基于Taguchi方法的微小通道性能分析与参数优化

以高效、紧凑、轻质的航空燃油换热器为研究背景,对影响微小通道换热和压力性能的多种工况条件和结构参数进行探究和优化。应用Taguchi方法的正交实验设计和损失函数分析,得到不同因子对性能指标的贡献度和影响规律,并通过可加性检验证明结论具有统计显著性。结果显示,入口流速和通道流型对微小通道传热和压力性能的贡献度最大,通道流型选择圆柱旋涡发生器通道能获得最佳综合性能。此外发现,换热过程中工质的物性变化会影响普朗特数计算,导致多种传热压力性能和综合性能的评价指标有不同影响规律和不同优化参数组合,因此研究时需要根据实际问题选择恰当的评价指标。     

Optimization of mesoporous alumina sol-gel synthesis by Taguchi and response surface methodology

Taguchi method (TM) and response surface methodology (RSM) have been employed to optimize three parameters, including the amounts of P123, the amounts of nitric acid and calcination temperature, in order to define an optimal setting for sol-gel synthesis of high surface area mesoporous alumina powder (MA). Herein, the comparison of the both statistical approaches has been examined and discussed considering the nitrogen adsorption as the response variable because this important character for mesoporous materials is exceedingly sensitive to the synthesis parameters. The BET surface area (S_BET) and pore volume of MA under Taguchi optimal condition were 323.5 m² g⁻¹ and 0.551 cm³ g⁻¹, respectively, by conducting confirmation test. Furthermore, the confirmation test showed high S_BET of MA (363.4 m² g⁻¹), which was in a good agreement with calculated S_BET result (431.25 m² g⁻¹) by a quadratic model under RSM optimal condition. Moreover, 3D response surface plots and 2D contour plots of desirability have been discussed to visualize the influence of input factors on response variable. It is also concluded that RSM shows more appropriate (12.33% higher S_BET than TM) and efficient optimal condition with determining a quadratic function as the relationship between S_BET and synthesis parameters.     

Experiment research on mix design and early mechanical performance of alkali-activated slag using response surface methodology (RSM)

To enhance the quality of alkali-activated slag (AAS) materials, scientific and efficient mix design method is preferred. This paper presents an optimization of AAS materials using Response Surface Methodology (RSM). Three factors related to early strength such as modulus (n), concentration of alkali activator (CAA) and liquid–solid ratio (LSR) were investigated. Specimens with different mix ratios were prepared based on RSM design. The early mechanical performance was assessed, after 2 or 3 h of curing. Then response surface models were established and the effect law of each factor was systemically analyzed. The result shows that both n and CAA have a significant effect on the early strength, while LSR affects slightly. By adjusting the mix design parameters, the early performance of AAS can be effectively improved. This study verifies that RSM is efficient in the preparation of AAS and it can control the early strength of AAS accurately.     

Optimization of process variables for a biosorption of nickel(II) using response surface method

The biosorption of nickel(II) was studied by using crab shell particles of diameter (d _p =0.012 mm) under different initial concentrations of nickel(II) in solution (0.01–5.0 g/l), temperature (20–40 °C), pH (2–6.5), and biosorbent dosages (0.5–10 g/l). The maximum removal of nickel(II) occurred at pH 6.5 and temperature 40 °C for a biosorbent dosage of 6 g/l. The results were modeled by response surface methodology (RSM), which determines the maximum biosorption of nickel(II) as a function of the above four independent variables, and the optimum values for the efficient biosorption of nickel(II) were obtained. The RSM studies were carried out using Box-Behnken design and the analysis of variance confirms the adequacy of the quadratic model with coefficient of correlation R² to be 0.9999. The quadratic model fitted the data well with Prob>F to be <0.0001, indicating the applicability of the present proposed model.     

Design of experiments for statistical modeling and multi-response optimization of nickel electroplating process

The central composite experimental design and response surface methodology have been employed for statistical modeling and analysis of the results dealing with nickel electroplating process. The empirical models developed in terms of design variables (current density J (A/dm²), temperature T (°C) and pH) have been found statistically adequate to describe the process responses, i.e. cathode efficiency Y (%), coating thickness U (μm), brightness V (%) and hardness W (HV). The graphical representations consisted of 2D contour plots and 3D surface plots have been used for exploring and analysis of response surfaces in order to identify the main, quadratic and interaction effects. The multi-response optimization of nickel electroplating process has been carried out by means of desirability function approach. To this end, a genetic algorithm has been used for mathematical optimization of the multi-response problem. The optimization algorithm has conducted to a set of equivalent solutions named Pareto optimal set. The confirmation runs have been employed in order to make a decision about the optimal solution approved by experiment. Thus, the optimum conditions of nickel electroplating has been defined in this work as J* = 5.35 (A/dm²), T* = 33.44 (°C) and pH* = 6.22 and respectively the responses confirmed by experiment were Y = 79.12 ± 0.18 (%), U = 52.77 ± 0.48 (μm), V = 26.12 ± 0.45 (%) and W = 371.6 ± 1.77 (HV). In such conditions the quality of nickel electroplating deposit was the best one in accordance with experimental results.     

Simulation and optimization of the continuous tower process for styrene polymerization

The continuous tower process, a popular industrial process for the manufacture of polystyrene, was simulated and optimized. A kinetic model for the thermal polymerization of styrene, which takes into account the Trommsdorff effect and the volume change accompanying the reaction, was developed. This was used to formulate model equations for the continuous flow stirred tank reactor (CSTR) and plug flow reactor (several sections) in the tower process. The model can predict monomer conversion, number‐ and weight‐average molecular weights, polydispersity index (PDI), and temperature at various locations in the unit, under specified operating conditions. Multiobjective optimization of this process was also carried out, for which an adaptation of a genetic algorithm (GA) was used. The two objectives were maximization of the final monomer conversion and minimization of the PDI of the product. The conversion in the CSTR was constrained to lie within a desired range, and polymer having a specified value of the number‐average molecular weight was to be produced. The optimal solution was a unique point (no Pareto sets were obtained). The optimal solutions indicated that the tower process is operated under near‐optimal conditions. © 2004 Wiley Periodicals, Inc. J Appl Polym Sci 94: 775–788, 2004     

Experimental and modeling study for the removal of formic acid through bulk ionic liquid membrane using response surface methodology

Abstract

In this study, formic acid removal from its aqueous solutions through bulk ionic liquid membrane (BILM) was investigated. Tributyl phosphate (TBP) as a carrier in imidazolium-based ionic liquids was used. D-optimal design based on response surface methodology has been applied to investigate the effect of various operating factors. Initial formic acid concentration, TBP concentration, and NaOH concentration were selected as numerical factors, and ionic liquid type was chosen as a categorical factor. The model equations were obtained to determine BILM process behavior. The removal efficiencies, represented by the extraction and stripping efficiencies, were calculated from the experimental data. The highest removal efficiencies were determined at higher concentration values of TBP and NaOH. All ionic liquids studied in this study had good transport selectivity for the removal of formic acid. The design study showed that BILM is an effective method for the removal of formic acid from the water.     

Response surface methodological approach to optimize the coagulation-flocculation process in drinking water treatment

Performing jar tests often requires carrying out a time consuming iteration procedure to find out the right amount of chemical for coagulation-flocculation process in water treatment plants. Applying the response surface method (RSM) in jar tests as an alternative to the conventional methods was investigated in this study. The purpose is finding out the optimum combination of coagulant dose and pH with respect to the highest removal efficiency of turbidity and dissolved organic carbon (DOC). The results achieved using poly-aluminum chloride (PACl) were compared to those achieved using conventional coagulant such as alum. The quadratic models developed for the two responses (turbidity removal and DOC removal) indicated that the optimum conditions to be PACl concentration of 0.11 mM at pH 7.4 and alum concentration of 0.15 mM at pH 6.6. Compromising to simultaneously optimize the two responses resulted in 91.4% turbidity removal and 31.2% DOC removal using PACl whereas 86.3% turbidity and 34.3% DOC were removed using alum. Confirmation of experimental results was found to be close to the prediction derived from the models. This demonstrates the benefits of the approach based on the RSM in achieving good predictions while minimizing the number of required experiments.     

Optimization of photooxidative removal of p-nitrophenol in a spinning disc photoreactor using response surface methodology

In this article, response surface methodology (RSM) was used to obtain optimum conditions for removal of p-nitrophenol (PNP) by UV/H₂O₂ process using spinning disk photoreactor (SDP). For this purpose, the effect of five independent variables, the initial concentration of PNP, the initial concentration of H₂O₂, pH, solution volume, and irradiation time on the PNP removal percent, was investigated. Central composite design, one of the response surface techniques used for process optimization. The results showed a good agreement between the RSM predicted and experimental data with “R²” and “Adjusted R²” of 0.9692 and 0.9480, respectively. In addition, “Predicted R²” of 0.8909 is in reasonable agreement with “Adjusted R²” of 0.9488. At optimal conditions, that is, PNP concentration of 20.78?mg L^?1, H₂O₂ concentration of 1355.83?mg L^?1, solution volume of 566.08?mL, irradiation time of 12.30?min, and pH of 4.59 the removal percent predicted by RSM is 100% which has good correspondence with its experimental value (98.67%).     

Production and optimization of sustainable cement brick incorporating clay brick wastes using response surface method

This paper aims to fabricate and optimize eco-sustainable cement brick using different sizes of clay brick waste (CBW). The prime input factors of mixtures were clay brick powder (CBP) as a binder, fine-clay brick (FCB) as a fine aggregate, and coarse-clay brick (CCB) as a coarse aggregate, whereas the compressive strength was the main response of the generated eco-sustainable bricks. This was accomplished by utilizing the central composite design (CCD) and Response Surface Methodology (RSM) with Minitab-19. Twenty mixtures with CBW were generated and experimentally evaluated utilizing CCD concept in RSM. A multi-objective optimization approach was applied to obtain the optimum results for the input parameters. Based on an experimental program, the optimum mixtures were selected to investigate the physical and durability properties of the produced brick. The SEM test was also performed to determine the effect of the CBW particles on the microstructure of the brick. The life cycle assessment of mixtures is also performed in terms of global warming potential. The optimization showed that the input components CBP, FCB, and CCB had average optimum values of 21%, 0%, and 9.09%, respectively. The experimental results showed that employing CBW yields a durable and high freeze-thaw resistance of the eco-sustainable brick despite its high porosity and absorption. Furthermore, using cement brick with CBW particles is acknowledged as a more environmentally beneficial combination. The proposed models can speed up the process of mix design by using different sizes of brick waste to get the optimum eco-friendly cement brick properties.     

Optimization of a continuous ultrasound assisted oxidative desulfurization (UAOD) process of diesel using response surface methodology (RSM) considering operating cost

A continuous-flow ultrasound-assisted oxidative desulfurization(UAOD) of partially hydro-treated diesel has been investigated using hydrogen peroxide-formic acid as simple and easy to apply oxidation system. The effects of different operating parameters of oxidation stage including residence time(2–24 min), formic acid to sulfur molar ratio(10–150), and oxidant to sulfur molar ratio(5–35) on the sulfur removal have been studied using response surface methodology(RSM) based on Box–Behnken design. Considering the operating costs of the continuous-flow oxidation stage including chemical and electrical energy consumption, the appropriate values of operating parameters were selected as follows: residence time of 16 min, the formic acid to sulfur molar ratio of 54.47, and the oxidant to sulfur molar ratio of 8.24. In these conditions, the sulfur removal and the volume ratio of the hydrocarbon phase to the aqueous phase were 86.90% and 4.34, respectively. By drastic reduction in the chemical consumption in the oxidation stage, the volume ratio of the hydrocarbon phase to the aqueous phase was increased up to 10. Therefore, the formic acid to sulfur molar ratio and the oxidant to sulfur molar ratio were obtained 23.64 and 3.58, respectively, which lead to sulfur removal of 84.38% with considerable improvements on the operating cost of oxidation stage in comparison with the previous works.     

Photocatalytic oxidation of treated municipal wastewaters for the removal of phenolic compounds: optimization and modeling using response surface methodology (RSM) and artificial neural networks (ANNs)

BACKGROUND: TiO₂ heterogeneous photocatalysis should be optimized before application for the removal of pollutants in treated wastewaters. The response surface methodology (RSM) and artificial neural networks (ANNs) were applied to model and optimize the photocatalytic degradation of total phenolic (TPh) compounds in real secondary and tertiary treated municipal wastewaters. RESULTS: RSM was developed by considering a central composite design (CCD) with three input variables, i.e. TiO₂ mass, initial concentration of TPh and irradiation intensity. At the same time a feed‐forward multilayered perceptron ANN trained using back propagation algorithms was used and compared with RSM. Under the optimum conditions established in experiments ([TPh]₀ = 3 mg L^?1; [TiO₂] = 300 mg L^?1; I = 600 W m^?2) the degradation for both TPh and total organic carbon (TOC) followed pseudo‐first‐order kinetic model. Complete degradation of TPh took place in 180 min and reduction of TOC reached 80%. A significant abatement of the overall toxicity was accomplished as revealed by Microtox bioassay. CONCLUSIONS: It was found that the variables considered have important effects on TPh removal efficiency. The results demonstrated that the use of experimental design strategy is indispensable for successful investigation and adequate modeling of the process and that ANNs gave better modelling capability than RSM. Copyright © 2012 Society of Chemical Industry     

TOPSIS based Taguchi design optimization for CVD growth of graphene using different carbon sources: Graphene thickness,defectiveness and homogeneity

Chemical inhomogeneity of chemical vapor deposition (CVD) grown graphene compromises its usage in high-performance devices. In this study, TOPSIS based Taguchi optimization was performed to improve thickness uniformity and defect density of CVD grown graphene. 1.56% decrease in the mean 2D/G intensity ratio, 87.96% improvement in the mean D/G intensity ratio, 56.07% improvement in the standard deviation D/G intensity ratio, 25.21% improvement in the standard deviation 2D/G intensity ratio, and 69.32% improvement in the surface roughness were achieved with TOPSIS based Taguchi optimization. The statistical differences between the copper and silicon substrates have been found significantly in terms of their impacts on the graphene's properties with the 0.000 p-value for the mean D/G intensity ratio and with the 0.009 p-value for the mean 2D/G intensity ratio, respectively. Graphene having 11% lower mean D/G intensity ratio (low defective graphene products) compared to the values given in the literature using single-response optimization was obtained using multi-response optimization.     

新型除磷填料的制备及除磷吸附床运行参数的优化

为解决现有除磷吸附剂粒径小造成的材料易流失和系统压降过大等问题,以实现吸附除磷工艺在实际工程中的应用,以聚氨酯填料为载体,水溶性聚氨酯为介质,将水化硅酸钙负载到聚氨酯填料上制成负载型除磷填料。研究了制备条件对除磷填料除磷效果的影响,采用扫描电子显微镜（SEM）和傅里叶变换红外光谱仪（FTIR）观察分析了负载前后水化硅酸钙微观结构及化学基团的变化;利用除磷填料作为除磷吸附床的滤料,研究了运行条件对吸附床除磷效果的影响。在此基础上,利用响应曲面法研究了除磷吸附床磷酸盐去除率和各变量之间的关系,并对工艺参数进行了优化。结果表明,水性聚氨酯溶液的浓度和用量分别为100 g/L和50 ml,水化硅酸钙的质量为12 g的条件下所制备的除磷填料除磷效果最好;SEM和FTIR分析结果显示,水化硅酸钙负载前后其孔隙结构和化学基团没有明显的变化;预测模型的方差分析结果表明,HRT(X ₁)、进水ρ(PO₄ ^3--P)(X ₂)、温度(X ₃)、初始pH(X ₄)以及X ₁ X ₂,X ₁ X ₄,X ₂ X ₃,X ₂ X ₄的交互作用均对磷酸盐的去除具有显著影响 (P＜0.05),但X ₁ X ₃的交互作用对磷酸盐的去除影响不显著。通过预测模型获得的最佳运行条件为：HRT为79.77 min,进水ρ(PO₄ ^3--P)为1.70 mg/L, 温度为34.04℃,pH为9.68。在该条件下,反应器对磷酸盐的去除率可以达到93.46%。     

Multiobjective optimization of the continuous casting process for poly (methyl methacrylate) using adapted genetic algorithm

The nondominated sorting genetic algorithm (NSGA) has been used to optimize the operation of the continuous casting of a film of poly (methyl methacrylate). This process involves two reactors, namely, an isothermal plug flow tubular reactor (PFTR) followed by a nonisothermal film reactor. Two objective functions have been used in this study: the cross‐section average value of the monomer conversion, x̄_mf , of the product is maximized, and the length, z_f , of the film reactor is minimized. Simultaneously, the cross‐section average value of the number‐average molecular weight of the product is forced to have a certain prescribed (desired) value. It is also ensured that the temperature at any location in the film being produced lies below a certain value, to avoid degradation reactions. Seven decision variables are used in this study: the temperature of the isothermal PFTR, the flow rate of the initiator in the feed to the PFTR (for a specified feed flow rate of the monomer), the film thickness, the monomer conversion at the output of the PFTR, and three coefficients describing the wall temperature to be used in the film reactor. Sets of nondominating (equally good) optimal solutions (Pareto sets) have been obtained due to the conflicting requirements for the several conditions studied. It is interesting to observe that under optimal conditions, the exothermicity of the reactions drives them to completion near the center of the film, while heat conduction and higher wall temperature help to achieve this in the outer regions. © 2000 John Wiley & Sons, Inc. J Appl Polym Sci 78: 1439–1458, 2000     

Seawater desalination using PVDF-HFP membrane in DCMD process: assessment of operating condition by response surface method

Central composite design (CCD) was applied in this work to analyze the performance of poly(vinylidene fluoride-co-hexafluoropropylene) (PVDF-HFP) flat sheet membrane in the seawater desalination using direct contact membrane distillation (DCMD) process. It is the most popular in response surface method (RSM). Development on Quadratic Regression model for membrane performance as a function of the operating conditions was studied. The ranges for each operating condition were selected as follows: feed temperature (T_f): 48–58?°C, feed flow rate (Q_f): 80–180?mL/min, permeate temperature (T_p):17–22?°C and permeate flow rate (Q_p): 80–180?mL/min. The model R-squared of 0.9759 (adjusted to degree-of-freedom), Lack-of-fit test (p?=?0.4764), predicted residual error sum of squared (PRESS) statistic of 10.3 suggest that the model is adequate to correlate the impact of operating conditions on permeates. ANOVA analysis showed that factors as feed flow rate, feed temperature, and permeate temperature have a valuable impact (p?≤?0.05) on the response variable. Additionally, the interaction among feed temperature-feed flow rate, feed flow rate-permeate flow rate, and the quadratic impact of feed temperature, permeate temperature, and permeate flow rate have shown an important impact (p?≤?0.05) on the permeate flux. Optimization of operating conditions to make the permeate flux and salt rejection high as possible was determined according to desirability function approach. A desirability of 0.969 was achieved at a feed temperature of 58?°C, feed flow rate of 180?mL/min, permeate temperature of 18.8?°C, and permeate flow rate of 145.3?mL/min in which a permeate flux of 12.56?kg/m²h and a salt rejection of 99.97% was obtained.     

Optimization of acrylonitrile removal by activated carbon‐granular using response surface methodology

A statistical Box–Behnken design of experiments was performed to evaluate the effects of individual operating variables and their interactions on the acrylonitrile (AN) removal of C₀ = 100 mg/L as fixed input parameter. The variables examined in this study included activated carbon‐granular (AC) dosage, w, temperature, T, and time of contact, t. The significant variables and optimum conditions were identified (w = 4 g/L, T = 30°C, and t = 120 min with AN uptake of 23.97 mg/g of AC) from statistical analysis of the experimental results using response surface methodology (RSM).     

Biodegradation of coffee pulp tannin by Penicillium verrucosum for production of tannase,statistical optimization and its application

Coffee pulp is a primary by-product produced during coffee processing and represents 30% of the coffee fruit on a dry-weight basis. A novel potential tannin degrading fungi was isolated from coffee by-products. Among the various fungi isolated, Penicillium sp. CFR303 was found to be potent with 66.5 ± 0.9% tannin degradation. The potent tannin degrader was identified as Penicillium verrucosum using internal transcribed spacer's (ITS) −5.8S rDNA analysis. Solid state fermentation was carried out on coffee pulp as a sole carbon source and yielded 28.173 ± 1.4 U/gds of tannase. Further, 3.93 fold increase in tannase production (115.995 U/gds) was achieved using central composite rotatable design, a statistical approach. Model validations showed excellent agreement between the experimental results and the predicted responses with a confidence level of 95%. Coffee pulp accounts to 8–10% tannin content and the present study demonstrates coffee pulp as an excellent substrate for production of value added products. Aonla and pomegranate juice were treated with partially purified tannase and the degradation of tannins was evident by changes in the physicochemical parameters of the juice. Thus, the present investigation signifies utilization of coffee pulp for production of tannase as value addition and its potential application in the food industry.