Improving self-assembly quality of colloidal crystal guided by statistical design of experiments

A versatile and reliable approach is created to fabricate wafer-scale colloidal crystal that consists of a monolayer of hexagonally close-packed polystyrene （PS） spheres. Making wafer-scale colloidal crystal is usually challenging, and it lacks a general theoretical guidance for experimental approaches. To obtain the optimal conditions for self-assembly, a systematic statistical design and analysis method is utilized here, which applies the pick-the-winner rule. This new method combines spin-coating and thermal treatment, and introduces a mixture of glycol and ethanol as a dispersion system to assist self-assembly. By controlling the parameters of self-assembly, we improve the quality of colloidal crystal and reduce the effect of noise on the experiment. To our best knowledge, we are first to pave this path to harvest colloidal crystals. Importantly, a theoretical analysis using an energy landscape base on our process is also developed to provide insights into the PS spheres＇ self-assembly.

Application of Statistical Design Strategies to Optimize the Preparation of ZnO Nanoparticles by Hydrothermal Technique

Synthesis of ZnO nanoparticles by hydrothermal technique in presence of cetyltrimethylammonium bromide （CTAB） as surfactant was carried out by statistically designed experiments based on Box Behnken method. The mean parameters, surfactant concentration, time and temperature have been studied to show their effect on ZnO particle size and morphology. The results of experimental design indicate that the surfactant concentration, reaction time and temperature were significant. ZnO particles were investigated using XRD and SEM and the findings show that ZnO nanoparticles were formed at 100 ℃ and their crystallinity were improved with temperature rise from 100 to 200 ℃. Particle size of ZnO in the range of 39-76 nm is achieved using this technique.

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.

The Statistical Experimental Design for Chemical Reactors Modeling

The Statistical Experimental Design techniques are the most powerful tools for the chemical reactors experimental modeling. Empirical models can be formulated for representing the chemical behavior of reactors with the minimal effort in the necessary number of experimental runs, hence, minimizing the consumption of chemicals and the consumption of time due to the reduction in the number of experimental runs and increasing the certainty of the results. Four types of nonthermal plasma reactors were assayed seeking for the highest efficiency in obtaining hydrogen and ethylene. Three different geometries for AC high voltage driven reactors, and only a single geometry for a DC high voltage pulse driven reactor were studied. According to the fundamental principles of chemical kinetics and considering an analogy among the reaction rate and the applied power to the plasma reactor, the four reactors are modeled following the classical chemical reactors design to understand if the behavior of the nonthermal plasma reactors can be regarded as the chemical reactors following the flow patterns of PFR (Plug Flow Reactor) or CSTR (Continuous Stirred Tank Reactor). Dehydrogenation is a common elimination reaction that takes place in nonthermal plasmas. Owing to this characteristic, a paraffinic heavy oil with an average molecular weight corresponding to C15 was used to study the production of light olefins and hydrogen.

Science of empirical design in mining ground control

Many problems in rock engineering are limited by our imperfect knowledge of the material properties and failure mechanics of rock masses. Mining problems are somewhat unique, however, in that plenty of real world experience is generally available and can be turned into valuable experimental data.Every pillar that is developed, or stope that is mined, represents a full-scale test of a rock mechanics design. By harvesting these data, and then using the appropriate statistical techniques to interpret them,mining engineers have developed powerful design techniques that are widely used around the world.Successful empirical methods are readily accepted because they are simple, transparent, practical, and firmly tethered to reality. The author has been intimately associated with empirical design for his entire career, but his previous publications have described the application of individual techniques to specific problems. The focus of this paper is the process used to develop a successful empirical method. A sixstage process is described: identification of the problem, and of the end users of the final product; development of a conceptual rock mechanics model, and identification of the key parameters in that model;identification of measures for each of the key parameters, and the development of new measures(such as rating scales) where necessary; data sources and data collection; statistical analysis; and packaging of the final product. Each of these stages has its own potential rewards and pitfalls, which will be illustrated by incidents from the author's own experience. The ultimate goal of this paper is to provide a new and deeper appreciation for empirical techniques, as well as some guidelines and opportunities for future developers.

Characteristic Period Value of the Seismic Design Response Spectrum of UHV Electrical Equipment

Characteristic period is an important parameter of the seismic design response spectrum. There is important theoretical significance and engineering application value to the study of the characteristic period of seismic design response spectrum of ultra high voltage （UHV） electrical equipment. In this paper, 1448 horizontal earthquake records within the world scope including the United States and Japan for Site Class m were analyzed. Results show that both magnitude and epicentral distance have great influence on the characteristic period. About 80 % of characteristic periods of strong earthquake records are about 0. 9s. Statistical analysis was conducted on the seismic hazard assessment results of 312 projects of China in recent years, and it is found that about 70 % of characteristic periods are about 0. 9s. Combined with the related code comparison and analysis, it is suggested that the characteristic period of the seismic design response spectrmn of UHV electrical equipment should select 0. 9s in order to effectively guarantee the seismic safety of UHV electrical equipment.

Statistically designed enzymatic hydrolysis of an icariin/b-cyclodextrin inclusion complex optimized for production of icaritin

This study focuses on the preparation and enzymic hydrolysis of an icariin/bcyclodextrin inclusion complex to efficiently generate icaritin.The physical characteristics of the inclusion complex were evaluated by differential scanning calorimetry(DSC).Enzymatic hydrolysis was optimized for the conversion of icariin/b-cyclodextrin complex to icaritin by Box–Behnken statistical design.The inclusion complex formulation increased the solubility of icariin approximately 17-fold,from 29.2 to 513.5 mg/mL at 60℃.The optimum conditions were predicted by Box–Behnken statistical design as follows:60℃,pH 7.0,the ratio of enzyme/substrate(1:1.1)and reaction time 7 h.Under the optimal conditions the conversion of icariin was 97.91%and the reaction time was decreased by 68%compared with that without b-CD inclusion.Product analysis by melting point,ESI-MS,UV,IR,1H NMR and 13C NMR confirmed the authenticity of icaritin with a purity of 99.3%and a yield of 473 mg of icaritin from 1.1 g icariin.

Coal washing improvement by determination of optimal mixture of feed blends

Coals from different mines are feed in the Zirab plant without any control on weight percentage blending of them. Three major coal types of different ranks (Kiasar, Lavidj and Karmozd) were blended in various proportions to find an optimum condition in flotation circuit in Alborz Markazi coal washing plant. Flotation tests were conducted for prepared blended coal samples to assess floatability of various coal samples. In this paper, mixture design as a statistical method was used to optimize coal blend to increase recovery and grade in Zirab coal washing plant. The statistical analysis showed that the weight percent blending of different coals and interaction between Lavidj and Karmozd regions coal had significant effects on the coal recovery. The optimum condition of 95% recovery and 12% ash content could be reached with 10%, 20%, and 70% blending portion of Kiasar, Lavidj and Karmozd regions coal, respectively.

Combining the People Power and the Process Power to Achieve Six Sigma Process Capability——A Case Study

Achieving Six-Sigma process capability starts with l istening to the Voice of the Customers, and it becomes a reality by combining th e People Power and the Process Power of the organisation. This paper presents a Six-Sigma implementation case study carried out in a magnet manufacturing compa ny, which produces bearing magnets to be used in energy meters. If the thickness of the produced bearing magnets is between 2.35 mm and 2.50 mm, they will be ac cepted by the customers. All the time the company could not produce the bearing magnets within the specified thickness range, as their process distribution was flat with 2.20 mm as lower control limit and 2.60 mm as upper control limit. This resulted in a huge loss in the form of non-conformities, loss of time and goodwill. The process capability of the company then was around 0.40. Organisat ion restructuring was carried out to reap the benefit of the People Power of the organisation. Statistically designed experiments (Taguchi Method based Design o f Experiments), Online quality control tools (Statistical Process Control To ols) were effectively used to complete the DMAIC (Define, Measure, Analyse, Impr ove and Control) cycle to reap the benefit of the Process Power of the organisat ion. Presently the company enjoys a process capability of 1.75, a way towards Si x-Sigma Process Capability.

REVERSE MODELING FOR CONIC BLENDING FEATURE

A novel method to extract conic blending feature in reverse engineering is presented. Different from the methods to recover constant and variable radius blends from unorganized points, it contains not only novel segmentation and feature recognition techniques, but also bias corrected technique to capture more reliable distribution of feature parameters along the spine curve. The segmentation depending on point classification separates the points in the conic blend region from the input point cloud. The available feature parameters of the cross-sectional curves are extracted with the processes of slicing point clouds with planes, conic curve fitting, and parameters estimation and compensation, The extracted parameters and its distribution laws are refined according to statistic theory such as regression analysis and hypothesis test. The proposed method can accurately capture the original design intentions and conveniently guide the reverse modeling process. Application examples are presented to verify the high precision and stability of the proposed method.

Detailed parametric design methodology for hydrodynamics of liquid-solid circulating fluidized bed using design of experiments

A design-of-experiments methodology is used to develop a statistical model for the prediction of the hydrodynamics of a liquid–solid circulating fluidized bed. To illustrate the multilevel factorial design approach, a step by step methodology is taken to study the effects of the interactions among the independent factors considered on the performance variables. A multilevel full factorial design with three levels of the two factors and five levels of the third factor has been studied. Various statistical models such as the linear, two-factor interaction, quadratic, and cubic models are tested. The model has been developed to predict responses, viz., average solids holdup and solids circulation rate. The validity of the developed regression model is verified using the analysis of variance. Furthermore, the model developed was compared with an experimental dataset to assess its adequacy and reliability. This detailed statistical design methodology for non-linear systems considered here provides a very important tool for design and optimization in a cost-effective approach

A Wireframe Model-Based Method for Automated Internal Design

This paper proposes a wireframe model-based method for automated internal design. The method is used to extract geometric structure of an internal wireframe model and find out all loop structures of furniture models. The wireframe models are classified as the multiple independent sub-models according to the geometric structure by statistical analysis. The corresponding models are selected from a 3D model database to build an internal scene based on characteristic points of furniture wireframe models. In the experiments 3D database via manually selected 268 3D furniture models from Google 3D warehouse is built up. The experiments show that the method can construct 3D scenes in 1.1×103 ms. This method costs less time compared with traditional hierarchical method and depth-sensing camera method in the same experimental conditions. The method can be also used for 3D visualization either with complex backgrounds.

Bed dynamics of gas-solid fluidized bed with rod promoter

The dynamic characteristics of a gas-solid fluidized bed with different rod promoters have been investigated in terms of bed expansion and fluctuation, minimum fluidization velocity and distributor-to-bed pressure drop ratio at minimum fluidization velocity. Experimentation based on statistical design has been carried out and model equations using factorial design of experiments have been developed for the above mentioned quantities for a promoted gas-solid fluidized bed. The model equations have been tested with additional experimental data. The system variables include four types of rod promoters of varying blockage volume, bed particles of four sizes and four initial static bed heights. A comparison between the predicted values of the output variables using the proposed model equation with their corresponding experimental ones shows fairly good agreement.

Effect of Operating Parameters on Carbon Dioxide Depressurized Regeneration in Circulating Fluidized Bed Downer using Computational Fluid Dynamics

Typically,heating or high-temperature treatment has been used to regenerate solid sorbent.In this study,the depressurized regeneration using a circulating fluidized bed downer was proposed and the significance of its operating parameters was identified.Two-dimensional computational fluid dynamics were employed to systematically investigate the effects of operating parameters on carbon dioxide depressurized regeneration with potassium carbonate solid sorbent particles.The simulated model was based on a laboratory scale circulating fluidized bed downer.The chemical equilibrium model for predicting the highest outlet carbon dioxide mass fraction was then used.A central composite design was employed to identify the main,quadratic,and interaction effects of operating parameters to the regeneration process.The operating parameters consisted of the outlet system pressure,inlet gas velocity,and inlet solid circulation rate,while the response variable was the released outlet carbon dioxide mass fraction.Among the multiple operating parameters,there were two main operating parameters and their combinations,namely the inlet gas velocity,outlet system pressure,square of inlet gas velocity,and interaction between inlet gas velocity and outlet system pressure,which had great impacts on the regeneration.All the main,quadratic,and interaction effects were explained.Then,the optimal operating conditions were obtained through the response surface method.

Simultaneous saccharification and fermentation of wheat bran flour into ethanol using coculture of amylotic Aspergillus niger and thermotolerant Kluyveromyces marxianus

Studies on simultaneous saccharification and fermentation(SSF)of wheat bran flour,a grain milling residue as the substrate using coculture method were carried out with strains of starch digesting Aspergillus niger and nonstarch digesting and sugar fermenting Kluyveromyces marxianus in batch fermentation.Experi-ments based on central composite design(CCD)were conducted to maximize the glucose yield and to study the effects of substrate concentration,pH,temperature,and enzyme concentration on percentage conversion of wheat bran flour starch to glucose by treatment with fungalα-amylase and the above parameters were optimized using response surface methodology(RSM).The optimum values of substrate concentration,pH,temperature,and enzyme concentration were found to be 200g/L,5.5,65℃ and 7.5IU,respectively,in the starch saccharification step.The effects of pH,temperature and substrate concentration on ethanol concentration,biomass and reducing sugar concentration were also investigated.The optimum temperature and pH were found to be 30℃ and 5.5,respectively.The wheat bran flour solution equivalent to 6%(w/V)initial starch concentration gave the highest ethanol concentrationof 23.1g/Lafter 48hoffermentation at optimum conditions of pH and temperature.The growth kinetics was modeled using Monod model and Logistic model and product formation kinetics using Leudeking-Piret model.Simultaneous saccharificiation and fermenta-tion of liquefied wheat bran starch to bioethanol was studied using coculture of amylolytic fungus A.niger and nonamylolytic sugar fermenting K.marxianus.

Effect of a pulsating flow on hydrodynamics and fluid catalytic cracking chemical reaction in a circulating fluidized bed riser

The three-dimensional computational fuid dynamics(3D-CFD)of a pulsating flow applied to the fluid catalytic cracking(FCC)reaction was investigated in the riser of a circulating fluidized bed reactor.The kinetic parameters of the FCC and coke burning reactions for predicting the reactant conversion and product yield percentages were applied.To increase the reactant conversion level and product yield.the effect of the pulsating flow operating parameters was considered using a 2k statistical experimental design with four factors(amplitude,frequency,types of the waveform,and amplitude ratio).The 3DCFD simulation was successfully validated from the experimental literature data.The frequency and type of the waveform were found to be the significant operating parameters.The expression of the fitted regression model and response surface contour were derived and revealed that the pulsating flow provides a higher reactant conversion level and product yield percentages compared to a non-pulsating or steady flow.