Study on an improved rotating microchannel separator in the intensification for demulsification and separation process

An improved rotating microchannel(IRM) separator was further explored in the intensification for demulsification and separation process. Oil-in-water(O/W) emulsion system of 2-ethylhexyl phosphoric acid-2-ethylhexyl ester(P507)–water without emulsifier was employed to evaluate the performance of the new equipment. In this experiment, the influence on demulsification separation process was explored by changing the geometrical structure and channel height of the microchannel and combining the liquid–liquid two-phase flow pattern, and the correlation general graph between demulsification efficiency and dimensionless parameters was established. The total demulsification effect of the IRM and the separation capacity of the clear organic phase recovered from demulsification are significantly improved. In addition, the liquid–liquid two-phase flow pattern of the clear organic phase after demulsification and the remaining emulsion in the IRM are observed and recorded by high-speed photography. The separation ability of organic phase from the upper outlet can be significantly improved when the total demulsification rate of IRM is up to 90%. There are 3 types and 6 kinds of flow patterns observed. The results demonstrated that the suitable demulsification performance is obtained when the liquid–liquid two-phase inside the IRM is in a parallel pattern. Finally, the relation map between total demulsification efficiency and the universal flow is drawn, which provides a basis for the accurate control of the IRM device.

Developing super-hydrophobic and corrosion-resistant coating on magnesium-lithium alloy via one-step hydrothermal processing

Formation of super-hydrophobic and corrosion-resistant coatings can provide significant corrosion protection to magnesium alloys.However,it remains a grand challenge to produce such coatings for magnesium-lithium alloys due to their high chemical reactivity.Herein,a one-step hydrothermal processing was developed using a stearic-acid-based precursor medium,which enables the hydrothermal conversion and the formation of low surface energy materials concurrently to produce the super-hydrophobic and corrosion-resistant coating.The multiscale microstructures with nanoscale stacks and microscale spheres on the surface,as well as the through-thickness stearates,lead to the super-hydrophobicity and excellent corrosion resistance of the obtained coating.

Polarimetric Meteorological Satellite Data Processing Software Classification Based on Principal Component Analysis and Improved K-Means Algorithm

With the increasing variety of application software of meteorological satellite ground system, how to provide reasonable hardware resources and improve the efficiency of software is paid more and more attention. In this paper, a set of software classification method based on software operating characteristics is proposed. The method uses software run-time resource consumption to describe the software running characteristics. Firstly, principal component analysis (PCA) is used to reduce the dimension of software running feature data and to interpret software characteristic information. Then the modified K-means algorithm was used to classify the meteorological data processing software. Finally, it combined with the results of principal component analysis to explain the significance of various types of integrated software operating characteristics. And it is used as the basis for optimizing the allocation of software hardware resources and improving the efficiency of software operation.

In situ digital testing method for quality assessment of soft soil improvement with polyurethane

This study purposes an in situ testing method on quality assessment of soil improvement.Factual drilling data includes the spatial distribution and in situ strength of untreated and treated soil along three different drillholes measured by on-site drilling monitoring method.These factual drilling data can characterize the degree of soil improvement by penetration injection with permeable polyurethane.Result from on-site drilling monitoring shows that the linear zones represent constant drilling speeds shown in the plot of drill bit advancement vs.net drilling time,which indicates the spatial distributions of soil profile.The soil profile at the study site is composed of four layers,which includes fill,untreated silty clay,treated silty clay,and mucky soil.The results of soil profile are verified by the parallel site loggings.The constant drilling speeds profile the coring-resistant strength of drilled soils.By comparing with the untreated silty clay,the constant drilling speeds of the treated silty clay have been decreased by 13.0-62.8%.Two drilling-speed-based indices of 61.2%and 65.6%are proposed to assess the decreased average drilling speed and the increased in situ strength of treated silty clay.Laboratory tests,i.e.uniaxial compressive strength(UCS)test,have been performed with core sample to investigate and characterize in situ strength by comparing that with drilling speeds.Results show that the average predicted strengths of treated silty clay are 2.4-6.9 times higher than the average measured strength of untreated silty clay.The UCS-based indices of 374.5%and 344.2%verified the quality assessment(QA)results by this new in situ method.This method provides a cost-effective tool for quality assessment of soil improvement by utilizing the digital drilling data.

Synthesis of Anatase TiO_2 Nanoparticles by Improved Sol-Gel Process at Low Temperature

The nanocrystalline TiO_2 powder were prepared by improved sol-gel method at low temperature under ambient pressure. The prepared TiO_2 powder was characterized by X-ray diffraction (XRD), transmission electron microscopy (TEM). It is found that the yield of anatase TiO_2 significantly increases with the reduction of pH by increasing the nucleation rate of anatase. There is an optimum amount of water in sol for the formation of anatase by combining two effects on the concentration of Ti(OH)_4 in gels. Increasing in reaction temperature also benefit to the nucleation of anatase of TiO_2.

Energy-Efficient Process Planning Using Improved Genetic Algorithm

Nowadays,energy consumption which closely contacts with environmental impacts of manufacturing processes has been highly commented as a new productivity criterion.However,little attention has paid to the development of process planning methods that take energy consumption into account.An energy-efficient process planning model that incorporates manufacturing time and energy consumption is proposed.For solving the problem,an improved genetic algorithm method is employed to explore the optimal solution.Finally,a case study for process planning is given.The experimental result generates interesting effort,and therefore allows improving the energy efficiency of manufacturing processes in process planning.

Optimization of Generator Based on Gaussian Process Regression Model with Conditional Likelihood Lower Bound Search

The noise that comes from finite element simulation often causes the model to fall into the local optimal solution and over fitting during optimization of generator.Thus,this paper proposes a Gaussian Process Regression(GPR)model based on Conditional Likelihood Lower Bound Search(CLLBS)to optimize the design of the generator,which can filter the noise in the data and search for global optimization by combining the Conditional Likelihood Lower Bound Search method.Taking the efficiency optimization of 15 kW Permanent Magnet Synchronous Motor as an example.Firstly,this method uses the elementary effect analysis to choose the sensitive variables,combining the evolutionary algorithm to design the super Latin cube sampling plan;Then the generator-converter system is simulated by establishing a co-simulation platform to obtain data.A Gaussian process regression model combing the method of the conditional likelihood lower bound search is established,which combined the chi-square test to optimize the accuracy of the model globally.Secondly,after the model reaches the accuracy,the Pareto frontier is obtained through the NSGA-II algorithm by considering the maximum output torque as a constraint.Last,the constrained optimization is transformed into an unconstrained optimizing problem by introducing maximum constrained improvement expectation(CEI)optimization method based on the re-interpolation model,which cross-validated the optimization results of the Gaussian process regression model.The above method increase the efficiency of generator by 0.76%and 0.5%respectively;And this method can be used for rapid modeling and multi-objective optimization of generator systems.

Immune Clone Maximum Likelihood Estimation of Improved Non-homogeneous Poisson Process Model Parameters

Aiming at the solving problem of improved nonhomogeneous Poisson process( NHPP) model in engineering application,the immune clone maximum likelihood estimation( MLE)method for solving model parameters was proposed. The minimum negative log-likelihood function was used as the objective function to optimize instead of using iterative method to solve complex system of equations,and the problem of parameter estimation of improved NHPP model was solved by immune clone algorithm. And the interval estimation of reliability indices was given by using fisher information matrix method and delta method. An example of failure truncated data from multiple numerical control( NC) machine tools was taken to prove the method. and the results show that the algorithm has a higher convergence rate and computational accuracy, which demonstrates the feasibility of the method.

A Multi-feature Fusion Apple Classification Method Based on Image Processing and Improved SVM

In order to achieve accurate classification of apple, a multi-feature fusion classification method based on image processing and improved SVM was proposed in this paper. The method was mainly divided into four parts, including image preprocessing, background segmentation, feature extraction and multi-feature fusion classification with improved SVM. Firstly, the homomorphic filtering algorithm was used to improve the quality of apple images. Secondly, the images were converted to HLS space. The background was segmented by the QTSU algorithm. Morphological processing was employed to remove fruit stem and surface defect areas. And apple contours were extracted with the Canny algorithm. Then, apples’ size, shape, color, defect and texture features were extracted. Finally, the cross verification method was used to optimize the penalty factor in SVM. A multi-feature fusion classification model was established. And the weight of each index was calculated by Fisher. In this study, 146 apple samples were selected for training and 61 apple samples were selected for testing. The test results showed that the accuracy of the classification method proposed in this paper was 96.72%, which can provide a reference for apple automatic classification.

AN IMPROVED NONADIABATIC COLLISION MODEL FOR ION-PIR FORMATION PROCESS:A+BC→A^++BC^- Zheng Ting CAI and Yu Guang MU

Hickman's fast nonadiabatic collision model for the ion-pair formation reaction A+BC→A^++BC^- was improved,where the classical trajectory has been represented by solution of motion equation UR=-dV(R)/dR, here V(R)is Morse potential.Employing this model to the CS+O_2→CS^++O_2^-reaction,a satisfactory agreement with experimental data has been obtained.

Sustainable food waste management using modified fuzzy improved analytic hierarchy process:a study of Malaysia

Food waste generation is a pressing issue that requires urgent attention and concerted efforts worldwide.The staggering amount of food wasted each year not only wastes valuable resources but also exacerbates environmental,economic,and social challenges.Food Waste Management(FWM)consists of a complex array of criteria and sub-criteria,and treatments which seems interdependent.There is a need to evaluate the FWM with the help of important criteria and sub-criteria and treatments to address this challenge.In this study,we identified four important criteria,21 sub-criteria,and four alternatives of FWM for the case of Malaysia using the integrated approach of literature review and expert opinions.Further,we employed the approach of Modified Fuzzy Improved Analytical Hierarchy Process(IAHP)to corroborate the interrelationships among the identified criteria and sub-criteria,and their associated treatments.This study undertakes linear normalization methods to transform data into comparable numerical values and the Geometric Mean method to handle uncertainty in human judgments.Moreover,the Centroid method is employed to convert fuzzy weights into crisp sets for ease of interpretation.The results indicate that environmental is the most essential criterion,followed by social,economic,and technical.In addition,air and water pollution is identified as the most critical sub-criteria.Black Soldier Fly is discovered as the most sustainable FWM treatment,since it performs the best while meeting all the criteria and sub-criteria assessed.Sensitivity analysis demonstrates that the outputs from the proposed method are robust and reliable.The finding suggests a proper and robust approach to help decision-makers select suitable FWM treatments to tackle various criteria and alternatives especially when handling inconsistent and uncertain judgments during evaluation.

A rapid one-step electrodeposition process for fabrication of superhydrobic surfaces on anode and cathode

This work presents a method to solve the weak solubility of zinc chloride(ZnCl_2) in the ethanol by adding some reasonable water into an ethanol electrolyte containing ZnCl_2 and myristic acid(CH_3(CH_2)_(12)COOH).A rapid one-step electrodeposition process was developed to fabricate anodic(2.5 min) and cathodic(40 s) superhydrophobic surfaces of copper substrate(contact angle more than 150°) in an aqueous ethanol electrolyte.Morphology,composition,chemical structure and superhydrophobicity of these superhydrophobic surfaces were investigated by SEM,FTIR,XRD,and contact angle measurement,respectively.The results indicate that water ratio of the electrolyte can reduce the required deposition time,superhydrophobic surface needs over 30 min with anhydrous electrolyte,while it needs only 2.5 min with electrolyte including 10 mL water,and the maximum contact angle of anodic surface is 166° and that of the cathodic surface is 168°.Two copper electrode surfaces have different reactions in the process of electrodeposition time,and the anodic copper surface covers copper myristate(Cu[CH_3(CH_2)_(12)COO]_2) and cupric chloride(CuCl);while,zinc myristate(Zn[CH_3(CH_2)_(12)COO]_2) and pure zinc(Zn) appear on the cathodic surface.

Improvement Detecting Method of Optical Axes Parallelism of Shipboard Photoelectrical Theodolite Based on Image Processing

An improvement detecting method was proposed according to the disadvantages of testing method of optical axes parallelism of shipboard photoelectrical theodolite (short for theodolite) based on image processing. Pointolite replaced 0.2'' collimator to reduce the errors of crosshair images processing and improve the quality of image. What’s more, the high quality images could help to optimize the image processing method and the testing accuracy. The errors between the trial results interpreted by software and the results tested in dock were less than 10'', which indicated the improve method had some actual application values.

An Improved Immune Algorithm for Solving Path Optimization Problem in Deep Immune Learning of Gene Network

In order to overcome some defects of the traditional immune algorithm, the immune algorithm was improved for solving a path optimization problem in deep immune learning of a gene network. Firstly, the diversity of the solution population was enhanced in the evolution process by improving the memory cell processing method. Moreover, effective gene information was dynamically extracted from the genes of the excellent antibodies to make good vaccines in the process of immune evolution. Worse antibodies were optimized by vaccinating these antibodies, and the convergence of the immune algorithm to the optimal solution was improved. Finally, the feasibility of the improved immune algorithm was verified in the experimental simulation for solving the classic NP problem in deep immune learning of the gene network.

Analysis of the factors affecting the fuel rate in the COREX process and improvement measures

Increasing production capacity and operating rate, reducing fuel rates and costs of hot metal （HM） are the urgent tasks for the COREX process. In this study ,the various factors on the fuel consumption of COREX are researched from the theoretical analysis based on the calculations of material balances and heat balances. Combined with the production performances and practices of COREX-2000 （ Saldanha, India） and COREX-3000 （ Baosteel ）, the technical measures of reducing the fuel rate are analyzed and the way forward of technical innovation is addressed and discussed with the standpoint of the COREX process improvement.

Statistical Analysis of Process Monitoring Data for Software Process Improvement and Its Application

Software projects influenced by many human factors generate various risks. In order to develop highly quality software, it is important to respond to these risks reasonably and promptly. In addition, it is not easy for project managers to deal with these risks completely. Therefore, it is essential to manage the process quality by promoting activities of process monitoring and design quality assessment. In this paper, we discuss statistical data analysis for actual project management activities in process monitoring and design quality assessment, and analyze the effects for these software process improvement quantitatively by applying the methods of multivariate analysis. Then, we show how process factors affect the management measures of QCD (Quality, Cost, Delivery) by applying the multiple regression analyses to observed process monitoring data. Further, we quantitatively evaluate the effect by performing design quality assessment based on the principal component analysis and the factor analysis. As a result of analysis, we show that the design quality assessment activities are so effective for software process improvement. Further, based on the result of quantitative project assessment, we discuss the usefulness of process monitoring progress assessment by using a software reliability growth model. This result may enable us to give a useful quantitative measure of product release determination.

Heat Transfer Analysis During "One-Step" Directional Solidification Process for Giant Magnetostrictive Materials

By theoretical analysis of heat transfer during the "one-step" directional solidification process, the functional relation between the temperature in solid-liquid interface and its effect factor was studied. The thermal gradient in solid liquid interface and heat transfer coefficient between the samples and surroundings were also calculated. On the basis of the above analysis, some suggestions for improving the thermal gradient in solid-liquid interface were put forward. It will provide a theoretical instruction for preparing high performance giant magnetostrictive materials (GMM).

Research on Knowledge Transfer Influencing Factors in Software Process Improvement

Knowledge transfer model of software process improvement (SPI) and the conceptual framework of influencing factors are established. The model includes five elements which are knowledge of transfer, sources of knowledge, recipients of knowledge, relationship of transfer parties, and the environment of transfer. The conceptual framework includes ten key factors which are ambiguity, systematism, transfer willingness, capacity of impartation, capacity of absorption, incen-tive mechanism, culture, technical support, trust and knowledge distance. The research hypothesis is put forward. Em-pirical study concludes that the trust relationship among SPI staffs has the greatest influence on knowledge transfer, and organizational incentive mechanism can produce positive effect to knowledge transfer of SPI. Finally, some sug-gestions are put forward to improve the knowledge transfer of SPI: establishing a rational incentive mechanism, exe-cuting some necessary training to transfer parties and using software benchmarking.

Research on Explicit and Tacit Knowledge Interaction in Software Process Improvement Project

This research develops a knowledge model for Software Process Improvement (SPI) project based on knowledge creation theory and its twenty-four measurement items, and proposes two hypothesizes about the interaction of explicit knowledge and tacit knowledge in SPI. Eleven factors are extracted through statistical analysis. Three knowledge-creation practices for capturing tacit knowledge contribute greatly to SPI, which are communication among members, crossover collaboration in practical work and pair programming. Two knowledge-creation practices for capturing explicit knowledge have significant positive impact on SPI, which are integrating project document and on-the-job training. Ultimately, suggestions for improvement are put forward, that is, encouraging communication among staff and integrating documents in real time, and future research is also illustrated.

Empirical Research on Critical Success Factors of Agile Software Process Improvement

In this paper, we discuss agile software process improvement in P company with their description of process management in current level and analysis of problems, design the P Company success factors model in organizational culture, systems, products, customers, markets, leadership, technology and other key dimensions, which is verified through questionnaire in P company. In the end, we apply knowledge creation theory to analyze the open source software community with successful application of the typical agile software method, propose ten principles of knowledge creation in open source software community: Self-organizing, Code sharing, Adaptation, Usability, Sustention, Talent, Interaction, Collaboration, Happiness, and Democracy.