant (m2, m3) plane.

Consideration of a target product concentration level in the optimal design of a four-zone simulated moving bed process for binary separation

In the stage of optimizing a simulated moving bed (SMB) process for continuous separation, the extent of product concentration can sometimes be as important as the other performance criteria such as throughput and product purities. In such cases, the issue of maintaining the product concentration higher than a given target level needs to be taken into account during the SMB optimization. To investigate this issue, the throughput of an SMB process for binary separation was optimized in this study using a model separation system while placing a constraint on product concentration as well as pressure drop. The resultant throughput from such SMB optimization was highly affected by column length. It was found first that the throughput was limited by the constraint on the product concentration in the region of short columns but limited by the constraint on the pressure drop in the region of long columns. As a result, the optimal column length leading to the highest throughput occurred at the boundary between the product-concentration limiting region and the pressure-drop limiting region. In addition to the column length, the column configuration also played an important role in the optimization of the SMB with the constraint on the product concentration. As the target level of the raffinate product concentration was set higher, the optimal column configuration leading to the maximum throughput showed the pattern of placing more columns in zone IV. By contrast, the placement of more columns in zone I became the pattern of optimal column configuration when the target level of the extract product concentration was set higher. The results and methodology in this article will be useful when there is a necessity for developing SMBs that are to meet a certain requirement imposed on product concentration.

Comparison of Amberchrom-CG161C and Dowex99 as the adsorbent of a four-zone simulated moving bed process for removal of acetic acid from biomass hydrolyzate

One of the important steps in the application of biomass to producing sugars, which can be converted into bio-ethanol and other valuable chemicals by fermentation, is to hydrolyze the biomass components by sulfuric acid. It was reported that such a hydrolysis entailed the generation of acetic acid, which has been recognized as a key impurity to be surely removed from the biomass hydrolyzate for ensuring high fermentability of the hydrolyzed sugars. Regarding such a removal task, there has been a previous application of a simulated moving bed (SMB) process based on the Dowex99 adsorbent, whose performance, however, was limited by low selectivity between acetic acid and sugars. To overcome such a limitation, another adsorbent alternative to Dowex99 was searched in this study. It was found that Amberchrom-CG161C allowed higher selectivity between acetic acid and sugars than Dowex99. To investigate the relative superiority of Amberchrom-CG161C over Dowex99 as the adsorbent of an SMB process for removing acetic acid from the biomass hydrolyzate, the two SMB processes based on Amberchrom-CG161C and Dowex99 were optimized using the SMB optimization tool based on standing wave design (SWD) method. The optimization results revealed that the Amberchrom-CG161C SMB outperformed the Dowex99 SMB by a wide margin.

Optimal design of a tandem simulated moving bed process for separation of paclitaxel, 13-dehydroxybaccatin III, and 10-deacetylpaclitaxel

Paclitaxel, 13-dehydroxybaccatin III (13-DHBIII), and 10-deacetylpaclitaxel (10-DAP), which came from the plant cell culture, have been regarded as highly valuable because of their efficacy in the anticancer treatments. Due to these values, the necessity for separating the three components in an economical way has been a matter of grave concern in industry. In this study, a tandem simulated moving bed (SMB) process that consisted of two four-zone SMB units in series was applied to such a ternary separation. First, a series of pulse injection experiments were performed for estimation of the adsorption isotherm and mass-transfer parameters. The estimated parameters were utilized in the tandem SMB optimization tool that was prepared based on the standing wave design principle. During the optimization of interest, the throughput of the tandem SMB was maximized while meeting the requirements on product purities and pressure drop. The results proved that the most economical strategy of utilizing the tandem SMB was to recover paclitaxel in the first SMB unit and then separate the remaining two components (13-DHBIII and 10-DAP) in the second SMB unit. Furthermore, such a strategy was also found to result in better tandem SMB performances over the entire region of a pressure drop limit.

Standing wave optimization of SMB using a hybrid simulated annealing and genetic algorithm (SAGA)

In this paper we draw on two stochastic optimization techniques, Simulated Annealing and Genetic Algorithm (SAGA), to create a hybrid to determine the optimal design of nonlinear Simulated Moving Bed (SMB) systems. A mathematical programming model based on the Standing Wave Design (SWD) offers a significant advantage in optimizing SMB systems. SAGA builds upon the strength of SA and GA to optimize the 16 variables of the mixed-integer nonlinear programming model for single- and multi-objective optimizations. The SAGA procedure is shown to be robust with computational time in minutes for single-objective optimization and in a few hours for a multi-objective optimization, which is comprised of more than one hundred points.

Large scale optimization strategies for zone configuration of simulated moving beds

Simulated moving bed (SMB) processes are widely used in sugar, petrochemical, and pharmaceutical industries. However, systematic optimization of SMB, especially finding the optimal zone configuration including the standard and modified non-standard configurations, is still a challenging problem. This paper proposes a simultaneous, fully discretized approach with an SMB superstructure using an interior-point solver. To find the optimal structure, two superstructures are analyzed to develop standard and non-standard configurations. In case studies of the linear and bi-Langmuir isotherms, optimal zone configurations have been successfully obtained without introducing discrete variables. Finally, the effect of the number of columns on the optimal throughput is investigated.

Multiobjective optimization of SMB and varicol process for chiral separation

AbstractThe multiobjective optimization of continuous countercurrent chromatography separation units, such as simulated moving bed (SMB) and Varicol, is considered. The Varicol system is based on a nonsynchronous shift of the inlet and outlet ports instead of the synchronous one used in the SMB technology. The optimization problem is complicated by the relative large number of decision variables, including continuous variables, such as flow rates and lengths, as well as discontinuous ones, such as column number and configuration. It is also important to reformulate the optimization problem as multiobjective, since the factors affecting the cost of a given separation process are multiple and often in conflict with each other. A typical example is simultaneous maximization of the productivity of the process and the purity of the corresponding products. A new optimization procedure based on a genetic algorithm allows handling these complex optimization problems. An existing literature chiral separation model was used to illustrate the potential of this optimization procedure. This work also offered a unique opportunity to compare the optimal separation performance achievable with the SMB and Varicol technologies.