Impact Resistance of Engineered Cementitious Composites Reinforced with Hybrid Fibers

To develop ECC with excellent impact resistance, this study investigates the impact performance of hybrid fiber reinforced specimens through drop-weight impact tests. The results show that the number of impacts to failure increases with fiber volume and fiber modulus. At the same volume of fibers, PE fiber reinforced specimens exhibit impact resistance 3.45 times and 2.92 times higher than those reinforced with PP fibers and glass fibers, respectively. The specimens reinforced with high modulus steel fibers exhibit localized punching shear damage at the impact site while maintaining better structural integrity. An impact damage evolution equation and a service life prediction model are established based on the two-parameter Weibull distribution. A comparative analysis of various algorithmic models is conducted to advance the application of machine learning in predicting the failure impact energy of the specimens.

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Publication Details

Journal
Journal of Advanced Concrete Technology
Published
2025-07-24
DOI
https://doi.org/10.3151/jact.23.296
Primary Topic
Innovative concrete reinforcement materials
Type
article
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article

Impact Resistance of Engineered Cementitious Composites Reinforced with Hybrid Fibers

Dongyue Liu, Zongcai Deng
4 links
Journal of Advanced Concrete Technology
Innovative concrete reinforcement materials
article

Impact Resistance of Engineered Cementitious Composites Reinforced with Hybrid Fibers

Dongyue Liu, Zongcai Deng
article en

Abstract

To develop ECC with excellent impact resistance, this study investigates the impact performance of hybrid fiber reinforced specimens through drop-weight impact tests. The results show that the number of impacts to failure increases with fiber volume and fiber modulus. At the same volume of fibers, PE fiber reinforced specimens exhibit impact resistance 3.45 times and 2.92 times higher than those reinforced with PP fibers and glass fibers, respectively. The specimens reinforced with high modulus steel fibers exhibit localized punching shear damage at the impact site while maintaining better structural integrity. An impact damage evolution equation and a service life prediction model are established based on the two-parameter Weibull distribution. A comparative analysis of various algorithmic models is conducted to advance the application of machine learning in predicting the failure impact energy of the specimens.

Journal of Advanced Concrete TechnologyVol. 23(7)
Beijing University of Technology (CN)
Sustainable cities and communities
Openalex Percentile: Top 81%
Innovative concrete reinforcement materials
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