4.6 Article

The Behavior of Hybrid Fiber-Reinforced Concrete Elements: A New Stress-Strain Model Using an Evolutionary Approach

期刊

APPLIED SCIENCES-BASEL
卷 12, 期 4, 页码 -

出版社

MDPI
DOI: 10.3390/app12042245

关键词

fibrous concrete; high-strength concrete (HSC); mechanical characteristics; steel fiber; hybrid fibers; concrete damage plasticity (CDP); concrete modeling

资金

  1. University of Baghdad-Iraq
  2. Universiti Kebangsaan Malaysia
  3. Ministry of Science and Technology
  4. University of Technology-Iraq

向作者/读者索取更多资源

This study presents a new empirical stress-strain model for predicting the strength of polyvinyl alcohol and steel fiber reinforced concrete. Through experiments and data analysis, it was found that the model is consistent with the experimental results. Furthermore, case studies of hybrid fiber-reinforced concrete structures provide insights into the behavior of this material.
Several stress-strain models were used to predict the strengths of steel fiber reinforced concrete, which are distinctive of the material. However, insufficient research has been done on the influence of hybrid fiber combinations (comprising two or more distinct fibers) on the characteristics of concrete. For this reason, the researchers conducted an experimental program to determine the stress-strain relationship of 30 concrete samples reinforced with two distinct fibers (a hybrid of polyvinyl alcohol and steel fibers), with compressive strengths ranging from 40 to 120 MPa. A total of 80% of the experimental results were used to develop a new empirical stress-strain model, which was accomplished through the application of the particle swarm optimization (PSO) technique. It was discovered in this investigation that the new stress-strain model predictions are consistent with the remaining 20% of the experimental stress-strain curves obtained. Case studies of hybrid-fiber-reinforced concrete constructions were investigated in order to better understand the behavior of such elements. The data revealed that the proposed model has the highest absolute relative error (ARE) frequencies (ARE 10%) and the lowest absolute relative error (ARE > 15%) frequencies (ARE > 15%).

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