Collaborative Visualization Analysis of Train Dynamics by Cloud Simulation-driven

被引：0

作者：

Wang L. ^{[1
]}

Tang Z. ^{[1
]}

Li R. ^{[2
]}

Gu Z. ^{[1
]}

Hu Y. ^{[1
]}

Li Y. ^{[1
]}

Zhang J. ^{[1
]}

机构：

[1] State Key Laboratory of Traction Power, Southwest Jiaotong University, Chengdu

[2] School of Mechanical Engineering, Southwest Jiaotong University, Chengdu

来源：

Zhongguo Jixie Gongcheng/China Mechanical Engineering | 2023年 / 34卷 / 18期

关键词：

cloud rendering; cloud simulation; integrated model; real-time visualization; web real-time communica-tion(WebRTC) technology;

D O I：

10.3969/j.issn.1004-132X.2023.18.012

中图分类号：

学科分类号：

摘要：

To address the challenges of insufficient automation in scene construction, inconvenient multi-role multi-user collaboration, poor analysis timeliness of analysis, and high client hardware requirements in the traditional train dynamics analysis processes, a cloud simulation-driven train dynamics collaborative visualization analysis framework driven by simulation was proposed. A train dynamics simulation and visualization analysis framework, a remote visualization interaction framework, and a solver integration model for real-time analysis were designed. These respectively achieved service-oriented multi-dimensional visualization analysis scene construction, multi-role and multi-group collaborative remote visualization analysis, and efficient module interconnection and node elastic expansion. Based on the proposed framework, a software system was built and validated in the project. The validation results show that the framework and system have outstanding visualization performance and concurrent solving capabilities while ensuring accuracy. The successful applications of the framework also indicate that cloud simulation has great potential for use in train dynamics visualization analysis. © 2023 China Mechanical Engineering Magazine Office. All rights reserved.

引用

页码：2248 / 2256

页数：8

共 18 条

[1] ZHU Haiyan, ZENG Qingtao, WANG Yuhao, Et al., Research Progress on Dynamics Performance of High-speed Train[J], Journal of Traffic and Transportation Engineering, 21, 3, pp. 57-92, (2021)
[2] TANG Zhao, DONG Shaodi, LUO Ren, Et al., Application Advances of Artificial Intelligence Algorithms in Dynamics Simulation of Railway Vehicle [J], Journal of Traffic and Transportation Engineering, 21, pp. 250-266, (2021)
[3] DING Sansan, CHEN Dawci, LIU Jiali, Research, Development and Prospect of China High-speed Train [J], Chinese Journal of Theoretical and Applied Mechanics, 53, 1, pp. 35-50, (2021)
[4] RILL G, BAUER F, KIRCHBECK M., VTT-a Virtual Test Truck for Modern Simulation Tasks [J], Vehicle System Dynamics, 59, 4, pp. 635-656, (2021)
[5] WU Q, GE X, HAN Q L, Et al., Dynamics and Control Simulation of Railway Virtual Coupling[J], Vehicle System Dynamics, (2022)
[6] LI Bohu, CHAI Xudong, HOU Baocun, Et al., Networked Modeling &- Simulation Platform Based on Concept of Cloud Computing-"Cloud Simulation Platform"[J], Journal of System Simulation, 21, 17, pp. 5292-5299, (2009)
[7] FAN Wcnhui, WU Jiahui, Development and Future Trend of Computer Simulation and Quantum Computer Simulation[J], Journal of System Simulation, 29, 6, pp. 1161-1167, (2017)
[8] Yuc HE, CHEN Maosong, DAI Zhimin, Preliminary Design and Implementation of 'TMSR Cloud Simulation Platform[J], Nuclear 'Techniques, 11, 7, pp. 79-86, (2018)
[9] ZHANG Binqiao, A Dissertation Submitted in Par- tial Fulfillment of the Min Equircmcnts for Chemical the Degree of Doctor of Philosophy in Science [D], (2017)
[10] TAYLOR S J, ANAGNOSTOU A, KISS T, Et al., Enabling Cloud-based Computational Fluid Dynamics with a Platform-as-a-scrvicc Solution [J], 1E1E1E! Transactions on Industrial Informatics, 15, 1, pp. 85-91, (2018)

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