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| 1 | Fractal kinetic characteristics for dissolving and leaching processes of strontium residue显示文摘The pore structural characteristics of strontium residue were studied with the N2 adsorption method(ASAP2010).The kinetic properties concerning dissolving and leaching strontium waste were described by determining the concentrations of Sr2+,Ba2+ and soluble sulphides in solutions.The results showed that the specific surface area and pore volume increased with decreasing granule diameter,and the micropore surface of the residue was fractal.In the dissolving and leaching processes of strontium residue,soluble ion concentrations increased with decreasing granule diameter of the residue,and the reaction dimension was lower than the fractal dimension of pore surface.Sr2+ and soluble sulphide concentrations significantly exceeded the defined standard values,while Ba2+ concentrations did not,either in the dissolving or leaching solutions.In addition,dissolving and leaching reactions selectively occurred on the micropore surface of strontium residue. | XU Longjun WANG Xingmin QU Ge ZHOU Zhengguo YUE Fenhua | 2010 | Chinese Journal Of Geochemistry2010，29，4： | 4 |
| 2 | 在碳隐遁,土壤保留和水之间的交易在中国的 Guanzhong-Tianshui 经济区域让步显示文摘自然生态系统向人的社会提供很重要的产品和服务。随人口和自然资源的在利用上的快速的增加,人不断地在损坏其它的情况下正在提高一些服务的生产。这份报纸在中国的 Guanzhong-Tianshui 经济区域在生态系统服务,和在这些服务之间的关系估计变化。这些生态系统变化具有到这个经济区域的持续发展的大意义。生产可能性边疆(PPF ) 的概念被使用评估在碳隐遁,水收益和土壤保留之间的交易和协同作用。三陆地使用策略计划情形,使用评估潜力的利用和保护在生态系统服务变化。这研究表明在碳隐遁,土壤保留和水之间的显著交易让步,与在碳隐遁和土壤保留之间的协同作用。在在三种情形的碳隐遁,水收益和土壤保留之间有协同作用。保护情形是为调整生态系统服务能力的最赞成的陆地使用策略。这种情形导致最高的碳隐遁,水收益和土壤保留。结果能有含意因为计划的自然资本和生态系统服务,管理和土地使用决策。 | YANG Xiaonan ZHOU Zixiang LI Jing FU Xin MU Xingmin LI Ting | 2016 | Journal of Geographical Sciences2016，26，10： | 3 |
| 3 | Ecological basis of alpine mead-ow ecosystem management in Tibet:Haibei alpine meadow e-cosystem research station显示文摘 | Zhao Xinquan Zhou Xingmin | 1999 | A Journal of the Human Envi-ronment1999，28，8： | 1 |
| 4 | Ecological basis of alpine meadow ecosystem management in Tibet: llaibei alpine meadow ecosystem research station显示文摘 | Zhao Xinquan Zhou Xingmin | 1999 | Ambio1999，28，： | 1 |
| 5 | A spanwise loss model for axial compressor stator based on machine learning显示文摘In the early stage of aircraft engine design, the through-flow method is an important tool for designers. The accuracy of the through-flow method depends heavily on the accuracy of the loss model. However, most existing models cannot(or cannot well) provide the spanwise loss distribution. To construct an effective spanwise loss model, both turbomachinery knowledge and machine learning skills were used in this paper. A large number of numerical simulations were carried out to build a database containing more than 1000 compressor cascade numerical samples. Secondary flow intensity was introduced as the independent variable to carry out feature engineering. A model containing a selector based on support vector machine regression and estimators based on K-nearest neighbor regression was constructed. Numerical test set and design data of two former highpressure core compressors were used for validation. Results suggest that the spanwise loss model show good consistency with both numerical test set and data of two former compressors. It can reflect the influence of secondary flow and can also predict both value and trend of total pressure loss coefficient well, with mean absolute error general around or less than 1% and R^(2)(coefficient of determination) more than 0.8 on the test set. Especially when dealing with loss coefficient at midspan position, the model shows even better performance, with R^(2)over 0.97 on the test set. And the selector of the model can well classify the samples, predict the intensity of secondary flow and help estimators to capture the phenomenon that end-wall secondary flow extends to the mid-span. | Zixuan YUE Chenghua ZHOU Donghai JIN Xingmin GUI | 2022 | Chinese Journal of Aeronautics2022，35，11： | 0 |
| 6 | Experimental search for high-performance ferroelectric tunnel junctions guided by machine learning显示文摘Ferroelectric tunnel junction(FTJ)has attracted considerable attention for its potential applications in nonvolatile memory and neuromorphic computing.However,the experimental exploration of FTJs with high ON/OFF ratios is a challenging task due to the vast search space comprising of ferroelectric and electrode materials,fabrication methods and conditions and so on.Here,machine learning(ML)is demonstrated to be an effective tool to guide the experimental search of FTJs with high ON/OFF ratios.A dataset consisting of 152 FTJ samples with nine features and one target attribute(i.e.,ON/OFF ratio)is established for ML modeling.Among various ML models,the gradient boosting classification model achieves the highest prediction accuracy.Combining the feature importance analysis based on this model with the association rule mining,it is extracted that the utilizations of{graphene/graphite(Gra)(top),LaNiO_(3)(LNO)(bottom)}and{Gra(top),Ca_(0.96)Ce_(0.04)MnO_(3)(CCMO)(bottom)}electrode pairs are likely to result in high ON/OFF ratios in FTJs.Moreover,two previously unexplored FTJs:Gra/BaTiO_(3)(BTO)/LNO and Gra/BTO/CCMO,are predicted to achieve ON/OFF ratios higher than 1000.Guided by the ML predictions,the Gra/BTO/LNO and Gra/BTO/CCMO FTJs are experimentally fabricated,which unsurprisingly exhibit≥1000 ON/OFF ratios(~8540 and~7890,respectively).This study demonstrates a new paradigm of developing high-performance FTJs by using ML. | Jingjing Rao Zhen Fan Qicheng Huang Yongjian Luo Xingmin Zhang Haizhong Guo Xiaobing Yan Guo Tian Deyang Chen Zhipeng Hou Minghui Qin Min Zeng Xubing Lu Guofu Zhou Xingsen Gao Jun-Ming Liu | 2022 | Journal of Advanced Dielectrics2022，12，3： | 0 |
| 7 | Numerical and experimental investigation of quantitative relationship between secondary flow intensity and inviscid blade force in axial compressors显示文摘The secondary flow attracts wide concerns in the aeroengine compressors since it has become one of the major loss sources in modern high-performance compressors.But the research about the quantitative relationship between secondary flow and inviscid blade force needs to be more detailed.In this paper,a database of 889 three-dimensional linear cascades was built.An indicator,called Secondary Flow Intensity(SFI),was used to express the loss caused by secondary flow.The quantitative relationship between the SFI and inviscid blade force deterioration was researched.Blade oil flow and Computation Fluid Dynamics(CFD)results of some cascades were also used to cross-validate.Results suggested that all numerical cascade cases can be divided into 3 clusters by the SFI,which are called Clusters A,B and C in the order of the increasing SFI indicator.The corner stall,known as the strong corner separation,only happens when the SFI is high.Both calculations and oil flow experiments show that the SFI would stay at a low level if the vortex core at the endwall surface does not appear.The strong interaction of Kutta condition and endwall cross-flow is considered the dominant mechanism of higher secondary flow losses,rather than the secondary flow penetration depth on the suction surface.In conclusion,the inviscid blade force spanwise deterioration is strongly related to the SFI.The correlation of the SFI and spanwise inviscid blade force deterioration is given in this paper.The correlation could provide a quantitative reference for estimating secondary flow losses in the design. | Chenghua ZHOU Zixuan YUE Hanwen GUO Xiwu LIU Donghai JIN Xingmin GUI | 2023 | Chinese Journal of Aeronautics2023，36，10： | 0 |
| 8 | Efficient subtree results computation for XML keyword queries显示文摘 | Ziyang CHEN | 2015 | Frontiers of Computer Science2015，9，2： | 0 |
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