A bifunctional catalyst Pt/HY-β was prepared from a bimicroporous composite zeolite Y-β. Characterization results showed that the specific surface area, pore volume, and acid amount of the catalyst Pt/HY-β all decr...A bifunctional catalyst Pt/HY-β was prepared from a bimicroporous composite zeolite Y-β. Characterization results showed that the specific surface area, pore volume, and acid amount of the catalyst Pt/HY-β all decreased compared to the original zeolite. The catalytic performance of this catalyst in n-octane hydroisomerization was investigated in a fixed bed stainless steel tubular reactor. The results showed that at a hydrogen/n-octane volume ratio of 1000, pressure of 0.6 MPa, temperature of 230 ℃ and LHSV of 3 h^-1, the conversion of n-octane, yield of liquid, hydrocracking rate and yield of iso-octane were 52.32%, 88.66%, 12.60%, 39.51%, respectively.展开更多
Phase unwrapping is one of the key roles in fringe projection three-dimensional(3D)measurement technology.We propose a new method to achieve phase unwrapping in camera array light filed fringe projection 3D measuremen...Phase unwrapping is one of the key roles in fringe projection three-dimensional(3D)measurement technology.We propose a new method to achieve phase unwrapping in camera array light filed fringe projection 3D measurement based on deep learning.A multi-stream convolutional neural network(CNN)is proposed to learn the mapping relationship between camera array light filed wrapped phases and fringe orders of the expected central view,and is used to predict the fringe order to achieve the phase unwrapping.Experiments are performed on the light field fringe projection data generated by the simulated camera array fringe projection measurement system in Blender and by the experimental 3×3 camera array light field fringe projection system.The performance of the proposed network with light field wrapped phases using multiple directions as network input data is studied,and the advantages of phase unwrapping based on deep learning in light filed fringe projection are demonstrated.展开更多
基金sponsored by China Petroleumand Chemical Corporation(No.:090701)
文摘A bifunctional catalyst Pt/HY-β was prepared from a bimicroporous composite zeolite Y-β. Characterization results showed that the specific surface area, pore volume, and acid amount of the catalyst Pt/HY-β all decreased compared to the original zeolite. The catalytic performance of this catalyst in n-octane hydroisomerization was investigated in a fixed bed stainless steel tubular reactor. The results showed that at a hydrogen/n-octane volume ratio of 1000, pressure of 0.6 MPa, temperature of 230 ℃ and LHSV of 3 h^-1, the conversion of n-octane, yield of liquid, hydrocracking rate and yield of iso-octane were 52.32%, 88.66%, 12.60%, 39.51%, respectively.
基金the National Natural Science Foundation of China(No.61905178)the Science&Technology Development Fund of Tianjin Education Commission for Higher Education(No.2019KJ021)the Natural Science Foundation of Tianjin(No.18JCQNJC71100)。
文摘Phase unwrapping is one of the key roles in fringe projection three-dimensional(3D)measurement technology.We propose a new method to achieve phase unwrapping in camera array light filed fringe projection 3D measurement based on deep learning.A multi-stream convolutional neural network(CNN)is proposed to learn the mapping relationship between camera array light filed wrapped phases and fringe orders of the expected central view,and is used to predict the fringe order to achieve the phase unwrapping.Experiments are performed on the light field fringe projection data generated by the simulated camera array fringe projection measurement system in Blender and by the experimental 3×3 camera array light field fringe projection system.The performance of the proposed network with light field wrapped phases using multiple directions as network input data is studied,and the advantages of phase unwrapping based on deep learning in light filed fringe projection are demonstrated.
