Based on a new type of tunnel configuration model with flue in the top of it, the paper simulated the smoke pervasion when fire happens in this type of tunnel by FDS. The results show that the setting up of the flue o...Based on a new type of tunnel configuration model with flue in the top of it, the paper simulated the smoke pervasion when fire happens in this type of tunnel by FDS. The results show that the setting up of the flue outlet reduces the backing up distance of combustion smoke, and the distance of people fleeing is also shortened. But under this condition the smoke density inside and outside of the two flue outlet increases evidently. However, when the exhausted fans are designed at smoking outlet, the smoke movement is accelerated and almost moved into the upper space. This configuration makes the fire smoke density outside of the flue outlet reduced greatly. When the exhausted velocity increased up to a certain critical level, the smoke concentration outside of the flue outlet will reduce at the value which is no harmonious to people＇s life. This situation will offer a relatively safe space for people fleeing, and fire rescuing can also be carried out from two directions. Therefore, this tunnel configuration mentioned in this article give a new reference mode for personnel flee, fire rescuing and tunnel maintenance.展开更多
Incessant fire-outbreak in urban settlements has remained intractable especially in developing countries like Nigeria. This is often characterized by grave socio-economic aftermath effects. Urban fire outbreak in Nige...Incessant fire-outbreak in urban settlements has remained intractable especially in developing countries like Nigeria. This is often characterized by grave socio-economic aftermath effects. Urban fire outbreak in Nigerian cities has been on increase in recent times. The major problem faced by fire fighters in Nigerian urban centres is that there are no mechanisms to detect fire outbreaks early enough to save lives and properties. They often rely on calls made by neighbours or occupants when an outbreak occurs and this accounts for the delay in fighting fire outbreaks. This work uses Artificial Neural Networks (ANN) with backpropagation method to detect the occurrence of urban fires. The method uses smoke density, room temperature and cooking gas concentration as inputs. The work was implemented using Java programming language and results showed that it detected the occurrence of urban fires with reasonable accuracy. The work is recommended for use to minimize the effect of urban fire outbreak.展开更多
文摘Based on a new type of tunnel configuration model with flue in the top of it, the paper simulated the smoke pervasion when fire happens in this type of tunnel by FDS. The results show that the setting up of the flue outlet reduces the backing up distance of combustion smoke, and the distance of people fleeing is also shortened. But under this condition the smoke density inside and outside of the two flue outlet increases evidently. However, when the exhausted fans are designed at smoking outlet, the smoke movement is accelerated and almost moved into the upper space. This configuration makes the fire smoke density outside of the flue outlet reduced greatly. When the exhausted velocity increased up to a certain critical level, the smoke concentration outside of the flue outlet will reduce at the value which is no harmonious to people＇s life. This situation will offer a relatively safe space for people fleeing, and fire rescuing can also be carried out from two directions. Therefore, this tunnel configuration mentioned in this article give a new reference mode for personnel flee, fire rescuing and tunnel maintenance.
文摘Incessant fire-outbreak in urban settlements has remained intractable especially in developing countries like Nigeria. This is often characterized by grave socio-economic aftermath effects. Urban fire outbreak in Nigerian cities has been on increase in recent times. The major problem faced by fire fighters in Nigerian urban centres is that there are no mechanisms to detect fire outbreaks early enough to save lives and properties. They often rely on calls made by neighbours or occupants when an outbreak occurs and this accounts for the delay in fighting fire outbreaks. This work uses Artificial Neural Networks (ANN) with backpropagation method to detect the occurrence of urban fires. The method uses smoke density, room temperature and cooking gas concentration as inputs. The work was implemented using Java programming language and results showed that it detected the occurrence of urban fires with reasonable accuracy. The work is recommended for use to minimize the effect of urban fire outbreak.
