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RISS 인기검색어
- 검색키워드
- 저자 : Qifeng Gao (검색결과 2 건)
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Qifeng Gao,Jun Ye,Bingfeng Wang,Jin Zhao 한국유체기계학회 2019 International journal of fluid machinery and syste Vol.12 No.3
In order to study the unsteady pressure pulsation and internal flow in a centrifugal pump under low flow rate, numerical calculation of a centrifugal pump was carried out. The accuracy of the numerical calculation method was verified with the external characteristic test. The characteristics of the unsteady pressure pulsation and internal flow of the centrifugal pump were analyzed in detail. The results show that the interaction between the impeller and the volute has a significant effect on the unsteady pressure pulsation of the centrifugal pump. The essential reason of the periodic pressure pulsation was explained, and the evolution of separation vortex formation and collapse in the impeller was presented. Regulation of the generation and development of the high pressure zone in the volute was revealed. With the reduction of the flow rate, the influence of the low pressure zone in the impeller is enhanced and the pressure near the volute tongue is decreased. The results can provide a reference for the centrifugal pump design and optimization.
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Layout Optimization Method of Railway Transportation Route Based on Deep Convolution Neural Network
Cong Qiao,Qifeng Gao,Huayan Xing 한국정보처리학회 2023 Journal of information processing systems Vol.19 No.1
To improve the railway transportation capacity and maximize the benefits of railway transportation, a methodfor layout optimization of railway transportation route based on deep convolution neural network is proposedin this study. Considering the transportation cost of railway transportation and other factors, the layout modelof railway transportation route is constructed. Based on improved ant colony algorithm, the layout model ofrailway transportation route was optimized, and multiple candidate railway transportation routes were output. Taking into account external information such as regional information, weather conditions and actual informationof railway transportation routes, optimization of the candidate railway transportation routes obtained bythe improved ant colony algorithm was performed based on deep convolution neural network, and the optimalrailway transportation routes were output, and finally layout optimization of railway transportation routes wasrealized. The experimental results show that the proposed method can obtain the optimal railway transportationroute, the shortest transportation length, and the least transportation time, maximizing the interests of railwaytransportation enterprises.
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