A study of the influence of separation bubbles around a generic freight train on pressure waves inside tunnels using 1D and 3D numerical methods

Due to the increased effective blockage area caused by the bluff nature of a freight train, traditional one-dimensional (1D) numerical modelling techniques struggle to predict the initial pressure wave formation for these train types. This paper presents, for the first time, a detailed study of this phenomenon for typical freight train locomotives, and a redeveloped 1D code capable of solving for bluff freight vehicles. Firstly, a 1D numerical model for tunnel pressure development is written and validated with previous research. Then, 3D simulations using computational fluid dynamics (CFD) have been carried out to model a freight train entering into a tunnel, with a view to characterising the key regions of flow separation. According to this, the 1D code is redeveloped to simulate the changing effective blockage area of the freight train, caused by flow separation at the blunted train head. A separation bubble model is built to calculate the effective blockage area. Results show that the error between the results obtained from the modified 1D model and the experiment is significantly reduced in relation to traditional 1D numerical models. To provide further functionality through the ability to apply the model to various types of freight train locomotives, a parameterisation study is conducted to obtain the relationship between the vehicle shape (bluntness) and new input parameters for the separation bubble model. Finally, the separation bubble model and parameterisation equation is tested to validate its applicability, with results indicating good agreement for a range of train designs.

Automated summary

Due to the bluff nature of freight trains, traditional 1D numerical modelling techniques struggle to predict pressure wave formation accurately. This paper presents a detailed study on this phenomenon and introduces a redeveloped 1D code capable of simulating bluff freight vehicles. The code accurately predicts the changing effective blockage area caused by flow separation at the train head.