Applied Mechanics and Materials· 2014
Neural Network Prognostic Model for Predicting the Fire Resistance of Eccentrically Loaded RC Columns
- 42citations
- 2014year
Short summary
A neural network model accurately predicts the fire resistance of eccentrically loaded reinforced concrete (RC) columns exposed to standard fire from one side.
AI-generated from the title and abstract; the full text is not read.
Key points
- A neural network model was created to predict the fire resistance of RC columns.
- The model uses input parameters derived from numerical analyses.
- It specifically addresses columns under eccentric loading and one-sided standard fire (ISO 834).
- Numerical analyses were conducted using FIRE software, simulating nonlinear heat flow and stress-strain responses.
AI-generated from the title and abstract; the full text is not read.
Abstract
Using the concept of the artificial neural networks and the results of the performed numerical analyses as input parameters, the prediction model for defining the fire resistance of RC columns incorporated in walls and exposed to standard fire from one side, has been made. A short description of the numerical analyses of columns exposed to standard fire ISO 834, conducted by the computer software FIRE are presented in this paper. The software is capable of predicting the nonlinear response of reinforced concrete elements and plane frame structures subjected to fire loading, carrying out the nonlinear transient heat flow analysis and nonlinear stress-strain response associated with fire.
The authors' abstract, as published at the source. Applied Mechanics and Materials, 2014 · DOI ↗
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Field: Nuclear Energy and Engineering
Nuclear Energy and EngineeringEnergy