Fire resistance of concrete: prediction using artificial neural networks

A model based on an artificial neural network (ANN) for predicting the loss of strength of concrete tinder high temperatures (75-1200 degrees C) is pr esented. The ANN is a recent development and is particularly useful for eva luating non-linear systems with several variables the relationships between which cannot be defined explicitly by mathematical equations. It has been reported in the literature that the Jive resistance of concrete is related to several material and environmental factors, but this relationship is dif ficult to quantify mathematically The advantage of the ANN is that it can b e trained, using experimental data assembled from published research, to re cognize the relationship between these influencing factors and the fire res istance of concrete measured by the loss of strength. After training, the A NN is applied to predict the loss of strength of concrete with new material and environmental factors. In the tests conducted the prediction errors be tween the network outputs and the actual experimental results were less tha n 15%.