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Abstract
The violent goods vibration during curve negotiation is a huge threat to the vehicle running safety. Qualified load restraint assemblies that can significantly suppress the cargo vibration are necessary. This study proposes a novel method for evaluating the essential restraint strength, focusing on the relative motion between cargo and wagon. In the beginning, as a comparison, current methods are used to calculate the necessary stiffness of lashings, which are adopted to restrain the cargo vibration on the wagon. Based on the data of the field test, the accuracy of the established wagon-cargo coupled dynamics model is validated. The loaded wagon model negotiates the curve under different running and loading conditions. The simulation results and analysis demonstrate effective strategies for suppressing the vibration of the cargo and reveal the necessary lashing stiffness. The comparison among the results of different evaluation methods shows that the stability of the cargo can be improved by optimizing the lashing stiffness with the method of dynamics simulations. We hope this study will make a positive contribution to the safety of railway freight transportation.
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Details
1 Southwest Jiaotong University, School of Transportation and Logistics, Chengdu, People’s Republic of China (GRID:grid.263901.f) (ISNI:0000 0004 1791 7667); National Rail Transit Electrification and Automation Engineering Technology Research Center (Hong Kong Branch), Hong Kong, People’s Republic of China (GRID:grid.263901.f); The Hong Kong Polytechnic University, Department of Civil and Environmental Engineering, Hong Kong, People’s Republic of China (GRID:grid.16890.36) (ISNI:0000 0004 1764 6123)
2 National Rail Transit Electrification and Automation Engineering Technology Research Center (Hong Kong Branch), Hong Kong, People’s Republic of China (GRID:grid.16890.36); The Hong Kong Polytechnic University, Department of Civil and Environmental Engineering, Hong Kong, People’s Republic of China (GRID:grid.16890.36) (ISNI:0000 0004 1764 6123)
3 Southwest Jiaotong University, School of Transportation and Logistics, Chengdu, People’s Republic of China (GRID:grid.263901.f) (ISNI:0000 0004 1791 7667); Southwest Jiaotong University, National United Engineering Laboratory of Integrated and Intelligent Transportation, Chengdu, People’s Republic of China (GRID:grid.263901.f) (ISNI:0000 0004 1791 7667)
4 National Rail Transit Electrification and Automation Engineering Technology Research Center (Hong Kong Branch), Hong Kong, People’s Republic of China (GRID:grid.263901.f); The Hong Kong Polytechnic University, Department of Civil and Environmental Engineering, Hong Kong, People’s Republic of China (GRID:grid.16890.36) (ISNI:0000 0004 1764 6123)
5 City University of Macau, Faculty of Business, Macau, People’s Republic of China (GRID:grid.445020.7) (ISNI:0000 0004 0385 9160)