http://chineseinput.net/에서 pinyin(병음)방식으로 중국어를 변환할 수 있습니다.
변환된 중국어를 복사하여 사용하시면 됩니다.
- 中文 을 입력하시려면 zhongwen을 입력하시고 space를누르시면됩니다.
- 北京 을 입력하시려면 beijing을 입력하시고 space를 누르시면 됩니다.
RISS 인기검색어
- 검색키워드
- 저자 : Baorui Zhang (검색결과 2 건)
- 무료
- 기관 내 무료
- 유료
-
Yingying Zhang,Penghao Yu,Baorui Sun,Yi Zhou,Peijian Chen,Junhao Xu,Yushuai Zhao 대한토목학회 2024 KSCE Journal of Civil Engineering Vol.28 No.2
This paper investigated the seismic performance of a typical “Integrated Station-Bridge high-speed railway station structure with a composite isolation system. The influential mechanism of the structure with isolation system was analyzed based on shaking table tests, mainly investigating on the failure mode, acceleration response and displacement response. Besides, a parameter optimization method of isolation layer for long-span structures was proposed based on genetic algorithm to better enhance the isolation performance of the large-span structure. The research revealed that there was no obvious damage to the composite isolation system under the PGA = 0.82 g. The nature frequency of the structure with isolation system is only 12.5% of that of non-isolation structure. The first three natural vibration frequency of the structure with isolation system only reduce 3.4%, 3.2%, 6.14% after the PGA = 1.27 g, that of the non-isolation structure reduce by more than 20%. The acceleration amplification factor of each layer of composite isolation system is less than 1, in particular, that of truss is about 0.3. The displacement response and acceleration response of the structure with isolation system have been reduced by about 90%. The proposed optimization method of isolation layer parameters provides an important reference for the isolation design for high-speed railway stations.
-
Application of artificial neural network for the critical flow prediction of discharge nozzle
Hong Xu,Tao Tang,Baorui Zhang,Yuechan Liu 한국원자력학회 2022 Nuclear Engineering and Technology Vol.54 No.3
System thermal-hydraulic (STH) code is adopted for nuclear safety analysis. The critical flow model(CFM) is significant for the accuracy of STH simulation. To overcome the defects of current CFMs (lowprecision or long calculation time), a CFM based on a genetic neural network (GNN) has been developedin this work. To build a powerful model, besides the critical mass flux, the critical pressure and criticalquality were also considered in this model, which was seldom considered before. Comparing with thetraditional homogeneous equilibrium model (HEM) and the Moody model, the GNN model can predictthe critical mass flux with a higher accuracy (approximately 80% of results are within the ±20% errorlimit); comparing with the Leung model and the Shannak model for critical pressure prediction, the GNNmodel achieved the best results (more than 80% prediction results within the ±20% error limit). For thecritical quality, similar precision is achieved. The GNN-based CFM in this work is meaningful for the STHcode CFM development
ScienceON연관 검색어 추천
이 검색어로 많이 본 자료
활용도 높은 자료
