Prognostic modelling of fire resistance of RC columns using the concept of ANN
Date Issued
2017
Author(s)
Abstract
The application of artificial neural networks, as an unconventional and innovative method for solving complex civil engineering problems, is very important for modernization of the construction design processes. Many published studies show that neural-based approach can be successfully used in different engineering fields. Neural networks are being used for creating prognostic models mainly in those cases where some prior (numerical or experimental) analyses were already made.
This paper presents a neural network prognostic model used for determination of fire resistance of reinforced concrete columns exposed to standard fire from all four sides is presented in the paper. The proposed model relies on the concept of artificial neural networks, in which numerical analysis results are used as input parameters. A brief description of the modelling process is given, and an appropriate example of the neural network prognostic model is presented.
This paper presents a neural network prognostic model used for determination of fire resistance of reinforced concrete columns exposed to standard fire from all four sides is presented in the paper. The proposed model relies on the concept of artificial neural networks, in which numerical analysis results are used as input parameters. A brief description of the modelling process is given, and an appropriate example of the neural network prognostic model is presented.
Subjects