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 of Oregano Oil Microspheres by Box-Behnken Response Surface Methodology

[Objectives]To optimize the formulation and preparation of oregano oil microspheres by Box-Behnken response surface methodology.[Methods]Chitosan was used as the carrier material to prepare oregano oil microspheres by emulsion crosslinking method.The encapsulation efficiency,drug loading and ID 50 were used as the evaluation indicators,and the comprehensive score(OD)obtained by"coefficient of variation-AHP comprehensive weighting method"was used as the final evaluation indicator.The formulation design and preparation process were optimized by single factor experiment and Box-Behnken response surface methodology,and the optimal process parameters were determined.[Results]The optimal formulation and preparation process parameters of oregano oil microspheres were as follows:the ratio of oregano oil to chitosan was 2∶1,the emulsifying speed of double emulsion was 200 r/min,the amount of emulsifier in the colostrum was 4%,and the volume of curing agent was 1.0 mL.The average encapsulation efficiency was 45.33%±1.32%,the average drug loading was 30.59%±2.45%,and the median diameter(ID 50)was 52.596μm±0.023%.[Conclusions]The encapsulation efficiency,drug loading and ID 50 of oregano oil chitosan microspheres prepared by emulsion crosslinking method met the requirements.The drug-loaded microsphere not only can be used as a preparation finished product for direct application,but also be used as a product intermediate to lay a foundation for the research and development of subsequent dosage forms.

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.

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 ℃.

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.

Application of response surface methodology and central composite rotatable design for modeling the influence of some operating variables of the lab scale thickener performance

This study discussed the application of response surface methodology(RSM)and central composite rotatable design(CCRD)for modeling and optimization of the influence of some operating variables on the performance of a lab scale thickener for dewatering of tailing in the flotation circuit.Four thickener operating variables,namely feed flowrate,solid percent,flocculant dosage and feedwell height were changed during the tests based on CCRD.The ranges of values of the thickener variables used in the design were a feed flowrate of 9–21 L/min,solid percent of 8%–20%,flocculant dosage of 1.25–4.25 g/t and feedwell height of 16–26 cm.A total of 30 thickening tests were conducted using lab scale thickener on flotation tailing obtained from the Sarcheshmeh copper mine,Iran.The underflow solid percent and bed height were expressed as functions of four operating parameters of thickener.Predicted values were found to be in good agreement with experimental values(R2values of 0.992 and 0.997 for underflow solid percent and bed height,respectively).This study has shown that the RSM and CCRD could effciently be applied for the modeling of thickener for dewatering of flotation tailing.

Modeling the Effects of Tool Shoulder and Probe Profile Geometries on Friction Stirred Aluminum Welds Using Response Surface Methodology

The present paper discusses the modeling of tool geometry effects on the friction stir aluminum welds using response surface methodology. The friction stir welding tools were designed with different shoulder and tool probe geometries based on a design matrix. The matrix for the tool designing was made for three types of tools, based on three types of probes, with three levels each for defining the shoulder surface type and probe profile geometries. Then, the effects of tool shoulder and probe geometries on friction stirred aluminum welds were experimentally investigated with respect to weld strength, weld cross section area, grain size of weld and grain size of thermo-mechanically affected zone. These effects were modeled using multiple and response surface regression analysis. The response surface regression modeling were found to be appropriate for defining the friction stir weldment characteristics.

Response Surface Modeling of Fuel Rich and Fuel Lean Catalytic Combustion of the Stabilized Confined Turbulent Gaseous Diffusion Flames

The Response Surface Methodology (RSM) has been applied to explore the thermal structure of the experimentally studied catalytic combustion of stabilized confined turbulent gaseous diffusion flames. The Pt/γAl2O3 and Pd/γAl2O3 disc burners were situated in the combustion domain and the experiments were performed under both fuel-rich and fuel-lean conditions at a modified equivalence (fuel/air) ratio (ø) of 0.75 and 0.25 respectively. The thermal structure of these catalytic flames developed over the Pt and Pd disc burners were inspected via measuring the mean temperature profiles in the radial direction at different discrete axial locations along the flames. The RSM considers the effect of the two operating parameters explicitly (r), the radial distance from the center line of the flame, and (x), axial distance along the flame over the disc, on the measured temperature of the flames and finds the predicted maximum temperature and the corresponding process variables. Also the RSM has been employed to elucidate such effects in the three and two dimensions and displays the location of the predicted maximum temperature.

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%.

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).

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.

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.

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.

Empirical model for bio-extraction of copper from low grade ore using response surface methodology

The copper extraction in shaking bioreactors was modeled and optimized using response surface methodology（RSM）. Influential parameters in the mesophilic bioleaching process of a low-grade copper ore including p H value, pulp density, and initial concentration of ferrous ions were comprehensively studied. The effect of leaching time on the response（copper extraction） at the 1st, 4th, 9th, 14 th and 22 nd days of treatment was modeled and examined. The central composite design methodology（CCD） was used as the design matrix to predict the optimal level of these parameters. Then, the model equation at the 22 nd day was optimized using the quadratic programming（QP） to maximize the total copper extraction within the studied experimental range. Under the optimal condition（initial p H value of 2.0, pulp density of 1.59%, and initial concentration of ferrous ions of 0 g/L）, the total copper extraction predicted by the model is 85.98% which is significantly close to that obtained from the experiment（84.57%）. The results show that RSM could be useful to predict the maximum copper extraction from a low-grade ore and investigate the effects of variables on the final response. Besides, a couple of statistically significant interactions are derived between p H value and pulp density as well as p H value and initial ferrous ion concentration which are precisely interpreted. However, there is no statistically significant interaction between the initial ferrous ion concentration and the pulp density. Additionally, the response at optimal levels of p H value and pulp density is found to be independent on the level of initial ferrous concentration.

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.

Comparative Study of Response Surface Designs with Errors-in-Variables Model

This paper investigates the scaled prediction variances in the errors-in-variables model and compares the performance with those in classic model of response surface designs for three factors.The ordinary least squares estimators of regression coefficients are derived from a second-order response surface model with errors in variables.Three performance criteria are proposed.The first is the difference between the empirical mean of maximum value of scaled prediction variance with errors and the maximum value of scaled prediction variance without errors.The second is the mean squared deviation from the mean of simulated maximum scaled prediction variance with errors.The last performance measure is the mean squared scaled prediction variance change with and without errors.In the simulations,1 000 random samples were performed following three factors with 20 experimental runs for central composite designs and 15 for Box-Behnken design.The independent variables are coded variables in these designs.Comparative results show that for the low level errors in variables,central composite face-centered design is optimal;otherwise,Box-Behnken design has a relatively better performance.

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.

One-step process for production of biodiesel from Jatropha curcas L. seeds： Optimization using Response Surface Methodology （RSM）

Jatropha curcas L. （JCL） seeds were extracted and transesterified in-situ using supercritical methanol extraction in the absence of catalyst at different temperatures （200-280℃） and pressures （8-12 MPa）, and at a fixed reaction time of 30 min with seeds-to-methanol ratio of 1：40 w/v. Design of experiment approach using five-level-two-factors design of Response Surface Methodology （RSM） was used to observe the effect of two independent variables i.e. temperature and pressure and the percent of biodiesel yield which required 13 runs. For optimization of the variables, Central Composite Rotatable Design （CCRD） was used for regression analysis and analysis of variance （ANOVA）. The optimize conditions suggested by RSM were at T = 280℃ and P = 12.04 MPa. The predicted and experimental biodicsel yields were found to be 56.8% and 59.9%, respectively, with relatively small deviation errors of 1.59%.