Prediction of the maximum air velocities created by metro trains using an artificial neural network approach


KOC G., SERT C. , Albayrak K.

PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART F-JOURNAL OF RAIL AND RAPID TRANSIT, cilt.228, ss.759-767, 2014 (SCI İndekslerine Giren Dergi) identifier identifier

  • Cilt numarası: 228 Konu: 7
  • Basım Tarihi: 2014
  • Doi Numarası: 10.1177/0954409713488100
  • Dergi Adı: PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART F-JOURNAL OF RAIL AND RAPID TRANSIT
  • Sayfa Sayıları: ss.759-767

Özet

The maximum air velocity created by a moving train inside a tunnel is obtained using an artificial neural network approach. A neural network model is developed to represent a single train travelling in a single tunnel. A set of non-dimensional groups, which are known to influence the induced flow characteristics, is used for the training of the neural network. Various test runs are compared with the results of the authoritative software, Subway Environmental Simulation. The presence of ventilation shafts within a tunnel is included in the model by defining an aerodynamically equivalent single tunnel using major head loss characteristics of different parts of the system. This approach eliminated the requirement to train the neural network for a large number of possible tunnel/shaft configurations.