Parameters optimization for direct contact membrane distillation based on orthogonal experiment

Parameter optimization integrating operation parameters and structure parameters for the purpose of high permeate flux,high productivity and low exergy consumption of direct contact membrane distillation (DCMD) process was conducted based on Taguchi experimental design. L16(45) orthogonal experiments were carried out with feed inlet temperature,permeate stream inlet temperature,flow rate,module packing density and length-diameter ratio as optimization parameters and with permeate flux,water productivity per unit volume of module and water production per unit exergy loss separately as optimization objectives. By using range analysis method,the dominance degree of the various influencing factors for the three objectives was analyzed and the optimum condition was obtained for the three objectives separately. Furthermore,the multi-objectives optimization was performed based on a weight grade method. The combined optimum conditions are feed inlet temperature 75℃,packing density 30% ,length-diameter ratio 10,permeate stream inlet temperature 30 ℃ and flow rate 25 L/h,which is in order of their dominance degree,and the validity of the optimization scheme was confirmed.

New Spam Filtering Method with Hadoop Tuning-Based MapReduce Naïve Bayes

As the importance of email increases,the amount of malicious email is also increasing,so the need for malicious email filtering is growing.Since it is more economical to combine commodity hardware consisting of a medium server or PC with a virtual environment to use as a single server resource and filter malicious email using machine learning techniques,we used a Hadoop MapReduce framework and Naïve Bayes among machine learning methods for malicious email filtering.Naïve Bayes was selected because it is one of the top machine learning methods(Support Vector Machine(SVM),Naïve Bayes,K-Nearest Neighbor(KNN),and Decision Tree)in terms of execution time and accuracy.Malicious email was filtered with MapReduce programming using the Naïve Bayes technique,which is a supervised machine learning method,in a Hadoop framework with optimized performance and also with the Python program technique with the Naïve Bayes technique applied in a bare metal server environment with the Hadoop environment not applied.According to the results of a comparison of the accuracy and predictive error rates of the two methods,the Hadoop MapReduce Naïve Bayes method improved the accuracy of spam and ham email identification 1.11 times and the prediction error rate 14.13 times compared to the non-Hadoop Python Naïve Bayes method.

Performance Improvement of Distributed Systems by Autotuning of the Configuration Parameters

The performance of distributed computing systems is partially dependent on configuration parameters recorded in configuration files. Evolutionary strategies, with their ability to have a global view of the structural information, have been shown to effectively improve performance. However, most of these methods consume too much measurement time. This paper introduces an ordinal optimization based strategy combined with a back propagation neural network for autotuning of the configuration parameters. The strat- egy was first proposed in the automation community for complex manufacturing system optimization and is customized here for improving distributed system performance. The method is compared with the covariance matrix algorithm. Tests using a real distributed system with three-tier servers show that the strategy reduces the testing time by 40% on average at a reasonable performance cost.

Potential energy curve study on the ^3Π electronic states of GaX （X=F, Cl, and Br） molecules

The potential energy curves （PECs） of the 3Π states of GaX （X=F, Cl, and Br） molecules are calculated using the multireference configuration interaction method with a large contracted basis set aug-cc-pV5Z. The PECs are accurately fitted to analytical potential energy functions （APEFs） using the Murrell–Sorbie potential function. The spectroscopic parameters for the states are determined using the obtained APEFs, and compared with the theoretical and experimental data available presently in the literature.

Analysis and Key Parameter Optimization Design of Leningrader Seal Performance

In order to improve the performance and service life of the Leningrader seal of the Stirling engine piston rod,interference,pre-load and friction coefficient were taken as influencing factors,and the curved surface response method was adopted to reduce the contact stress of sealing surface and von Mises stress of the sealing sleeve as the response index,with the optimization goal of reducing wear and extending life.The above three key parameters are analyzed and optimized,the influence of each parameter on the sealing performance and service life is obtained,and the best combination scheme of the three is determined.The results show that the interaction between pre-tightening force and interference fit has the greatest impact on contact stress.The interaction between interference fit and friction coeffi-cient has the most significant effect on von Mises stress.The optimized parameters can reduce the maximum contact stress and maximum von Mises stress of the sealing sleeve by 26.3%and 20.6%,respectively,under a media pressure of 5-9 MPa.Test bench verification shows that the leakage of the optimized sealing device in 12 h is reduced by 0.44 cc·min^(-1)(1 cc=1 cm^(3)).The wear rate of the sealing sleeve is 1.08%before optimization and 0.45%after optimization,indicating that the optimized parameters in this paper are effective.

Effects of Machine Tool Configuration on Its Dynamics Based on Orthogonal Experiment Method

In order to analyze the influence of configuration parameters on dynamic characteristics of machine tools in the working space, the configuration parameters have been suggested based on the orthogonal experiment method. Dynamic analysis of a milling machine, which is newly designed for producing turbine blades, has been conducted by utilizing the modal synthesis method. The finite element model is verified and updated by experimental modal analysis （EMA） of the machine tool. The result gained by modal synthesis method is compared with whole-model finite element method （FEM） result as well. According to the orthogonal experiment method, four configuration parameters of machine tool are considered as four factors for dynamic characteristics. The influence of configuration parameters on the first three natural frequencies is obtained by range analysis. It is pointed out that configuration parameter is the most important factor affecting the fundamental frequency of machine tools, and configuration parameter has less effect on lower-order modes of the system than others. The combination of configuration parameters which makes the fundamental frequency reach the maximum value is provided. Through demonstration, the conclusion can be drawn that the influence of configuration parameters on the natural frequencies of machine tools can be analyzed explicitly by the orthogonal experiment method, which offers a new method for estimating the dynamic characteristics of machine tools.

Experimental study on the key factors of low-loss threshing of high-moisture maize

The rates of maize breakage and entrainment loss are high in the harvest of high-moisture maize,which remains an issue with the development of agricultural mechanization.In order to reduce the maize breakage and entrainment loss rates,the correlations among key factors,such as the threshing cylinder speed,concave clearance and feeding rate,and the rates of breakage and entrainment loss during high-moisture maize harvesting were studied in this paper.A single-factor experiment was carried out using a single-longitudinal-axial flow maize harvester,and an orthogonal experiment was carried out using single-and double-longitudinal-axial flow maize harvesters with the Taguchi experimental design method.The single-factor experiment revealed that when the cylinder speed increased,the breakage rate of maize decreased first and then increased,while the entrainment loss rate decreased.The breakage rate of maize decreased as the concave clearance increased,while the entrainment loss rate decreased first and then increased.The optimum value of the concave clearance was positively correlated with the ear diameter of maize;Additionally,the minimum breakage rate of maize occurred when the feeding rate was at the rated value,and the entrainment loss rate increased as the feeding rate increased.The orthogonal experiments revealed that the importance of cylinder speed,feeding rate,concave clearance on the maize breakage and entrainment loss rates were in descending order.The optimum values of parameters for the single-longitudinal-axial flow maize harvester were 370 r/min cylinder speed,40 mm concave clearance and 10 kg/s feeding rate.The optimum values of parameters the double-longitudinal-axial flow maize harvester were 550 r/min cylinder speed,35 mm concave clearance and 10 kg/s feeding rate.The research can provide a reference for parameter configuration and control strategy for the longitudinal-axial flow maize harvester with high-moisture maize.