Abstract
Steel fibers enhance the flexural strength, the compressive strength and the ductility of untra-high performance concrete, predicting the flexural strength and the compressive strength of ultra-high performance steel fiber reinforced concrete (UHPFRC) accurately has significant influence on controlling steel fiber volume fraction and optimizing UHPFRC mix proportion. In this study, to evaluate the effects of steel fibers on the mechanical properties of UHPFRC, two artificial neural networks were developed in order to predict the flexural strength and the compressive strength of UHPFRC, respectively. 102 test data sets and 162 test data sets from literature were trained and tested to establish the flexural strength model and the compressive strength model, respectively. In these two models, the influential parameters, including the water to binder ratio, the diameter, the length, the aspect ratio, and the volume fraction of steel fibers, as well as the compressive strength and the flexural strength of concrete without fibers were investigated as the inputs, while the compressive strength and the flexural strength of UHPFRC were the outputs. The results show that the artificial neural network models predicted the compressive strength and flexural strength of UHPFRC accurately. Then, by comparing with existing analytical models, it was determined that the proposed models had high applicability and reliability with respect to predicting the compressive strength and the flexural strength of UHPFRC.
Highlights
In ultra-high performance concrete (UHPC) mixture design, the compressive strength, and the flexural strength are two key mechanic parameters to evaluate the strength and the ductility of materials
The objective of this study is to develop two artificial neural networks (ANNs) models to predict the compressive strength and the flexural strength of ultra-high performance steel fiber reinforced concrete (UHPFRC)
Six indicators were applied in order to evaluate the performance specific limits to eliminate the non‐singular data, improve the precision of results, accelerate the of the compressive strength ANN model and five indicators for the flexural strength ANN model, convergence speed, and reduce the calculation time
Summary
In ultra-high performance concrete (UHPC) mixture design, the compressive strength, and the flexural strength are two key mechanic parameters to evaluate the strength and the ductility of materials. Because UHPC is brittle, the steel fibers with high tensile strength and high ultimate elongation, are always uniformly dispersed in UHPC to increase the ductility and the strength of concrete. The UHPC with steel fibers is called ultra-high performance steel fiber reinforced concrete (UHPFRC). The steel fibers in UHPFRC improve the cohesive forces between fibers and matrix, change the granular skeleton, and increase the anchorage length between fibers and the surrounding matrix [1,2]. Steel fibers bridge cracks and retard the propagation to increase.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
