Yujie Xu

Storing Energy in China—An Overview

Abstract The research and development of electrical energy storage technologies for stationary applications in China is reviewed. Particular attention is paid to pumped hydroelectric storage, compressed air, flywheel, lead–acid battery, sodium–sulfur battery, lithium-ion battery, and flow battery energy storage. Research and development into electrical energy storage has experienced fast and fruitful development over the past (10–15) years in China, and by all accounts electrical energy storage has a bright future in China.

Coal partial gasification studies applied to co-production of hydrogen and electricity

To search for the optimum working condition of coal partial gasification for co-production of hydrogen and electricity, a gasifier has been simulated and studied by the use of an Aspen Plus model. Oxygen-to-coal ratio, steam-to-coal ratio and steam temperature are optimization variables of the system. The optimization variables impact on syngas yield, syngas concentration, system exergy efficiency, HER and CO2 separation rate have been analyzed. It is found that the oxygen-to-coal ratio and the steam-to-coal ratio both have large influence on performances of gasifer and system and the steam temperature has the least influence.

Improving an SVM-based Liver Segmentation Strategy by the F-score Feature Selection Method

A fast and accurate computer-aided liver segmentation plays a vital role in the virtual hepatic surgery. Large amount of features yielded in supervised segmentation methods may lead to slow training and classifying processes. Therefore, feature selection is of importance in order to speed up the liver segmentation. Recently, a hybrid method was proposed by Liu et al. combining thresholding, classifier and region growing. However, this method suffers from long process time caused by the large amount of features. F-score is a simple technique to measure the discrimination of different features. We therefore combine F-score to the hybrid method to reduce the time required in the training and testing stage.