Modeling and Optimization of Reactive Extraction of Gallic Acid Using RSM

Reactive extraction was experimentally investigated for recovery of gallic acid (GA) from the aqueous solution using tri-n-octylamine (TOA) as extractant in hexanol. All experiments were carried out according to statistical design in order to develop a regression model used to optimize the extraction of GA. Two independent variables were selected as: initial concentration of GA (C_GA0) in aqueous phase and concentration of TOA (C_TOA) in organic phase. The statistical analysis showed that both the independent variables had significant effect on response value, followed by the quadratic and interactive effect on response. A five-level central composite rotatable design (CCRD) was employed. Analysis of variance (ANOVA) showed a high coefficient of determination (R²?=?99.0%). The optimal extraction conditions of GA were determined as: C_GA0?=?2.01?g/L, C_TOA?=?6.8% v/v. At the optimum conditions, the experimental yield of GA was 91.9%, which was in close agreement with the predicted value of 93.2%.     

Modeling and Optimization of Chemical Engineering Processes and Systems

Articles prepared based on the materials of the American-Russian Chemical Engineering Scientific School “Modeling and Optimization of Chemical Engineering Processes and Systems”, which was held at Kazan National Research Technological University on May 23?25, 2016, have been reviewed. The development and application of modern simulation and optimization methods for solving the problems of designing, managing, and studying chemical engineering processes and systems for using rationally energy and raw materials, ensure safety and protection of the environment, and provide sustainable development are discussed.     

Optimization of Rubber Wood Drying by Response Surface Method and Multiple Contour Plots

Abstract

By adopting the central-composite experiment design, the response surface methodology was used to optimize operating conditions of rubber wood drying. The independent variables are initial moisture content of rubber wood, and three drying environment parameters namely, temperature, relative humidity, and air velocity. The investigating responses are final moisture content, drying time, and energy consumption. The restriction of the optimization is the designated final moisture content, which is not greater than 16%. The third-order polynomial models with transformed responses were developed from experiment data to generate 3-D response surfaces and contour plots. The analysis of variance (ANOVA) was performed to identify the significant parameters affecting the rubber wood drying. Drying temperature and holding relative humidity are those two influential operating parameters that significantly control the final moisture of rubber wood and affect the drying time and energy. The multiple contour plots of drying responses show that the optimum operating regions are located mainly at high temperature drying zone. The high temperature drying practice can save energy and drying time by 44 and 25% respectively, in comparison to the conventional temperature drying.     

Optimization of Rubber Wood Drying by Response Surface Method and Multiple Contour Plots

By adopting the central-composite experiment design, the response surface methodology was used to optimize operating conditions of rubber wood drying. The independent variables are initial moisture content of rubber wood, and three drying environment parameters namely, temperature, relative humidity, and air velocity. The investigating responses are final moisture content, drying time, and energy consumption. The restriction of the optimization is the designated final moisture content, which is not greater than 16%. The third-order polynomial models with transformed responses were developed from experiment data to generate 3-D response surfaces and contour plots. The analysis of variance (ANOVA) was performed to identify the significant parameters affecting the rubber wood drying. Drying temperature and holding relative humidity are those two influential operating parameters that significantly control the final moisture of rubber wood and affect the drying time and energy. The multiple contour plots of drying responses show that the optimum operating regions are located mainly at high temperature drying zone. The high temperature drying practice can save energy and drying time by 44 and 25% respectively, in comparison to the conventional temperature drying.     

Optimization of supercritical dimethyl carbonate (SCDMC) technology for the production of biodiesel and value-added glycerol carbonate

In the present study, biodiesel has been successfully produced from triglycerides and dimethyl carbonate, instead of the conventional alcohol. In this non-catalytic supercritical dimethyl carbonate (SCDMC) technology, valuable compound of glycerol carbonate is obtained as side product, rather than the undesirable glycerol. Glycerol carbonate has higher commercial value compared to glycerol and its application in industries is enormous. In this optimization study, the effects of important parameters including reaction temperature, molar ratio of dimethyl carbonate to oil and reaction time were investigated and optimized by employing response surface methodology (RSM) analysis. It was found that the mathematical model developed was statistically significant and adequate to predict the optimum yield. The optimum conditions for SCDMC process was found to be 380 °C for reaction temperature, 39:1 mol/mol of dimethyl carbonate to oil molar ratio and 30 min of reaction time to obtain 91% optimum yield of biodiesel.     

A Modified Model for Flexibility Analysis in Chemical Engineering Processes

This paper discussed an extended model for flexibility analysis of chemical process. Under uncertainty, probability density function is used to describe uncertain parameters instead of hyper-rectangle, and chance-constrained programming is a feasible way to deal with the violation of constraints. Because the feasible region of control variables would change along with uncertain parameters, its smallest acceptable size threshold is presented to ensure the controllability condition. By synthesizing the considerations mentioned above, a modified model can describe the flexibility analysis problem more exactly. Then a hybrid algorithm, which integrates: stochastic simulation and genetic algorithm, is applied to solve this model and maximize the flexibility region. Both numerical and chemical process examples are presented to demonstrate the effectiveness of the method.     

Optimization of Food Waste Bioevaporation Process Using Response Surface Methodology

A proven bioevaporation process was used to treat food waste (FW) by mixing ground FW with biodried sludge (BS). Organic loading (OL), moisture content (MC), and air flow rate (Q_g) showed significant influences on FW bioevaporation performance. Single-parameter experiments for MC and Q_g were conducted and ranges were determined to be 55–67 wt% and 0.04–0.14 m³/kg TS_mixture · h, respectively. In order to optimize the FW bioevaporation process, a central composite design (CCD) and response surface method (RSM) were applied over the preselected ranges of OL (0.00–0.16 kg VS_FW/kg TS_BS), MC (50.91–71.09 wt%), and Q_g (0.01–0.17 m³/kg TS_mixture · h). The results indicated that OL of 0.06 kg VS_FW/kg TS_BS, MC of 59.2 wt%, and Q_g of 0.09 m³/kg TS_mixture · h were the optimal conditions for the FW bioevaporation process. Water evaporation of 123.1% and VS degradation of 108.4% were obtained under these estimated optimal conditions.     

Optimization of L-Asparaginase Immobilization onto Calcium Alginate Beads

In this study, anti-leukemic enzyme L-asparaginase (E.C.3.5.1.1) from Escherichia coli ATCC 11303 was modified by the microencapsulation technique onto calcium alginate beads. Using response surface methodology (RSM), a three-level full factorial design, the values of concentration of sodium alginate, concentration of calcium chloride, and enzyme loading were investigated to obtain the highest residual L-asparaginase (L-ASNase) activity % (immobilized enzyme activity/free enzyme activity). The effects of the studied factors on immobilization were evaluated The predicted values by the model were close to the experimental values, indicating suitability of the model. The results presented that an increase in sodium alginate concentration increased the percent of residual activity of L-ASNase at any given calcium chloride concentration and the moderate amount of enzyme loading increased the percent residual activity. The optimal immobilization conditions were as follows: sodium alginate 1.98% (w/v), calcium chloride concentration 3.70% (w/v), and enzyme load 46.91% (v/v). The highest residual L-ASNase activity % obtained was 34.49%.     

Optimization of Vegetal Pear Drying Using Response Surface Methodology

The aim of this work was to optimize the drying process of vegetal pear and minimize energy resources (cost) under prefixed limits involving vegetal pear moisture, color, and productivity. The optimization of vegetal pear drying was made by using response surface methodology (RSM) for minimum process cost and color difference between fresh and dried samples (moisture ≤0.10 g water g d.m.^?1). A pilot-plant dryer was used for dehydrating vegetal pear slices (0.5 cm thickness). The tests were carried out at different air temperature (60 to 70°C), samples diameter (4 to 7 cm), and pretreatment with ascorbic acid solutions (0–0.1% w/w). The optimum drying conditions were found at air temperature of 63°C with 5-cm sample diameter and 0.075% of ascorbic acid concentration. On the optimized drying conditions, dried vegetal pear presented values with moisture content of 0.052 g water g d.m.^?1, color difference of 11.65, production rate of 0.0073 kg h^?1, and total cost of $30.58/kg dried product^?1     

响应面法优化低组胺发酵香肠的工艺条件

目的 以组胺基因缺失植物乳杆菌配合啤酒酵母作为发酵剂,采用响应面法优化低组胺发酵香肠的工艺参数。方法对组胺基因缺失植物乳杆菌和啤酒酵母的菌种间比例、接种量、发酵温度和发酵时间4个因素分别进行单因素试验,根据单因素试验结果设计Box-Benhnken中心组合试验,以组胺含量为指标,采用响应面分析法确定最优发酵工艺参数。以优化的工艺制作发酵香肠,并测定各项质量指标。结果发酵香肠最优工艺参数为:组胺基因缺少植物乳杆菌与啤酒酵母菌种间比为7∶4,接种量0.71%,发酵温度30.84℃,发酵时间22.89 h,发酵香肠中组胺含量为3.94 mg/kg。以优化的工艺制作的发酵香肠各项质量指标均符合国家标准,组胺含量降低了54.5%。结论以优化的工艺制作的发酵香肠组胺含量降低,安全性得到提高。     

Optimization of Fluidized Bed Drying Process of Green Peas Using Response Surface Methodology

The fluidized bed drying process of green peas was optimized using the response surface methodology for the process variables: drying air temperature (60–100°C), tempering time (0–60 min), pretreatment, and mass per unit area (6.3–9.5 g/cm²). The green peas were pretreated by pricking, hot water blanching, or chemical blanching. Product quality parameters such as rehydration ratio, color, texture, and appearance were determined and analyzed. Second-order polynomial equations, containing all the process variables, were used to model the measured process and product qualities. Rehydration ratio was influenced mostly by pretreatment followed by tempering time, temperature, and mass per unit area. Pretreatment and mass per unit area significantly affected color and texture. Higher levels of temperature and lower levels of tempering time and mass per unit area increased the rehydration ratio. The optimum process conditions were derived by using the contour plots on the rehydration ratio and sensory scores generated by the second-order polynomials. Optimum conditions of 79.4°C drying air temperature, 35.8-min tempering time, pretreatment of the once pricked peas with chemical blanching in a solution of 2.5% NaCl and 0.1% NaHCO₃, and mass per unit area of 6.8 g/cm² were recommended for the fluidized bed drying of green peas. At these conditions the rehydration ratio was 3.49.     

A Mixed Coding Scheme of a Particle Swarm Optimization and a Hybrid Genetic Algorithm with Sequential Quadratic Programming for Mixed Integer Nonlinear Programming in Common Chemical Engineering Practice

In this paper, mixed integer nonlinear programming (MINLP) is optimized by PSO_GA–SQP, the mixed coding of a particle swarm optimization (PSO), and a hybrid genetic algorithm and sequential quadratic programming (GA–SQP). The population is separated into two groups: discrete and continuous variables. The discrete variables are optimized by the adapted PSO, while the continuous variables are optimized by the GA–SQP using the discrete variable information from the adapted PSO. Therefore, the population can be set to a smaller size than usual to obtain a global solution. The proposed PSO_GA–SQP algorithm is verified using various MINLP problems including the designing of retrofit heat exchanger networks. The fitness values of the tested problems are able to reach the global optimum.     

Optimization of Cellulase Production from Isolated Cellulolytic Bacterium: Comparison between Genetic Algorithms,Simulated Annealing,and Response Surface Methodology

The present study discusses optimization of cellulase production from isolated cellulolytic bacterium. A simulated annealing (SA) algorithm is proposed for optimization of these processes to achieve the desired production goal. The approach was compared to the use of evolutionary algorithms, i.e., genetic algorithms (GAs) and response surface methodology (RSM). Ochrobactrum haematophilum was identified as the isolated bacteria. Carboxymethyl cellulose (CMC) concentration, yeast extract, pH, and incubation temperature were the significant factors screened by Plackett–Burman design and further optimized using a central composite design. The optimum values obtained were CMC concentration = 4.76% (w/v), yeast extract = 2.03% (w/v), pH = 6.3, and temperature = 44.2°C. Carboxy methyl cellulase (CMCase) activity at these values was experimentally determined to be 3.55 ± 0.16 U/ml, which was 2.8 times than the unoptimized system (1.23 U/ml). The growth-associated and non-growth-associated Leudeking–Piret constants, α and β, were respectively determined to be 0.3943 and 0.0105. The Michaelis–Menten constants, V_max and K_m, were determined to be 0.67 µmol/min and 2.42 mg CMC/ml, respectively. The variable-sized SA seems to be the best alternative, outperforming the GAs, showing a fast convergence and low variability among the several runs for optimized production cellulose recovery. The SA models are found to be capable of better predictions of cellulase production. The results of the SA-based RSM model indicate that it is much more robust and accurate in estimating the values of dependent variables when compared with the GA-based RSM models and only RSM models.     

Optimization of solar-powered reverse osmosis desalination pilot plant using response surface methodology

A solar thermal and photovoltaic-powered reverse osmosis (RO) desalination plant has been constructed and optimized for brackish water desalination. The central composite experimental design of orthogonal type and response surface methodology (RSM) have been used to develop predictive models for simulation and optimization of different responses such as the salt rejection coefficient, the specific permeate flux and the RO specific performance index that takes into consideration the salt rejection coefficient, the permeate flux, the energy consumption and the conversion factor. The considered input variables were the feed temperature, the feed flow-rate and the feed pressure. Analysis of variance (ANOVA) has been employed to test the significance of the RSM polynomial models. The optimum operating conditions have been determined using the step adjusting gradient method. An optimum RO specific performance index has been achieved experimentally under the obtained optimal conditions. The RO optimized plant guarantees a potable water production of 0.2 m³/day with energy consumption lower than 1.3 kWh/m³.     

Optimization of crude oil dehydration in an industrial spiral-type gravitational coalescer

This research is focused on modelling and optimization of crude oil dehydration in a spiral-type gravitational coalescer process. The process is modelled based on the population balance to calculate water cut and droplet size distribution in the treated crude oil. The effects of fresh water rate, oil temperature and mixing pressure drop on characteristics of treated crude oil are investigated using response surface methodology. The optimum condition of process is determined considering output water cut, salt content and produced gas in gravitational coalescer as objective functions. The results show that water cut in the treated crude oil is decreased about 21.2% at optimal condition.     

利用响应面分析法优化鸟苷发酵培养基

目的利用响应面分析法对鸟苷发酵培养基进行优化,提高鸟苷产量。方法采用响应面分析法对鸟苷发酵培养基的3种主要成分葡萄糖、酵母粉和豆饼水解液进行优化。用Design-Expert软件对实验数据进行多元回归分析,并建立3种因素与鸟苷产量之间的函数关系。用最终优化的配方进行3次验证试验。结果通过岭脊分析,获得培养基中3因素最佳浓度为:葡萄糖12.0%,酵母粉1.4%,豆饼水解液4.0%,发酵液鸟苷最高产量可达28.3g/L。3次验证试验所测得的鸟苷产量分别为28.14、28.32和27.86g/L,平均值为28.10g/L,与预测结果基本一致。结论利用响应面分析法可优化鸟苷发酵培养基,显著提高鸟苷的产量。     

Optimization of Phospholipid Nanoparticle Formulations Using Response Surface Methodology

The present study deals with the optimization of phospholipid liposome formulations to mimic red blood cells. Optimization of different concentrations of distearylphosphatidylcholine, dipalmitoylphosphatidylcholine, and phosphatidylserine at a fixed concentration of lecithin and Tween^® 80 was done using response surface methodology. The optimized formulation produced liposomes with a particle size in the range of 112–196 nm. The optimized formulation shows low encapsulation efficiency at low levels of insulin but increases at higher loading levels. Formulated vesicles fulfill the size requirement for intravenous drug delivery. The present system is environmentally friendly with respect to biodegradability and biocompatibility.     

Application of Response Surface Methodology for Optimization of Water Treatment by Fe3O4/SiO2/TiO2 Core-Shell Nano-Photocatalyst

In the present work, Fe₃O₄/SiO₂/TiO₂ nano-photocatalyst with a core-shell structure was successfully used for the removal of Methylene Blue (MB) as a model organic pollutant from water. The resultant nanoparticles were characterized by X-ray diffraction, field emission scanning electron microscopy, Fourier-transform infrared spectroscopy, vibrating sample magnetometry, Brunauer–Emmett–Teller method, and Barrett–Joyner–Halenda method. Response surface methodology (Box–Behnken approach) was applied to optimize the removal of MB from water. This optimization was used to evaluate the effect of experimental variables and their interaction in achieving the optimum conditions in removal of MB from water which was measured via UV-visible spectroscopy. The optimum conditions were found to be at Si/Fe₃O₄ wt% = 17.35%, Ti/Fe₃O₄ wt% = 50.17%, and calcination temperature = 392°C with a 91.1% removal efficiency. Finally, a model was established and the predicted results from the model fitted well with the experimental values indicating that the optimization was successful.     

响应面法优化胶原蛋白发酵培养基和培养条件

目的利用统计学方法对重组大肠杆菌发酵培养基进行优化,提高胶原蛋白产量。方法应用Plackett-Burman试验设计法和响应面法,对发酵培养基6种组分配比和2个初始发酵条件进行优化;用Design-Expert软件对实验数据进行多元回归分析,并建立3种主要因素(葡萄糖、混合氮源和K2HPO4)与胶原蛋白产量之间的函数关系。用最终优化的配方进行5次验证试验。结果培养基3个最佳浓度为:葡萄糖为14.69 g/L、混合氮源为15.04 g/L、K2HPO4为11.91 g/L,胶原蛋白表达率可达33.95%。5次验证试验所测得的胶原蛋白平均表达率为34.02%,与预测结果基本一致。结论优化的重组大肠杆菌发酵培养基可显著提高胶原蛋白产量。     

响应面法优化产低温脂肪酶工程菌Cl02的发酵条件

目的采用响应面法优化产低温脂肪酶工程菌Cl02的发酵条件。方法通过单因素试验考察培养基中酵母氮源含量、pH值、甘油含量和甲醇含量对酶活的影响,确定产酶的主要影响条件,在此基础上,根据Box-Benheken中心组合试验设计原理,采用三因素三水平的响应面分析法,综合考察各因子对低温脂肪酶酶活的影响,建立低温脂肪酶酶活的二次回归模型。结果培养基中酵母氮源含量、pH值和甲醇含量对酶活的影响显著。最适产低温脂肪酶条件为:酵母氮源含量7.3 g/L、pH 6.0、甲醇含量9.1 g/L,在此条件下,低温脂肪酶酶活可达42.25 IU/ml,比优化前(28.0 IU/ml)提高了50.9%。结论利用响应面法优化的发酵条件可显著提高工程菌的产酶能力,为规模化生产低温脂肪酶奠定了基础。