A rule-based parametric modeling method of generating virtual environments for coupled systems in high-speed trains

Abstract A rule-based parametric modeling (RPM) method is proposed to dynamically generate virtual environments for simulation and analysis of the dynamics of coupled systems in high-speed trains. First, a precise and complete basic-element model base is built according to the modeling requirements of virtual simulation environments. Meanwhile, the classes of and relationships between the basic-element models are defined with respect to the geometrical, topological, semantical and appearance properties of these models. Then, multi-level semantic constraint rules and a parametric modeling method are designed to accurately analyze the simulation parameters and to rapidly integrate various basic-element models for automatic generation of virtual high-speed railway environments. Finally, after a prototype system is developed, various experiments are carried out for analysis of the advantages of the RPM method. The experimental results show that the RPM method can be used to normalize the error-prone modeling procedure and rapidly generate precise and realistic virtual environments.

[1]  Cong Guan,et al.  The Simulation of Traction and Braking Performance for High-Speed Railway Virtual Reality System , 2013, 2013 5th International Conference on Computational Intelligence and Communication Networks.

[2]  Jangbom Chai,et al.  Dynamic analysis of a pantograph–catenary system using absolute nodal coordinates , 2006 .

[3]  Yuanyou Xia,et al.  Research on Three-dimensional modelling of railway route in railway route selection , 2010, 2010 International Conference on Mechanic Automation and Control Engineering.

[4]  James A. Richard.  STABILITY OF RAILWAY-CAR RUNNING AT HIGH SPEED , 1987 .

[5]  Yi Li,et al.  A collaborative virtual geographic environment for emergency dam-break simulation and risk analysis , 2016 .

[6]  Lu Guonian.  Development of Virtual Geographic Environments and the New Initiative in Experimental Geography , 2009 .

[7]  ShuGuang Zhang,et al.  Dynamics of high speed wheel/rail system and its modelling , 2007 .

[8]  Yuzhong Shen,et al.  Automatic high-fidelity 3D road network modeling based on 2D GIS data , 2014, Adv. Eng. Softw..

[9]  Jorge Ambrósio,et al.  Influence of the aerodynamic forces on the pantograph–catenary system for high-speed trains , 2009 .

[10]  Ahmed M. D. E. Hassanein,et al.  Building a Geographical Ontology for the Nile River , 2014 .

[11]  Robert Stevens,et al.  Protégé4US: Harvesting Ontology Authoring Data with Protégé , 2014, ESWC.

[12]  Min Chen,et al.  A procedural modelling method for virtual high-speed railway scenes based on model combination and spatial semantic constraint , 2015, Int. J. Geogr. Inf. Sci..

[13]  Germanico Gonzalez-Badillo,et al.  The development of a physics and constraint-based haptic virtual assembly system , 2014 .

[14]  Lutz Plümer,et al.  Topology of surfaces modelling bridges and tunnels in 3D-GIS , 2011, Comput. Environ. Urban Syst..

[15]  Yanmei Cao,et al.  Theoretical modeling and characteristic analysis of moving-train induced ground vibrations , 2010 .

[16]  Ping Wei,et al.  Research on Realtime Rendering of 3D High-Speed Rail GIS , 2013, 2013 Seventh International Conference on Image and Graphics.

[17]  Lin Hui,et al.  A grid-based collaborative virtual geographic environment for the planning of silt dam systems , 2010 .

[18]  Gordon Bell,et al.  Beyond the Data Deluge , 2009, Science.

[19]  Nan Zhang,et al.  Vehicle bridge interaction analysis under high-speed trains , 2008 .

[20]  Qing Zhu,et al.  Mathematical morphology-based generalization of complex 3D building models incorporating semantic relationships , 2012 .

[21]  Dai Qiang-ling.  Research on 3D Scene Quickly Reproduce Facing Railway Industry , 2011 .

[22]  Hui Lin,et al.  Virtual Geographic Environment: A Workspace for Computer-Aided Geographic Experiments , 2013 .

[23]  Wei Hua Zhang.  The development of China’s high-speed railway systems and a study of the dynamics of coupled systems in high-speed trains , 2014 .

[24]  Giuseppe Muscolino,et al.  A substructure approach for the dynamic analysis of train-track-bridge system , 2005 .

[25]  Wang Ming-sheng,et al.  The Research of Modeling method of railway 3D Landscape , 2014 .

[26]  Hui Lin,et al.  Virtual Geographic Environments (VGEs): A New Generation of Geographic Analysis Tool , 2013 .

[27]  Qing Zhu,et al.  A semantics-constrained profiling approach to complex 3D city models , 2013, Comput. Environ. Urban Syst..

[28]  Zhang Shuguang.  Dynamics and Service Simulation for General Coupling System of High-Speed Trains , 2008 .

[29]  Makoto Tanabe,et al.  Simulation and visualization of a high-speed Shinkansen train on the railway structure , 2000 .

[30]  W. Bainbridge.  The Scientific Research Potential of Virtual Worlds , 2007, Science.

[31]  Zili Li,et al.  A three-dimensional finite element solution of frictional wheel–rail rolling contact in elasto-plasticity , 2015 .

[32]  Zhu Ju.  Combinational Modeling Method of Virtual High-Speed Railway Scene Based on Entity-Relationship Conceptual Model , 2014 .

[33]  Guillaume Koum.  Geo-Ontology and Geographical Information System Extended by a first-order logic language: Application to malaria control , 2012 .

[34]  Jing Zeng,et al.  Stability Analysis of High Speed Railway Vehicles , 2004 .