Central Composite Design Method Research Articles

Type-1 and type-2 radial basis function neural networks Mandami system to evaluate quality features

This paper presents a methodology that uses the central composite design and the radial basis function neural networks in type-1 or in interval type-2 model to generate a network that evaluates quality features in an industrial image processing. The methodology includes a couple of radial basis functions as Huygen’s tractrix and triangular membership functions as complementary contributions that have not been reported in literature as radial basis functions. The advantage of using this proposal is that the training is not required to get an accurate result, also the generation of the IT2 RBFNN fuzzy rule base for evaluating quality characteristics is simplified by using the central composite design method and statistical indicators extracted from the product specification data. Experimental results show an error reduction of 90% when the interval type-2 Mandami Radial basis function neural network was compared against its type-1 counterpart using the Gaussian membership functions onto a radial basis function network. On the other hand, the implementation of the Huygen’s tractrix, found a reduction error of 50% in comparison to the Gaussian function.

Characterisation of foam bitumen mixes with diffrent RAP content at elevated mixing temperature using design of experiment (DOE) approach

ABSTRACT Cold recycling using foam bitumen is one of the most popular rehabilitation techniques for bituminous pavements. Effect on mixing temperature reclaimed asphalt pavement (RAP) material content and foam binder content on the performance of foam bitumen mix (FBM) has been evaluated in the present study. This paper discusses the statistical approach adopted for FBM design and the development of the model consisting of three factors which are mixing temperature, foam bitumen content, and RAP material content. The experiment was designed according to the 23 factorial design using the central composite design (CCD) method and the desirability approach was adopted for determining the optimum parameter. Dry and wet indirect tensile strength parameters were considered as responses to optimise the input parameters. Results show that with increasing the mixing temperature of FBM, the performance of FBM improves at lesser binder content. The developed quadratic models using the response surface methodology (RSM) optimisation tool have higher determination coefficients for dry IDT and wet IDT indicating a good model fit between the actual and predicted values. A scanning electron microscope analysis was conducted to evaluate the impact of RAP content and mixing temperature on the dispersion of bitumen in the FBM matrix.

Analysis of RSM Based BBD and CCD Techniques Applied for Biodiesel Production from Waste Cotton-Seed Cooking Oil via Ultrasound Method

Biodiesel was produced from the waste cotton-seed cooking oil with methanol in presence of the calcium oxide catalyst by the ultrasound-assisted transesterification method. The ultrasonication approach was used for biodiesel production as it significantly lower reaction time and is highly energy-efficient. This paper-work focused on the optimization of biodiesel production parameters methanol: oil molar ratio (A), CaO amount (B), process temperature (C) using the two different response surface methodology (RSM) such as box-behnken design and central composite design (CCD). Also a comparison of the results of the box-behnken design (BBD) and central composite design (CCD) has been carried out. Quadratic polynomial equations are obtained by investigating the experimental yield of the transesterification process. The impact of process parameters on biodiesel yield is discussed by various plots. It was found that the foremost influential parameter on biodiesel production was the CaO amount based on both BBD and CCD methods. A critical relationship with experimental results in BBD method R2 value is 97.73%, while within the case of the CCD method R2 value is 99.90%. The Optimized process parameters for the CaO catalyst were determined as Methanol: oil molar ratio: 12:1; CaO amount (w/w)%: 1%; reaction temperature: 50°C; and the corresponding yield: 96.45% for BBD and CCD methods, respectively.

Comparison of RSM Based FFD and CCD Methods for Biodiesel Production Using Microwave Technique

This paper deals with the optimization of reaction parameters of production of biodiesel from waste cotton-seed cooking oil (WCCO) via calcium oxide (CaO) catalyzed microwave irradiated transesterification process. The optimization of factors that affects biodiesel yield is done by applying RSM (Response surface methodology). Design-Expert software version 11 was used for optimization purpose. Present study describes the comparison of optimization results of biodiesel yield by applying RSM based Full Factorial Design (FFD) and Central Composite Design (CCD). The effect of methanol to oil ratio (M: O molar ratio) (A), CaO loading (B) and process time (C) on biodiesel yield was studied. It was found that while applying FFD method, the optimized values are 9.6:1, 1.33 (w/w %) and 9.7 min, for A, B and C respectively whereas while applying CCD method, the optimized values are 9.63:1, 1.34 (w/w %) and 9.87 min for A, B and C, respectively. From perturbation plots of FFD and CCD method analyze that the effect of CaO loading is high on the biodiesel yield. The R2 value for FFD and CCD method is 96.28% and 99.83%, respectively. The statistical analysis show that the CCD method was better than FFD method.

Study on Central Composite Design Method to Optimize the Preparation Process of Chrysophanol‐Pluronic F127 Nanomicelles and Pharmacokinetics

Objective. In order to find the best process for the preparation of Chrysophanol‐Pluronic F127 nanomicelles in the laboratory, the preparation of Chrysophanol‐Pluronic F127 nanomicelles was optimized using the central composite design method. In order to investigate the properties of the prepared Chrysophanol‐Pluronic F127 nanomicelles, physicochemical properties were examined and in vitro dissolution experiments were performed, and the pharmacokinetics of Chrysophanol and Chrysophanol‐Pluronic F127 nanomicelles were investigated in rabbits. Methods. In the preexperimental study, the best physical solubilization method and organic solvent for Chrysophanol were selected. The ratio of drug dosage to excipient dosage and the amount of organic solvents were evaluated by single‐factor test. Based on the single‐factor test, the optimal prescription was obtained by screening the formulation and optimizing the preparation process using the central composite design method with the encapsulation efficiency as the index. Chrysophanol‐Pluronic F127 nanomicelles were prepared according to the optimal prescription, and their particle size, potential, appearance, and in vitro release experiments were carried out. Chrysophanol and Chrysophanol‐Pluronic F127 nanomicelles were injected intravenously through the ear margins to rabbits, and the drug concentrations in the blood were measured at different time points by HPLC. The obtained blood concentration data were fitted with PK Solver 2.0 program to obtain pharmacokinetic parameters. Results. In the preexperimental study, ultrasonic method was selected as the physical solubilization method, and acetone was selected as the organic solvent. In single‐factor test, the highest encapsulation efficiency was achieved when the ratio of drug dosage to excipient dosage was 1 : 15; the highest encapsulation efficiency was achieved when the amount of organic solvent (acetone) was 8 mL. The equation fitted to the model for the optimized prescription by the central composite design method is as follows: R1 = −166.93629 + 16.86478A + 32.55582B − 0.169750AB − 0.4826752 − 2.25797B2(R2 = 0.9457). The best prescription for the preparation of Chrysophanol‐Pluronic F127 nanomicelles was obtained in the ratio of drug dosage to excipient dosage of 1 : 16.309 and the dosage of organic solvent was 6.595 mL. The prepared nanomicelles have a particle size of 152.8 nm and a potential of ‐23.9 mV. It was observed by transmission electron microscope that the prepared nanomicelles are uniform and spherical in appearance. The drug metabolism of Chrysophanol and nanomicelles in rabbits conforms to the two‐compartment open model, and both of them show linear kinetics in the drug dose range. T(1/2α) was 0.31 ± 0.21 h and 0.47 ± 0.35 h, and T(1/2β) was 2.06 ± 1.14 h and 7.72 ± 2.04 h for Chrysophanol and Chrysophanol‐Pluronic F127 nanomicelles, respectively. Conclusions. The adopted central composite design method can well optimize the prescription process of Chrysophanol‐Pluronic F127 nanomicelles prepared by dialysis, and the method is simple and easy to be prepared in the laboratory. The prepared nanomicelles have uniform particle size and good zeta potential and appear as uniform black spherical shape under transmission electron microscopy. In vitro release studies showed that the Chrysophanol‐Pluronic F127 nanomicelles released significantly better than Chrysophanol. The results of pharmacokinetics of Chrysophanol and Chrysophanol‐Pluronic F127 nanomicelles in rabbits showed that the Chrysophanol‐Pluronic F127 nanomicelles did not change the metabolic process of the drug in vivo but could stay in vivo for a longer period of time and exert longer effects. It is hoped that this study can provide a laboratory basis for the preparation of Chrysophanol‐Pluronic F127 nanomicelles and a reference for further in vivo studies of Chrysophanol.

Effects of infrared radiation on the mechanical properties of an epoxy-amine adhesive using a Central Composite Design method

Recently, the aerospace industry has been facing many challenges, including an increase in the production rates to meet the market needs. In the context of adhesives and liquid shim applications, this means the possibility of on-demand curing. In other words, adhesives must cure slowly at room temperature and this process must be accelerated at any time to allow for the fastest polymerization possible. However, while on-demand curing is possible in several ways (ultraviolet radiation, induction, or microwave), the route chosen in this study is infrared (IR) radiation. This is because this method allows curing at low temperatures (i.e., around 50°C) and is universal, hence requiring no modification in the adhesive formulation. Given that the acceleration of polymerization using thermal (temperature) and nonthermal (radiation–matter interaction) effects has been demonstrated in another study, it is now important to study the properties of such an adhesive after curing under IR radiation. In this study, we measured the following properties: adherence on aluminum 2024-T3 via three-point bending, tensile strength and modulus, and flexural strength and modulus. We also studied the parameters of the IR lamp, including the lamp–adhesive distance and the rate and temperature of polymerization. For this purpose, a composite design of experiments was used, which generally has two main advantages: screening and response surface methodology. On the one hand, screening allows determining the factors, among those selected, that have a significant influence on the studied responses. At the same time, it allows determining the interactions (synergistic effects) between the influencing parameters. On the other hand, response surface methodology allows quantifying the influence of the parameters and determining the optimal ones.

Simulation‐Based Multiobjective Optimization of Open‐Pit Mine Haulage System: A Modified‐NBI Method and Meta Modeling Approach

A large number of engineering problems involve several conflicting objectives, which today are often solved through expensive simulation calculations. Methods based on meta‐models are one of the approaches to solving this group of problems. In this paper, multiobjective optimization in the extraction system of a copper open‐pit mine complex is presented by the modified‐NBI optimization method and regression meta‐model. For this purpose, two objective functions of maximizing the amount of total extraction, which is the sum of the extraction of sulfide, oxide, low‐grade ores, and waste in this mine, and minimizing the transport time of haulage according to the limitation of its storage capacity, transport equipment, and budget are considered. The Central Composite Design (CCD) method is used to build the Design of Experiments (DOE) for the design variables. The considered design variables are the number of trucks of 120 tons, 240 tons, 35 tons, and 100 tons. The number of targets considered in each design combination is considered the response surface. The suitable meta‐model to maximize the total extraction rate and minimize the transport time of the haulage, two modified functions of nonlinear regression have been determined. The accuracy of the models for selection has been done using PRESS and R2 statistics. The most common PRESS error has also been used to validate the meta‐models. Then the multiobjective optimization problem was solved using the modified‐NBI method. Finally, Pareto and optimal solutions using the proposed approach were presented and discussed.

Modeling of extraction of silica rendemen husk rice (Oryza sativa l.) by microwave extraction assisted (MAE) using response surface methodology (RSM)

Nutrient immobilization technology in plants has been developed to increase the ability of the soil to grow plants. Immobilization is a technique to trap compounds in tablets so that they can be used to retain nutrients in the soil, especially in paddy fields. The purpose of this study was to determine the effect of the use of synthetic fertilizer concentration from rice husk in the manufacture of tablets, as well as to optimize the yield response with the independent variables of KOH concentration and time using Response Surface Methodology (RSM). The result of this research is that the highest organic matter content contained in the material after extraction is 52.54%. Optimization was carried out using Response Surface Methodology (RSM) with the Central Composite Design (CCD) method on Design-Expert software with the independent variables being KOH concentration (2.5%, 5%, 7.5%) and time (5 minutes, 7.5 minutes, 10 minutes while) the response variable is the result. The summary statistics data model suggested by the software is linear where the lowest standard deviation value is 0.6130, the highest R2 value is 0.8469, the highest adjusted R2 value is 0.8341, the highest R2 predicted value is 0.8063, and the PRESS value (the lowest prediction error sum of square) was 11.41. Then the result of the response from the software is 5.033%.

Optimization of electrical process parameters of WEDM on ECAP Al7075 alloys considering Radial Overcut (ROC) as output response

The aim and objective of the present experimental work is to find out the predicted value of Radial overcut (ROC) while processing of Al7075 alloy through Equal Channel Angular Pressing (ECAP) with channel angel 90 degree and edge angle 20 degree with chosen process route C and alongwith suitable back pressure and subsequently machining that ECAP sample by Wire cut electric discharge machining (WEDM). Response Surface Methodology is applied in present study to predict the ROC in WEDM process for previously ECAP Al7075 alloy. Pulse off time (Toff), pulse on time (Ton), peak current (IP) and servo voltage (SV) are taken as input electrical parameters of process to study the ROC. The experiment was designed to perform based on Central Composite Design (CCD) method. After performing 31 experimental runs a mathematical model was being evolved for finding out the correlation and significance of electrical parameters on ROC. The coefficients were obtained by performing analysis through ANOVA at 95% confidence level.Observation shows that Ton and IP has got significant impact on ROC. The forecasted results based on mathematical model generated are found to be in a reasonably good degree of accuracy with the experimental result. Optimum value of radial overcut is obtained experimentally as 26.075 µm against Ton 7 µs, Toff 54 µs, for IP value 100 A and SV 25 V respectively.

Experimental investigation of rheological properties of water-base mud with zinc oxide nanoparticles using response surface methodology

Special and advanced techniques at drilling and production operations are used to drill and produce hydrocarbons from different eccentric reservoirs such as deep-water reservoirs, shale gas, and shale oil necessitates. However, these advanced techniques are considered to be costly and affecting the environment. Therefore, nanotechnology has been implemented in the drilling fluids to improve the rheological properties, hydrogen concentration, and filtration rate. This study is, therefore, aimed at evaluating the properties of zinc oxide nanoparticles and their previous implementation in drilling fluids, examining the rheological properties of water base mud from atmospheric temperature to downhole condition (90 °C). The experiment was designed to investigate the effect of nanoparticles concentration and temperature variation on the rheological properties of water-based mud using response surface methodology. A rotational viscometer was used to measure viscosity, yield point and gel strength. Moreover, a Consistometer was used to heat the fluid sample to different temperatures reaching up to downhole condition (90 °C). It was observed experimentally that addition of zinc oxide nanoparticles impressively improved the rheological properties of water-base mud by 50% for viscosity and gel strength, and 80% for yield point. It also allowed them to maintain their quality at all temperatures. Furthermore, addition of higher concentrations of zinc oxide nanoparticles of more than 1 wt% (6 g) at low temperatures (below 40 °C) gave the highest and most effective results of the rheological properties. • The effects of zinc oxide nanoparticles on rheological properties of water base mud were investigated. • Regression models were developed via Central Composite Design (CCD) method. • Zinc oxide nanoparticles impressively improved viscosity and gel strength by 50% and yield point by 80%. • Addition of more than 1 wt% (6 g) of zinc oxide nanoparticles at low temperatures below 40 °C was found effective. • The developed models' accuracy was affirmed at optimum point.

Optimal Selection of Cutting Parameters for Surface Roughness in Milling Machining of AA6061-T6

Due to its ability to remove material quickly while maintaining optimum surface quality, end milling is considered one of the most frequent metal cutting procedures in industry. The present study aimed to investigate the impacts of cutting parameters and tool geometry on milling of Aluminum Alloy 6061-T6 to examine the impact surface roughness by utilizing response surface methodology (RSM). RSM was used to create a second-order mathematical model of surface roughness for this purpose. A multiple regression analysis used the analysis of variance to demonstrate the effect of machining settings on surface roughness and determine experiment performance. The trials for optimizing surface roughness were set up utilizing the central composite design (CCD) method and various cutting parameters such as spindle speed, feed rate and depth of cut. Also the parameters used in tool geometry are the radial rake angle (10, 13, 16, 19 and 22 degrees), and nose radius (0, 0.2, 0.4, 0.6 and 0.8 mm). The result shows that the nose radius has more significant effect on the surface roughness followed by the radial rake angle. Moreover, the effect of the depth of cut on surface roughness is more dominant than cutting speed. The optimum combinations of cutting and tool geometry parameters were cutting speed (60.53 m/min), feed rate (0.025 mm/tooth), depth of cut (0.84 mm), radial rake angle (12.72 degree) and nose radius (0.34 mm).

H2O2/UV catalytic degradation of furacilin by Fe-Ni oxyhydroxides synthesized via coprecipitation

The article considers the structural and photocatalytic properties of nickel–iron double oxyhydroxide synthesized by co-precipitation. X-ray phase analysis of the powder and scanning electron microscopy showed that the NiOOH-FeOOH nanostructures have a crystalline structure and a scaly-layered structure.UV spectroscopy confirmed the photocatalytic activity of nanostructures in the degradation of furacilin under the action of UV light. The process of photocatalytic decomposition of furacilin in the presence of a synthesized photocatalyst is considered. The statistical model was developed using central composite rotatable design method. The calculated values of the degree of degradation of furacilin are confirmed by experimental results. The optimal process parameters were also determined, namely the concentration of the photocatalyst, hydrogen peroxide and processing time.

Microwave assisted biodiesel production: Assessment of optimization via RSM techniques

This paper is targeted on the assessment of response surface methodology (RSM) based optimization techniques for biodiesel synthesis from waste cooking oil/used cooking oil via CaO catalyzed microwave irradiated process. The biodiesel yield was optimized using following parameters: MeOH: Oil molar ratio (A), CaO amount (w/w %) (B), reaction interval (C). These parameters have an effect on the biodiesel yield which is analyze by various statistical plots. By employing Full Factorial Design (FFD), Box-Behnken Design (BBD) and Central Composite Design (CCD) method, the determined optimum results for A is 9.6:1, 9.33:1, and 9.63:1, for B(w/w %) is 1.33, 1.37 and 1.34, for C (min) is 9.7, 9.28 and 9.87, respectively. Based on Analysis of variance (ANOVA) analysis and analysis of statistical plots, BBD and CCD approach is best fitted to the model and may select over FFD approach.

Prediction of optimal ranges of mix ratio of self-compacting mortars (SCMs) based on response surface method (RSM)

The influences of constituents on the rheological and mechanical properties of self-compacting mortars and efficient mix proportion optimization are two key issues in the design of self-compacting mortars (SCMs). Due to the lack of specifications of the mix design, a wider range of variable optimization can provide great feasibility to meet wider requirements of rheological and hardening properties of SCMs. In this study, response surface methodology (RSM) was adopted to systematically investigate on the independent and interactive effects of fly ash (FA), silica fume (SF), sand-binder ratio (s/b) and water-binder ratio (w/b) on the rheological and mechanical properties of SCMs. A total of 30 SCMs mixes were formulated by using the Central Composite Design (CCD) method to determine the contents of the four variables at 5 levels, e.g., FA range from 0 to 30%, SF ranged from 0 to 16%, sand-binder ratio varied from 1.0 to 1.4 and water-binder ratio from 0.34 to 0.38. The results showed that these four variables and their partial interactions have significant influences on the rheological and mechanical properties of SCMs, especially SF and sand-to-binder ratio. The prediction of the optimal range of variables in multi-response optimization was developed and validated. The result showed that the contents of FA, SF, s/b, w/b ranging in 10–20%, 6–10%, 1.1–1.2, 0.35–0.36 respectively leaded a better workability and greater compressive strength of SCMs.

Artificial neural network and response surface methodology modeling for diclofenac removal by quaternized mesoporous silica SBA-15 in aqueous solutions

Diclofenac (DCF) is a non-steroidal, anti-inflammatory drug commonly prescribed for humans and animals. DCF has been widely detected in aquatic environments and wastewater, and so various adsorbents have been applied for DCF removal from aqueous solutions. Here, we explored DCF removal by quaternary ammonium-functionalized mesoporous silica SBA-15 (q-SBA-15) in aqueous solutions using artificial neural network (ANN) and response surface methodology (RSM) modeling. For this purpose, SBA-15 was synthesized and quaternized with dimethyloctyl[3-(trimethoxysilyl)propyl] ammonium chloride to obtain q-SBA-15. The physicochemical characteristics of q-SBA-15 were examined using various instruments including field emission scanning electron microscopy, transmission electron microscopy, elemental analysis, nitrogen gas adsorption-desorption analysis, nuclear magnetic resonance spectroscopy, X-ray diffractometry, Fourier-transform infrared spectrometry (FTIR), and X-ray photoelectron spectrometry (XPS). N2 adsorption-desorption analysis indicated that q-SBA-15 had a BET surface area of 125.1 m2/g, an average pore diameter of 3.86 nm, and a mesopore volume of 0.121 cm3/g. In the FTIR spectra, several new peaks appeared after DCF removal, confirming DCF adsorption onto the surface of q-SBA-15. The XPS spectra illustrated that DCF was adsorbed onto N+ surface sites on the quaternary ammonium moiety of q-SBA-15 through anion exchange between anionic DCF− and chloride ion. Single-parameter experiments were conducted in terms of initial pH, adsorbent dosage, reaction time, and initial DCF concentration. DCF removal rate decreased gradually in the initial pH of 6.0–10.0. DCF removal reached equilibrium at 12 h with the maximum removal capacity of 593 mg/g. Multi-parameter experiments were designed using the central composite design method with four input parameters and two output parameters (DCF removal rate and final pH). Fifty-six experiments (28 experimental conditions in duplicate) were conducted to examine the simultaneous effects of the input parameters on the output parameters. Based on the experimental data, RSM and ANN models were developed to predict the DCF removal rate and final pH. The additional experimental data (4 experimental conditions in duplicate) demonstrated that the developed ANN model had better predictability than the RSM model for the output parameters.

Production enhancement of the glycopeptide antibiotic A40926 by an engineered Nonomuraea gerenzanensis strain

To improve the production of A40926, a combined strategy of constructing the engineered strain and optimizing the medium was implemented. The engineered strain lcu1 with the genetic features of dbv23 deletion and dbv3-dbv20 coexpression increased by 30.6% in the production of A40926, compared to the original strain. In addition, a combined medium called M9 was designed to be further optimized by the central composite design method. The optimized M9 medium was verified to significantly improve the A40926 yield from 257 to 332mgl-1. The engineered strain lcu1 could significantly promote A40926 production in the optimized M9 medium, which indicated that the polygenic genetic manipulation and the media optimization played an equally important role in increasing the A40926 yield.

Development of a needle trap device packed with the Schiff base network-1/single-walled carbon nanotube for sampling phenolic compounds in air

This paper introduced needle traps filled with the new Schiff base network-1/single-walled carbon nanotube (SNW-1/SWCNT) adsorbent for sampling and analyzing phenolic compounds (phenol, 3-chlorophenol, o-cresol, and p-cresol) in air. In this perusal, the SNW-1/SWCNT adsorbent was synthesized and packaged using a 22-gauge spinal needle. This approach was first examined inside the laboratory and then applied in the field for real sampling. A 3-inlet container was placed on a heater at a specific temperature to produce different concentrations of phenolic compounds. The response surface methodology and central composite design methods were used to evaluate the desorption and breakthrough volume parameters of needle trap device packed with SNW-1/SWCNT. The Limit of detection and limit of quantitation values of this technique were 0.002–0.011 ng/ml and 0.008–0.037 ng/ml, respectively, indicating that the proposed sampler had very high sensitivity. The maximum response of the peak area was obtained at the extraction temperature of 270 °C and the extractions time of 5 min. The current technique was compared to the NIOSH-2546 method, and an R2 of 0.9812 was obtained between the two methods. The proposed method was used to determine the concentration of target compounds in the air of a plastic factory. The results showed that the concentration was less than the threshold limit values for phenolic compounds. SNW-1/SWCNTs have selectivity and the proposed method is a one-step procedure for analyzing phenolic compounds from the air.

Multi-objective optimization of a composite orthotropic bridge with RSM and NSGA-II algorithm

To address the problems of pavement damage and fatigue cracking of orthotropic steel deck (OSD) in bridges with traditional asphalt overlay, an innovative composite bridge deck composed of OSD with open ribs and ultra-high performance concrete (UHPC) layer was proposed. This paper firstly investigates the stress responses of fatigue-prone details in the composite bridge deck by refined two-scale finite element analysis. The results show that the rib-to-deck joint can achieve an infinite fatigue life, while the floorbeam detail of rib-to-floorbeam joint indicates finite fatigue life. Then, approximate regression models of stress ranges of fatigue details and structure weight were derived via both the central composite design and response surface method. The analysis of correlation and variance demonstrates that the response surface models are significant and sufficiently accurate to predict the objective responses. And 3-D response surface plots were developed to display the interaction effect between each pair of structural parameters on objective responses. Finally, to improve the fatigue performance for achieving an infinite fatigue life under relatively low structure weight, the multi-objective optimization was executed by an Improved Non-dominated Sorting Genetic Algorithm (NSGA-II). The obtained Pareto front shows that there is a strong competition between the stress range of fatigue-prone detail and structure weight. Under the principle of relatively low structure weight, the obtained structural parameters satisfying infinite fatigue life imply that the deck plate thickness is 10 mm, and the floorbeam spacing is 2.4 m as well as the floorbeam thickness is not less than 12 mm.

Optimization of Trans-esterification Process and Characterization of Biodiesel from Soapstock Using Silica Sulfuric Acid as a Heterogeneous Solid Acid Catalyst

The main objective of this study was production, optimization, and fuel quality characterization of biodiesel from equal weight ratio blended acid oil of cottonseed and sunflower soapstock using silica sulfuric acid as a solid acid catalyst in laboratory scale. The physicochemical properties of soap stock samples and extracted acid oil from each soap stock were determined. The experiment was designed by design expert (version 11) software. The 5-level 4-factors (methanol to acid oil molar ratio, catalyst weight, stirring rate, and reaction time) were designed using the central composite design method. From the experimental results, the maximum biodiesel yield of 90.68% was obtained using methanol to acid oil molar ratio of 7:1 using catalyst 5.5(%wt/wt) with a stirring rate of 300rpm at 3hr reaction time. The average value of triplicate experiment of biodiesel yield from the experimentation at optimized condition was 92.62%. The analysis of variance results indicated that satisfactory results were achieved. The carried out physiochemical properties of produced biodiesel were within a range and some were closest to American and European biodiesel standards.

Instructions for the preparation of a numerical investigation on crack parameters of cantilever beam using FEA

Purpose: The operation of engineering structures may cause various type of damages like cracks, alterations. Such kind of defects can lead to change in vibration characteristics of cantilever beam. The superposition of frequency causes resonance leading to amplitude built up and failure of beam. The current research investigates the effect of crack dimensional parameters on vibrational characteristics of cantilever beam. Design/methodology/approach: The CAD design and FE simulation studies are conducted in ANSYS 20 simulation package. The natural frequencies, mode shapes and response surface plots are generated, and comparative studies are performed. The effect of crack dimensional parameters is then investigated using Taguchi Design of Experiments. The statistical method of central composite design (CCD) scheme in Response Surface Optimization is used to generated various design points based on variation of crack width and crack depth. Findings: The research findings have shown that crack depth or crack height have significant effect on magnitude of deformation and natural frequency. The deformation is minimum at 0.009 m crack height and reaches maximum value at 0.011 m crack height. Research limitations/implications: The crack induced in the cantilever beam needs to be repaired properly in order to avoid crack propagation due to resonance. The present study enabled to determine frequencies of external excitation which should be avoided. The limitation of current research is the type of crack studied which is transverse type. The effect of longitudinal cracks on vibration characteristics is not investigated. Practical implications: The study on mass participation factor has shown maximum value for torsional frequency which signifies that any external excitation along this direction should be avoided which could cause resonance and lead to amplitude build up. Originality/value: The beams are used in bridge girders and other civil structures which are continuously exposed to moist climate. The moisture present in the air causes corrosion which initiates crack. This crack propagates and alters the natural frequency of beam.