Modeling of Flexural Strength of Fiber Reinforced Concretes Containing Silica Fume or Fly Ash by GEP
Session
Civil Engineering, Infrastructure and Environment
Description
In this paper, a mathematical equation based on the gene expression programming (GEP) model has been developed to predict the flexural strength (ffs) of steel fiber reinforced concretes (SFRCs) containing silica fume (SF) or fly ash (FA). In order to obtain a mathematical equation of this model, the training, testing and validation sets using the experimental results for 175 specimens produced with 118 different mixtures were gathered from different literatures. The data used in the input variables of GEP model are arranged in a format of eleven input parameters that cover the age of specimen, the amounts of concrete mixtures and the properties of steel fibers. According to these input parameters, the ffs values of SFRCs were predicted in the GEP model. The training, testing and validation results in the model have shown that the model has strong potential to predict the ffs values of SFRCs containing SF or FA.
Keywords:
Fiber reinforced concrete, Silica fume, Fly ash, Flexural strength
Proceedings Editor
Edmond Hajrizi
ISBN
978-9951-437-50-9
First Page
32
Last Page
42
Location
Durres, Albania
Start Date
28-10-2016 9:00 AM
End Date
30-10-2016 5:00 PM
DOI
10.33107/ubt-ic.2016.12
Recommended Citation
Saridemir, Mustafa and Sinani, Besian, "Modeling of Flexural Strength of Fiber Reinforced Concretes Containing Silica Fume or Fly Ash by GEP" (2016). UBT International Conference. 12.
https://knowledgecenter.ubt-uni.net/conference/2016/all-events/12
Included in
Modeling of Flexural Strength of Fiber Reinforced Concretes Containing Silica Fume or Fly Ash by GEP
Durres, Albania
In this paper, a mathematical equation based on the gene expression programming (GEP) model has been developed to predict the flexural strength (ffs) of steel fiber reinforced concretes (SFRCs) containing silica fume (SF) or fly ash (FA). In order to obtain a mathematical equation of this model, the training, testing and validation sets using the experimental results for 175 specimens produced with 118 different mixtures were gathered from different literatures. The data used in the input variables of GEP model are arranged in a format of eleven input parameters that cover the age of specimen, the amounts of concrete mixtures and the properties of steel fibers. According to these input parameters, the ffs values of SFRCs were predicted in the GEP model. The training, testing and validation results in the model have shown that the model has strong potential to predict the ffs values of SFRCs containing SF or FA.