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.

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.

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.

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.

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%.

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.

Adsorption of Malachite Green Using Activated Carbon from Mangosteen Peel: Optimization Using Box-Behnken Design

In this research,activated carbon from mangosteen peel has been synthesized using sulfuric acid as an activator.The adsorption performance of the activated carbon was optimized using malachite green dye as absorbate.Mala-chite green dye waste is a toxic and non-biodegradable material that damages the environment.Optimization of adsorption processes was carried out using Response Surface Methodology(RSM)with a Box-Behnken Design(BBD).The synthesized activated carbon was characterized using FTIR and SEM instruments.The FTIR spectra confirmed the presence of a sulfonate group(-SO_(3)H)in the activated carbon,indicating that the activation pro-cess using sulfuric acid was successful.SEM characterization shows that activated carbon has porous morphology.Optimization was carried out for three adsorption parameters,namely contact time(20,60,and 120 min),adsor-bent mass(0.005,0.025,and 0.05 g),and initial concentration of malachite green solution(5,50,and 100 mg·L^(-1)).The concentration of the malachite green solution was determined using a UV-Vis spectrophotometer at the max-imum wavelength of malachite green,618 nm.The optimum of malachite green adsorption using mangosteen peel activated carbon was obtained at a contact time of 80 min,an adsorbent mass of 0.032 g,and malachite green initial concentration of 25 mg·L^(-1),with a maximum removal percentage and maximum adsorption capacity of 93.66%and 19.345 mg·g^(-1),respectively.

Clinical/Behavioral Monitoring of Rodents and Rabbits Undergoing Scientific Experiments

Background: We currently have international and national guidelines regarding the assessment and monitoring of clinical signs and humane endpoints in animals used in teaching and research, which make the performance of these activities mandatory for any experiment and professional working in this area. Assigning the severity of a research experiment is the result of an analysis of records of observations of the animal’s behavior, and clinical signs. The aim of this study was to describe the importance of carrying out a severity assessment associated with clinical and behavioral monitoring of rodents and rabbits during experimentation to maintain the welfare of these animals undergoing scientific research. Methods: The literature search was carried out using the following terms: “Monitoring”;“Humane endpoints”;“Animal welfare”, “Rodents”;“Rabbits”, and as connectors “and”;“or”, in the following databases: PubMed;LILACS/BIREME and SciELO. Results: A total of 987 articles were identified in the databases, and 20 of these studies were included in this review. Conclusions: Humane endpoint protocols and procedure severity tables are of the utmost importance, both from an ethical point and to refine the results of research conducted on laboratory animals. They should be drawn up jointly by the teams responsible for the project and the maintenance of the animals during the research period, and the data obtained should be published so that the scientific community can have access to it, helping to disseminate these practices, as well as helping to draw up new procedures. Monitoring and evaluating the welfare and clinical condition of animals undergoing scientific research procedures is the responsibility of the professors, researchers, veterinarians, and animal facility coordinators. The Ethics Committee on the Use of Animals must monitor all the activities conducted with the animals, by inspecting the experimental procedures and the physical environment of the laboratory animal facility where the animals are housed.

基于MATLAB App Designer的加工误差统计分析实验系统设计

机械加工误差的统计分析是机械制造基础课程中典型的实验内容,同时也是机械专业生产实习期间评定工艺过程加工精度的重要巩固环节。为了使学生从理论更直接地过渡到实际应用中,改善传统实验教学手段的单一化,设计了一种基于MATLAB App Designer的加工误差统计分析实验系统。该系统针对多个常见工序随机产生能够模拟真实工序尺寸的样本,并引导学生按照实验步骤完成工艺过程的分布图法分析与点图法分析。实验过程中可随时查看分数,学生可反思纠错、反复练习。同时提供了可用于参考的测量尺寸频数分布图、x−R图,能帮助学生灵活直观地掌握加工误差的统计分析原理与应用过程,提高实验教学的水平。

Orthogonal experiment design of EMI of security monitoring system in coal mines

Security monitoring system of coal mines is indispensable to ensure the safe and efficient production of colliery. Due to the special and narrow underground field of the coal mine, the electromagnetic interference can cause a series of misstatements and false positives on the monitoring system, which will severely hamper the safe production of coal industry. In this paper, first, the frequency characteristics of the interference source on the power line are extracted when equipment runs normally. Then the finite difference time domain method is introduced to analyze the effects of the electromagnetic interference parameters on the security monitoring signal line. And the interference voltage of the two terminal sides on the single line is taken as evaluating indexes. Finally, the electromagnetic interference parameters are optimized by orthogonal experimental design based on the MATLAB simulation on the normal operation of equipment.

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.

Cavitation Optimization for a Centrifugal Pump Impeller by Using Orthogonal Design of Experiment

Cavitation is one of the most important performance of centrifugal pumps. However, the current optimization works of centrifugal pump are mostly focusing on hydraulic efficiency only, which may result in poor cavitation performance. Therefore, it is necessary to find an appropriate solution to improve cavitation performance with acceptable efficiency. In this paper, to improve the cavitation performance of a centrifugal pump with a vaned diffuser, the influence of impeller geometric parameters on the cavitation of the pump is investigated using the orthogonal design of experiment （DOE） based on computational fluid dynamics. The impeller inlet diameter D1, inlet incidence angle Aft, and blade wrap angle ~0 are selected as the main impeller geometric parameters and the orthogonal experiment of L9（3＂3） is performed. Three-dimensional steady simulations for cavitation are conducted by using constant gas mass fraction model with second-order upwind, and the predicated cavitation performance is validated by laboratory experiment. The optimization results are obtained by the range analysis method to improve cavitation performance without obvious decreasing the efficiency of the centrifugal pump. The internal flow of the pump is analyzed in order to identify the flow behavior that can affect cavitation performance. The results show that D1 has the greatest influence on the pump cavitation and the final optimized impeller provides better flow distribution at blade leading edge. The final optimized impeller accomplishes better cavitation and hydraulic performance and the NPSHR decreases by 0.63m compared with the original one. The presented work supplies a feasible route in engineering practice to optimize a centrifugal pump impeller for better cavitation performance.

Study on solder joint reliability of ceramic ball grid array component based on design of experiment method

Four process parameters, pad diameter, stencil thickness, ball diameter and stand-off were chosen as four control factors. By using an L25 （5^6 ） orthogonal array the ceramic ball grid array （ CBGA ） solder joints which have 25 different combinations of process parameters were designed. The numerical models of all the 25 CBGA solder joints were developed using the Sugrace Evolver. Utilizing the sugrace coordinate exported from the 25 CBGA solder joints numerical models, the finite element analysis models were set up and the nonlinear finite element analysis of the CBGA solder joints under thermal cycles were pegrormed by ANSYS. The thermal fatigue life of CBGA solder joint was calculated using Coffin-Manson equation. Based on the calculated thermal fatigue life results, the range analysis and the variance analysis were pegrormed. The results show that the fatigue life of CBGA solder joint is affected by the pad diameter, the stencil thickness, the ball diameter and the stand-off in a descending order, the best combination of process parameters results in the longest fatigue life is 0.07 mm stand-off, 0.125 mm stencil thickness of, 0.85 mm ball diameter and 0. 89 mm pad diameter. With 95% confidence the pad diameter has a significant effect on the reliability of CBGA solder joints whereas the stand-off, the stencil thickness and the ball diameter have little effect on the reliability of CBGA solder joints.

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 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.

Hydrogen-based direct reduction of industrial iron ore pellets:Statistically designed experiments and computational simulation

As part of efforts to reduce anthropogenic CO_(2) emissions by the steelmaking industry,this study investigated the direct reduction of industrially produced hematite pellets with H_(2) using the Doehlert experimental design to evaluate the effect of pellet diameter(10.5-16.5 mm),porosity(0.36-0.44),and temperature(600-1200℃).A strong interactive effect between temperature and pellet size was observed,indicating that these variables cannot be considered independently.The increase in temperature and decrease in pellet size considerably favor the reduction rate,while porosity did not show a relevant effect.The change in pellet size during the reduction was negligible,except at elevated temperatures due to crack formation.A considerable decrease in mechanical strength at high temperatures suggests a maximum process operating temperature of 900℃.Good predictive capacity was achieved using the modified grain model to simulate the three consecutive non-catalytic gas-solid reactions,considering different pellet sizes and porosities,changes during the reaction from 800 to 900℃.However,for other temperatures,different mechanisms of structural modifications must be considered in the modeling.These results represent significant contributions to the development of ore pellets for CO_(2)-free steelmaking technology.

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.

Application of Monte-Carlo statistical experiments in design of ocean engineering - Estimating the parameters, models and probabilities

Recently, some results have been acquired with the Monte- Carlo statistical experiments in the design of ocean en gineering. The results show that Monte-Carlo statistical experiments can be widely used in estimating the parameters of wave statistical distributions, checking the probability model of the long- term wave extreme value distribution under a typhoon condition and calculating the failure probability of the ocean platforms.