Numerical Simulation for Mine Oblique Lane Fire Based on PDF Non-Premixed Combustion

ABSTRACT

In the mine fire period, the smoke plume temperature, critical air velocity, back-flow layer and other fire parameters in the lanes are subjected to environmental factors such as lane dip angle and airflow conditions, coupled with uncertain evolution process. In view of this, a numerical simulation is performed for exploring the dynamic evolution law of fire possibly occurred in the mine. The ANSYS Fluent PDF non-premixed combustion model is applied to reveal the fire development in the lanes with different dip angles under different air velocity. The temperature distribution in the lanes and the evolution law of the fire back-flow layer are also analyzed. Here introduces the dimensionless number-Richardson number (Ri value) to determine the critical value of the development of the fire back-flow layer. The results show that there is a regular relationship of the spatiotemporal evolution properties of fire in the inclined lane with the two factors: dip angle, airflow velocity, According to this law, the calculation model of smoke back-flow layer length with respect to air velocity and inclination angle is established, and the critical air velocity prediction model under the condition of large inclination angle is revised. Based on the critical air velocity and critical angle, the critical value of the Richardson number is determined to be 91.6. When Ri is greater than 91.6, the fire back-flow layer appears, otherwise, it disappears. The findings provide certain clues to identifying the fire in the underground tunnel and predicting the fire development and smoke spread.

KEYWORDS:

• Tunnel fire
• characteristic parameter
• critical air velocity
• back-flow layer
• Richardson number

Additional information

Funding

This research was supported by the National Key R&D Program of China [grant number 2018YFC0808201]; Special scientific research project of Shaanxi Provincial Education Department [grant number 17JK0495]; Natural Science Basic Research Program of Shaanxi [grant number 2018JQ5080]; Natural Science Basic Research Program of Shaanxi [grant number 2018JM5009].