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%.

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.

Synthesis of boron nitride nanorod and its performance as a metalfree catalyst for oxidative desulfurization of diesel fuel

In order to reduce the sulfur compounds in diesel fuel,boron nitride(BN)has been used as a novel metal-free catalyst in the present research.This nanocatalyst was synthesized via template-free approach followed by heating treatment at 900℃ in nitrogen atmosphere that the characteristics of the sample were identified by the X-ray diffraction,Fourier-transform infrared spectroscopy,Raman spectroscopy,field emission scanning electron microscopy,transmission electron microscopy,atomic force microscopy,and N2 adsorption-desorption isotherms.The results of structural and morphological analysis represented that BN has been successfully synthesized.The efficacy of the main operating parameters on the process was studied by using response surface methodology based on the Box-Behnken design method.The prepared catalyst showed high efficiency in oxidative desulfurization of diesel fuel with initial sulfur content of 8040 mg·kg^(-1)S.From statistical analysis,a significant quadratic model was obtained to predict the sulfur removal as a function of efficient parameters.The maximum efficiency of 72.4%was achieved under optimized conditions at oxidant/sulfur molar ratio of 10.2,temperature of 71℃,reaction time of 113 min,and catalyst dosage of 0.36 g.Also,the reusability of the BN was studied,and the result showed little reduction in activity of the catalyst after 10 times regeneration.Moreover,a plausible mechanism was proposed for oxidation of sulfur compounds on the surface of the catalyst.The present study shows that BN materials can be selected as promising metal-free catalysts for desulfurization process.

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.

Evaluation of Moving Grid Adjustment (MGA) Method in Field Variation Control

Spatial variation is often encountered when large scale field trials are conducted which can result in biased estimation or prediction of treatment (i.e. genotype) values. An effective removal of spatial variation is needed to ensure unbiased estimation or prediction and thus increase the accuracy of field data evaluation. A moving grid adjustment (MGA) method, which was proposed by Technow, was evaluated through Monte Carlo simulation for its statistical properties regarding field spatial variation control. Our simulation results showed that the MGA method can effectively account for field spatial variation if it does exist;however, this method will not change phenotype results if field spatial variation does not exist. The MGA method was applied to a large-scale cotton field trial data set with two representative agronomic traits: lint yield (strong field spatial pattern) and lint percentage (no field spatial pattern). The results suggested that the MGA method was able to effectively separate the spatial variation including blocking effects from random error variation for lint yield while the adjusted data remained almost identical to the original phenotypic data. With application of the MGA method, the estimated variance for residuals was significantly reduced (62.2% decrease) for lint yield while more genetic variation (29.7% increase) was detected compared to the original data analysis subject to the conventional randomized complete block design analysis. On the other hand, the results were almost identical for lint percentage with and without the application of the MGA method. Therefore, the MGA method can be a useful addition to enhance data analysis when field spatial pattern exists.

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.

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.

Auxiliary guidance manufacture and revealing potential mechanism of perovskite solar cell using machine learning

To promote the development of global carbon neutrality,perovskite solar cells(PSCs)have become a research hotspot in related fields.How to obtain PSCs with expected performance and explore the potential factors affecting device performance are the research priorities in related fields.Although some classical computational methods can facilitate material development,they typically require complex mathematical approximations and manual feature screening processes,which have certain subjectivity and one-sidedness,limiting the performance of the model.In order to alleviate the above challenges,this paper proposes a machine learning(ML)model based on neural networks.The model can assist both PSCs design and analysis of their potential mechanism,demonstrating enhanced and comprehensive auxiliary capabilities.To make the model have higher feasibility and fit the real experimental process more closely,this paper collects the corresponding real experimental data from numerous research papers to develop the model.Compared with other classical ML methods,the proposed model achieved better overall performance.Regarding analysis of underlying mechanism,the relevant laws explored by the model are consistent with the actual experiment results of existing articles.The model exhibits great potential to discover complex laws that are difficult for humans to discover directly.In addition,we also fabricated PSCs to verify the guidance ability of the model in this paper for real experiments.Eventually,the model achieved acceptable results.This work provides new insights into integrating ML methods and PSC design techniques,as well as bridging photovoltaic power generation technology and other fields.

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.

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.

Selection Model in Buyer-Supplier Relationships

This paper proposes a new method of selecting appropriate buyer supplier relationships (BSR) for specific projects. Because it is almost impossible in reality to establish mathematical relationships between the BSR attributes and the factors of a project, the concept of relationship indices (RI) is introduced to quantify such BSR which are in turn established through design of experiments. Based on the experimental results, the contributions of project factors, known as factors relationship worths (RW...

Technology for Enzymolysis of Jellyfish Brain Protein by Bromelain

[Objective] This study aimed to investigate the optimal technology for en- zymolysis of jeUyfish brain protein by bromefain. [Method] Effects of enzymolysis temperature, the amount of added enzyme, solid/liquid ratio, enzymolysis time and pH on the enzymolysis of total protein were investigated through single factor ex- periments, and some technical parameters were optimized by orthogonal experi- ments. [Result] The results revealed that enzymolysis temperature of 55℃, the amount of added enzyme of 4 000 U/g, solid/liquid ratio of 1：4, the amount of added enzyme time for 5 h and pH 7 were the optimal combination of parameters for the enzymolysis; the average degree of hydrolysis obtained from the verification tests was 36.9%, indicating that the optimized results of the orthogonal experiment were credible. [Conclusion] This study provides the optimized conditions reliable theo- retical foundation and technical support for the exploitation and utilization of jellyfish resources as medicines or functional food in China.

Preliminary Study on the Low Energy Ion Beam Mediated Parameters with Fractional Factorial Design Method

[Objective] The aim was to explore the biological effect of low energy ion beam mediated parameters with fractional factorial design method. [Method] The twin-embryos seed of autotetraploid rice DER10-04-01 was taken as the receptor material,and the Elymus dahuricus Turcz. was used as materials to provide DNA to carry out the ion beam mediated experiment. And the fractional factorial design method was used to study the parameters of low enery N＋ ion beam mediated foreign genes into rice. [Result] The implantation energy,dose,DNA concentrations and immersion time of DNA showed significant biological effects on the normal growth and development of DER10-04-01,in which the biological effects of implantation dose and DNA concentrations were relatively obvious. [Conclusion] The implantation energy,dose,DNA concentrations and immersion time of DNA were major factors showing important effects on the experimental result in ion beam mediated foreign genetic materials.

Research on the Process of Yield Formation Based on Dynamic Design in Winter Wheat

[Objective]The aim was to research on construction of yield formation model of winter wheat.[Method]In the case of variety Shijiazhuang 8,the process of yield trait formation was studied by the dynamic ideal and uniform experimental design;the differences between plant dry weight and population indexes were analyzed by using multiple comparison analysis,and the yield formation model was developed by multiple regression analysis.[Result]The results showed that multiple correlation coefficients of yield formation model ranged from 0.91 to 0.97.[Conclusion]The model was significant which provide certain theoretical base for high yield and high efficiency cultivation of winter wheat.

Optimization of PCR Reaction System for Random Single-strand DNA Pool in SELEX Technology

[Objective] This study aimed to optimize the PCR amplification conditions for random ssDNA pool in SELEX technology. [Method] L16（45） orthogonal experimental design was adopted for optimization of five important factors affecting PCR reaction system for random single-stranded DNA pool including Mg2＋ concentration, dNTP concentration, amount of Taq DNA polymerase, primer concentration and amount of random single-stranded DNA pool at four levels. Meanwhile, the annealing temperature and number of PCR reaction cycles were optimized to establish the optimal reaction system and PCR procedure. [Result] The optimal combination of PCR reaction system for random ssDNA pool was obtained, with a total system volume of 20 μl containing 2.0 μl of 10 × Buffer, 0.5 ng of random ssDNA pool, 2.5 mmol/L Mg2＋, 0.25 mmol/L dNTP Mixture, 0.6 μmol/L upstream and downstream primers and 1.5 U of Taq DNA polymerase; the optimal annealing temperature was 68 ℃ and the optimal number of cycles was 12. Under the above conditions, clear and stable bands with high specificity for random ssDNA pool were amplified. [Conclusion] This study laid the foundation for selection of parameters with higher specificity in SELEX technology.

Influences of aerodynamic loads on hunting stability of high-speed railway vehicles and parameter studies

The influences of steady aerodynamic loads on hunting stability of high-speed railway vehicles were investigated in this study.A mechanism is suggested to explain the change of hunting behavior due to actions of aerodynamic loads：the aerodynamic loads can change the position of vehicle system（consequently the contact relations）,the wheel/rail normal contact forces,the gravitational restoring forces/moments and the creep forces/moments.A mathematical model for hunting stability incorporating such influences was developed.A computer program capable of incorporating the effects of aerodynamic loads based on the model was written,and the critical speeds were calculated using this program.The dependences of linear and nonlinear critical speeds on suspension parameters considering aerodynamic loads were analyzed by using the orthogonal test method,the results were also compared with the situations without aerodynamic loads.It is shown that the most dominant factors a ff ecting linear and nonlinear critical speeds are different whether the aerodynamic loads considered or not.The damping of yaw damper is the most dominant influencing factor for linear critical speeds,while the damping of lateral damper is most dominant for nonlinear ones.When the influences of aerodynamic loads are considered,the linear critical speeds decrease with the rise of cross wind velocity,whereas it is not the case for the nonlinear critical speeds.The variation trends of critical speeds with suspension parameters can be significantly changed by aerodynamic loads.Combined actions of aerodynamic loads and suspension parameters also a ff ect the critical speeds.The effects of such joint action are more obvious for nonlinear critical speeds.