Flashovers are some of the most dangerous situations firefighters encounter, as they cause nearly all combustible items in a burning room to ignite at once, with little to no warning.
With a view to reducing the firefighter deaths caused by this phenomenon, a team of scientists from the US National Institute of Standards and Technology (NIST), the Hong Kong Polytechnic University and other institutions have developed a Flashover Prediction Neural Network (FlashNet) model to forecast these events precious seconds before they erupt.
The model was able to predict flashovers with an accuracy of up to 92.1 per cent for over a dozen common residential floorplans in the US, according to a study published in Engineering Applications of Artificial Intelligence.
Flashovers tend to suddenly flare up at approximately 600ºC and can then cause temperatures to shoot up further. Until now, most prediction tools rely on constant streams of temperature data from burning...