Effect of Steel Fiber on First-Cracking Behavior of Ultra-High-Performance Concrete: New Insights from Digital Image Correlation Analysis

The first-cracking behavior of ultra-high-performance concrete (UHPC) is critical for the functionality and durability of its structures. However, determining the first-cracking strength by the linear limit point is challenging due to the nonlinear behavior before the initial crack. This study utilizes an improved Digital Image Correlation (DIC) technique to detect cracks and directly determine the first-cracking strength. The effect of steel fiber length, volume fraction, diameter, and shape on the first-cracking behavior was evaluated through direct tensile testing. Results indicate that incorporating steel fibers can enhance the first-cracking strength of UHPC to varying extents, ranging from 26.07% to 121.31%. Specifically, the length and volume fraction of steel fibers significantly affect the first-cracking strength, whereas the diameter and shape have minimal impact. The shape of steel fibers can influence the initial crack pattern due to stress concentration in deformed fibers. On the other hand, the inclusion of steel fibers can also negatively impact the first-cracking strength due to the introduction of air voids. Finally, considering both the positive and adverse effects of steel fibers, an updated predictive model for the first-cracking strength is proposed based on regression analysis of the experimental data. The proposed model can accurately predict the first-cracking strength of UHPC, fitting well with the existing data.

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Publication Details

Journal
Buildings
Published
2025-05-20
DOI
https://doi.org/10.3390/buildings15101727
Citations
3
Primary Topic
Innovative concrete reinforcement materials
Type
article
Field-Weighted Citation Impact
2.86

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article

Effect of Steel Fiber on First-Cracking Behavior of Ultra-High-Performance Concrete: New Insights from Digital Image Correlation Analysis

Chengjun Tan, Xing Lu, Lei Tu, Hua Zhao
3 citations
Buildings
Innovative concrete reinforcement materials
2.86
article

Effect of Steel Fiber on First-Cracking Behavior of Ultra-High-Performance Concrete: New Insights from Digital Image Correlation Analysis

Chengjun Tan, Xing Lu, Lei Tu, Hua Zhao
article en
3 citations

Abstract

The first-cracking behavior of ultra-high-performance concrete (UHPC) is critical for the functionality and durability of its structures. However, determining the first-cracking strength by the linear limit point is challenging due to the nonlinear behavior before the initial crack. This study utilizes an improved Digital Image Correlation (DIC) technique to detect cracks and directly determine the first-cracking strength. The effect of steel fiber length, volume fraction, diameter, and shape on the first-cracking behavior was evaluated through direct tensile testing. Results indicate that incorporating steel fibers can enhance the first-cracking strength of UHPC to varying extents, ranging from 26.07% to 121.31%. Specifically, the length and volume fraction of steel fibers significantly affect the first-cracking strength, whereas the diameter and shape have minimal impact. The shape of steel fibers can influence the initial crack pattern due to stress concentration in deformed fibers. On the other hand, the inclusion of steel fibers can also negatively impact the first-cracking strength due to the introduction of air voids. Finally, considering both the positive and adverse effects of steel fibers, an updated predictive model for the first-cracking strength is proposed based on regression analysis of the experimental data. The proposed model can accurately predict the first-cracking strength of UHPC, fitting well with the existing data.

BuildingsVol. 15(10)
Hunan University (CN), Changsha University of Science and Technology (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 10%
Innovative concrete reinforcement materials
2.86
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Effect of Steel Fiber on First-Cracking Behavior of Ultra-High-Performance Concrete: New Insights from Digital Image Correlation Analysis — Chengjun Tan, Xing Lu, et al. · Buildings (2025) | TGRS Research Map | TGRS