Temperature Prediction in Timber Using Artificial Neural Networks

Neural networks are a powerful tool used to model properties and behaviour of materials in many areas of civil engineering applications. In the present paper, the models in artificial neural networks for predicting the temperatures in timber under fire loading have been developed. For building these models, training and testing using the available numerical results obtained using design methods of Eurocode 5 have been used. The data used in the multilayer feed forward neural network models are arranged in a format of three input parameters that cover the density of timber, the time of fire exposure and the distance from exposed side. With these input parameter used in the multilayer feed forward neural network models the temperatures in timber are predicted. The training and testing results in the neural network model have shown that neural networks can accurately calculate the temperature in timber members subjected to fire.