Effect of droplet characteristics on liquid-phase distribution in spray zone of internal mixing air-mist nozzle

In continuous casting production,droplet characteristics are important parameters for evaluating the nozzle atomization quality,and have a significant impact on the secondary cooling effect and the slab quality.In order to study the behavior of atomized droplets after reaching the slab surface and to optimize the spray cooling effect,the influence of droplet diameter and droplet velocity on the migration behavior of droplets in the secondary cooling zone was analyzed by FLUENT software.Results show that the droplets in the spray zone and on the slab surface are mainly concentrated in the center,thus,the liquid volume fraction in the center is higher than that of either side.As the droplet diameter increases,the region of high liquid volume fraction on the slab surface becomes wider,and the liquid phase distribution in the slab width direction becomes uneven.Although increasing the droplet velocity at the nozzle exit has little effect on droplet diffusion in the spray zone,the distribution becomes more uneven due to more liquid reaches the slab surface per unit time.A prediction formula of the maximum water flow rate on the slab surface for specific droplet characteristics was proposed based on dimensionless analysis and validated by simulated data.A nozzle spacing of 210 mm was recommended under the working conditions in this study,which ensures effective coverage of the spray water over the slab surface and enhances the distribution uniformity of water flow rate in the transverse direction.

The New Mixed Generalized Erlang Distribution

In probability theory, the mixture distribution M has a density function for the collection of random variables and weighted by wi ≥ 0 and . These mixed distributions are used in various disciplines and aim to enrich the collection distribution to more parameters. A more general mixture is derived by Kadri and Halat, by proving the existence of such mixture by wi ∈ R, and maintaining . Kadri and Halat provided many examples and applications for such new mixed distributions. In this paper, we introduce a new mixed distribution of the Generalized Erlang distribution, which is derived from the Hypoexponential distribution. We characterize this new distribution by deriving simply closed expressions for the related functions of the probability density function, cumulative distribution function, moment generating function, reliability function, hazard function, and moments.

Analysis of College Students’ Test Scores Based on Two-Component Mixed Generalized Normal Distribution

In order to improve the fitting accuracy of college students’ test scores, this paper proposes two-component mixed generalized normal distribution, uses maximum likelihood estimation method and Expectation Conditional Maxinnization (ECM) algorithm to estimate parameters and conduct numerical simulation, and performs fitting analysis on the test scores of Linear Algebra and Advanced Mathematics of F University. The empirical results show that the two-component mixed generalized normal distribution is better than the commonly used two-component mixed normal distribution in fitting college students’ test data, and has good application value.

Improving source-in-the-middle continuous-variable quantum key distribution using a heralded hybrid linear amplifier

A hybrid linear amplifier is inserted at the output of the source-in-the-middle distribution protocol to overcome the shortcomings of the transmission distance.The modified protocol aims to maintain a high key rate for long-distance transmission under high noise.It has the potential to significantly broaden the application range of the continuous variable quantum key distribution protocol.The effects of amplifier parameters and noise on the modified protocol are analyzed in detail with regard to applying it to a practical system.To make the simulation more realistic,the effect of finite size on the new protocol is taken into account.It will serve as a guideline for the future use of hybrid linear amplifiers.Different parameters can be adjusted to achieve the best performance for key rates of different quantum channels.

Behavioral Decision-Making of Key Stakeholders in Public-Private Partnerships:A Hybrid Method and Benefit Distribution Study

Public-private partnerships(PPPs)have been used by governments around the world to procure and construct infrastructural amenities.It relies on private sector expertise and funding to achieve this lofty objective.However,given the uncertainties of project management,transparency,accountability,and expropriation,this phenomenon has gained tremendous attention in recent years due to the important role it plays in curbing infrastructural deficits globally.Interestingly,the reasonable benefit distribution scheme in a PPP project is related to the behavior decisionmaking of the government and social capital,aswell as the performance of the project.In this paper,the government and social capital which are the key stakeholders of PPP projects were selected as the research objects.Based on the fuzzy expected value model and game theory,a hybrid method was adopted in this research taking into account the different risk preferences of both public entities and private parties under the fuzzy demand environment.To alleviate the problem of insufficient utilization of social capital in a PPP project,this paper seeks to grasp the relationship that exists between the benefit distribution of stakeholders,their behavioral decision-making,and project performance,given that they impact the performance of both public entities and private parties,as well as assist in maximizing the overall utility of the project.Furthermore,four game models were constructed in this study,while the expected value and opportunity-constrained programming model for optimal decision-making were derived using alternate perspectives of both centralized decision-making and decentralized decision-making.Afterward,the optimal behavioral decision-making of public entities and private parties in four scenarios was discussed and thereafter compared,which led to an ensuing discussion on the benefit distribution system under centralized decision-making.Lastly,based on an example case,the influence of different confidence levels,price,and fuzzy uncertainties of PPP projects on the equilibrium strategy results of both parties were discussed,giving credence to the effectiveness of the hybrid method.The results indicate that adjusting different confidence levels yields different equilibriumpoints,and therefore signposts that social capital has a fair perception of opportunities,as well as identifies reciprocal preferences.Nevertheless,we find that an increase in the cost coefficient of the government and social capital does not inhibit the effort of both parties.Our results also indicate that a reasonable benefit distribution of PPP projects can assist them in realizing optimum Pareto improvements over time.The results provide us with very useful strategies and recommendations to improve the overall performance of PPP projects in China.

Multicomponent mixed metallic hierarchical ZnNi@Ni@PEDOT arrayed structures as advanced electrode for high-performance hybrid electrochemical cells

Engineering multicomponent nanomaterials as an electrode with rationalized ordered structures is a promising strategy for fulfilling the high-energy storage needs of supercapacitors(SCs).Even now,the fundamental barrier to utilizing hydroxides/hydroxyl carbonates is their poor electrochemical performance,resulting from the significantly poor electrical conductivity and sluggish charge storage kinetics.Hence,a multilayered structural approach is primarily and successfully used to construct electrodes as one of the efficient approaches.This method has made it possible to develop well-ordered nanostructured electrodes with good performance by taking advantage of tunable approach parameters.Herein,we report the design of multilayered heterostructure porous zinc-nickel nanosheets@nickel flakes hydroxyl carbonates and/or hydroxides integrated with conductive PEDOT fibrous network(i.e.,ZnNi@Ni@PEDOT) via facile synthesis methods.The combined hybrid electrode acquires the features of high electrical conductivity from one part and various valance states from another one to develop a well-organized nanosheet/flake/fibrous-like heterostructure with decent mechanical strength,creating robust synergistic results.Thus,the designed binder-free ZnNi@Ni@PEDOT electrode delivers a high areal capacity value of 1050.1 μA h cm^(-2) at 3 mA cm^(-2) with good cycling durability,significantly outperforming other individual electrodes.Moreover,its feasibility is also tested by constructing a hybrid electrochemical cell(HEC).The assembled HEC exhibits a high areal capacity value of 783.8 μA h cm^(-2) at5 mA cm^(-2).and even at a high current density of 100 mA cm^(-2)(484.6 μA h cm^(-2)),the device still retains a rate capability of 61,82%,Also,the HEC shows maximum energy and power densities of0.595 mW h cm^(-2) and 77.23 mW cm^(-2),respectively,along with good cycling stability.The obtained energy storage capabilities effectively power various electronic components.These results provide a viable and practical way to construct a positive electrode with innovative heterostructures for highperformance energy storage devices and profoundly influence the development of electrochemical SCs.

A Novel Mixed Precision Distributed TPU GAN for Accelerated Learning Curve

Deep neural networks are gaining importance and popularity in applications and services.Due to the enormous number of learnable parameters and datasets,the training of neural networks is computationally costly.Parallel and distributed computation-based strategies are used to accelerate this training process.Generative Adversarial Networks(GAN)are a recent technological achievement in deep learning.These generative models are computationally expensive because a GAN consists of two neural networks and trains on enormous datasets.Typically,a GAN is trained on a single server.Conventional deep learning accelerator designs are challenged by the unique properties of GAN,like the enormous computation stages with non-traditional convolution layers.This work addresses the issue of distributing GANs so that they can train on datasets distributed over many TPUs(Tensor Processing Unit).Distributed learning training accelerates the learning process and decreases computation time.In this paper,the Generative Adversarial Network is accelerated using the distributed multi-core TPU in distributed data-parallel synchronous model.For adequate acceleration of the GAN network,the data parallel SGD(Stochastic Gradient Descent)model is implemented in multi-core TPU using distributed TensorFlow with mixed precision,bfloat16,and XLA(Accelerated Linear Algebra).The study was conducted on the MNIST dataset for varying batch sizes from 64 to 512 for 30 epochs in distributed SGD in TPU v3 with 128×128 systolic array.An extensive batch technique is implemented in bfloat16 to decrease the storage cost and speed up floating-point computations.The accelerated learning curve for the generator and discriminator network is obtained.The training time was reduced by 79%by varying the batch size from 64 to 512 in multi-core TPU.

Power Quality Improvement Using ANN Controller For Hybrid Power Distribution Systems

In this work,an Artificial Neural Network(ANN)based technique is suggested for classifying the faults which occur in hybrid power distribution systems.Power,which is generated by the solar and wind energy-based hybrid system,is given to the grid at the Point of Common Coupling(PCC).A boost converter along with perturb and observe(P&O)algorithm is utilized in this system to obtain a constant link voltage.In contrast,the link voltage of the wind energy conversion system(WECS)is retained with the assistance of a Proportional Integral(PI)controller.The grid synchronization is tainted with the assis-tance of the d-q theory.For the analysis of faults like islanding,line-ground,and line-line fault,the ANN is utilized.The voltage signal is observed at the PCC,and the Discrete Wavelet Transform(DWT)is employed to obtain different features.Based on the collected features,the ANN classifies the faults in an effi-cient manner.The simulation is done in MATLAB and the results are also validated through the hardware implementation.Detailed fault analysis is carried out and the results are compared with the existing techniques.Finally,the Total harmonic distortion(THD)is lessened by 4.3%by using the proposed methodology.

Simulation and Exploration of the Mechanisms Underlying the Spatiotemporal Distribution of Surface Mixed Layer Depth in a Large Shallow Lake

The aquatic eco-environment is significantly affected by temporal and spatial variation of the mixed layer depth （MLD） in large shallow lakes. In the present study, we simulated the three-dimensional water temperature of Taihu Lake with an unstructured grid with a finite-volume coastal ocean model （FVCOM） using wind speed, wind direction, short-wave radiation and other meteorological data measured during 13-18 August 2008. The simulated results were consistent with the measurements. The temporal and spatial distribution of the MLD and the possible relevant mechanisms were analyzed on the basis of the water temperature profile data of Taihu Lake. The results indicated that diurnal stratification might be established through the combined effect of the hydrodynamic conditions induced by wind and the heat exchange between air and water. Compared with the net heat flux, the changes of the MLD were delayed approximately two hours. Furthermore, there were significant spatial differences of the MLD in Taihu Lake due to the combined impact of thermal and hydrodynamic forces. Briefly, diurnal stratification formed relatively easily in Gonghu Bay, Zhushan Bay, Xukou Bay and East Taihu Bay, and the surface mixed layer was thin. The center of the lake region had the deepest surface mixed layer due to the strong mixing process. In addition, Meiliang Bay showed a medium depth of the surface mixed layer. Our analysis indicated that the spatial difference in the hydrodynamic action was probably the major cause for the spatial variation of the MLD in Taihu Lake.

Estimation of Wave Crest Amplitudes Distribution and Freak Wave Occurrence in A Short Crested Mixed Sea

In this study we have for the first time proposed a novel transformed linear simulation method for the estimation of wave crest amplitudes distribution and freak wave occurrence in a short crested mixed sea with a bimodal 3D spectrum. For implementing the proposed transformed linear simulation method, a Hermite transformation model expressed in a monotonic cubic polynomial has been constructed so that the first four moments of the original true process match the corresponding moments of the transformed model. The proposed novel simulation method has been applied to forecast the freak wave occurrence in two short crested mixed sea states, one with a directional wave spectrum based on the measured surface elevation data at the coast of Yura, and the other one with a typical directional bimodal Torsethaugen wave spectrum. It is shown in the two cases that the proposed novel simulation method can offer more accurate forecasting results than those obtained from the traditional linear simulation method or by using Rayleigh distribution model. It is also demonstrated in this article that the proposed novel simulation method is more efficient than the nonlinear simulation method.

Reliability Estimation of Aviation Pyrotechnics System Based on Mixed Beta Distribution

For evaluating reliability of an aviation pyrotechnics system,a Bayesian reliability estimation method utilizing reliability information of a system and its units was put forward. Firstly,an inheritance factor was determined by chi-square goodness of fit test.Then the mixed prior distribution was obtained based on the inheritance factor. Finally, the density function of posterior distribution was obtained and used to assess the reliability of system.According to the new method, the reliability of an aviation pyrotechnics system was evaluated to reach 0. 989 6 at the confidence level of 0. 90. To reach the reliability index,the required numbers of trials of system and its units were given. It is instructional to apply the new method on the reliability estimation of aviation pyrotechnics systems.

Introducing the Mixed Distribution in Fitting Rainfall Data

Several types of mixed distribution are proposed and tested in order to determine the best model in describing daily rainfall amount in Peninsular Malaysia for the time period of 33 years. A mixed distribution is a mixture of discrete and continuous daily rainfall which included the dry days. The mixed distributions tested in this study were exponential distribution, gamma distribution, weibull distribution and lognormal distribution. The model will be selected based on the Akaike Information Criterion (AIC). In general, the mixed lognormal distribution has been selected as the best model for most of the rain gauge stations in Peninsular Malaysia. However, these results are greatly influenced by the topographical, geographical and climatic changes of the rain gauge stations.

Exponential distribution-based genetic algorithm for solving mixed-integer bilevel programming problems

Two classes of mixed-integer nonlinear bilevel programming problems are discussed. One is that the follower＇s functions are separable with respect to the follower＇s variables, and the other is that the follower＇s functions are convex if the follower＇s variables are not restricted to integers. A genetic algorithm based on an exponential distribution is proposed for the aforementioned problems. First, for each fixed leader＇s variable x, it is proved that the optimal solution y of the follower＇s mixed-integer programming can be obtained by solving associated relaxed problems, and according to the convexity of the functions involved, a simplified branch and bound approach is given to solve the follower＇s programming for the second class of problems. Furthermore, based on an exponential distribution with a parameter λ, a new crossover operator is designed in which the best individuals are used to generate better offspring of crossover. The simulation results illustrate that the proposed algorithm is efficient and robust.

A New Approach for Parameter Estimation of Mixed Weibull Distribution:A Case Study in Spindle

In order to improve the accuracy and efficiency of graphical method and maximum likelihood estimation( MLE) in Mixed Weibull distribution parameters estimation,Graphical-GA combines the advantage of graphical method and genetic algorithm( GA) is proposed.Firstly,with the analysis of Weibull probability paper( WPP),mixed Weibull is identified to data fitting.Secondly,the observed value of shape and scale parameters are obtained by graphical method with least square,then optimizing the parameters of mixed Weibull with GA.Thirdly,with the comparative analysis on graphical method,piecewise Weibull and two-Weibull,it shows graphical-GA mixed Weibull is the best.Finally,the spindle MTBF point estimation and interval estimation are got based on mixed Weibull distribution.The results indicate that graphical-GA are improved effectively and the evaluation of spindle can provide the basis for design and reliability growth.

Capacity of unsignalized intersection with mixed distribution headway

In order to describe the time-headway distribution more precisely in urban traffic network,the mixed distribution model was introduced which has been widely used in mathematical statistics,and a capacity model of unsignalized intersections was obtained based on gap acceptance theory.The new model is suitable for absolute and limited priority controlled conditions and can be regarded as a more general form which handles simple headway distributions including lognormal distribution,negative exponential distribution and shifted negative exponential distribution.Through analyses of the main influencing factors in this model,the proportion of free flowing and the standard variance of gaps between any two continuous following vehicles are high sensitivity with the capacity when major stream volume is low.Besides,the capacity is affected deeply by the mean value of following vehicle gaps when major stream value is fixed and the proportion of free flowing is small.At last,the observed minor stream capacity is obtained by the survey date in Changchun city,and the average relative error between the theoretical capacity proposed in this paper is 13.73%,meanwhile the accuracy increases by 16.68% compared with the theoretical value when major stream obeys shifted negative exponential distribution.

Parameter Estimation of Mixed Weibull Distributions Using Cuckoo Search

The lifetime data of products with multiple failure modes which are collected from life testing are often fitted by the mixed Weibull distributions. Since the mixed Weibull distributions contain no less than five parameters,the parameter estimation is difficult and inaccurate. In order to enhance the accuracy,a new method of parameter estimation based on Cuckoo search( CS) is proposed. An optimization model for the mixed Weibull distribution is formulated by minimizing the residual sum of squares. The optimal parameters are searched via CS algorithm. In the case study,the lifetime data come from the life testing of diesel injectors and are fitted by the twocomponent Weibull mixture. Regarding the maximum absolute error and the accumulative absolute error between estimated and observed values as the accuracy index of parameter estimation,the results of four parameter estimation methods that the graphic estimation method,the nonlinear least square method,the optimization method based on particle swarm optimization( PSO) and the proposed method are compared. The result shows that the proposed method is more efficient and more accurate than the other three methods.

Spatial and Temporal Distributions of Soil Organic Matter in the Mixed Plantations of Alder and Cypress in the Hilly Areas of Central Sichuan Basin

The investigation was conducted on the spatial and temporal distributions of soil organic mater （SOM） in the mixed plantations of alder （Aluns crernastogyne） and cypress （Cupressus funebris ） （MPAC）, which distributed in the hilly areas of central Sichuan Basin （HACSB）. The results show that： （1） the spatial distribution of SOM among different sites at the same age are not significant before 15-year-old, but significant at 20-year-old, and not significant again after 25-year-old; （2） the SOM contents in 0-15 cm and 15-30 cm layers increase sharply from 10- to 15-year-old, and decline gradually from 15- to 30- year-old; the SOM contents of the 30-year-old PCP were 80. 38% and 78.42% higher than that of the 10-year-old, but 29.16% and 53.37% lower than that of 15-year-old in the 0-15 cm and 15-30 cm layers, respectively. The decrease of SOM contents would lead to the degradation of soil fertility and the decline of forest productivity.

Clustering-based maintainability demonstration for complex systems with a mixed maintenance time distribution

During maintainability demonstration,the maintenance time for complex systems consisting of mixed technologies generally conforms to a mixture distribution.However existing maintainability standards and guidance do not explain explicitly how to deal with this situation.This paper develops a comprehensive maintainability demonstration method for complex systems with a mixed maintenance time distribution.First of all,a K-means algorithm and an expectation-maximization(EM)algorithm are used to partition the maintenance time data for all possible clusters.The Bayesian information criterion(BIC)is then used to choose the optimal model.After this,the clustering results for equipment are obtained according to their degree of membership.The degree of similarity for the maintainability of different kinds of equipment is then determined using the projection method.By using a Bootstrap method,the prior distribution is obtained from the maintenance time data for the most similar equipment.Then,a test method based on Bayesian theory is outlined for the maintainability demonstration.Finally,the viability of the proposed approach is illustrated by means of an example.

Microfluidic Behavior of Ternary Mixed Carrier Solvents Based on the Tube Radial Distribution in Triple-Branched Microchannels in a Microchip

Microfluidic behavior of ternary mixed carrier solvents of water-acetonitrile-ethyl acetate (2:3:1 volume ratio) was examined by use of a microchip incorporating microchannels in which one wide channel was separated into three narrow channels, i.e., triple-branched microchannels. When the ternary carrier solution containing the fluorescent dyes, hydrophobic perylene (blue) and relatively hydrophilic Eosin Y (green), was fed into the wide channel under laminar flow conditions, the carrier solvent molecules or fluorescence dyes were radially distributed in the channel, forming inner (organic solvent-rich major;blue) and outer (water-rich minor;green) phases in the wide channel. And then, in the narrow channels, perylene molecules mostly appeared to flow through the center narrow channel and Eosin Y, which is distributed in the outer phases in the wide channel, flowed through the both side narrow channels. A metal ion, Cu(II) as a model, dissolved in the ternary mixed carrier solution was also examined. The Cu(II) showed fluidic behavior, transferring from the homogeneous carrier solution to the water-rich solution in the side narrow channels through the triple-branched microchannels.

Robust Variance Components Estimation in the PERG Mixed Distributions of Empirical Variances—PEROBVC Method

A mixed distribution of empirical variances, composed of two distributions the basic and contaminating ones, and referred to as PERG mixed distribution of empirical variances, is considered. In the paper a robust inverse problem solution is given, namely a (new) robust method for estimation of variances of both distributions—PEROBVC Method, as well as the estimates for the numbers of observations for both distributions and, in this way also the estimate of contamination degree.