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Heting Qiao,Shijie Wang,Tiejun Zhao,Henan Tang 대한기계학회 2019 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.33 No.2
This paper presents a hybrid algorithm for topology optimization of lightweight cellular materials and structures simultaneously by combining solid isotropic material with penalization (SIMP) and bi-directional evolutionary structural optimization (BESO). Microstructure of the lightweight cellular material is assumed unique in the structure to make the proposed method feasible. A new sensitivity analysis formula with respect to the discrete variable is derived by a principal submatrix stiffness matrix, by which the material can be effectively removed from or added to cellular. Moreover, the validity of the proposed method is then demonstrated through two numerical examples (a simple supported beam and a cantilever beam), which can be easily applied in a variety of practical situations.
Preparation and Characterization of A Semi-interpenetrating Network Alkaline Anion Exchange Membrane
Yifu Wang,Heting Wan,Dan Wang,Jilin Wang,Lulu Wang,Ruijiang Feng 한국섬유공학회 2018 Fibers and polymers Vol.19 No.1
A series of semi-interpenetrating network (semi-IPN) anion exchange membranes (QCS/St-G8-2-8, Quaternized chitosan/styrene-[maleic alkylene group diethyl bis (octyl dimethyl chloro/bromide), abbreviated as G8-2-8] were prepared via in-situ polymerization by Styrene (St) and G8-2-8 in QCS casting solution. During the process of in-situ polymerization, linearblock polymers (St-G8-2-8) of Styrene and G8-2-8 was constructed, then was mixed with QCS casting solution, followed crosslinking the QCS by glutaraldehyde (GA). With the increasing content of linear block polymer, water uptake and swelling ratio of the composite membrane decreased; This kind of linear structure makes an order arrangement of quaternaryammonium groups which improves the OH− migration efficiency. At 70 oC, the M-30 composite membrane performs a high OH− conductivity of 8.20×10-2 S·cm-1, the methanol permeability is 3.23×10-6 cm-2·s-1 which is still lower than Nafion 115 of 2.42×10-6 cm-2·s-1, but M-30 shows a higher selectivity of 25.3 than Nafion 115 of 11.6. Furthermore, the membranes exhibited excellent thermal stability (≥150 oC), the tensile strength of the composite membrane is in the range of 14-25 MPa and elongation at break is in the range of 16-37 % at room temperature, as well as superior chemical stability in 1.0 M KOH solution for 250 h.
Fuzzy Dynamic Sliding Mode Controller Design for Uncertain Nonlinear Markovian Jump Systems
Wenqiang Ji,Yujian An,Heting Zhang 제어·로봇·시스템학회 2019 International Journal of Control, Automation, and Vol.17 No.7
This paper investigates the problem of sliding mode control (SMC) for a class of uncertain nonlinearMarkovian jump systems through T-S fuzzy models. By adopting some convexification techniques, new results onstochastic stability analysis of the sliding motion are attained. Then two new SMC design approaches are proposedto force the closed-loop system states onto the sliding surface in finite time. Finally, two simulation examples areshown to verify the effectiveness of the proposed approaches.
Use of High-performance Graphics Processing Units for Power System Demand Forecasting
He, Ting,Meng, Ke,Dong, Zhao-Yang,Oh, Yong-Taek,Xu, Yan The Korean Institute of Electrical Engineers 2010 Journal of Electrical Engineering & Technology Vol.5 No.3
Load forecasting has always been essential to the operation and planning of power systems in deregulated electricity markets. Various methods have been proposed for load forecasting, and the neural network is one of the most widely accepted and used techniques. However, to obtain more accurate results, more information is needed as input variables, resulting in huge computational costs in the learning process. In this paper, to reduce training time in multi-layer perceptron-based short-term load forecasting, a graphics processing unit (GPU)-based computing method is introduced. The proposed approach is tested using the Korea electricity market historical demand data set. Results show that GPU-based computing greatly reduces computational costs.