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

Processes ◽  
2021 ◽  
Vol 9 (2) ◽  
pp. 360
Author(s):  
Jian Wang ◽  
Wenwei Chen ◽  
Yan Li ◽  
Jin Xu ◽  
Weifang Yu ◽  
...  

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.

Author(s):  
H. Schramm ◽  
M. Kaspereit ◽  
A. Kienle ◽  
A. Seidel-Morgenstern

2003 ◽  
Vol 1006 (1-2) ◽  
pp. 77-86 ◽  
Author(s):  
Henning Schramm ◽  
Malte Kaspereit ◽  
Achim Kienle ◽  
Andreas Seidel-Morgenstern

2014 ◽  
Vol 26 (1) ◽  
pp. 84-131 ◽  
Author(s):  
Masashi Sugiyama ◽  
Gang Niu ◽  
Makoto Yamada ◽  
Manabu Kimura ◽  
Hirotaka Hachiya

Information-maximization clustering learns a probabilistic classifier in an unsupervised manner so that mutual information between feature vectors and cluster assignments is maximized. A notable advantage of this approach is that it involves only continuous optimization of model parameters, which is substantially simpler than discrete optimization of cluster assignments. However, existing methods still involve nonconvex optimization problems, and therefore finding a good local optimal solution is not straightforward in practice. In this letter, we propose an alternative information-maximization clustering method based on a squared-loss variant of mutual information. This novel approach gives a clustering solution analytically in a computationally efficient way via kernel eigenvalue decomposition. Furthermore, we provide a practical model selection procedure that allows us to objectively optimize tuning parameters included in the kernel function. Through experiments, we demonstrate the usefulness of the proposed approach.


1995 ◽  
Vol 34 (1) ◽  
pp. 288-301 ◽  
Author(s):  
Giuseppe Storti ◽  
Renato Baciocchi ◽  
Marco Mazzotti ◽  
Massimo Morbidelli

2003 ◽  
Vol 58 (23-24) ◽  
pp. 5217-5227 ◽  
Author(s):  
H. Schramm ◽  
A. Kienle ◽  
M. Kaspereit ◽  
A. Seidel-Morgenstern

2014 ◽  
Vol 1360 ◽  
pp. 196-208 ◽  
Author(s):  
Gaurav Agrawal ◽  
Jungmin Oh ◽  
Balamurali Sreedhar ◽  
Shan Tie ◽  
Megan E. Donaldson ◽  
...  

2020 ◽  
Vol 58 (4) ◽  
pp. 362-372
Author(s):  
Liangyu Li ◽  
Wanxia Liu ◽  
Dawei Song ◽  
Chaoyang Li ◽  
Pengyu Jia ◽  
...  

Abstract Tartary buckwheat shell is an important by-product of Tartary buckwheat production. Previous studies shown that Tartary buckwheat shells are rich in flavonoids, which are responsible for their antioxidant properties. Due to lack of advanced separation technologies, the purification for Tartary buckwheat shell is still in the laboratory scale, and could not realize the industrialization production. According to the results of static adsorption experiment, AB-8 resin was selected for Tartary buckwheat shell flavonoids (TBSF) adsorption. The adsorption isotherm, resin adsorption thermodynamic and dynamic adsorption parameters were studied. And the adsorption of AB-8 resin for TBSF was determined as an endothermic process. Results of preparative chromatography experiment showed that TBSF could be efficiently purified by AB-8 resin. And the optimal parameters were: feed concentration 25 mg/mL, desorption flow rate 2.5 mL/min. Under these conditions, the TBSF were separated effectively. Results of liquid chromatography-mass spectrometer (LC-MS) indicated that there were seven kinds of flavonoids in Tartary buckwheat shell, which were mainly from the 40 and 60% of ethanol elution. Simulated moving bed (SMB) was applied for TBSF purification the first time in this study. The optimal conditions of SMB were as following: adsorption zone flow rate 7.0 mL/min, contaminant removal zone flow rate 17.9 mL/min, product elution zone flow rate 22.3 mL/min, regeneration zone flow rate 21.5 mL/min, water washing zone flow rate 27.5 mL/min, switching time 1260 S, and the purity and yield of TBSF was 90 ± 0.22% and 85 ± 0.28%, respectively. The IC50 values of α-glucosidase inhibition activities and DPPH scavenging activity of the purified TBSF were 57.09 ± 0.15 and 7.92 ± 0.23 μg/mL, respectively. The constituents of TBSF showed higher α-glucosidase inhibition activities and antioxidant than raw TBSF and rutin. The results suggest that SMB is a proper method for industrial production of TBSF, and SMB could be applied for other natural products purification.


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