The effects of the different landforms of the cutting leeward on the aerodynamic performance of high-speed trains were analyzed based on the three-dimensional, steady, and incompressible Navier-Stokes equation and k-e...The effects of the different landforms of the cutting leeward on the aerodynamic performance of high-speed trains were analyzed based on the three-dimensional, steady, and incompressible Navier-Stokes equation and k-e double-equation turbulent model. Results show that aerodynamic forces increase with the cutting leeward slope decreasing. The maximum adding value of lateral force, lift force, and overturning moment are 147%, 44.3%, and 107%, respectively, when the slope varies from 0.67 to -0.67, and the changes in the cutting leeward landform have more effects on the aerodynamic performance when the train is running in the line No. 2 than in the line No. 1. The aerodynamic forces, except the resistance force, sharply increase with the slope depth decreasing. By comparing the circumstance of the cutting depth H=-8 m with that of H=8 m, the resistance force, lateral force, lift force, and overturning moment increase by 26.0%, 251%, 67.3% and 177%, respectively. With the wind angle increasing, the resistance force is nonmonotonic, whereas other forces continuously rise. Under three special landforms, the changes in the law of aerodynamic forces with the wind angle are almost similar to one another.展开更多
An irregular segmented region coding algorithm based on pulse coupled neural network(PCNN) is presented. PCNN has the property of pulse-coupled and changeable threshold, through which these adjacent pixels with approx...An irregular segmented region coding algorithm based on pulse coupled neural network(PCNN) is presented. PCNN has the property of pulse-coupled and changeable threshold, through which these adjacent pixels with approximate gray values can be activated simultaneously. One can draw a conclusion that PCNN has the advantage of realizing the regional segmentation, and the details of original image can be achieved by the parameter adjustment of segmented images, and at the same time, the trivial segmented regions can be avoided. For the better approximation of irregular segmented regions, the Gram-Schmidt method, by which a group of orthonormal basis functions is constructed from a group of linear independent initial base functions, is adopted. Because of the orthonormal reconstructing method, the quality of reconstructed image can be greatly improved and the progressive image transmission will also be possible.展开更多
Human's real life is within a colorful world. Compared to the gray images, color images contain more information and have better visual effects. In today's digital image processing, image segmentation is an im...Human's real life is within a colorful world. Compared to the gray images, color images contain more information and have better visual effects. In today's digital image processing, image segmentation is an important section for computers to "understand" images and edge detection is always one of the most important methods in the field of image segmentation. Edges in color images are considered as local discontinuities both in color and spatial domains. Despite the intensive study based on integration of single-channel edge detection results, and on vector space analysis, edge detection in color images remains as a challenging issue.展开更多
Discriminant space defining area classes is an important conceptual construct for uncertainty characterization in area-class maps.Discriminant models were promoted as they can enhance consistency in area-class mapping...Discriminant space defining area classes is an important conceptual construct for uncertainty characterization in area-class maps.Discriminant models were promoted as they can enhance consistency in area-class mapping and replicability in error modeling.As area classes are rarely completely separable in empirically realized discriminant space,where class inseparabil-ity becomes more complicated for change categorization,we seek to quantify uncertainty in area classes(and change classes)due to measurement errors and semantic discrepancy separately and hence assess their relative margins objectively.Experiments using real datasets were carried out,and a Bayesian method was used to obtain change maps.We found that there are large differences be-tween uncertainty statistics referring to data classes and information classes.Therefore,uncertainty characterization in change categorization should be based on discriminant modeling of measurement errors and semantic mismatch analysis,enabling quanti-fication of uncertainty due to partially random measurement errors,and systematic categorical discrepancies,respectively.展开更多
This article discusses computational methods for the numerical simulation of unsteady Bingham visco-plastic flow. These methods are based on time-discretization by operator-splitting and take advantage of a characteri...This article discusses computational methods for the numerical simulation of unsteady Bingham visco-plastic flow. These methods are based on time-discretization by operator-splitting and take advantage of a characterization of the solutions involving some kind of Lagrange multipliers. The full discretization is achieved by combining the above operator-splitting methods with finite element approximations, the advection being treated by a wave-like equation 'equivalent' formulation easier to implement than the method of characteristics or high order upwinding methods. The authors illustrate the methodology discussed in this article with the results of numerical experiments concerning the simulation of wall driven cavity Bingham flow in two dimensions.展开更多
基金Project(U1134203) supported by the National Natural Science Foundation of ChinaProject(132014) supported by Fok Ying Tong Education Foundation,ChinaProject(2011G006) supported by the Technological Research and Development Program of the Ministry of Railways,China
文摘The effects of the different landforms of the cutting leeward on the aerodynamic performance of high-speed trains were analyzed based on the three-dimensional, steady, and incompressible Navier-Stokes equation and k-e double-equation turbulent model. Results show that aerodynamic forces increase with the cutting leeward slope decreasing. The maximum adding value of lateral force, lift force, and overturning moment are 147%, 44.3%, and 107%, respectively, when the slope varies from 0.67 to -0.67, and the changes in the cutting leeward landform have more effects on the aerodynamic performance when the train is running in the line No. 2 than in the line No. 1. The aerodynamic forces, except the resistance force, sharply increase with the slope depth decreasing. By comparing the circumstance of the cutting depth H=-8 m with that of H=8 m, the resistance force, lateral force, lift force, and overturning moment increase by 26.0%, 251%, 67.3% and 177%, respectively. With the wind angle increasing, the resistance force is nonmonotonic, whereas other forces continuously rise. Under three special landforms, the changes in the law of aerodynamic forces with the wind angle are almost similar to one another.
基金National Natural Science Foundation of China(60572011) 985 Special Study Project(LZ85 -231 -582627)
文摘An irregular segmented region coding algorithm based on pulse coupled neural network(PCNN) is presented. PCNN has the property of pulse-coupled and changeable threshold, through which these adjacent pixels with approximate gray values can be activated simultaneously. One can draw a conclusion that PCNN has the advantage of realizing the regional segmentation, and the details of original image can be achieved by the parameter adjustment of segmented images, and at the same time, the trivial segmented regions can be avoided. For the better approximation of irregular segmented regions, the Gram-Schmidt method, by which a group of orthonormal basis functions is constructed from a group of linear independent initial base functions, is adopted. Because of the orthonormal reconstructing method, the quality of reconstructed image can be greatly improved and the progressive image transmission will also be possible.
基金National Natural Science Foundation of China (No.60374071)
文摘Human's real life is within a colorful world. Compared to the gray images, color images contain more information and have better visual effects. In today's digital image processing, image segmentation is an important section for computers to "understand" images and edge detection is always one of the most important methods in the field of image segmentation. Edges in color images are considered as local discontinuities both in color and spatial domains. Despite the intensive study based on integration of single-channel edge detection results, and on vector space analysis, edge detection in color images remains as a challenging issue.
基金Supported by the National Natural Science Foundation of China (No.41171346,No. 41071286)the Fundamental Research Funds for the Central Universities (No. 20102130103000005)the National 973 Program of China (No. 2007CB714402‐5)
文摘Discriminant space defining area classes is an important conceptual construct for uncertainty characterization in area-class maps.Discriminant models were promoted as they can enhance consistency in area-class mapping and replicability in error modeling.As area classes are rarely completely separable in empirically realized discriminant space,where class inseparabil-ity becomes more complicated for change categorization,we seek to quantify uncertainty in area classes(and change classes)due to measurement errors and semantic discrepancy separately and hence assess their relative margins objectively.Experiments using real datasets were carried out,and a Bayesian method was used to obtain change maps.We found that there are large differences be-tween uncertainty statistics referring to data classes and information classes.Therefore,uncertainty characterization in change categorization should be based on discriminant modeling of measurement errors and semantic mismatch analysis,enabling quanti-fication of uncertainty due to partially random measurement errors,and systematic categorical discrepancies,respectively.
文摘This article discusses computational methods for the numerical simulation of unsteady Bingham visco-plastic flow. These methods are based on time-discretization by operator-splitting and take advantage of a characterization of the solutions involving some kind of Lagrange multipliers. The full discretization is achieved by combining the above operator-splitting methods with finite element approximations, the advection being treated by a wave-like equation 'equivalent' formulation easier to implement than the method of characteristics or high order upwinding methods. The authors illustrate the methodology discussed in this article with the results of numerical experiments concerning the simulation of wall driven cavity Bingham flow in two dimensions.
