A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Using Model Updating to Predict the Failure of Reinforced Concrete Elements
Finding an accurate analytical model that is a good match for experimental data is not a straightforward task. Generally, analytical model parameters are tuned, using previously tested methods, to achieve an acceptable match for the experimental results. Model updating is a popular method that has been widely used since the early 1990s for this purpose. In this paper, research carried out for predicting the behaviour of masonry wall panels has been extended to find a suitable non-linear model for reinforced concrete (RC) beams that matches the experimental laboratory results. Data from laboratory experiments carried out by other researchers are used to confirm the validity of this analytical model. A Genetic Algorithm (GA) tool is used for the model updating process. The GA optimisation process finds a set of optimum parameters for use in the FE model. The outcome of this study was a close match with the experimental results, thus utilisation of this technique will dramatically reduce the number of expensive laboratory experimental tests which would otherwise be necessary.
Using Model Updating to Predict the Failure of Reinforced Concrete Elements
Finding an accurate analytical model that is a good match for experimental data is not a straightforward task. Generally, analytical model parameters are tuned, using previously tested methods, to achieve an acceptable match for the experimental results. Model updating is a popular method that has been widely used since the early 1990s for this purpose. In this paper, research carried out for predicting the behaviour of masonry wall panels has been extended to find a suitable non-linear model for reinforced concrete (RC) beams that matches the experimental laboratory results. Data from laboratory experiments carried out by other researchers are used to confirm the validity of this analytical model. A Genetic Algorithm (GA) tool is used for the model updating process. The GA optimisation process finds a set of optimum parameters for use in the FE model. The outcome of this study was a close match with the experimental results, thus utilisation of this technique will dramatically reduce the number of expensive laboratory experimental tests which would otherwise be necessary.
Using Model Updating to Predict the Failure of Reinforced Concrete Elements
Rafiq, Yaqub M. Y. (author) / Al-Farttoosi, M. (author)
ASCE International Workshop on Computing in Civil Engineering ; 2013 ; Los Angeles, California
Computing in Civil Engineering (2013) ; 459-467
2013-06-24
Conference paper
Electronic Resource
English
Using Model Updating to Predict the Failure of Reinforced Concrete Elements
| British Library Conference Proceedings | 2013
Concrete Shear Failure in Reinforced-Concrete Elements
| British Library Online Contents | 1996
Concrete Shear Failure in Reinforced-Concrete Elements
| Online Contents | 1996
| British Library Conference Proceedings | 2014