The influence of enlarged section parameters on pressure transients of high-speed train passing through a tunnel was investigated by numerical simulation.The calculation results obtained by the structured and unstruct...The influence of enlarged section parameters on pressure transients of high-speed train passing through a tunnel was investigated by numerical simulation.The calculation results obtained by the structured and unstructured grid and the experimental results of smooth wall tunnel were verified.Numerical simulation studies were conducted on three tunnel enlarged section parameters,the enlarged section distribution along circumferential direction,the enlarged section area and the enlarged section distribution along tunnel length direction.The calculation results show that the influence of the different enlarged section distributions along tunnel circumferential direction on pressure transients in the tunnel is basically consistent.There is an optimal enlarged section area for the minimum value of the pressure variation amplitude and the average pressure variation in the tunnel.The law of the pressure variation amplitude and the average pressure variation of the enlarged section distribution along tunnel length direction are obtained.展开更多
To overcome the limitations of low efficiency and reliance on manual processes in the measurement of geometric parameters for bridge prefabricated components,a method based on deep learning and computer vision is deve...To overcome the limitations of low efficiency and reliance on manual processes in the measurement of geometric parameters for bridge prefabricated components,a method based on deep learning and computer vision is developed to identify the geometric parameters.The study utilizes a common precast element for highway bridges as the research subject.First,edge feature points of the bridge component section are extracted from images of the precast component cross-sections by combining the Canny operator with mathematical morphology.Subsequently,a deep learning model is developed to identify the geometric parameters of the precast components using the extracted edge coordinates from the images as input and the predefined control parameters of the bridge section as output.A dataset is generated by varying the control parameters and noise levels for model training.Finally,field measurements are conducted to validate the accuracy of the developed method.The results indicate that the developed method effectively identifies the geometric parameters of bridge precast components,with an error rate maintained within 5%.展开更多
The water contamination on the side windows of moving vehicles is a crucial issue in improving the driving safety and the comfort.In this paper,an effective optimization method is proposed to reduce the water contamin...The water contamination on the side windows of moving vehicles is a crucial issue in improving the driving safety and the comfort.In this paper,an effective optimization method is proposed to reduce the water contamination on the side windows of automobiles.The accuracy and the efficiency of the numerical simulation are improved by using the lattice Boltzmann method,and the Lagrangian particle tracking method.Optimized parameters are constructed on the basis of the occurrence of the water deposition on a vehicle’s side window.The water contamination area of the side window and the aerodynamic drag are considered simultaneously in the design process;these two factors are used to form the multi-objective optimization function in the genetic algorithm(GA)method.The approximate model,the boundary-seeded domain method,and the GA method are combined in this study to enhance the optimization efficiency.After optimization,the optimal parameters for the A-pillar section are determined by setting the boundary to an area of W=7.77 mm,L=1.27 mm and H=11.22 mm.The side window’s soiling area in the optimized model is reduced by 66.93%,and the aerodynamic drag is increased by 0.41%only,as compared with the original model.It is shown that the optimization method can effectively solve the water contamination problem of side windows.展开更多
We proposed a new approach to determination of Judd-Ofelt intensity parameters of Er^（3＋） doped phosphors via their absorption spectra. To validate this approach, JO parameters of Er^（3＋） doped Ba BaGd_2ZnO_5/PM...We proposed a new approach to determination of Judd-Ofelt intensity parameters of Er^（3＋） doped phosphors via their absorption spectra. To validate this approach, JO parameters of Er^（3＋） doped Ba BaGd_2ZnO_5/PMMA and NaYF_4/PMMA composites were calculated and in a good agreement with the other glass and crystal. The spontaneous radiative transition probability, branching ratio, and radiative lifetime of the optical transitions were calculated by using the Judd-Ofelt theory. Intense near-infrared emission at 1553 nm was observed under 980 nm laser diode excitation at room temperature. The samples possessing high full-width at half-maximum reach 85 nm have potential application in broadband optical amplifier.展开更多
基金Project (2016YFB1200602-11) supported by National Key R&D Plan of China
文摘The influence of enlarged section parameters on pressure transients of high-speed train passing through a tunnel was investigated by numerical simulation.The calculation results obtained by the structured and unstructured grid and the experimental results of smooth wall tunnel were verified.Numerical simulation studies were conducted on three tunnel enlarged section parameters,the enlarged section distribution along circumferential direction,the enlarged section area and the enlarged section distribution along tunnel length direction.The calculation results show that the influence of the different enlarged section distributions along tunnel circumferential direction on pressure transients in the tunnel is basically consistent.There is an optimal enlarged section area for the minimum value of the pressure variation amplitude and the average pressure variation in the tunnel.The law of the pressure variation amplitude and the average pressure variation of the enlarged section distribution along tunnel length direction are obtained.
基金The National Natural Science Foundation of China(No.52338011,52378291)Young Elite Scientists Sponsorship Program by CAST(No.2022-2024QNRC0101).
文摘To overcome the limitations of low efficiency and reliance on manual processes in the measurement of geometric parameters for bridge prefabricated components,a method based on deep learning and computer vision is developed to identify the geometric parameters.The study utilizes a common precast element for highway bridges as the research subject.First,edge feature points of the bridge component section are extracted from images of the precast component cross-sections by combining the Canny operator with mathematical morphology.Subsequently,a deep learning model is developed to identify the geometric parameters of the precast components using the extracted edge coordinates from the images as input and the predefined control parameters of the bridge section as output.A dataset is generated by varying the control parameters and noise levels for model training.Finally,field measurements are conducted to validate the accuracy of the developed method.The results indicate that the developed method effectively identifies the geometric parameters of bridge precast components,with an error rate maintained within 5%.
基金Project supported by the National Science Foundation of China(Grant No.51875238).
文摘The water contamination on the side windows of moving vehicles is a crucial issue in improving the driving safety and the comfort.In this paper,an effective optimization method is proposed to reduce the water contamination on the side windows of automobiles.The accuracy and the efficiency of the numerical simulation are improved by using the lattice Boltzmann method,and the Lagrangian particle tracking method.Optimized parameters are constructed on the basis of the occurrence of the water deposition on a vehicle’s side window.The water contamination area of the side window and the aerodynamic drag are considered simultaneously in the design process;these two factors are used to form the multi-objective optimization function in the genetic algorithm(GA)method.The approximate model,the boundary-seeded domain method,and the GA method are combined in this study to enhance the optimization efficiency.After optimization,the optimal parameters for the A-pillar section are determined by setting the boundary to an area of W=7.77 mm,L=1.27 mm and H=11.22 mm.The side window’s soiling area in the optimized model is reduced by 66.93%,and the aerodynamic drag is increased by 0.41%only,as compared with the original model.It is shown that the optimization method can effectively solve the water contamination problem of side windows.
基金supported by the National Natural Science Foundation of China(11474083)Department of Education Fund of Hebei Province(ZD2014069)Natural Science Fund of Hebei Province(A2015201192)
文摘We proposed a new approach to determination of Judd-Ofelt intensity parameters of Er^（3＋） doped phosphors via their absorption spectra. To validate this approach, JO parameters of Er^（3＋） doped Ba BaGd_2ZnO_5/PMMA and NaYF_4/PMMA composites were calculated and in a good agreement with the other glass and crystal. The spontaneous radiative transition probability, branching ratio, and radiative lifetime of the optical transitions were calculated by using the Judd-Ofelt theory. Intense near-infrared emission at 1553 nm was observed under 980 nm laser diode excitation at room temperature. The samples possessing high full-width at half-maximum reach 85 nm have potential application in broadband optical amplifier.
