Evaluation of the XP2 Smoke Density Chamber

2009 ◽  
pp. 106-106-19 ◽  
Author(s):  
F. J. Rarig ◽  
A. J. Bartosic
Keyword(s):  
Smoke Density

scholarly journals Numerical Investigations on the Propagation of Fire in a Railway Carriage

Energies ◽  
2020 ◽  
Vol 13 (19) ◽  
pp. 4999
Author(s):  
Matthew Craig ◽  
Taimoor Asim
Keyword(s):  
Fire Spread ◽  
Ignition Energy ◽  
Fire Dynamics ◽  
Fire Propagation ◽  
Average Temperature ◽  
Smoke Density ◽  
Smoke Layer ◽  
Most Significant Change ◽  
Computational Fluid Dynamics Cfd ◽  
Safety Guidelines

In this study, advanced Computational Fluid Dynamics (CFD)-based numerical simulations have been performed in order to analyse fire propagation in a standard railway compartment. A Fire Dynamics Simulator (FDS) has been employed to mimic real world scenarios associated with fire propagation within railway carriages in order to develop safety guidelines for railway passengers. Comprehensive parametric investigations on the effects of ignition location, intensity and cabin upholstery have been carried out. It has been observed that a fire occurring near the exits of the carriage results in a lower smoke layer height, due to the local carriage geometry, than an identical fire igniting at the center of the carriage. This in turn causes the smoke density along the aisleway to vary by around 30%. Reducing the ignition energy by half has been found to restrict combustion, thus reducing smoke density and carbon exhaust gases, reducing the average temperature from 170 °C to 110 °C. Changing the material lining of the seating has been found to cause the most significant change in output parameters, despite its relative insignificance in bulk mass. A polyester sample produces a peak carbon monoxide concentration of 7500 ppm, which is 27× greater compared with nylon. This difference has been found to be due to the fire spread and propagation between fuels, signifying the polyester’s unsuitability for use in railway carriages.

The effect of test conditions on apparent smoke density from various materials

1980 ◽  
Vol 16 (2) ◽  
pp. 113-117
Author(s):  
Carlos J. Hilado ◽  
Regina M. Murphy ◽  
Colleen J. Casey
Keyword(s):  
Test Conditions ◽  
Smoke Density

A Wave-Shaped Deep Neural Network for Smoke Density Estimation

2020 ◽  
Vol 29 ◽  
pp. 2301-2313 ◽  
Author(s):  
Feiniu Yuan ◽  
Lin Zhang ◽  
Xue Xia ◽  
Qinghua Huang ◽  
Xuelong Li
Keyword(s):  
Neural Network ◽  
Density Estimation ◽  
Deep Neural Network ◽  
Smoke Density
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