Title:
State of the Art on Self-Healing Capacity of Cementitious Materials Based on Data Mining Strategies
Author(s):
Shashank Gupta, Salam Al-Obaidi, and Liberato Ferraral
Publication:
Symposium Paper
Volume:
350
Issue:
Appears on pages(s):
27-44
Keywords:
durability-based design; meta-analysis; self-healing concrete
DOI:
10.14359/51734310
Date:
11/1/2021
Abstract:
Concrete and cement-based materials inherently possess an autogenous self-healing capacity, which is even higher in High- and Ultra-High-Performance Concrete (HPC, UHPC) because of the high content of cement and supplementary cementitious materials (SCM) and low water/binder ratios. In this study, quantitative correlation through statistical models have been investigated based on the meta-data analysis. The employed approaches aim at establishing a correlation between the mix proportions, exposure type, and time and width of the initial crack against suitably defined self-healing indices. This study provides a holistic investigation of the autogenous self-healing capacity of cement-based materials based on extensive literature data mining. This is also intended to pave the way towards consistent incorporation of self-healing concepts into durability-based design approaches for reinforced concrete structures. The study has shown that the exposure type and duration, crack width size, and chemical admixtures have the most significant promotion on self-healing indices. However, other parameters, such as fibers and mineral admixtures have less impact on the autogenous self-healing of UHPC. The study also proposes suitably built design charts to quickly predict and evaluate the self-healing efficiency of cement-based materials which can significantly reduce, in the design stage, the time and efforts of laboratory investigation.
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