Experimental and theoretical studies of drag embedment plate anchors recently carried out in Tianjin University are summarized in this research paper, which involve a series of important topics relevant to the study o...Experimental and theoretical studies of drag embedment plate anchors recently carried out in Tianjin University are summarized in this research paper, which involve a series of important topics relevant to the study of drag anchors. The techniques for measuring the trajectory and movement direction of drag anchors in soils, the techniques for measuring the moving embedment point and reverse eatenary shape of the embedded drag line, the penetration mechanism and kinematic behavior of drag anchors, the ultimate embedment depth of drag anchors, the movement direction of the anchor with an arbitrary fluke section, the reverse catenary properties of the embedded drag line, the interaetional properties between drag anchor and installation line, the kinematic model of drag anchors in seabed soils, and the analytical method for predicting the anchor trajectory in soils will all be examined. The present work remarkably reduces the uncertainties in design and analysis of drag embedment plate anchors, and is beneficial to improving the application of this new type of drag anchor in offshore engineering.展开更多
Railway seat inventory control strategies play a crucial role in the growth of profit and train load factor. The railway passenger seat inventory control problem in China was addressed. Chinese passenger railway opera...Railway seat inventory control strategies play a crucial role in the growth of profit and train load factor. The railway passenger seat inventory control problem in China was addressed. Chinese passenger railway operation features and seat inventory control practice were analyzed firstly. A dynamic demand forecasting method was introduced to forecast the coming demand in a ticket booking period. By clustering, passengers' historical ticket bookings were used to forecast the demand to come in a ticket booking period with least squares support vector machine. Three seat inventory control methods: non-nested booking limits, nested booking limits and bid-price control, were modeled under a single-fare class. Different seat inventory control methods were compared with the same demand based on ticket booking data of Train T15 from Beijing West to Guangzhou. The result shows that the dynamic non-nested booking limits control method performs the best, which gives railway operators evidence to adjust the remaining capacity in a ticket booking period.展开更多
Performance parameter prediction technology is the core research content of aeroengine health management,and more and more machine learning algorithms have been applied in the field.Regularized extreme learning machin...Performance parameter prediction technology is the core research content of aeroengine health management,and more and more machine learning algorithms have been applied in the field.Regularized extreme learning machine(RELM)is one of them.However,the regularization parameter determination of RELM consumes computational resources,which makes it unsuitable in the field of aeroengine performance parameter prediction with a large amount of data.This paper uses the forward and backward segmentation(FBS)algorithms to improve the RELM performance,and introduces an adaptive step size determination method and an improved solution mechanism to obtain a new machine learning algorithm.While maintaining good generalization,the new algorithm is not sensitive to regularization parameters,which greatly saves computing resources.The experimental results on the public data sets prove the above conclusions.Finally,the new algorithm is applied to the prediction of aero-engine performance parameters,and the excellent prediction performance is achieved.展开更多
A one-equation turbulence model which relies on the turbulent kinetic energy transport equation has been developed to predict the flow properties of the recirculating flows. The turbulent eddy-viscosity coefficient is...A one-equation turbulence model which relies on the turbulent kinetic energy transport equation has been developed to predict the flow properties of the recirculating flows. The turbulent eddy-viscosity coefficient is computed from a recalibrated Bradshaw's assumption that the constant a1= 0.31 is recalibrated to a function based on a set of direct numerical simulation(DNS) data. The values of dissipation of turbulent kinetic energy consist of the near-wall part and isotropic part, and the isotropic part involves the von Karman length scale as the turbulent length scale. The performance of the new model is evaluated by the results from DNS for fully developed turbulence channel flow with a wide range of Reynolds numbers. However, the computed result of the recirculating flow at the separated bubble of NACA4412 demonstrates that an increase is needed on the turbulent dissipation, and this leads to an advanced tuning on the self-adjusted function. The improved model predicts better results in both the non-equilibrium and equilibrium flows, e.g. channel flows, backward-facing step flow and hump in a channel.展开更多
基金Foundation item： Supported by the National Natural Science Foundation of China （Grant nos. 50639030 and 50979070） and the 863 Program of China （Grant no. 2006AA09Z348）.
文摘Experimental and theoretical studies of drag embedment plate anchors recently carried out in Tianjin University are summarized in this research paper, which involve a series of important topics relevant to the study of drag anchors. The techniques for measuring the trajectory and movement direction of drag anchors in soils, the techniques for measuring the moving embedment point and reverse eatenary shape of the embedded drag line, the penetration mechanism and kinematic behavior of drag anchors, the ultimate embedment depth of drag anchors, the movement direction of the anchor with an arbitrary fluke section, the reverse catenary properties of the embedded drag line, the interaetional properties between drag anchor and installation line, the kinematic model of drag anchors in seabed soils, and the analytical method for predicting the anchor trajectory in soils will all be examined. The present work remarkably reduces the uncertainties in design and analysis of drag embedment plate anchors, and is beneficial to improving the application of this new type of drag anchor in offshore engineering.
基金Project(2009BAG12A10)supported by the State Technical Support Program of ChinaProject(71201009)supported by National Natural Science Foundation of ChinaProject(RCS2009ZT009)supported by the State Key Laboratory of Rail Traffic Control and Safety,Beijing Jiaotong University,China
文摘Railway seat inventory control strategies play a crucial role in the growth of profit and train load factor. The railway passenger seat inventory control problem in China was addressed. Chinese passenger railway operation features and seat inventory control practice were analyzed firstly. A dynamic demand forecasting method was introduced to forecast the coming demand in a ticket booking period. By clustering, passengers' historical ticket bookings were used to forecast the demand to come in a ticket booking period with least squares support vector machine. Three seat inventory control methods: non-nested booking limits, nested booking limits and bid-price control, were modeled under a single-fare class. Different seat inventory control methods were compared with the same demand based on ticket booking data of Train T15 from Beijing West to Guangzhou. The result shows that the dynamic non-nested booking limits control method performs the best, which gives railway operators evidence to adjust the remaining capacity in a ticket booking period.
文摘Performance parameter prediction technology is the core research content of aeroengine health management,and more and more machine learning algorithms have been applied in the field.Regularized extreme learning machine(RELM)is one of them.However,the regularization parameter determination of RELM consumes computational resources,which makes it unsuitable in the field of aeroengine performance parameter prediction with a large amount of data.This paper uses the forward and backward segmentation(FBS)algorithms to improve the RELM performance,and introduces an adaptive step size determination method and an improved solution mechanism to obtain a new machine learning algorithm.While maintaining good generalization,the new algorithm is not sensitive to regularization parameters,which greatly saves computing resources.The experimental results on the public data sets prove the above conclusions.Finally,the new algorithm is applied to the prediction of aero-engine performance parameters,and the excellent prediction performance is achieved.
基金supported by the National Basic Research Program of China(Grant No.2014CB744804)
文摘A one-equation turbulence model which relies on the turbulent kinetic energy transport equation has been developed to predict the flow properties of the recirculating flows. The turbulent eddy-viscosity coefficient is computed from a recalibrated Bradshaw's assumption that the constant a1= 0.31 is recalibrated to a function based on a set of direct numerical simulation(DNS) data. The values of dissipation of turbulent kinetic energy consist of the near-wall part and isotropic part, and the isotropic part involves the von Karman length scale as the turbulent length scale. The performance of the new model is evaluated by the results from DNS for fully developed turbulence channel flow with a wide range of Reynolds numbers. However, the computed result of the recirculating flow at the separated bubble of NACA4412 demonstrates that an increase is needed on the turbulent dissipation, and this leads to an advanced tuning on the self-adjusted function. The improved model predicts better results in both the non-equilibrium and equilibrium flows, e.g. channel flows, backward-facing step flow and hump in a channel.
