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 and Characterization of Cellulose Extraction from Grevillea robusta (Silky Oak) Leaves by Soda-Anthraquinone Pulping Using Response Surface Methodology

Response surface methodology (RSM) using the central composite design (CCD) was applied to examine the impact of soda-anthraquinone pulping conditions on Grevillea robusta fall leaves. The pulping factors studied were: NaOH charge 5% to 20% w/v, pulping time 30 to 180 minutes, and the anthraquinone charge 0.1 to 0.5% w/w based on the oven-dried leaves. The responses evaluated were the pulp yield, cellulose content, and the degree of delignification. Various regression models were used to evaluate the effects of varying the pulping conditions. The optimum conditions attained were;NaOH charge of 14.63%, 0.1% anthraquinone, and a pulping period of 154 minutes, corresponding to 20.68% pulp yield, 80.56% cellulose content, and 70.34% lignin removal. Analysis of variance (ANOVA), was used to determine the most important variables that improve the extraction process of cellulose. The experiment outcomes matched those predicted by the model (Predicted R2 = 0.9980, Adjusted R2 = 0.9994), demonstrating the adequacy of the model used. FTIR analysis confirmed the elimination of the non-cellulosic fiber constituents. The lignin and hemicellulose-related bands (around 1514 cm−1, 1604 cm−1, 1239 cm−1, and 1734 cm−1) decreased with chemical treatment, indicating effective cellulose extraction by the soda-anthraquinone method. Similar results were obtained by XRD, SEM and thermogravimetric analysis of the extracted cellulose. Therefore, Grevillea robusta fall leaves are suitable renewable, cost-effective, and environmentally friendly non-wood biomass for cellulose extraction.

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.

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.

Optimization of Extraction Process of Clerodendrum philippinum Schauer var. simplex Mlodenke Total Flavonoids(CPTF) by Central Composite Design-Response Surface Methodology

[Objectives] The research aimed to optimize extraction process of Clerodendrum philippinum Schauer var. simplex Mlodenke total flavonoids( CPTF),and provide reference for its development and utilization. [Methods] Based on single-factor test,ethanol concentration,extraction temperature and extraction time were taken as independent variables,and total flavonoids yield was taken as dependent variable. The test was conducted according to central composite design principle. Multivariate linear regression and binomial equation fitting of the result were conducted,and extraction process of CPTF was optimized by using response surface methodology. [Results]The optimal extraction process of CPTF was as below: ethanol concentration 54. 76%,extraction temperature 83. 92℃,extraction time 102. 64 min,solid-liquid ratio 1:20,extraction for twice. [Conclusions] The extraction process of CPTF by central composite design-response surface methodology was simple and feasible,with reliable prediction result,which was suitable for industrial production.

Optimization of Extraction Process of Total Flavonoids from Akebia trifoliata (Thunb.) Koidz. by Central Composite Design-Response Surface Methodology

[Objectives]To optimize extraction process of total flavonoids from Akebia trifoliata( Thunb.) Koidz.,so as to provide references for development and use of Akebia trifoliata( Thunb.) Koidz. [Methods]The extraction rate of total flavonoids of Akebia trifoliata( Thunb.)Koidz. was taken as observation indicator. On the basis of single factor experiment,central composite design( CCD) was used to evaluate the effects of the extraction temperature,extraction time,and ethanol concentration on the extraction process. Multiple linear regression and binomial fitting were used,and response surface methodology( RSM) was used to select the optimum extraction process. [Results] The optimum extraction process conditions for total flavonoids of Akebia trifoliata( Thunb.) Koidz. was extraction temperature: 83. 92 ℃; extraction time:96. 47 min; ethanol concentration: 63. 92%; extraction times: two times; solid to liquid ratio: 1 ∶ 20; extraction rate of total flavonoids:4. 55%. [Conclusions] The central composite design-response surface methodology( CCD-RSM) is simple,convenient,and feasible for extraction of total flavonoids from Akebia trifoliata( Thunb.) Koidz.,and the prediction results are reliable.

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 process parameters for in situ casting of Al/TiB_2 composites through response surface methodology

The mathematical models were developed to predict the ultimate tensile strength （UTS） and hardness of Al/TiB2 MMCs fabricated by in situ reaction process. The process parameters include temperature, reaction time and mass fraction of TiB2. The in-situ casting was carried out based on three-factor five-level central composite rotatable design using response surface methodology （RSM）. The validation of the model was carried out using ANOVA. The mathematical models developed for the mechanical properties were predicted at 95% confidence limit.

Optimization of Mortar Compressive Strength Prepared with Waste Glass Aggregate and Coir Fiber Addition Using Response Surface Methodology

Waste Glass(WGs)and Coir Fiber(CF)are not widely utilized,even though their silica and cellulose content can be used to create construction materials.This study aimed to optimize mortar compressive strength using Response Surface Methodology(RSM).The Central Composite Design(CCD)was applied to determine the optimization of WGs and CF addition to the mortar compressive strength.Compressive strength and microstructure testing with Scanning Electron Microscope(SEM),Fourier-transform Infrared Spectroscopy(FT-IR),and X-Ray Diffraction(XRD)were conducted to specify the mechanical ability and bonding between the matrix,CF,and WGs.The results showed that the chemical treatment of CF produced 49.15%cellulose,with an average particle size of 1521μm.The regression of a second-order polynomial model yielded an optimum composition consisting of 12.776%WGs and 2.344%CF with a predicted compressive strength of 19.1023 MPa.C-S-H gels were identified in the mortars due to the dissolving of SiO_(2) in WGs and cement.The silica from WGs increased the C-S-H phase.CF plays a role in preventing,bridging,and branching micro-cracks before reaching maximum stress.WGs aggregates and chemically treated CF are suitable to be composited in mortar to increase compressive strength.

Production of mahogany sawdust reinforced LDPE wood–plastic composites using statistical response surface methodology

We produced wood–plastic composite board by using sawmill wastage of mahogany（Swietenia macrophylla） wood and low density polyethylene.We used multi-response optimization to optimize the process parameters of composite board production including mixing ratio,fire retardant（%） and pressing time（min）.We investigated the effects of these three process parameters in the mechanical and physical properties of the composite board.Afterwards,Box–Behnken design was performed as response surface methodology with desirability functions to attain the optimal level of mixing ratio,fire retardant and pressing time（min）.The maximum modulus of elasticity（MOE） and modulus of rupture（MOR） were achieved at the optimal conditions of wood plastic mixing ratio of60：40,pressing time of 9 min and zero fire retardant percentage.The optimized MOR and MOE were 13.12 and1,781.0 N mm-2,respectively.

Response Surface Methodology-Based SERS for Determination of Gymnodimine

Gymnodimine (GYM), a fast-acting marine toxin, is destructive to aquaculture and human health through contaminated shellfish. The current detection methods in GYM have definite drawbacks in operation, such as the demand for delicate instruments and the consumption of time. Therefore, silver colloid was utilized as a surface-enhanced Raman scattering (SERS) desirable substrate for sensitive and rapid detection of GYM in lake and shellfish samples. The theoretical spectrum of GYM is calculated by density functional theory (DFT), and the substrate performance is evaluated by a rhodamine 6 G probe. Under the optimal SERS experimental condition calculated by the response surface methodology, the low limit of detection of 0.105 μM with R2 of 0.9873 and a broad linearity range of 0.1 - 10 μM was achieved for GYM detection. In addition, the substrate was satisfyingly applied to detect gymnodimine in the lake and shellfish matrix samples with LOD as low as 0.148 μM and 0.170 μM, respectively. These results demonstrated a promising SERS platform for detecting marine toxins in seafood for food safety and pharmaceutical research.

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.

Optimization of Stirring Parameters for Stir-Cast Magnesium Matrix Composites Using Response Surface Methodology

The response surface methodology is used to study the effect of stirring parameters on the mechanical properties of magnesium matrix composites(MMCs).The composites are manufactured using different stirring speeds(500,600,and 700 r/min),stirring time(10,20,and 30 min),and weight fractions(0,2.5%,5%,and10%)of silicon carbide particles.The experimental results show that 700 r/min and 20 min are the best conditions for obtaining the best mechanical properties.Based on the desirability function methodology,the optimum parameter values for the best mechanical characteristics of produced composites are reached at 696.102 r/min,19.889 min,and9.961%(in weight).

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.

Extraction Process Optimization of Total Flavonoids from Mallotus apelta Stems by Central Composite Design/Response Surface Method

[Objectives] To optimize the extraction process of total flavonoids in stems of Mallotus apelta. [Methods]On the basis of singlefactor test,with volume fraction of ethanol,extraction time and ratio of solvent as independent variables,the content of total flavonoids as dependent variables,the completely secondary response surface regression fitting was conducted on the independent and dependent variables,and the Response Surface Method was used to optimize the optimum extraction process of total flavonoids in Mallotus apelta stems and predict the optimum process. [Results] The optimum extraction process of total flavonoids in Mallotus apelta was determined as follows: ethanol concentration of 71. 5%; extraction time of 154. 6 min; solid-liquid ratio of 1∶19. 2; total flavonoids content of 7. 060 mg/g; fitted binomial squared correlation coefficient R^2= 0. 8751.[Conclusions]Composite Design/Response Surface Method could be used in the extraction process optimization of total flavonoids in Mallotus apelta stems,the mathematical model established had high prediction accuracy,the method was simple and operability was good.

Device Robust-Design by Using Response Surface Methodology

Device robust-design is inherently a multiple-objective optimization problem.Using design of experiments (DoE) combined with response surface methodology (RSM) can satisfy the great incentive to reduce the number of technology CAD(TCAD) simulations that need to be performed.However,the errors of RSM models might be large enough to diminish the validity of the results for some nonlinear problems.To find the feasible design space,a new method with objectives-oriented design in generations that takes the errors of RSM model into account is presented.After the augment design of experiments in promising space according to the results of RSM model in current generation,the feasible space will be emerging as the model errors deceasing.The results on FIBMOS examples show that the methodology is efficient.

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.

Optimal design of butterfly-shaped linear ultrasonic motor using finite element method and response surface methodology

A new method for optimizing a butterfly-shaped linear ultrasonic motor was proposed to maximize its mechanical output. The finite element analysis technology and response surface methodology were combined together to realize the optimal design of the butterfly-shaped linear ultrasonic motor. First, the operation principle of the motor was introduced. Second, the finite element parameterized model of the stator of the motor was built using ANSYS parametric design language and some structure parameters of the stator were selected as design variables. Third, the sample points were selected in design variable space using latin hypercube Design. Through modal analysis and harmonic response analysis of the stator based on these sample points, the target responses were obtained. These sample points and response values were combined together to build a response surface model. Finally, the simplex method was used to find the optimal solution. The experimental results showed that many aspects of the design requirements of the butterfly-shaped linear ultrasonic motor have been fulfilled. The prototype motor fabricated based on the optimal design result exhibited considerably high dynamic performance, such as no-load speed of 873 ram/s, maximal thrust of 27.5 N, maximal efficiency of 43%, and thrust-weight ratio of 45.8.

Formulation optimization of scutellarin-loaded HP-β-CD/chitosan nanoparticles using response surface methodology with Box–Behnken design

The aim of this paper is to investigate and optimize the preparation of scutellarin(SCU)-loaded HP-β-CD/chitosan(CS) nanoparticles(CD/CS-SCU-NPs). CD/CS-SCU-NPs were prepared by ionic cross-linking method and the process and formulation variables were optimized using response surface methodology(RSM) with a three-level, three factor Box–Behnken design(BBD).The independent variables were the added amounts of CS, sodium tripolyphosphate(TPP)and Pluronic F-68 during the preparation. Dependent variables(responses) were particle size and entrapment efficiency. Mathematical equations and respond surface plots were used to correlate independent and dependent variables.The preparation process and formulation variables were optimized to achieve minimum particle size and maximum entrapment efficiency by calculating the overall desirability value(OD). The optimized NP formulation was characterized for particle size, PDI, zeta potential, entrapment efficiency and in vitro drug release.According to the results, an optimized CD/CS-SCU-NP formulation was prepared. Results for particle size, PDI, zeta potential and entrapment efficiency were found to be around 200 nm,0.5, 25 mV, and 70% respectively. For in vitro study, the release of SCU from the NPs exhibited a biphasic release and was in accordance with Higuchi equation. The optimized preparation was simple with the probability for industrialization. The combination use of RSM, BBD and overall desirability values could provide a promising application for incorporating CD into CS nanoparticles as drug delivery carrier and help develop lab-scale procedures.

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.