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Title: Enhancing the piston effect in underground railways
Author: Marshall Cross, Daniel
ISNI:       0000 0004 6497 6838
Awarding Body: University of Sheffield
Current Institution: University of Sheffield
Date of Award: 2017
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The purpose of this study was to investigate methods of enhancing the piston effect in underground railways for the improvement of thermal conditions on platforms. In many underground railways, the piston effect is used to provide ventilation. However, in older underground railways insufficient ventilation can lead to high temperatures, largely due to heat from train braking. Additionally, the energy demand from ventilation and cooling equipment in newer underground railways can be significant. Enhancing the piston effect can provide additional ventilation for improved thermal conditions or a reduced energy demand. Two novel devices for the enhancement of the piston effect were investigated; a train fin and aerofoil. Through influencing the air flow patterns around a train, the devices alter the train air displacement and aerodynamic work. Moreover, variation of the fin size or the aerofoil angle of inclination allows the air displacement and aerodynamic work to be controlled. The influence of an enhanced piston effect on the thermal conditions on an underground platform is shown to reduce the air temperatures, through the enhanced displacement of braking heat. Two- and three-dimensional computational fluid dynamics models were developed, and verified with experimental data from the literature, to study numerically the piston effect, train fin and aerofoil and the thermal conditions on an underground platform. The results from the numerical analysis showed that a train aerofoil can increase air displacement by around 8%, with no increase in the aerodynamic work. It was found that an increase in the piston effect 10m^3s^-1 could reduce the highest air temperatures on an underground platform by between 0.16-0.29 °C. The cooling effect of enhancing the piston effect was found to be between 4.5-5.6 kW.
Supervisor: Ma, Lin ; Pourkashanian, Mohamed Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available