BDQC-2C型定量装车控制仪的应用

金陵分公司油品装车车间的22个柴油装车鹤位全部安装了BDQC-2C型定量装车控制仪，并与操作室的上位机联网，组成一套完整的定量装车控制系统，该系统的定量设置既可以在装车现场通过本地控制面板设定预装量，也可以在操作室通过计算机设置预装量，当实装量达到预装量时，定量控制仪发出关阀指令．关闭阀门，结束装车操作，实现了装车操作的定量控制。

Implementation of Efficient Burst Assembly Algorithm with Traffic Prediction

This paper reports on the implementation of efficient burst assembly algorithms and traffic prediction. The ultimate goal is to propose a new burst assembly algorithm which is based on time-burst length （hybrid） threshold with traffic prediction to reduce burst assembly delay in OBS （Optical Burst Switching） networks. Research has shown that traffic always change from time to time, hence, any measure that is put in place should be able to adapt to such changes. With our implemented burst assembly algorithm, the traffic rate is predicted and the predicted rate is used to dynamically adjust the burst assembly length. This work further investigates the impact of the proposed algorithm on traffic self similarity.

Effects of automatic variable preload device on performance of spindle

To increase the machine accuracy by improving the stiffness of bearings,a preload was applied to bearings.A variable preload technology was necessary to perform machining processes in both low and high speed regions.An automatic variable preload device was fabricated using an eccentric mass.By installing the fabricated device on a spindle,the effect of the automatic variable preload device on the performance of the spindle was analyzed.In the results of the vibration measurement of the spindle,the vibration is increased by 20%-37% according to measurement points at the maximum rotation speed of 5 000 r/min.And,in the results of the noise measurement of the spindle,the spindle rotation speed is increased by about 1.9% and 1.5% at the front and side of the spindle,respectively.Based on the results of this analysis,an improved method that reduces such effects on the performance of the spindle is proposed.

Synthesis of Mesoporous Chromium Silicates Molecular Sieves in Strong Acidic Media by Assembly of Preformed CrS1 Precursors with Triblock Copolymer

Chromium-incorporated mesoporous silica materials （MCrS） have been successfully prepared in strong acidic media by assembly of preformed CrSI precursors with triblock copolymer of the Pluronic type （P123） by a two steps procedure. Various techniques including XRD, N2 adsorption, FT-IR spectroscopy, diffuse reflectance UV-vis （DRUV-vis） and EPR were employed for the materials characterization. MCrS materials have a hexagonal structure with uniform mesopores and contain Cr（V） and Cr（VI） under low and high Cr content and that the mesoporous walls contain the MFI structure building units.

An Evaluation of South Korean Container Sea Port Development Policy

As Busan New Port has been developed with a total scale of 30 berths in 2020, the chronic problem of Busan port, a lack of port facilities, is being addressed, and there is a growing interest in regard to port development with an optimal scale. The Korean container port development under the master plan for national port development reveals a severe problem of excess supply of port facility in some ports. This paper, the authors analysed the second and the third master plan for national port development implemented in 2001 and 2011, and a revised plan in 2006, along with the amended predictions for container throughput. Furthermore, the effectiveness of the implementation of the initial plan, and the current situation of South Korea＇s main container ports of Busan, Gwangyang, Incheon, and Pyeongtaek ＆ Dangjin was examined. Through the analysis of port vitalizations, we have examined the actual problems for the prediction of container throughput. Also, this research analysed the functional difference of each port and organized the function of each one discriminatively. Therefore, identifies the problems, which arise with making the container throughput forecasts, which is a fimdamental aspect of existing port development policy, and suggest a direction for future port development by synthesizing the results of analysis.

Numerical Noise Prediction in Fluid Machinery

Numerical methods successively became important in the design and optimization of fluid machinery. However, as noise emission is considered, one can hardly find standardized prediction methods combining flow and acoustical optimization. Several numerical field methods for sound calculations have been developed. Due to the complexity of the considered flow, approaches must be chosen to avoid exhaustive computing. In this contribution the noise of a simple propeller is investigated. The configurations of the calculations comply with an existing experimental setup chosen for evaluation. The used in-house CFD solver SPARC contains an acoustic module based on Ffowcs Williams-Hawkings Acoustic Analogy. From the flow results of the time dependent Large Eddy Simulation the time dependent acoustic sources are extracted and given to the acoustic module where relevant sound pressure levels are calculated. The difficulties, which arise while proceeding from open to closed rotors and from gas to liquid are discussed.

Forecasting Container Throughput of Qingdao Port with a Hybrid Model

This paper proposes a hybrid forecasting method to forecast container throughput of Qingdao Port.To eliminate the influence of outliers,local outlier factor(lof) is extended to detect outliers in time series,and then different dummy variables are constructed to capture the effect of outliers based on domain knowledge.Next,a hybrid forecasting model combining projection pursuit regression(PPR) and genetic programming(GP) algorithm is proposed.Finally,the hybrid model is applied to forecasting container throughput of Qingdao Port and the results show that the proposed method significantly outperforms ANN,SARIMA,and PPR models.

A TRANSFER FORECASTING MODEL FOR CONTAINER THROUGHPUT GUIDED BY DISCRETE PSO

Abstract Accurate forecast of future container throughput of a port is very important for its con struction, upgrading, and operation management. This study proposes a transfer forecasting model guided by discrete particle swarm optimization algorithm （TF-DPSO）. It firstly transfers some related time series in source domain to assist in modeling the target time series by transfer learning technique, and then constructs the forecasting model by a pattern matching method called analog complexing. Finally, the discrete particle swarm optimization algorithm is introduced to find the optimal match between the two important parameters in TF-DPSO. The container throughput time series of two im portant ports in China, Shanghai Port and Ningbo Port are used for empirical analysis, and the results show the effectiveness of the proposed model.