Optimizing Bucket Elevator Performance through a Blend of Discrete Element Method, Response Surface Methodology, and Firefly Algorithm Approaches

This research introduces a novel approach to enhancing bucket elevator design and operation through the integration of discrete element method(DEM)simulation,design of experiments(DOE),and metaheuristic optimization algorithms.Specifically,the study employs the firefly algorithm(FA),a metaheuristic optimization technique,to optimize bucket elevator parameters for maximizing transport mass and mass flow rate discharge of granular materials under specified working conditions.The experimental methodology involves several key steps:screening experiments to identify significant factors affecting bucket elevator operation,central composite design(CCD)experiments to further explore these factors,and response surface methodology(RSM)to create predictive models for transport mass and mass flow rate discharge.The FA algorithm is then applied to optimize these models,and the results are validated through simulation and empirical experiments.The study validates the optimized parameters through simulation and empirical experiments,comparing results with DEM simulation.The outcomes demonstrate the effectiveness of the FA algorithm in identifying optimal bucket parameters,showcasing less than 10%and 15%deviation for transport mass and mass flow rate discharge,respectively,between predicted and actual values.Overall,this research provides insights into the critical factors influencing bucket elevator operation and offers a systematic methodology for optimizing bucket parameters,contributing to more efficient material handling in various industrial applications.

Practical Aspects for Designing Statistically Optimal Experiments

Due to operational or physical considerations, standard factorial and response surface method （RSM） design of experiments （DOE） often prove to be unsuitable. In such cases a computer-generated statistically-optimal design fills the breech. This article explores vital mathematical properties for evaluating alternative designs with a focus on what is really important for industrial experimenters. To assess ＂goodness of design＂ such evaluations must consider the model choice, specific optimality criteria （in particular D and I）, precision of estimation based on the fraction of design space （FDS）, the number of runs to achieve required precision, lack-of-fit testing, and so forth. With a focus on RSM, all these issues are considered at a practical level, keeping engineers and scientists in mind. This brings to the forefront such considerations as subject-matter knowledge from first principles and experience, factor choice and the feasibility of the experiment design.

AIRCRAFT DESIGN EXPERIENCE

Some of the author's experiences of aircraft design are described in the present report, and it is hoped that they would be of some interest to the aircraft designers.

Design of Ecotourism Experience in Shennongjia

Ecotourism experience means that tourists obtain ecological enjoyment,ecological perception and ecological aesthetic taste through the senses and thinking activities in ecotourism activities.Shennongjia has excellent ecological environment,but lacks deep experience ecotourism products.Based on the principles of ecotourism experience design,the ecotourism experience theme,ecotourism experience product and ecotourism experience atmosphere of Shennongjia are designed.

A Brief Talk on Environmental Experience Graphic Design in the Construction of Characteristic Tourism From Signage Design

With the continuous development of the national economy and the improvement of the design industry,the wayfinding system has gradually been accepted and valued by the public,and the research on the wayfinding system of the public environment has become more and more in-depth.In recent years,the research on the wayfinding system has begun to develop into the integration of human culture and cultural implantation in the environment,forming a new visual system design concept,Environment Graphic Design.With the deepening of research,environmental graphic design has once again developed and deepened,studying the detailed experience of people in the environment and presenting it in the form of graphic design.That is,Experience Graphic Design.This article will discuss the application of environmental graphic experience design in the construction of characteristic tourism from the perspective of signage design.

Brand communication by brand experience design of APP for hotel

In the era of experience economy, customers do not always focus on the functional attributes of goods or services, but pay more attention to experiences. Therefore, firms have to manage to offer their customers a unique, memorable and valuable experience actively in the process brand establishment. With the development of mobile Internet and the use of application （APP）, the brand communication among customers and providers has been strengthened. The research purpose is to help hotel marketers figure out how to implement brand communication with brand experience of APP for hotel. It is founded that sensory brand experience design and social brand experience all have positive influence on customer brand loyalty.

DADOS:A Cloud-based Data-driven Design Optimization System

This paper presents a cloud-based data-driven design optimization system,named DADOS,to help engineers and researchers improve a design or product easily and efficiently.DADOS has nearly 30 key algorithms,including the design of experiments,surrogate models,model validation and selection,prediction,optimization,and sensitivity analysis.Moreover,it also includes an exclusive ensemble surrogate modeling technique,the extended hybrid adaptive function,which can make use of the advantages of each surrogate and eliminate the effort of selecting the appropriate individual surrogate.To improve ease of use,DADOS provides a user-friendly graphical user interface and employed flow-based programming so that users can conduct design optimization just by dragging,dropping,and connecting algorithm blocks into a workflow instead of writing massive code.In addition,DADOS allows users to visualize the results to gain more insights into the design problems,allows multi-person collaborating on a project at the same time,and supports multi-disciplinary optimization.This paper also details the architecture and the user interface of DADOS.Two examples were employed to demonstrate how to use DADOS to conduct data-driven design optimization.Since DADOS is a cloud-based system,anyone can access DADOS at www.dados.com.cn using their web browser without the need for installation or powerful hardware.

Active Machine Learning for Chemical Engineers:A Bright Future Lies Ahead!

By combining machine learning with the design of experiments,thereby achieving so-called active machine learning,more efficient and cheaper research can be conducted.Machine learning algorithms are more flexible and are better than traditional design of experiment algorithms at investigating processes spanning all length scales of chemical engineering.While active machine learning algorithms are maturing,their applications are falling behind.In this article,three types of challenges presented by active machine learning—namely,convincing the experimental researcher,the flexibility of data creation,and the robustness of active machine learning algorithms—are identified,and ways to overcome them are discussed.A bright future lies ahead for active machine learning in chemical engineering,thanks to increasing automation and more efficient algorithms that can drive novel discoveries.

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.

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.

Optimization by the Taguchi Method of a Robust Synthesis Protocol of Calcium Carbonate Phosphate

The experimental processes are difficult to model by physical laws, because a multitude of factors can intervene simultaneously and are responsible for their instabilities and their random variations. Two types of factors are to be considered;those that are easy to manipulate according to the objectives, and those that can vary randomly (uncontrollable factors). These could eventually divert the system from the desired target. It is, therefore, important to implement a system that is insensitive to fluctuations in factors that are difficult to control. The aim of this study is to optimize the synthesis of an apatitic calcium carbonate phosphate characterized with a Ca/P ratio equal to 1.61 by using the experimental design method based on the Taguchi method. In this process, five factors are considered and must be configured to achieve the previously defined objective. The temperature is a very important factor in the process, but difficult to control experimentally, so considered to be a problem factor (noise factor), forcing us to build a robust system that is insensitive to the last one. Therefore, a much simpler model to study the robustness of a synthetic solution with respect to temperature is developed. We have tried to parameterize all the factors considered in the process within a wide interval of temperature variation (60˚C - 90˚C). Temperature changes are no longer considered as a problem for apatitic calcium carbonate phosphate synthesis. In this finding, the proposed mathematical model is linear and efficient with very satisfactory statistical indicators. In addition, several simple solutions for the synthesis of carbonate phosphate are proposed with a Ca/P ratio equal to 1.61.

Effects of additives on performance of zinc electrode

In order to improve the properties of the nickel?zinc battery and study the effects of the additives on performance of zinc electrode, 3 levels and 4 factors (acetylene black, Bi2O3, PbO, Ca[Zn(OH)3]2·2H2O coated by La(OH)3 ) that affect the zinc electrode were tested with orthogonal design experiments. The charge?discharge experiments of zinc electrode made up of only zinc oxide were done in 20% KOH solution to investigate the function of the additive. In order to better understand the discharge capability attenuation of electrode, the ratios of zinc to calcium in the worst sample and the best sample of the orthogonal design test were analyzed. The samples were characterized by charge?discharge cycling, phase structure analysis, cyclic voltammetry and X-ray diffraction. Experimental evidences indicate that the optimum ratio of electrode additive is as follows: 0.02 g acetylene black, 0.5 g Bi2O3, 0.3 g PbO and 0.2 g Ca[Zn(OH)3]2·2H2O coated with La(OH)3 in 5 g sample.

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.

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.

Device Robust-Design by Using Response Surface Methodology

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

Prediction and optimization of process parameter of friction stir welded AA5083-H111 aluminum alloy using response surface methodology

A systematic approach was presented to develop the empirical model for predicting the ultimate tensile strength of AA5083-H111 aluminum alloy which is widely used in ship building industry by incorporating friction stir welding(FSW) process parameters such as tool rotational speed,welding speed,and axial force.FSW was carried out considering three-factor five-level central composite rotatable design with full replications technique.Response surface methodology(RSM) was applied to developing linear regression model for establishing the relationship between the FSW process parameters and ultimate tensile strength.Analysis of variance(ANOVA) technique was used to check the adequacy of the developed model.The FSW process parameters were also optimized using response surface methodology(RSM) to maximize the ultimate tensile strength.The joint welded at a tool rotational speed of 1 000 r/min,a welding speed of 69 mm/min and an axial force of 1.33 t exhibits higher tensile strength compared with other joints.

Kinetics of phenol and m-cresol biodegradation by an indigenous mixed microbial culture isolated from a sewage treatment plant

An acclimatized mixed microbial culture,predominantly Pseudomonas sp.,was enriched from a sewage treatment plant,and its potential to simultaneously degrade mixtures of phenol and m-cresol was investigated during its growth in batch shake flasks.A 22 full factorial design with the two substrates at two different levels and different initial concentration ranges(low and high),was employed to carry out the biodegradation experiments.The substrates phenol and m-cresol were completely utilized within 21 h when ...

Optimization of flotation variables for the recovery of hematite particles from BHQ ore

The technology for beneficiation of banded iron ores containing low iron value is a challenging task due to increasing demand of quality iron ore in India. A flotation process has been developed to treat one such ore, namely banded hematite quartzite （BHQ） containing 41.8wt% Fe and 41.5wt% SiO2,by using oleic acid, methyl isobutyl carbinol （MIBC）, and sodium silicate as the collector, frother, and dispersant, respectively. The relative effects of these variables have been evaluated in half-normal plots and Pareto charts using central composite rotatable design. A quadratic response model has been developed for both Fe grade and recovery and optimized within the experimental range. The optimum reagent dosages are found to be as follows： collector concentration of 243.58 g/t, dispersant concentration of 195.67 g/t, pH 8.69, and conditioning time of 4.8 min to achieve the maximum Fe grade of 64.25% with 67.33% recovery. The predictions of the model with regard to iron grade and recovery are in good agreement with the experimental results.

Optimizing the Pulsed Current Gas Tungsten Arc Welding Parameters

The selection of process parameter in the gas tungsten arc （GTA） welding of titanium alloy was presented for obtaining optimum grain size and hardness. Titanium alloy （Ti-6Al-4V） is one of the most important non-ferrous metals which offers great potential application in aerospace, biomedical and chemical industries, because of its low density （4.5 g/cm^3）, excellent corrosion resistance, high strength, attractive fracture behaviour and high melting point （1678℃）. The preferred welding process for titanium alloy is frequent GTA welding due to its comparatively easier applicability and better economy. In the case of single pass （GTA） welding of thinner section of this alloy, the pulsed current has been found beneficial due to its advantages over the conventional continuous current process. Many considerations come into the picture and one needs to carefully balance various pulse current parameters to reach an optimum combination. Four factors, five level, central composite, rotatable design matrix were used to optimize the required number of experimental conditions. Mathematical models were developed to predict the fusion zone grain size using analysis of variance （ANOVA） and regression analysis. The developed models were optimized using the traditional Hooke and Jeeve＇s algorithm. Experimental results were provided to illustrate the proposed approach.