http://chineseinput.net/에서 pinyin(병음)방식으로 중국어를 변환할 수 있습니다.
변환된 중국어를 복사하여 사용하시면 됩니다.
Layout Optimization for Blended Wing Body Aircraft Structure
Wensheng Zhu,Xiongqing Yu,Yu Wang 한국항공우주학회 2019 International Journal of Aeronautical and Space Sc Vol.20 No.4
Structural layout design of blended wing body (BWB) aircraft in the preliminary design phase is a challenging optimization problem due to large numbers of design variables and various constraints. A two-loop optimization strategy is proposed to solve the BWB aircraft structural layout design problem considering constraints of the displacement, stress, strain, and buckling. The two-loop optimization consists of an inner loop and an outer loop. The inner loop is to optimize each stiffened panel of the BWB aircraft structure, and outer loop is to find the best layout design. To improve computational efficiency, an equivalent finite element model is applied to BWB aircraft structure analysis, and an analytical method is used for buckling and static analysis of the stiffened panels. The proposed method can efficiently solve the structural layout optimization problem of a notional BWB aircraft with acceptable computational burden. The result indicates the mass of main load-carrying structure of the BWB aircraft is reduced by 9.28% compared to that of the initial structural layout.
Combining ICA and SVR in Times Series Predication
Wensheng Dai,Jui-Yu Wu,Chi-Jie Lu 인하대학교 정석물류통상연구원 2009 인하대학교 정석물류통상연구원 학술대회 Vol.2009 No.10
In this paper, a time series prediction approach by combing independent component analysis (ICA) and support vector regression (SVR)is proposed ICA is a novel statistical signal processing technique that was originally proposed to find the latent source signals from observed mixture signal without knowing any prior knowledge of the mixing mechanism. SVR is and artificial intelligence forecasting technique and has been widely applied in time series prediction problems. The proposed approach First uers ICA to the forecasting variables for generating the independent components(ICs). After identifying and removing the ICs containing the noise, the rest of the ICs are then used to reconstruct the forecasting variables which contain less noise. The SVR then uses the denoised forecasting variables to build the forecausting model. in order to evaluaate the performance of the proposed approach the TAIEX(Taiwan Stock Exchange Capitalization weighted Steock index) closing cash index is usde as the illusrtative example. Experimental results show that the proposed model outperforms the SVR model with mon ?filtered forecasting variables and random walk model
Jing Yao,Xinlu Wang,Xinru Zhao,Jinxian Wang,Hongbo Zhang,Wensheng Yu,Guixia Liu,Xiangting Dong 대한금속·재료학회 2016 ELECTRONIC MATERIALS LETTERS Vol.12 No.6
The Li2MnO3-modified Li1.2NixCo0.1Mn0.9-xO2 (x = 0.2, 0.45, 0.7)as cathode materials for lithium-ion batteries have beensuccessfully synthesized by a simple electrospinning process. Thestructure, morphology and electrochemical performances of theresulting products are studied systematically. The as-preparedLi2MnO3-modified Li1.2NixCo0.1Mn0.9-xO2 (x = 0.2, 0.45, 0.7) with adiameter of 200-300 nm has an initial discharge capacity of168.740 mAh·g−1, coulombic efficiency of 99.6% and a reversiblecapacity as high as 139.016 mAh·g−1 after 200 cycles at a currentrate of 0.2 C. The excellent electrochemical performances ofwhich are attributed to the stabilization of Li2MnO3 structure, therole of Li2MnO3 is contribute extra lithium to the reversiblecapacity and to facilitate Li+ transport through the structure.