Response Surface Methodology as an Approach for Optimization of Vinegar Fermentation Conditions Using Three Different Thermotolerant Acetic Acid Bacteria

This study aimed to investigate optimal fermentation conditions of biological acetic acid fermentation for vinegar production. Optimization was performed on 3 acetic acid bacteria strains namely VMA1, VMA7 and VMAO using Response Surface Methodology (RSM). A Box-Behnken-Design (BBD) was achieved with three different independent process parameters involving: fermentation temperature, original alcohol concentration and original acetic acid concentration and one dependent variable (acetic acid yield). The results showed that the mathematical models describe correctly the relationship between responses and factors (F values of the models (p R2 (coefficient of correlation) respectively 0.96, 0.94, 0.98, and adjusted R2 0.95, 0.92, 0.98). The maximum acidity was obtained respectively at fermentation temperatures, original alcohol concentrations and original acetic acid concentrations ranging from [37.5°C - 45°C], [16% - 20% (v/v)], [1.5% - 2% (w/v)] for VMA1, [40°C - 45°C], [14.5% - 20% (v/v)], [1.7% - 2% (w/v)] for VMA7 and [42°C - 45°C], [17% - 20% (v/v)], [1.5% - 2% (w/v)] for VMAO. The use of these acetic strains in the production of vinegar may seriously lead to a decrease or even an ablation of the costs related to the cooling of bioreactors especially in warm and hot countries, in the context of global warming.

Catalytic Hydrothermal Liquefaction of Water Hyacinth Using Fe3O4/NiO Nanocomposite: Optimization of Reaction Conditions by Response Surface Methodology

This research aimed at optimizing the reaction conditions for the catalytic hydrothermal liquefaction (HTL) of water hyacinth using iron oxide/nickel oxide nanocomposite as catalysts. The iron oxide/nickel oxide nanocomposite was synthesized by the co-precipitation method and used in the hydrothermal liquefaction of water hyacinth. The composition and structural morphology of the synthesized catalysts were determined using X-ray diffraction (XRD), transmission electron microscopy (TEM), scanning electron microscopy (SEM), and atomic absorption spectroscopy (AAS). The particle size distribution of the catalyst nanoparticles was determined by the Image J software. Three reaction parameters were optimized using the response surface methodology (RSM). These were: temperature, residence time, and catalyst dosage. A maximum bio-oil yield of 59.4 wt% was obtained using iron oxide/nickel oxide nanocomposite compared to 50.7 wt% obtained in absence of the catalyst. The maximum bio-oil yield was obtained at a temperature of 320°C, 1.5 g of catalyst dosage, and 60 min of residence time. The composition of bio-oil was analyzed using gas chromatography-mass spectroscopy (GC-MS) and elemental analysis. The GC-MS results showed an increase of hydrocarbons from 58.3% for uncatalyzed hydrothermal liquefaction to 88.66% using iron oxide/nickel oxide nanocomposite. Elemental analysis results revealed an increase in the hydrogen and carbon content and a reduction in the Nitrogen, Oxygen, and Sulphur content of the bio-oil during catalytic HTL compared to HTL in absence of catalyst nanoparticles. The high heating value increased from 33.5 MJ/Kg for uncatalyzed hydrothermal liquefaction to 38.6 MJ/Kg during the catalytic HTL. The catalyst nanoparticles were recovered from the solid residue by sonication and magnetic separation and recycled. The recycled catalyst nanoparticles were still efficient as hydrothermal liquefaction (HTL) catalysts and were recycled four times. The application of iron oxide/ nickel oxide nanocomposites in the HTL of water hyacinth increases the yield of bio-oil and improves its quality by reducing hetero atoms thus increasing its energy performance as fuel. Iron oxide/nickel oxide nanocomposites used in this study are widely available and can be easily recovered magnetically and recycled. This will potentially lead to an economical, environmentally friendly, and sustainable way of converting biomass into biofuel.

SCRAMJET INLET MULTI-OBJECTIVE OPTIMIZATION BASED ON RESPONSE SURFACE METHODOLOGY

The uniform design and response surface methodology （RSM） are applied to the multi-objective optimization of a 2-D mixed compression scramjet inlet. The set of experimental design points on the design space is selected by the uniform design, and the inlet performance is analyzed by computational fluid dynamics （CFD）. Then complete quadratic polynomial response surface approximation models are constructed based on the performance analysis results and then used to replace theoriginal complex inlet performance model. The optimization is conducted using a multi-objective genetic algorithm NSGA-Ⅱ, and the Pareto optimal solution set is obtained. Results show that the uniform design and RSM can reduce the computational complexity of numerical simulation and improve the optimization efficiency.

Application of response surface methodology in medium optimization for pyruvic acid production of Torulopsis glabrata TP19 in batch fermentation

Response surface methodology (RSM) was used to optimize the fermentation medium for enhancing pyruvic acid production by Torulopsis glabrata TP19. In the first step of optimization, with Plackett-Burman design, ammonium sulfate, glucose and nicotinic acid were found to be the important factors affecting pyruvic acid production significantly. In the second step, a 23 full factorial central composite design and RSM were applied to determine the optimal concentration of each significant variable. A second-order polynomial was determined by the multiple regression analysis of the experimental data. The optimum values for the critical components were obtained as follows: ammonium sulfate 0.7498 (10.75 g/L), glucose 0.9383 (109.38 g/L) and nicotinic acid 0.3633 (7.86 mg/L) with a predicted value of maximum pyruvic acid production of 42.2 g/L. Under the optimal conditions, the practical pyruvic acid production was 42.4 g/L. The determination coefficient (R2) was 0.9483, which ensures adequate credibility of the model. By scaling up fermentation from flask to jar fermentor, we obtained promising results.

Multiple-response optimization for melting process of aluminum melting furnace based on response surface methodology with desirability function

To reduce the fuel consumption and emissions and also enhance the molten aluminum quality, a mathematical model with user-developed melting model and burning capacity model, were established according to the features of melting process of regenerative aluminum melting furnaces. Based on validating results by heat balance test for an aluminum melting furnace, CFD （computational fluid dynamics） technique, in association with statistical experimental design were used to optimize the melting process of the aluminum melting furnace. Four important factors influencing the melting time, such as horizontal angle between burners, height-to-radius ratio, natural gas mass flow and air preheated temperature, were identified by PLACKETT-BURMAN design. A steepest descent method was undertaken to determine the optimal regions of these factors. Response surface methodology with BOX-BEHNKEN design was adopted to further investigate the mutual interactions between these variables on RSD （relative standard deviation） of aluminum temperature, RSD of furnace temperature and melting time. Multiple-response optimization by desirability function approach was used to determine the optimum melting process parameters. The results indicate that the interaction between the height-to-radius ratio and horizontal angle between burners affects the response variables significantly. The predicted results show that the minimum RSD of aluminum temperature （12.13%）, RSD of furnace temperature （18.50%） and melting time （3.9 h） could be obtained under the optimum conditions of horizontal angle between burners as 64°, height-to-radius ratio as 0.3, natural gas mass flow as 599 m3/h, and air preheated temperature as 639 ℃. These predicted values were further verified by validation experiments. The excellent correlation between the predicted and experimental values confirms the validity and practicability of this statistical optimum strategy.

Milling Parameters Optimization of Al-Li Alloy Thin-Wall Workpieces Using Response Surface Methodology and Particle Swarm Optimization

To improve the milling surface quality of the Al-Li alloy thin-wall workpieces and reduce the cutting energy consumption.Experimental research on the milling processing of AA2195 Al-Li alloy thin-wall workpieces based on Response Surface Methodology was carried out.The single factor and interaction of milling parameters on surface roughness and specific cutting energy were analyzed,and the multi-objective optimization model was constructed.The Multiobjective Particle Swarm Optimization algorithm introducing the Chaos Local Search algorithm and the adaptive inertial weight was applied to determine the optimal combination of milling parameters.It was observed that surface roughness was mainly influenced by feed per tooth,and specific cutting energy was negatively correlated with feed per tooth,radial cutting depth and axial cutting depth,while cutting speed has a non-significant influence on specific cutting energy.The optimal combination of milling parameters with different priorities was obtained.The experimental results showed that the maximum relative error of measured and predicted values was 8.05%,and the model had high reliability,which ensured the low surface roughness and cutting energy consumption.It was of great guiding significance for the success of Al-Li alloy thin-wall milling with a high precision and energy efficiency.

Engineering Design Optimization Based on Intelligent Response Surface Methodology

An intelligent response surface methodology (IRSM) was proposed to achieve the most competitive metal forming products, in which artificial intelligence technologies are introduced into the optimization process. It is used as simple and inexpensive replacement for computationally expensive simulation model. In IRSM, the optimal design space can be reduced greatly without any prior information about function distribution. Also, by identifying the approximation error region, new design points can be supplemented correspondingly to improve the response surface model effectively. The procedure is iterated until the accuracy reaches the desired threshold value. Thus, the global optimization can be performed based on this substitute model. Finally, we present an optimization design example about roll forming of a "U" channel product.

Optimization of Methylene Blue Dye Adsorption onto Coconut Husk Cellulose Using Response Surface Methodology: Adsorption Kinetics, Isotherms and Reusability Studies

In this study, coconut husk cellulose was employed as a cost-effective and environmentally friendly adsorbent to eliminate methylene blue (MB) dye from aqueous solutions. The successful development of response surface methodology paired with a central composite design (RSM-CCD) enabled the optimization and modelling of the adsorption process. The study investigated the individual and combined effects of three variables (pH, contact time, and initial MB dye concentration) on the adsorption of MB dye onto coconut husk cellulose. The developed RSM-CCD model exhibited a remarkable degree of precision in predicting the removal efficiency of MB dye within the specified experimental parameters. This was demonstrated by the strong regression parameters, with an R2 value of 99.79% and an adjusted R2 value of 99.6%. The study depicted that the optimal parameters for attaining a 98.8827% removal of MB dye using coconut husk cellulose were as follows: an initial MB dye concentration of 30 mg∙L−1, contact time of 120 minutes, and pH 7 at a fixed adsorbent dose of 0.5 g. The Freundlich isotherm model provided the most satisfactory description of the equilibrium adsorption isotherms, suggesting that MB dye adsorption onto coconut husk cellulose occurs on a heterogeneous surface. The experimental results demonstrated a strong agreement with the pseudo-second-order kinetics model, indicating that the number of active sites present on the cellulose adsorbent predominantly influences the adsorption process of MB dye. Additionally, the adsorbent made from coconut husk cellulose exhibited the potential to be reused, as it retained its efficiency for a maximum of three cycles of adsorption of MB dye. The results of this study show that coconut husk cellulose has the potential to be an effective and sustainable adsorbent for removing MB dye from aqueous solutions.

Optimization of Cellulose Nanocrystal Isolation from Ayous Sawdust Using Response Surface Methodology

This study focuses on the extraction of cellulose nanocrystals (CNC), from microcrystalline cellulose (MCC), derived from Ayous sawdust. The process involves multiple steps and a large amount of chemical products. The objective of this research was to determine the effects of factors that impact the isolation process and to identify the optimal conditions for CNC isolation by using the response surface methodology. The factors that varied during the process were the quantity of MCC, the concentration of sulfuric acid, the hydrolysis time and temperature, and the ultrasonic treatment time. The response measured was the yield. The study found that with 5.80 g of microcrystalline cellulose, a sulfuric acid concentration of 63.50% (w/w), a hydrolysis time of 53 minutes, a hydrolysis temperature of 69˚C, and a sonication time of 19 minutes are the ideal conditions for isolation. The experimental yield achieved was (37.84 ± 0.99) %. The main factors influencing the process were the sulfuric acid concentration, hydrolysis time and temperature, with a significant influence (p < 0.05). Infrared characterization results showed that nanocrystals were indeed isolated. With a crystallinity of 35.23 and 79.74, respectively, for Ayous wood fiber and nanocrystalline cellulose were observed by X-ray diffraction, with the formation of type II cellulose, thermodynamically more stable than native cellulose type I.

Modeling and optimization of low-grade Mn bearing ore leaching using response surface methodology and central composite rotatable design

The application of leaching process to extracting Mn from a low-grade manganese ore was investigated using a software based design of experiments. Four main parameters, i.e. sulfuric acid concentration, oxalic acid concentration, time and temperature were considered in a central composite response surface design. The recoveries of Mn and Fe were selected as response of design. The optimum conditions under which the Mn and Fe recoveries were the highest and the time and temperature were the lowest were determined using statistical analysis and analysis of variance （ANOVA）. The results showed that Mn and Fe recoveries were 93.44% and 15.72% under the optimum condition, respectively. Also, sulfuric acid concentration was the most effective parameter affecting the process. The amounts of sulfuric and oxalic acid were obtained to be 7% and 42.50 g/L in optimum condition and the best time and temperature were 65 min and 63 ℃.

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.

Process Parameters Optimization of Laser Cladding for HT200 with 316L Coating Based on Response Surface Method

In order to improve the sealing surface performance of gray cast iron gas gate valves and achieve precise molding control of the cladding layer,as well as to reveal the influence of laser cladding process parameters on the morphology and structure of the cladding layer,we prepared the 316L coating on HT 200 by using Design-Expert software central composite design(CCD)based on response surface analysis.We built a regression prediction model and analyzed the ANOVA with the inspection results.With a target cladding layer width of 3.5 mm and height of 1.3 mm,the process parameters were optimized to obtain the best combination of process parameters.The microstructure,phases,and hardness variations of the cladding layer from experiments with optimal parameters were analyzed by the metallographic microscope,confocal microscope,and microhardness instrument.The experimental results indicate that laser power has a significant impact on the cladding layer width,followed by powder feed rate;scan speed has a significant impact on the cladding layer height,followed by powder feed rate.The HT200 substrate and 316L can metallurgically bond well,and the cladding layer structure consists of dendritic crystals,columnar crystals,and equiaxed crystals in sequence.The optimal process parameter combination satisfying the morphology requirements is laser power(A)of 1993 W,scan speed(B)of 8.949 mm/s,powder feed rate(C)of 1.408 r/min,with a maximum hardness of 1564.3 HV0.5,significantly higher than the hardness of the HT200 substrate.

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).

Extraction of Total Phenolic Compounds, Flavonoids, Anthocyanins and Tannins from Grape Byproducts by Response Surface Methodology. Influence of Solid-Liquid Ratio, Particle Size, Time, Temperature and Solvent Mixtures on the Optimization Process

The current work concerns the optimization process of phenolic compounds solid liquid extraction from grape byproducts at high temperatures and short incubation times. The effect of five experimental parameters (solidliquid ratio, particle size, time, temperature and solvent mixture) mostly believed to affect the extraction process was undertaken. A first response surface methodology experimental design was used to optimize the solid-liquid ratio and milling time parameters. A second design was used for the optimization of the quantitative and qualitative parameters. The quantitative parameters studied are: total phenolic compounds, flavonoid content, total monomeric anthocyanin composition and tannin concentration. The qualitative parameters analyzed are: antiradical activity and antioxidant capacity. The second design was based on the use of time, temperature and solvent mixture as optimization parameters. The assays were first conducted separately revealing the best experimental conditions for the maximization of each response variable alone. A simultaneous response surface methodology of all the responses taken together was then conducted, showing the optimal extraction conditions to be: 93 minutes at 94?C and in 66% ethanol/water solvent. The maximal response values obtained for each parameter are: Total Phenolic Compounds yield (5.5 g GAE/100g DM), Flavonoid Content (5.4 g GAE/100g DM), Total Monomeric Anthocyanin yield (70.3 mg/100g DM), Tannin Concentration (12.3 g/L), Antiradical Activity (67.3%) and Total Antioxidant Capacity (393 mgAAE/L). All of the optimal values were acquired at 3 mL/g solid-liquid ratio and 6.8 min milling time. The obtained extracts could be used as natural bioactive compounds in several industrial applications.

Aerodynamic Optimization of a Centrifugal Fan Using Response Surface Methodology

In this paper, the optimization scheme of a centrifugal fan under the constraints of the total pressure difference, efficiency and shaft power was carried out. The blade inlet angle ?1A and the blade outlet angle ?2A of the centrifugal impeller were optimized using the Response Surface Methodology (RSM). Nine optimization cases were presented. The aerodynamic performance and the flow field of the optimized model were carefully compared with the original model. The results show that the total pressure difference and the total-pressure efficiency increase by 5.7% and 4.2% respectively after the optimization. Compared with the original fan, the flow field inside the impeller of the optimized fan has been improved. The flow separation existing around the blade suction surface outlet is suppressed significantly. For fields in the volute, the optimization scheme has reduced the local vortex intensity and weakened the vortex scale. The flow field stability around the volute tongue is also correspondingly improved.

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.

Heat treatment optimization for tensile properties of 8011 Al/15% SiCp metal matrix composite using response surface methodology

In this study,a mathematical model was developed to optimize the heat treatment process for maximum tensile strength and ductility of aluminum(8011) silicon carbide particulate composites.The process parameters are solutionizing time,aging temperature,and aging time.The experiments were performed on an universal testing machine according to centre rotatable design matrix.A mathematical model was developed with the main and interactive effects of the parameters considered.The analysis of variance technique was used to check the adequacy of the developed model.The optimum parameters were obtained for maximum tensile strength.Fractographic examination shows the cracks and dimples on the fractured surfaces of heat-treated specimen.

Removal of CO2 in a multistage fluidized bed reactor by amine impregnated activated carbon: optimization using response surface methodology

Carbon dioxide (CO2) is the major component of greenhouse gas. Increase in concentration of CO2 in the atmosphere leads to global warming. To remove the CO2 from waste flue gas a four-stage counter-current multistage fluidized bed adsorber was developed and operated in continuous bubbling fluidization regime for the two丒phase system. This paper describes the optimum condition for CO2 removal efficiency in a multistage fluidized bed reactor using amine impregnated activated carbon. Response surface methodology with central composite design was used to determine the effect of three variables on the response. The variables are inlet concentration of CO2 in ppm (ranging from 3000 to 20,000), impregnation ratio of monoethanol amine (ranging from 0.2 to 0.6) and weir height in mm (20-60). The response was CO2 removal efficiency. The factor which was most influential has been identified from the analysis of variance. The optimum CO2 removal efficiency for the amine impregnated activated carbon (MEA-AC) was found to be 95.17%, at initial concentration of CO2 7312.85 ppm, chemical impregnation ratio of 0.31, and weir height 48.65 mm. From the experiment, the CO2 removal efficiency was found to be 95.97% at the same operating conditions. The predicted response was found to relevance with experimental data.

Medium Optimization for Antifungal Active Substance Production from Streptomyces Lydicus Using Response Surface Methodology

Response surface methodology was used to optimize the medium for antifungal active substance production from Streptomyces lydicus E12 in flask cultivation. Initially, the component factors, which influence antifungal substance production, were studied by varying one factor at a time. Starch, soybean cake powder, K2HPO4·3H2O and MgSO4·7H2O were found to have a significant effect on the production of antifungal substances by the traditional design. Then, a Box–Behnken design was applied for further optimization. A quadratic model was found to fit antifungal active substance production. The analysis revealed that the optimum values of the tested variable were starch 84.96 g/L, soybean cake powder 4.13 g/L, glucose 5 g/L, MgSO4·7H2O 1.23 g/L, K2HPO4·3H2O 2.14 g/L and NaCl 0.5 g/L. The test result of 67.44% antifungal inhibition agreed with the prediction and increased by 14.28% in comparison with the basal medium. © 2016, Tianjin University and Springer-Verlag Berlin Heidelberg.

Modeling and Optimization of Two Clays Acidic Activation for Phosphate Ions Removal in Aqueous Solution by Response Surface Methodology

This work deals with phosphate ions removal in aqueous solution by adsorption carried out using two clays, both in activated form. One, non-swelling clay, rich in kaolinite, is associated with illite and quartz. The other, swelling, richer in montmorillonite, is associated with kaolinite, illite and quartz. Seven factors including these two clays were taken into account in a series of experimental designs in order to model and optimize the acidic activation process favoring a better phosphate removal. In addition to the choice of clay nature, the study was also interested in the identification of the mineral acid, between hydrochloric acid and sulfuric acid, which would promote this acidic activation. Response Surface Methodology (RSM) was used for this purpose by sequentially applying Plackett and Burman Design and Full Factorial Design (FD) for screening. Then, a central composite design (CCD) was used for modeling the activation process. A mathematical surface model has been successfully established. Thus, the best acidic activation conditions were obtained by activating the montmorillonite clay with a 2N sulfuric acid solution, in an acid/clay mass ratio of 7.5 at 100°C for 16H. The phosphate removal maximum rate obtained was estimated at 89.32% ± 0.86%.