Exploring Fracture Energy in Engineered Cementitious Composites: A Comprehensive Review
Source abstract
Abstract
Engineered cementitious composites (ECC) boast superior tensile strain capacity and crack resistance compared to traditional concrete. A key contributor to this enhanced behavior is their high fracture energy, reflecting the material's ability to absorb energy before failure. This review paper comprehensively examines the factors influencing ECC fracture energy. It explores the impact of fiber properties (volume, type, aspect ratio), the binding matrix's characteristics, and the crucial fiber–matrix bond quality. The review dives deeper into established methods for measuring ECC fracture energy. It analyzes various test configurations and data analysis techniques used to quantify this vital property. Understanding how critical factors such as fiber volume, aspect ratio, and fiber type can improve or reduce the fracture process is discussed in this review. To optimize the ECC design, different experimental procedures along with their advantages and shortcomings and future testing methods to clearly evaluate the fracture behavior of ECC are discussed as well. This allows for achieving targeted fracture energy levels tailored to specific applications. Additionally, the review identifies promising directions for future research in ECC fracture energy. These include multi-scale modeling for enhanced design, exploration of advanced fiber engineering for improved performance, and the possibility of incorporating self-healing mechanisms for increased durability. Ultimately, this review aims to provide a comprehensive understanding of the factors governing fracture energy in ECC and the methods for its evaluation, paving the way for the development of next-generation ECC with superior functioning and broader applicability.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Innovative concrete reinforcement materials · Structural Behavior of Reinforced Concrete · Concrete Properties and Behavior
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
References (100+)
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