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RISS 인기검색어
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- 저자 : Liwei Fan (검색결과 5 건)
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Liwei Fan,Reti Hai,Zexiang Lu 한국화학공학회 2009 Korean Journal of Chemical Engineering Vol.26 No.5
A subsurface flow constructed wetland (SSFW) was simulated by using a commercial computational fluid dynamic (CFD) code (Fluent 6.22, Fluent Inc.). The liquid residence time distribution in the SSFW was obtained by the particle trajectory model. The simulation confirmed that the effect of the distribution and/or catchment area on the hydraulic efficiency is significant. An inappropriate horizontal distribution and/or catchment area can result in poor hydraulic efficiency. The hydraulic efficiency of the SSFW with the vertical distribution and/or catchment area can be kept at a high level (above 0.898). The design of the vertical distribution and/or catchment area in the SSFW is better than that of the horizontal. From the point of view of the engineering design, a small dimension distribution and/or catchment area in the SSFW is advisable, which maintains a considerable hydraulic efficiency of the SSFW (above 0.840), but also benefits the increase of the purge area.
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Yutian Fan,Liwei Lu,Tao Zhou,Hua Zhang,Fugang Qi,Min Ma,Zhiqiang Wu,Weitao Jia,Sha Zhang,Weiying Huang 대한금속·재료학회 2023 METALS AND MATERIALS International Vol.29 No.10
In this work, a novel process of repeated upsetting-extrusion (RUE) was used to fabricate the AQ80 magnesium (Mg) alloy. The effects of deformation passes on the microstructure and microhardness of the RUEed AQ80 Mg alloy were studied. The results showed that {10–12} extension twins appeared in the sample after 1 pass of deformation compared to the initial sample, which divided the coarse grains and achieved the preliminary refinement of the grains. The grains were uniformly refined further with increasing RUE deformation passes, and after 3 passes, the average grain size was reduced from 27.4 to 3.0 μm. The grains were refined mainly by continuous dynamic recrystallization (CDRX), particle-stimulated nucleation (PSN), and discontinuous dynamic recrystallization (DDRX) mechanisms. After RUE deformation, the peak component of the texture was tilted by 0–20° toward the extrusion direction (ED) because of the increased activation of pyramidal < c + a > slip. The microhardness of the 3-pass RUE deformed sample increased by 12.9% compared to the initial sample. This is mainly attributable to fine-grained strengthening and second phase strengthening.
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Yang Fan,Liu Kai,Zhu Liwei,Hu Jiayuan,Wang Xiaoyu,Shen Xiaoming,Luo Hanwu,Ammad Jadoon 한국자기학회 2017 Journal of Magnetics Vol.22 No.1
In order to detect the current flowing through concealed conductor, this paper proposes a new method based on derivative method. Firstly, this paper analyzes the main peak characteristic of the derivative function of magnetic field generated by a current-carrying conductor, and a relationship between the current flowing through the conductor and the main peak of the derivative function is obtained and applied to calculate the current. Then, the method is applied to detect the conductor current flowing through grounding grids of substations. Finally, the numerical experimental and field experiment verified the feasibility and accuracy of the method, and the computing results show that the method can effectively measure the conductor current of grounding grids with low error, and the error is within 5 %.
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Load Prediction Based on Optimization Ant Colony Algorithm
Li Wei,Tang Jingmin,Ma Han,Fan Min,Liu Simiao,Wang Jie 대한전기학회 2023 Journal of Electrical Engineering & Technology Vol.18 No.1
Short-term load in the power system is associated with huge computational consumption and low model utilization. Large input fluctuation tends to increase the training error of the neural network prediction model and reduce its generalization ability. To cope with this problem, this study aimed to introduce a method of radial basis function neural network algorithm based on least squares support vector machine algorithm. Based on the electricity market in an area of Yunnan province, the short-term loads were forecasted with historical data. First, the ant colony algorithm was improved using the chaos theory. Second, the improved ant colony was used to search least squares support vector machine and output the optimal parameters of the model. Then, the optimized model was used to train the data samples, and the output regression machine was used to provide better structures and parameters for the radial basis function neural network. The findings showed that compared with multiple prediction methods, the algorithm in this paper reduces the learning time and improves the fitting degree of the algorithm on the basis of improving the prediction accuracy. It shows that the algorithm in this paper has great advantages and good application prospects.
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Load Prediction Based on Optimization Ant Colony Algorithm
Li Wei,Tang Jingmin,Ma Han,Fan Min,Liu Simiao,Wang Jie 대한전기학회 2023 Vol.18 No.1
Short-term load in the power system is associated with huge computational consumption and low model utilization. Large input fl uctuation tends to increase the training error of the neural network prediction model and reduce its generalization ability. To cope with this problem, this study aimed to introduce a method of radial basis function neural network algorithm based on least squares support vector machine algorithm. Based on the electricity market in an area of Yunnan province, the short-term loads were forecasted with historical data. First, the ant colony algorithm was improved using the chaos theory. Second, the improved ant colony was used to search least squares support vector machine and output the optimal parameters of the model. Then, the optimized model was used to train the data samples, and the output regression machine was used to provide better structures and parameters for the radial basis function neural network. The fi ndings showed that compared with multiple prediction methods, the algorithm in this paper reduces the learning time and improves the fi tting degree of the algorithm on the basis of improving the prediction accuracy. It shows that the algorithm in this paper has great advantages and good application prospects.
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