Cr(Ⅲ) removal from simulated solution using hydrous magnesium oxide coated fly ash： Optimization by response surface methodology (RSM)

Hydrous magnesium oxide coated fly ash （MFA） has environmental remediation potential by providing a sub- strate for the adsorption of aqueous Cr（Ⅲ）. Aqueous Cr（Ⅲ） adsorption onto MFA was examined as a function of MFA dosage, pH and initial Cr（Ⅲ） concentration with the Box-Behnken approach used for experimental design and optimization using response surface methodology （RSM）. pH and dosage （dosage and concentration） have significant interactive effects on Cr（Ⅲ） adsorption efficiency. Analysis of variance shows that the response surface quadratic model is highly significant and can effectively predict the experimental outcomes. Cr（Ⅲ） removal effi- ciency of 98% was obtained using optimized conditions of MFA dosage, pH and initial Cr（Ⅲ） concentration of 1,5 7 g. L- 1, 4.11 and 126 mg. L- 1, respectively. Cr（Ⅲ） adsorption onto MFA is mainly attributed to the interaction between Or（Ⅲ） and the functional group --OH of the hydrous magnesium oxide, in all probability caused by chemisorptions. The results of this study can conduce to reveal the interactions between Cr（Ⅲ） pollutant and MFA characteristics, posing important implications for the cost-effective alternative adsorption technology in the treatment of heavy metal containing wastewater.

Optimization of Inactivation Conditions of High Hydrostatic Pressure Using Response Surface Methodology

Response surface methodology (RSM) was employed in the present work and a second orderquadratic equation for high hydrostatic pressure (HHP) inactivation was built. Theadequacy of the model equation for predicting the optimum response values was verifiedeffectively by the validation data. Effects of temperature, pressure, and pressureholding time on HHP inactivation of Escherichia coli ATCC 8739 were explored. Byanalyzing the response surface plots and their corresponding contour plots as well assolving the quadratic equation, the optimum process parameters for inactivation E. coliof six log cycles were obtained as: temperature 32.2℃, pressure 346.4 MPa, and pressureholding time 12.6min.

Response surface methodology-based hybrid robust design optimization for complex product under mixed uncertainties

Minimizing the impact of the mixed uncertainties(i.e.,the aleatory uncertainty and the epistemic uncertainty) for a complex product of compliant mechanism(CPCM) quality improvement signifies a fascinating research topic to enhance the robustness.However, most of the existing works in the CPCM robust design optimization neglect the mixed uncertainties, which might result in an unstable design or even an infeasible design. To solve this issue, a response surface methodology-based hybrid robust design optimization(RSM-based HRDO) approach is proposed to improve the robustness of the quality characteristic for the CPCM via considering the mixed uncertainties in the robust design optimization. A bridge-type amplification mechanism is used to manifest the effectiveness of the proposed approach. The comparison results prove that the proposed approach can not only keep its superiority in the robustness, but also provide a robust scheme for optimizing the design parameters.

Optimization for Microbial Degumming of Ramie with Bacillus subtilis DZ_(5) in Submerged Fermentation by Orthogonal Array Design and Response Surface Methodology

As a kind of natural fiber,ramie fiber has distinctive advantages in textile application,but the application is limited due to the traditional degumming mode.Compared with the traditional degumming process,the microbial degumming process has many advantages.To obtain the optimal conditions for degumming ramie with Bacillus subtilis DZ_(5)(BS DZ_(5)),a combined statistical approach of orthogonal array design(OAD)and response surface methodology(RSM)was used.The influences of initial pH of the bacteria medium,culture temperature,shaking speed,degumming time and inoculum size on submerged fermentation degumming were evaluated by using fractional factorial design.The main factors in the analysis were culture temperature,shaking speed and initial pH.The residual gum mass fraction was used as the optimization index,and the optimal conditions for degumming were determined by central composite design and RSM.Thus with only a limited number of experiments,an optimal ramie microbial degumming condition was found as the culture temperature of 40℃,the initial pH in the culture medium of 8.5,the shaking speed of 205 r/min,the degumming time of 96 h and the inoculum size of 5%.After microbial degumming of ramie under the optimal conditions,there was only 10.6%residual gum by mass in the fiber.In addition,the effective degumming of BS DZ_(5)was also confirmed by a scanning electron microscope(SEM).

Optimization of Culture Components for Laccase Activity from Pleurotus Ostreatus P40 Using Response Surface Methodology

High enzymatic activity is required for laccase applications.Central composite design （CCD）-based response surface methodology （RSM） can effectively increase the enzymatic activity of Pleurotus ostreatus P40 in liquid substrate fermentation.Initial screening of the nutritional components was performed using a Plackett-Burman design.The variables,namely,bran,bagasse,Tween 80,and yeast extract,were found to have statistically significant effects on laccase activity.These variables were further optimized using CCD-based RSM.Optimal concentrations for the maximum laccase activity were 8.144 2 g/L bran,50 g/L bagasse,0.424 1 mL/L Tween 80,and 2.832 5 g/L yeast extract.Under optimized conditions,the maximum measured laccase activity reached 96 480 U/L,which was close to the predicted value （104 830 U/L） by RSM.Therefore,RSM can be used to optimize culture components for laccase activity from Pieurotus ostreatus P40.

Mechanical and Permeability Analysis and Optimization of Recycled Aggregate Pervious Concrete Based on Response Surface Method

In this paper,the effects of different influencing factors and factor interaction on the compressive strength and permeability of recycled aggregate pervious concrete(RAPC)were studied based on the response surface method(RSM).By selecting the maximum aggregate size,water cement ratio and target porosity as design variables,combined with laboratory tests and numerical analysis,the influences of three factors on the compressive strength and permeability coefficient of RAPC were revealed.The regression equation of compressive strength and permeability coefficient of recycled aggregate pervious concrete were established based on RSM,and the response surface model was optimized to determine the optimal ratio of RAPC under the conditions of meeting the mechanical and permeability properties.The results show that the mismatch item of the model is not significant,the model is credible,and the accuracy and reliability of the test are high,but the degree of uncorrelation between the test data and the model is not obvious.The sensitivity of the three factors to the compressive strength is water cement ratio>maximum coarse aggregate particle size>target porosity,and the sensitivity to the permeability coefficient is target porosity>maximum coarse aggregate particle size>water cement ratio.The absolute errors of the model prediction results and the model optimization results are 1.28 MPa and 0.19 mm/s,and the relative errors are 5.06%and 4.19%,respectively.With high accuracy,RSM can match the measured results of compressive strength and permeability coefficient of RAPC.

Medium Optimization of Tetraselmis sp.-1 Using Response Surface Methodology

Response surface methodology (RSM) is used to optimize the medium of Tetraselmis sp.-1 which is cell fused microalgae capable of growing under mixotrophic condition. Empirical models are developed to describe the relationships between the operating variables (glucose, urea, sodium dehydrogenate phosphate, sodium chloride) and responses (cell density). Statistical analysis indicates that glucose and urea have significant effects on the microalgae cell density, but other two factors (sodium dehydrogenate phosphate, sodium chloride) have no obvious effect. The path of steepest ascent is used to approach the optimal region of medium composition. Optimal cell density (2.638 g dry weight/L) was reached when the operating conditions were glucose concentration (30.75 %), urea concentration (0.440 g/L), sodium dehydrogenate phosphate (15 mg/L) and sodium chloride (28 g/L).

Optimization of Bead Geometry in CO₂Laser Welding of Ti 6Al 4V Using Response Surface Methodology

In the presented study, the laser butt-welding of Ti 6Al 4V is investigated using 2.2 kw CO2 laser. Ti 6Al 4V alloy has widespread application in various fields of industries including the medical, nuclear and aerospace. In this study, Response Surface Methodology (RSM) is employed to establish the design of experiments and to optimize the bead geometry. The relationships between the input laser-welding parameters (i.e. laser power, welding speed and focal point position) and the process responses (i.e. welded zone width, heat affected zone width, welded zone area, heat affected zone area and penetration depth) are investigated. The multi-response optimizations are used to optimize the welding process. The optimum welding conditions are identified in order to increase the productivity and minimize the total operating cost. The validation results demonstrate that the developed models are accurate with low percentages of error (less than 12.5%).

Improvement of xylanase production by Aspergillus niger XY-1 using response surface methodology for optimizing the medium composition

Objective: To study the optimal medium composition for xylanase production by Aspergillus niger XY-1 in solid-state fermentation (SSF). Methods: Statistical methodology including the Plackett-Burman design (PBD) and the central composite design (CCD) was employed to investigate the individual crucial component of the medium that significantly affected the enzyme yield. Results: Firstly, NaNO3, yeast extract, urea, Na2CO3, MgSO4, peptone and (NH4)2SO4 were screened as the significant factors positively affecting the xylanase production by PBD. Secondly, by valuating the nitrogen sources effect, urea was proved to be the most effective and economic nitrogen source for xylanase production and used for further optimization. Finally, the CCD and response surface methodology (RSM) were applied to determine the optimal concentration of each sig-nificant variable, which included urea, Na2CO3 and MgSO4. Subsequently a second-order polynomial was determined by multiple regression analysis. The optimum values of the critical components for maximum xylanase production were obtained as follows: x1 (urea)=0.163 (41.63 g/L), x2 (Na2CO3)=?1.68 (2.64 g/L), x3 (MgSO4)=1.338 (10.68 g/L) and the predicted xylanase value was 14374.6 U/g dry substrate. Using the optimized condition, xylanase production by Aspergillus niger XY-1 after 48 h fermentation reached 14637 U/g dry substrate with wheat bran in the shake flask. Conclusion: By using PBD and CCD, we obtained the optimal composition for xylanase production by Aspergillus niger XY-1 in SSF, and the results of no additional expensive medium and shortened fermentation time for higher xylanase production show the potential for industrial utilization.

Synthesis of Poly(AAm-<i>co</i>-AA) and Investigation of its Swelling Behavior: Using Response Surface Methodology (RSM)

Unwanted water production together with oil and gas production is a striking problem in oil and gas industries, and many approaches have been examined to overcome this major problem. Preformed particle gels (PPGs) showed dramatically good properties for this purpose in mature oil and gas reservoirs. In this study, we carefully synthesized an efficient series of PPGs with using a design of experiments (DOE) software. Acrylamide (AAm)/Acrylic acid (AA) mole ratio, N,N’-methylenebisacrylamide (MBA) mole percentage and swelling time were considered as key parameters to examine PPG swelling behavior. Our results presented a detailed empirical correlation, which could significantly predict the swelling capacity of PPGs in CaCl2 salt solution (200,000 ppm).

Multi-Objective Optimization for an Industrial Grinding and Classification Process Based on PBM and RSM

The grinding and classification process is one of the key sub-processes in mineral processing, which influences the final process indexes significantly and determines energy and ball consumption of the whole plant. Therefore, optimal control of the process has been very important in practice. In order to stabilize the grinding index and improve grinding capacity in the process,a process model based on population balance model(PBM) is calibrated in this study. The correlation between the mill power and the operating variables in the grinding process is modelled by using the response surface method(RSM), which solves the problem where the traditional power modeling method relies on some unobservable mechanism-related parameters. On this basis, a multi-objective optimization model is established to maximize the useful power of the grinding circuit to improve the throughput of the grinding operation and improve the fraction of –0.074 mm particles in the hydrocyclone overflow to smooth the subsequent flotation operation. The elite non-dominated sorting genetic algorithm-II(NSGA-II) is then employed to solve the multi-objective optimization problem. Finally, subjective and objective weighting methods and integrated multi-attribute decision-making methods are used to select the optimal solution on the Pareto optimal solution set. The results demonstrate that the throughput of the mill and the fraction of –0.074 mm particles in the overflow of the cyclone are increased by 3.83 t/h and 2.53%, respectively.

Combined Size and Shape Optimization of Structures with DOE,RSM and GA

In this paper,size and shape optimization problem of a machine gun system is addressed with an efficient hybrid method,in which a novel and flexible mesh morphing technique is employed to achieve fast parameterization and modification of complexity structure without going back to CAD for reconstruction of geometric models or to finite element analysis（ FEA） for remodeling. Design of experiments（ DOE） and response surface method（ RSM） are applied to approximate the constitutive parameters of a machine gun system based on experimental tests. Further FEA,secondary development technique and genetic algorithm（ GA） are introduced to find all the optimal solutions in one go and the optimal design of the demonstrated machine gun system is obtained. Results of the rigid-flexible coupling dynamic analysis and exterior ballistics calculation validate the proposed methodology,which is relatively time-saving,reliable and has the potential to solve similar problems.

Application of Improved RSM in the Optimization of Automotive Frontal Crashworthiness

Based on the vehicle front crash finite element analysis, it shows that there is a large acceleration, so it needs further optimization. In order to improve the performance of vehicle collision, eight parts were selected which have large impact for the result, its thickness as design variables to the right of the B-pillar acceleration peak of optimization goal;17 sample points were selected by Latin hypercube sampling method. Many structure parameters are optimized using sequential quadratic program (SQP) based on the surrogate model. The results show that the improved RSM has high accuracy;the right B-pillar acceleration reduced approximately 22.8%, reached the expected objective and was more conducive to the occupant safety.

Optimization of succinic acid fermentation with Actinobacillus succinogenes by response surface methodology(RSM)

Succinic acid is considered as an important platform chemical. Succinic acid fermentation with Actinobacillus succinogenes strain BE-1 was optimized by central composite design （CCD） using a response surface methodology （RSM）. The optimized production of succinic acid was predicted and the interactive effects between glucose, yeast extract, and magnesium carbonate were investigated. As a result, a model for predicting the concentration of succinic acid production was developed. The accuracy of the model was confirmed by the analysis of variance （ANOVA）, and the validity was further proved by verification experiments showing that percentage errors between actual and predicted values varied from 3.02% to 6.38%. In addition, it was observed that the interactive effect between yeast extract and magnesium carbonate was statistically significant. In conclusion, RSM is an effective and useful method for optimizing the medium components and investigating the interactive effects, and can provide valuable information for succinic acid scale-up fermentation using A. succinogenes strain BE-I.

Reliability Based Optimization of Composite Laminates for Frequency Constraint

The reliability based optimization （RBO） issue of composite laminates trader fundamental frequency constraint is studied. Considering the tmcertainties of material properties, the frequency constraint reliability of the structure is evaluated by the combination of response surface method （RSM） and finite element method. An optimization algorithm is developed based on the mechanism of laminate frequency characteristics, to optimize the laminate in terms of the ply amount and orientation angles. Numerical examples of composite laminates and cylindrical shell illustrate the advantages of the present optimization algorithm on the efficiency and applicability respects. The optimal solutions of RBO are obviously different from the deterministic optimization results, and the necessity of considering material property uncertainties in the composite structural frequency constraint optimization is revealed.

Optimization of Processing Parameters of Power Spinning for Bushing Based on Neural Network and Genetic Algorithms

A neural network model of key process parameters and forming quality is developed based on training samples which are obtained from the orthogonal experiment and the finite element numerical simulation. Optimization of the process parameters is conducted using the genetic algorithm (GA). The experimental results have shown that a surface model of the neural network can describe the nonlinear implicit relationship between the parameters of the power spinning process:the wall margin and amount of expansion. It has been found that the process of determining spinning technological parameters can be accelerated using the optimization method developed based on the BP neural network and the genetic algorithm used for the process parameters of power spinning formation. It is undoubtedly beneficial towards engineering applications.

Multi-Objective Optimization of Surface-Mounted and Interior Permanent Magnet Synchronous Motor Based on Taguchi Method and Response Surface Method

The surface-mounted and interior permanent magnet synchronous motor(SIPMSM)has the characteristics of multiple variables,strong coupling and nonlinearity.In order to improve the performance of SIPMSM,this paper presents a multi-objective optimal design process using Taguchi and response surface methodology(RSM).The peak value of cogging torque(PVCT),ratio value of average torque and permanent magnet weight(RTW),torque ripple and back-EMF total harmonics distortion(ETHD)are selected as optimization goals.The experiment matrix is established by Taguchi method,and analyzed the tendency and proportion of the effect of the optimization parameters on SIPMSM performance.The rules of choosing multi-objective optimization parameters are obtained.The least-squares method is used to establish the optimal objective function,and RSM is used to obtain the resolutions of the optimization objective function.Comparing the initial performance with optimized performance verifies the effectiveness of the proposed method.

Optimization of Sensor Orientation in Railway Wheel Detector, Using Kriging Method

Considering the importance of axle counter function in detecting the train wheels and determining the clearance or occupancy of a track section, it is important to ensure a safe and reliable performance of this system. In this paper, in order to improve the sensor performance, the authors have focused on the orientation of magnetic sensors’ coils. In order to improve the detection capability of the system, through measuring the induced voltage in the receiver coil, it is important to adjust the relative orientation of the transmitter and receiver coils. Due to the existence of infinite relative orientations, in order to determine the optimum orientation for the sensor coils, Kriging methods which is one of the Response Surface Methodologies (RSMs) is applied. Finite Element Method (FEM) is utilized to provide sample data, as inputs to the Kriging algorithm. The analysis not only provides the optimum relative orientation of the sensor coils, it also improves analysis time, comparing to field based measurements. The analysis results are validated by the laboratory based data implemented in the control and signaling laboratory of the school of railway engineering and also field based tests in Iranian railway.

Investigation of colloidal biogenic sulfur flocculation:Optimization using response surface analysis

The colloidal properties of biogenic elemental sulfur（S^0）cause solid–liquid separation problems,such as poor settling and membrane fouling.In this study,the separation of S^0 from bulk liquids was performed using flocculation.Polyaluminum chloride（PAC）,polyacrylamide（PAM）and microbial flocculant（MBF）were compared to investigate their abilities to flocculate S^0 produced during the treatment of sulfate-containing wastewater.A novel approach with response surface methodology（RSM）was employed to evaluate the effects and interactions of flocculant dose,pH and stirring intensity,on the treatment efficiency in terms of the S^0 flocculation and the supernatant turbidity removal.The dose optimization results indicated that the S^0 flocculation efficiency decreased in the following order PAC〉MBF〉PAM.Optimum S^0 flocculation conditions were observed at pH 4.73,a stirring speed of 129 r/min and a flocculant dose of 2.42 mg PAC/mg S.During optimum flocculation conditions,the S^0f locculation rate reached 97.53%.Confirmation experiments demonstrated that employing PAC for S^0 flocculation is feasible and RSM is an efficient approach for optimizing the process of S^0 flocculation.The results provide basic parameters and conditions for recovering sulfur during the treatment of sulfate-laden wastewaters.

Optimization of the operating conditions in a TiO_2/Fe_3O_4-SiO_2 photocatalytic reactor for the treatment of industrial wastewater containing Procion Red MX-5B

According to the design principle of the central composite experimental,the method of response surface analysis with three factors and three levels was adopted based on one factor test.A second-order quadratic equation for photocatalysis of Procion Red MX-5B was built.Response surface and contour were graphed with the decoloration rate of Procion Red MX-5B as the response value.Based on the analysis of the response surface plots and their corresponding contour plots,effects of pH value,irradiation time and catalyst loading were explored.By using this new method,the optimum decoloration condition was obtained as follows:pH value,1.3;irradiation time,49.9 min;catalyst loading,0.57 g/L.In the optimization,R-Squared and Adj R-Squared correlation coefficients for quadratic model were evaluated quite satisfactorily as 0.9310 and 0.8620,respectively.Under the optimum conditions established,the performance of 99.47% for color removal was experimentally reached.It was found that all factors considered have an important effect on the decolorization efficiency of Procion Red MX-5B.By the ANOVA analysis and model confirmation the optimal solution obtained using RSM was experimentally validated and credible with preferable instructional ability for experiments.