Optimizing Bucket Elevator Performance through a Blend of Discrete Element Method, Response Surface Methodology, and Firefly Algorithm Approaches

This research introduces a novel approach to enhancing bucket elevator design and operation through the integration of discrete element method(DEM)simulation,design of experiments(DOE),and metaheuristic optimization algorithms.Specifically,the study employs the firefly algorithm(FA),a metaheuristic optimization technique,to optimize bucket elevator parameters for maximizing transport mass and mass flow rate discharge of granular materials under specified working conditions.The experimental methodology involves several key steps:screening experiments to identify significant factors affecting bucket elevator operation,central composite design(CCD)experiments to further explore these factors,and response surface methodology(RSM)to create predictive models for transport mass and mass flow rate discharge.The FA algorithm is then applied to optimize these models,and the results are validated through simulation and empirical experiments.The study validates the optimized parameters through simulation and empirical experiments,comparing results with DEM simulation.The outcomes demonstrate the effectiveness of the FA algorithm in identifying optimal bucket parameters,showcasing less than 10%and 15%deviation for transport mass and mass flow rate discharge,respectively,between predicted and actual values.Overall,this research provides insights into the critical factors influencing bucket elevator operation and offers a systematic methodology for optimizing bucket parameters,contributing to more efficient material handling in various industrial applications.

Optimization of Preparation Conditions of Modified Oyster Shell Powder/Ce-N-TiO2 by Response Surface Methodology (RSM)

A new composite photocatalyst of modified oyster shell powder/Ce-N-TiO2 was prepared by sol-gel method. Based on single factor experiment, Ce doping rate, N doping rate and calcination temperature were taken as input variables. Based on the central composite design (BBD) response surface model, two functional relationship models between three independent variables and glyphosate removal rate were established to evaluate the influence degree of independent variables and interaction on catalyst. The significance of the model and regression coefficient was tested by variance analysis. The analysis of the obtained data showed that the degradation performance of the composite photocatalyst was significantly affected by the calcination temperature and the rate of N doping, while the rate of Ce doping had little effect;at the calcination temperature of 505.440°C, the degradation rate of glyphosate reached the maximum of 82.15% under the preparation conditions of 17.057 mol% N doping and 0.165 mol% Ce doping, respectively.

Effects of main ecological factors on the growth of marine green alga Caulerpa sertularioides using the response surface methodology

Caulerpa sertularioides is an invasive potential blooming green alga in China but it remains poorly studied.We studied the effects of ecological factors on its growth.Optimum conditions of ecological factors,i.e.,irradiance,temperature,and salinity,for the growth of its fragments were determined in the response surface methodology(RSM).The specific growth rates(SGR)of the fragments were determined in single-factor experiment.The results show that the SGR of C.sertularioides peaked under the conditions of irradiance 37.5μmol/(m~2·s),temperature25℃,and salinity 30.Meanwhile,using the Box-Behnken design,the conditions were further optimized and verified to be:irradiance 39.03μmol/(m~2·s),temperature 25.29℃,and salinity 30.06,under which the SGR reached 4.66%.The results provide new theoretical data and solutions for the cultivation,invasion prediction,and monitoring of Caulerpa species in China and the world.The RSM method may have great potential applications in the environmental adaptation characteristics of new macroalgal cultivars,intensive orientation cultured germplasm,and environmental hazard analysis of cultivated species in the field.

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 Solid-state Fermentation Conditions of Sophora japonica cv.jinhuai by Response Surface Methodology

[Objectives]To optimize the solid-state fermentation process of Flos Sophorae Immaturus by Penicillium with Sophora japonica cv.jinhuai as raw material.[Methods]The fermentation conditions were optimized by single factor experiment and response surface methodology with quercetin content as the dependent variable.[Results]According to the established model,the optimal fermentation process of Flos Sophorae Immaturus was obtained as follows:temperature 29.97℃,time 6.88 d,rotation speed 180.86 rpm,inoculation amount 3.93 mL,and the expected content of quercetin was 34.8053 mg/g.Based on this,the fermentation parameters were adjusted,and the actual content was 33.67 mg/g,which was close to the predicted value.[Conclusions]The optimization of fermentation process of Flos Sophorae Immaturus by response surface methodology provides a reference for the development and utilization of this medicinal material.

Optimisation of beef tenderisation treated with bromelain using response surface methodology (RSM)

The purpose of this study is to determine the optimum condition for the tenderization of beef by bromelain using Response Surface Methodology (RSM). Initially, bromelain powder was produced from pineapple crown of variety N36. Production of the bromelain powder involves several process steps such as extraction, purification, desalting and freeze drying. The cube size beef of round part was treated with bromelain at different pHs of beef, immersion temperatures, bromelain solution concentrations, and immersion times according to the experimental design which was recommended by RSM of MINITAB software version 15. Beef tenderness was then measured by Texture Analyser. The MINITAB software Version 15 was used to optimise the tenderisation of beef by bromelain. The determination coefficient R2 was 99.97% meaning that the experimental data were acceptable. It was found that beef could be optimize tenderised 89.907% at the optimum condition at pH of beef of 5.4, immersion temperature of60℃, bromelain solution concentration of 0.1682% and immersion time of 10 minutes. The verification value of beef ten-derisation at the feasible optimum condition which was determined by experiment was 89.571%. Since the difference between the veri- fication and predicted values was less than 5%, therefore, the optimum condition for the tenderisation of beef predicted by MINITAB software Version 15 could be accepted.

Optimization of medium components using response surface methodology (RSM) for mycelium biomass and exopolysaccharide production by <i>Lentinus squarrosulus</i>

The interaction between sucrose, yeast extract and initial pH was investigated to optimize critical medium components for mycelium biomass and production of exopolysaccharide (EPS) of Lentinus squarrosulus using Response Surface Methodology (RSM). A central composite design (CCD) was applied and a polynomial regression model with quadratic term was used to analyse the experimental data using analysis of variance (ANOVA). ANOVA analysis showed that the model was very significant (p Lentinus squarrosulus are as follows: sucrose concentration 114.61 g/L, yeast extract 1.62 g/L and initial pH of 5.81;sucrose concentration 115.8 g/L, yeast extract of 3.39 g/L and initial pH of 6.44 respectively.

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.

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 substrate for the adsorption of aqueous Cr(Ⅲ). Aqueous Cr(Ⅲ) adsorption onto MFA was examined as a function of MFA dosage, p H and initial Cr(Ⅲ) concentration with the Box–Behnken approach used for experimental design and optimization using response surface methodology(RSM). p H 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 efficiency of 98% was obtained using optimized conditions of MFA dosage, p H and initial Cr(Ⅲ) concentration of 1.57 g·L^(-1), 4.11 and 126 mg·L^(-1), respectively. Cr(Ⅲ) adsorption onto MFA is mainly attributed to the interaction between Cr(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.

Removal of Fluoride from Water Using Mesoporous MCM-41: An Optimization Approach Using Response Surface Methodology (RSM)

Fluoride above 1.5 mg·L-1 is injurious to health. Removal of fluoride from water using mesoporous MCM-41 as a strong adsorbent material has been attempted. Characterization using transmission electron microscopic study of calcined MCM-41 showed the regular hexagonal array of mesoporous channels with an average size of 20 nm and the surface area (BET study) of 1306.96 m2·g-1. The average pore size of the particles was found to be 14.21 nm. A study on the effect of contact time on the removal of fluoride revealed that more than 85% uptake of fluoride onto MCM-41 was achieved at a contact time of 120 min. From the Langmuir adsorption study, the maximum sorption capacity of fluoride was found to be 63.05 mg/g at 301 K. From the thermodynamic study, the +ΔHo value of 2.29 kJ·mol-1 indicated the endothermic nature of the removal process. Application of Response Surface Model suggested that 77.88% of fluoride removal can be achieved at fluoride concentration of 10 mg·L-1, pH (6.3), and contact time of 120 min.

Optimization of Multigrain Premix for High Protein and Dietary Fibre Biscuits Using Response Surface Methodology (RSM)

In order to improve the nutritional quality of biscuits, a multigrain premix (MGP) was developed by using whole barley, sorghum, chickpea, pea and defatted soya flour, each at 20% level. The developed MGP had 26.28% protein, 10.13% insoluble dietary fiber and 7.38% soluble dietary fiber. The experiment was designed to optimise the MGP and wheat flour concentration for the development of multigrain biscuits with high protein, dietary fibre and to maximize the acceptability by the application of central composite rotatable design (CCRD) of Response Surface Methodology (RSM). The levels of incorporation of MGP and wheat flour were taken as variables whereas protein, soluble, insoluble fibers, biscuit dough hardness, breaking strength and overall acceptability (OAA) as responses. The optimum level of MGP and wheat flour obtained using numerical optimization was found to be 40 g and 60 g respectively. The biscuits prepared using these had 16.61% protein, 2.57% soluble fibre, and 6.67% insoluble fibre which is significantly (p ≤ 0.05) higher than control biscuit.

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).

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.

Application of dielectric barrier discharge(DBD) plasma packed with glass and ceramic pellets for SO_2 removal at ambient temperature: optimization and modeling using response surface methodology

Air pollution is a major health problem in developing countries and has adverse effects on human health and the environment. Non-thermal plasma is an effective air pollution treatment technology. In this research, the performance of a dielectric barrier discharge(DBD) plasma reactor packed with glass and ceramic pellets was evaluated in the removal of SO_2 as a major air pollutant from air in ambient temperature. The response surface methodology was used to evaluate the effect of three key parameters(concentration of gas, gas flow rate, and voltage) as well as their simultaneous effects and interactions on the SO2 removal process. Reduced cubic models were derived to predict the SO_2 removal efficiency(RE) and energy yield(EY). Analysis of variance results showed that the packed-bed reactors(PBRs) studied were more energy efficient and had a high SO2 RE which was at least four times more than that of the non-packed reactor. Moreover, the results showed that the performance of ceramic pellets was better than that of glass pellets in PBRs. This may be due to the porous surface of ceramic pellets which allows the formation of microdischarges in the fine cavities of a porous surface when placed in a plasma discharge zone. The maximum SO_2 RE and EY were obtained at 94% and 0.81 g kWh^(-1),respectively under the optimal conditions of a concentration of gas of 750 ppm, a gas flow rate of 2lmin^(-1), and a voltage of 18 kV, which were achieved by the DBD plasma packed with ceramic pellets. Finally, the results of the model's predictions and the experiments showed good agreement.

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.

Interaction of temperature and salinity on the expression of immunity factors in different tissues of juvenile turbot Scophthalmus maximus based on response surface methodology

Central Composite Design(CCD) and response surface methodology were used in the experiment to examine the combined effect of temperature(16-28℃) and salinity(18-42) on Hsp70 and IgM genes expression levels in turbot(Scophthalmus maximus) liver and kidney.The results showed that the coefficients of determination(R^2=0.965 2 for liver Hsp70,0.972 9 for kidney Hsp70,0.921 for liver IgM and 0.962 1 for kidney IgM) and probability values(P<0.01) were significant for the regression model.The interactive effect between temperature and salinity on liver Hsp70,kidney Hsp70 and liver IgM were not significant(P>0.05),while the interactive effect between temperature and salinity on kidney IgM was significant(P<0.01).The model equation could be used in practice for forecasting Hsp70 and IgM genes expression levels in the liver and kidney of juvenile turbot via applying statistical optimization of the response of interest,at which the maximum liver Hsp70,kidney Hsp70,liver IgM and kidney IgM of1.48,1.49,2.48,and 1.38,respectively,were reached.The present model may be valuable in assessing the feasibility of turbot farming at different geographic locations and,furthermore,could be a useful reference for scientists studying the immunity of turbot.

Regression-Based Artificial Neural Network Methodology in Response Surface Methodology

Response surface methodology (RSM) is an important tool for process parameter optimization, robust design and other quality improvement efforts. When the relationship between influential input variables and output response is very complex, it’s hard to find the real response surface using RSM. In recent years artificial neural network(ANN) has been used in RSM. But the classical ANN does not work well under the constraints of real applications. An algorithm of regression-based ANN(R-ANN) is proposed in this paper, which is a supplement to the classical ANN methodology. It makes network closer to the response surface, so that training time is reduced and robustness is strengthened. The procedure of improving ANN by regressions is described and the comparisons among R-ANN,RSM and classical ANN are computed graphically in three examples. Our research shows that the R-ANN methodology is a good supplement to the RSM and classical ANN methodology, which can yield lower standard error of prediction under conditions that the scope of experiment is rigidly restricted.

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.