Experimental validation of non-linear multi-body railroad vehicle system algorithms

Abstract

The current trend in railroad industry is the development of reliable non-linear computational dynamic algorithms that can be used in the simulations of vehicle behaviour under different operating conditions. Of similar importance, is the development of experimental models that can be used in the validation of the proposed numerical algorithms. The objective of this investigation is to examine the accuracy of the results obtained using different multi-body contact formulations by comparing these results with experimental results. The numerical results are obtained using two different multi-body contact formulations: the embedded constraint contact formulation and the quasi-elastic contact formulation; both are implemented in general purpose multi-body computer programs. The numerical results obtained using these two different methods are analysed and compared. These results are also compared with the test results of a bogie prototype that can be used with a roller rig built at Turin Polytechnic. The roller rig, which is designed to be used with full scale or reduced scale models, provides an efficient and economic way to validate the results of the computer algorithms. This roller rig, which can also be used to perform tests on bogies with different rail gauge and wheel base, has been designed using Jaschinski's scaling method. A bogie computer model based on the same dimensions and material properties of the Turin roller rig was developed using two different general purpose multi-body computer programs that employ the two different non-linear wheel/rail contact formulations and two different numerical algorithms for the automatic generation and solution of the system equations of motion. The results of the two different multi-body formulations used in this study show a good agreement. Furthermore, the results show that the bogie critical speed predicted using the computer simulations is very close to the one obtained using the roller rig.