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RISS 인기검색어
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- 저자 : Lingfeng Luo (검색결과 3 건)
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Lingfeng Luo,Deshan Shan,Miao He 대한토목학회 2021 KSCE JOURNAL OF CIVIL ENGINEERING Vol.25 No.10
This paper presents an accurate sampling method for suspension-bridge finite element (FE) model updating. The proposed method utilizes a coupled suspension-bridge modeling approach, which integrates a numerical shape-finding method with conventional FE analysis to efficiently achieve parametric modeling during the sampling process. This study also employs the Nelder-Mead algorithm (NMA) to ensure the efficiency and robustness of the numerical shape-finding calculation. First, the accuracy of the NMA-based coupled modeling approach is examined by numerical investigation of the baseline model of an actual suspension bridge. Then, the computational results of two groups of samples with different sample sizes are compared to test the efficiency of the proposed method. Finally, by relying on the structural health monitoring (SHM) system of this bridge, the measured natural frequencies over half a year are identified, and almost all of them are within the calculated sample space.Therefore, the feasibility of the proposed suspension-bridge FE model sampling method is validated by the uncertainties of the measured responses over half a year.
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Mold design and forming process parameters optimization for passenger vehicle front wing plate
Wenbin Luo,Lingfeng Tang,Fucheng Guo 대한기계학회 2022 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.36 No.1
The main objective of the present article is to solve the problems of poor molding quality, large warpage, inadequate cooling effect and unsuitable selection of process parameters, in the injection molding process for passenger vehicle front-end plastic wing plate. The thickness and parting surface of the vehicle front-end fender were determined, the injection mold and its cooling system were designed. The relevant process parameters, affecting the product molding quality, were tested, according to orthogonal experimental approach, while their influence on the warpage was obtained, by analyzing the data. Finally, the BP neural network of warpage model was established and globally optimized using genetic algorithm. The optimal parameter combination of the injection molding process was derived as: melt temperature 236 °C, mold temperature 51 °C, cooling time 32 s, packing pressure 97 MPa and packing time 16 s.
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Analytical Solution of Loosening Pressure Model for Shallow Tunnel Based on Pile-beam-arch Method
Tao Li,Zhongyu Zhang,Muchi Luo,Bo Liu,Yanlong Wang,Lingfeng Li 대한토목학회 2022 KSCE JOURNAL OF CIVIL ENGINEERING Vol.26 No.8
Loosening of earth pressure by tunnels is an important parameter for the structural design of subway stations, this study analyzes the difference between the loosening pressures of each span of a shallow multi-span tunnel station using the pile-beam-arch (PBA) method. By conducting a similarity model test of the PBA method, we simulate the complete excavation process. We study the sliding failure mode of the overlying soil of the shallow-buried station and the law of change of the loosening pressure of each span. A simplified calculation model for the loosening pressure of shallow buried multi-span tunnels by the cavity pile method was developed, and the applicability of the formulae and sensitivity analysis of the parameters were carried out. The results reveal that the loosening pressure of the mid-span is transferred to the stress of the side-span during tunnel excavation. This finding contradicts Terzaghi’s and Bierbaumer’s methods, which do not consider the influence of tunnel structure on the loosening pressure of the overlying soil. The side span relaxation pressure is only related to the soil capacity and the depth of burial of the tunnel This research can provide an important theoretical reference for the design of the overburden load and lateral confining pressure of the PBA structure design.
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