A Mixed-Variable Experimental Design Method

Mixed-variable problems are inevitable in engineering. However, few researches pay attention to discrete variables. This paper proposed a mixed-variable experimental design method (ODCD): first, the design variables were divided into discrete variables and continuous variables;then, the DVD method was employed for handling discrete variables, the LHD method was applied for continuous variables, and finally, a Columnwise-Pairwise Algorithm was used for the overall optimization of the design matrix. Experimental results demonstrated that the ODCD method outperforms in terms of the sample space coverage performance.

Designing an Experimental Device for Swinging Excitation Spray Cooling

In this paper,we introduce the design principle of the oscillating excited spray cooling experimental device.We then designed an oscillating excited spray cooling experimental device.By using the device,the swaying motion can be realized through the control system,and the motion of the droplet under different vibration frequencies can be observed.By measuring the liquid flow rate and pressure,the changes in liquid flow rate,pressure,and temperature with time under different vibration frequencies were studied.The trajectory of the droplet and the temperature distribution of the droplet under different vibration frequencies could be observed.The device has a simple structure,is easy to control,and can achieve continuous observation of the spray cooling process.

Optimization of Center of Gravity Position and Anti-Wave Plate Angle of Amphibious Unmanned Vehicle Based on Orthogonal Experimental Method

When the amphibious vehicle navigates in water,the angle of the anti-wave plate and the position of the center of gravity greatly influence the navigation characteristics.In the relevant research on reducing the navigation resistance of amphibious vehicles by adjusting the angle of the anti-wave plate,there is a lack of scientific selection of parameters and reasonable research of simulation results by using mathematical methods,and the influence of the center of gravity position on navigation characteristics is not considered at the same time.To study the influence of the combinations of the angle of the anti-wave plate and the position of the center of gravity on the resistance reduction characteristics,a numerical calculation model of the amphibious unmanned vehicle was established by using the theory of computational fluid dynamics,and the experimental data verified the correctness of the numerical model.Based on this numerical model,the navigation characteristics of the amphibious unmanned vehicle were studied when the center of gravity was located at different positions,and the orthogonal experimental design method was used to optimize the parameters of the angle of the anti-wave plate and the position of the center of gravity.The results show that through the parameter optimization analysis based on the orthogonal experimental method,the combination of the optimal angle of the anti-wave plate and the position of the center of gravity is obtained.And the numerical simulation result of resistance is consistent with the predicted optimal solution.Compared with the maximum navigational resistance,the parameter optimization reduces the navigational resistance of the amphibious unmanned vehicle by 24%.

A Spider Monkey Optimization Algorithm Combining Opposition-Based Learning and Orthogonal Experimental Design

As a new bionic algorithm,Spider Monkey Optimization(SMO)has been widely used in various complex optimization problems in recent years.However,the new space exploration power of SMO is limited and the diversity of the population in SMO is not abundant.Thus,this paper focuses on how to reconstruct SMO to improve its performance,and a novel spider monkey optimization algorithm with opposition-based learning and orthogonal experimental design(SMO^(3))is developed.A position updatingmethod based on the historical optimal domain and particle swarmfor Local Leader Phase(LLP)andGlobal Leader Phase(GLP)is presented to improve the diversity of the population of SMO.Moreover,an opposition-based learning strategy based on self-extremum is proposed to avoid suffering from premature convergence and getting stuck at locally optimal values.Also,a local worst individual elimination method based on orthogonal experimental design is used for helping the SMO algorithm eliminate the poor individuals in time.Furthermore,an extended SMO^(3)named CSMO^(3)is investigated to deal with constrained optimization problems.The proposed algorithm is applied to both unconstrained and constrained functions which include the CEC2006 benchmark set and three engineering problems.Experimental results show that the performance of the proposed algorithm is better than three well-known SMO algorithms and other evolutionary algorithms in unconstrained and constrained problems.

Factorial Experimental Design to Study the Effects of Layers and Fiber Content on Concrete Flexural Behavior

Experimentation has come a long in helping researchers achieve breakthroughs in their different scientific areas and engineering happens to be one of those areas with the most impact from experimental advancement. The need for valid experimental results free from biases and confounding conclusions has prompted the development of new experimental techniques that takes consideration of all applicable factor and combinations in providing answers on a research topic, and the Factorial Experimental design credited to Sir Ronald Fisher is one technique yielding highly valid results. This paper uses the factorial design of experiments to research the flexural impact of polyvinyl acetate fiber and layered concrete in construction. The experiment considered two levels of fiber contents and two levels of layers, and prepared samples with all combinations of the variable factors. The samples were tested after 7 days from casting for flexural strength and an advance statistical analysis was performed on the flexural responses of the samples using R-program. The results from the analyses revealed the significance of the variables to the flexural strength of the samples, as well as their interactions. The experiment concluded that based on the number of layers and fiber content used for the experiment, casting concrete in layers does have a significant negative effect on the flexural strength of concrete, and the failure pattern of concrete members under flexural load in evidently influenced by the material composition of the concrete, and that it can be evidently influenced by casting the concrete in layers.

The Study of Optimizing Reservoir Model Using Experimental Design in Stochastic Models

In response to the main problems in commonly used model selection methods,a method was proposed to apply the concept of experimental design to the optimization of uncertain reservoir models.Firstly,based on the actual situation of the oil field,the uncertain variables were determined that affect the geological reserves of the model and their possible range of variation,and experimental design was used to determine the modeling plan.Then,multiple geological models were established and reserves were calculated,and multiple regression was performed between uncertain variables and the corresponding geological reserves of the model.Finally,Monte Carlo simulation technology was applied to determine the parameters of the P10,P50,and P90 models for probabilistic reserves,and P10,P50,and P90 models were established.This method is not only more objective and time-saving in the application process,but also can determine the main geological variables that affect geological reserves,providing a new idea for evaluating the uncertainty of geological reserves.

Design and Application of Experimental Teaching in Consumer Behavior Courses

This article mainly elaborates on the design and application of experimental teaching in the teaching of consumer behavior.To study consumer behavior,it is necessary to understand their information collection activities before acquiring goods and services,as well as the evaluation and selection of goods,services,or brands.It is also important to pay attention to how they handle products and activities based on their satisfaction after purchasing products or services.In addition,through inquiry experiments,the learning effects of students can be improved,thereby highlighting the significance of inquiry experiments.

Experimental Design for Computer System Platform Course

The computer system platform course is a comprehensive platform course formed by modifying and optimizing the content of the relevant basic courses of computer major to meet the requirement for basic computer knowledge in digital media technology major.The scope and extent of the course content make its experimental design more challenging.By considering the scope of contents,the difficulty of experiments,and the rationality of intrinsic logic,the experiments covering from operating system to computer network are designed.The relevance and continuity of the experiments are ensured,so as to achieve the goals of promoting students’understanding of key concepts,improving their hands-on ability,cultivating their interest,and guiding their self-learning within the limited class time.

Optimization of mechanical properties using D-optimal factorial design of experiment: Electromagnetic stir casting process of A357-SiC nanocomposite

Electromagnetic stir casting process of A357-Si C nanocomposite was discussed using the D-optimal design of experiment(DODOE) method. As the main objective, nine random experiments obtained by DX-7 software were performed. By this method, A357-Si C nanocomposites with 0.5, 1.0 and 1.5 wt.% Si C were fabricated at three different frequencies(10, 35 and 60 Hz) in the experimental stage. The microstructural evolution was characterized by scanning electron and optical microscopes, and the mechanical properties were investigated using hardness and roomtemperature uniaxial tensile tests. The results showed that the homogeneous distribution of Si C nanoparticles leads to the microstructure evolution from dendritic to non-dendritic form and a reduction of size by 73.9%. Additionally, based on DODOE, F-values of 44.80 and 179.64 were achieved for yield stress(YS) and ultimate tensile strength(UTS), respectively, implying that the model is significant and the variables(Si C fraction and stirring frequency) were appropriately selected. The optimum values of the Si C fraction and stirring frequency were found to be 1.5 wt.% and 60 Hz, respectively. In this case, YS and UTS for A357-Si C nanocomposites were obtained to be 120 and 188 MPa(57.7% and 57.9 % increase compared with those of the as-cast sample), respectively.

Remediation of Heavy Metal (Cd, Cr, Cu, Co, and Ni) Ions from Kaolinite Clay Using Molecular Micelles Chelators and D-Optimum Experimental Design

This study investigated the potential utility of poly (sodium N-undecanoyl-L-leucyl-valinate) (poly-L-SULV), poly (sodium N-undecanoyl-L-leucyl-alanate) (poly-L-SULA), and poly (sodium N-undecanoyl-glycinate) (poly-SUG) molecular micelles (MMs) as chelators for heavy metal (Cd, Cr, Cu, Co, and Ni) ion remediation of kaolinite clay using D-optimum experimental design. D-optimum experimental design was employed to simultaneously investigate the influence of design variables such as the buffer pH, chelator concentration, and centrifuge speed to evaluate the optimum conditions and to reduce the time and cost of metal ion remediation. The partition coefficients of the metal ion concentrations between the kaolinite clay and chelator equilibrium were also evaluated. In addition, the influence of metal ion concentrations on the remediation capability of the chelators was evaluated by conducting remediation studies at four different (10 ppm, 40 ppm, 60 ppm, and 80 ppm) metal ion concentrations. In general, the results of the remediation efficiency and partition coefficients obtained in this study are highly metal ion dependent and also dependent upon the chelator used for the remediation. Specifically, the remediation efficiency of the molecular micelles was found to be comparable to or better than the corresponding remediation efficiency obtained when SDS or EDTA was used for the remediation. However, at optimum conditions, poly-SULV and poly-L-SULA molecular micelle chelators demonstrated superior remediation efficiencies for Cr, with remediation efficiency of 99.9 ± 8.7% and 99.1 ± 0.7%, respectively.

Optimization of rheological parameter for micro-bubble drilling fluids by multiple regression experimental design

In order to optimize plastic viscosity of 18 mPa·s circulating micro-bubble drilling fluid formula,orthogonal and uniform experimental design methods were applied,and the plastic viscosities of 36 and 24 groups of agent were tested,respectively.It is found that these two experimental design methods show drawbacks,that is,the amount of agent is difficult to determine,and the results are not fully optimized.Therefore,multiple regression experimental method was used to design experimental formula.By randomly selecting arbitrary agent with the amount within the recommended range,17 groups of drilling fluid formula were designed,and the plastic viscosity of each experiment formula was measured.Set plastic viscosity as the objective function,through multiple regressions,then quadratic regression model is obtained,whose correlation coefficient meets the requirement.Set target values of plastic viscosity to be 18,20 and 22 mPa·s,respectively,with the trial method,5 drilling fluid formulas are obtained with accuracy of 0.000 3,0.000 1 and 0.000 3.Arbitrarily select target value of each of the two groups under the formula for experimental verification of drilling fluid,then the measurement errors between theoretical and tested plastic viscosity are less than 5%,confirming that regression model can be applied to optimizing the circulating of plastic-foam drilling fluid viscosity.In accordance with the precision of different formulations of drilling fluid for other constraints,the methods result in the optimization of the circulating micro-bubble drilling fluid parameters.

Application of Uniform Experimental Design in Optimizing Excitation Parameters for Magnetic Frequency Mixing Measurements

Excitation parameter preferences are key factors a ecting the performance of magnetic frequency mixing detection.A uniform experimental design method was used to analyze this influence.Using fuzzy theory,a comprehensive model is established for evaluating the e ect of magnetic frequency mixing.A polynomial is selected as the regression function to express explicitly the correlation between the excitation parameters and the frequency-mixing e ect.The excitation parameters were then optimized using genetic algorithm.Magnetic frequency mixing experiments were conducted to measure the surface hardness of some ferromagnetic materials.Frequency mixing is further enhanced under the optimal settings,resulting in an improvement in the measurement sensitivity.The results of this study support the application of the magnetic frequency mixing technique in non-destructive testing.

Application of orthogonal experimental design and Tikhonov regularization method for the identification of parameters in the casting solidification process

The inverse heat conduction method is one of methods to identify the casting simulation parameters. A new inverse method was presented according to the Tikhonov regularization theory. One appropriate regularized functional was established, and the functional was solved by the sensitivity coefficient and Newtonaphson iteration method. Moreover, the orthogonal experimental design was used to estimate the appropriate initial value and variation domain of each variable to decrease the number of iteration and improve the identification accuracy and efficiency. It illustrated a detailed case of AlSiTMg sand mold casting and the temperature measurement experiment was done. The physical properties of sand mold and the interracial heat transfer coefficient were identified at the meantime. The results indicated that the new regularization method was efficient in overcoming the ill-posedness of the inverse heat conduction problem and improving the stability and accuracy of the solutions.

Key design parameters and optimum method of medium- and high-velocity synchronous induction coilgun based on orthogonal experimental design

The energy conversion efficiency of a multistage synchronous induction coilgun(MSSICG) has become one of the key factors that restricts its industrialization. To improve the launch efficiency of medium-and high-velocity MSSICG,we propose an optimization design scheme combining orthogonal experimental design(OED) and self-consistent design method in this paper. The OED is introduced to reduce the number of iterations and improve the identification accuracy and efficiency. A self-consistent design model is established to overcome a defect that the parameters that need to be optimized will multiply as the number of coil stages increases. The influence of six factors(radial thickness of armature, axial length of armature, axial length of coil, capacitance, wire diameter, and slip speed) on the launch efficiency are then evaluated by range analysis. This work presents a valuable reference for optimizing medium-and high-velocity MSSICG.

Oxidative desulfurization of model and real oil samples using Mo supported on hierarchical alumina–silica: Process optimization by Box–Behnken experimental design

The catalytic performance of Mo supported on hierarchical alumina–silica(Si/Al = 15) with Mo loadings of 3, 6 and 15 wt% was investigated for the oxidative desulfurization(ODS) of model and real oil samples. Hierarchical alumina–silica(h Al–Si) was synthesized by economical and ecofriendly silicate-1 seed-induced route using cetyltrimethylammonium bromide(CTAB) as mesoporogen. The effect of CTAB on the structure of catalyst was studied by characterization techniques. The results revealed that 6%Mo/h Al–Si had the highest sulfur removal compared to the other catalyst loadings. The effect of operating parameters was evaluated using Box–Behnken experimental design. The optimal desulfurization conditions with the 6%Mo/h Al–Si catalyst were determined at oxidation temperature of 67 ℃, oxidation time of 42 min, H2O2/S molar ratio of 8 and catalyst dosage of 0.008 g·ml^-1 for achieving a conversion of 95%. Under optimal conditions, different sulfur-containing compounds with initial concentration of 1000 ppm, Dibenzothiophene(DBT), Benzothiophene(BT) and Thiophen(Th), showed the catalytic oxidation reactivity in the order of DBT > BT>Th. According to the regeneration experiments, the 6%Mo/h Al–Si catalyst was reused 4 times with a little reduction in the performance. Also, the total sulfur content of gasoline and diesel after ODS process reached 156.6 and 4592.2 ppm, respectively.

Electro-Chemical Impedance Spectral (EIS) Study of Patinated Bronze Corrosion in Sulfate Media: Experimental Design Approach

The aim of the present investigation was to model the experimental conditions of tin bronze patination using full factorial experimental design. In this sense, a full factorial design approach was developed to model the corrosion behavior of patinated tin bronze alloy in sulfate electrolyte. Three experimental factors (the immersion time in the chloride electrolyte, the potential limit for the anodic sweep Elim, and the potential scan rate) were chosen to identify the significant factor on the patina growth process at the bronze substrate. The experimental responses were the kinetic parameters extracted from the electro-chemical spectra (EIS) for eight different experiments. An equivalent electrical circuit containing an electrolyte resistance (Re), a double layer capacitance (CPEdl), a charge transfer resistance (Rt) and Gerischer element (G), was developed to model the patinated bronze corrosion process. The electro-chemical spectra (EIS) show that the corrosion process of the patinated bronze alloy occurred from a chemical reaction is followed by an electrochemical one. Analysis of the experimental responses showed that while the scan rate is the most influent factor for the corrosion potential (Ecorr), the electrolyte resistance (Re), and the double layer capacitance CPEdl variation, the potential limit is the significant factor for charge transfer resistance Rt, reciprocal of the admittance parameter Y0 and the effective transfer rate of the chemical reaction k variation.

Process Characterization of the Transesterification of Rapeseed Oil to Biodiesel Using Design of Experiments and Infrared Spectroscopy

For optimization of production processes and product quality,often knowledge of the factors influencing the process outcome is compulsory.Thus,process analytical technology(PAT)that allows deeper insight into the process and results in a mathematical description of the process behavior as a simple function based on the most important process factors can help to achieve higher production efficiency and quality.The present study aims at characterizing a well-known industrial process,the transesterification reaction of rapeseed oil with methanol to produce fatty acid methyl esters(FAME)for usage as biodiesel in a continuous micro reactor set-up.To this end,a design of experiment approach is applied,where the effects of two process factors,the molar ratio and the total flow rate of the reactants,are investigated.The optimized process target response is the FAME mass fraction in the purified nonpolar phase of the product as a measure of reaction yield.The quantification is performed using attenuated total reflection infrared spectroscopy in combination with partial least squares regression.The data retrieved during the conduction of the DoE experimental plan were used for statistical analysis.A non-linear model indicating a synergistic interaction between the studied factors describes the reactor behavior with a high coefficient of determination(R^(2))of 0.9608.Thus,we applied a PAT approach to generate further insight into this established industrial process.

Application of experimental design in optimization of crude oil adsorption from saline waste water using raw bagasse

Experimental design was applied in the optimization of crude oil adsorption from saline waste water using raw bagasse.The application of response surface methodology(RSM) was presented with temperature,salinity of water,pH,adsorbent dose,and initial oil content as factors.A quadratic model could be used to approximate the mathematical relationship of crude oil removal on the five significant independent variables.Predicted values and experimental values are found to be in good agreement with R2 of 97.44%.The result of optimization shows that the maximum crude oil removal is equal to 67.38% under the optimal condition of temperature of 46.53 °C,salinity of 37.2 g/L,pH of 3,adsorbent dose of 9 g/L and initial oil content of 300×10-6.

Optimization of Proportion and Formulation Process of Jinweng Granule by D-Optimal Mixture Design

[Objectives] To study the optimal proportion and formulation process of Jinweng granule,the physicochemical properties of the optimal preparing process was observed. [Methods] Adopting the D-optimal mixture design method,selecting the mixing ratio of starch,dextrin,fumei powder and lactose as tested factors,and selecting the most significant factor between hygroscopicity,formability,solubility as the evaluation index,the optimal proportion of filler was examined by system experiments. Granularity,solubility,the angle of repose,and critical relative humidity( CRH) were used to evaluate the optimal proportion and formulation process of Jinweng granule. [Results]The optimal prescription of Jinweng granule is extract∶ starch∶ dextrin∶ lactose∶ fumei powder( 1∶ 0. 5∶ 0. 05∶ 0. 3∶ 0. 15),and the binder was consisted of 1% sodium carboxymethylcellulose( CMC) slurry and 3% starch syrup. The CRH of the optimum formulation process of granule is 72%,and the fluidity,solubility and granularity were qualified. [Conclusions] The process model established by D-optimum mixture design has good predictability,and the granule prepared by the optimal proportion has good repeatability,and the granule proportion and formulation process is stable and reliable.

An iterated local coordinate-exchange algorithm for constructing experimental designs for multi-dimensional constrained spaces

Iterated local search(ILS)is used to construct the optimal experimental designs for multi-dimensional constrained spaces,in which the inner loop is based on the stochastic coordinate-exchange(SCE)algorithm.Every time a local optimal solution is found by the SCE algorithm,the perturbation operator is applied to it,and then a new solution is explored in the areas where the exchange of coordinates may produce improvement,so as to retain the features and attributes of the current optimal solution and avoid the defects of random restart.We implement the iterated local coordinate-exchange algorithm for experimental designs in the multi-dimensional constrained spaces.In addition,sensitivity analysis was conducted to analyze the impacts of the parameters on the performance of the proposed algorithm.Also we compared the performance of the proposed algorithm to the SCE algorithm using the random restart strategy.The analysis shows that the proposed algorithm is better than the SCE algorithm in terms of efficiency and quality,especially in the experimental designs for high-dimensional constrained space.