Title: Self-healing Capacity of Cementitious Materials Based on Data Mining Strategies

Author(s): Liberato Ferrara

Publication: Web Session

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Date: 4/1/2021

Abstract:
Concrete and cement-based materials inherently possess a autogenous self-healing capacity, which is even high in High and Ultra High Performance Concretes (HPC, UHPC) because of the high cement and supplementary cementitious materials (SCM) and low water/binder ratios. Despite the huge amount of literature on the topic self-healing concepts still fail to consistently enter into design strategies able to effectively quantify their benefits of the structural performance. In this study, quantitative relationships through statistical models have been carried out. The employed approaches aimed at establishing a correlation between the mix proportions, mainly in terms of quantity and type of binders, exposure type, and time and width of the initial crack against suitably defined self-healing indices, quantifying the recovery of material performances which can be of interest for intended applications. Therefore, this study provides, for the first time in the literature to the authors’ knowledge, a holistic investigation on the autogenous self-healing capacity of cement-based materials based on extensive literature data mining. This is also intended to pave the way towards consistence incorporation of self-healing concepts into durability based design approaches for reinforced concrete structures, aimed at quantifying, with reliable confidence, the benefits in terms of slower degradation of the structural performance and extension of the service life-span. The main purpose of the study has been to quantify a “healable crack width” as a function of the structural service scenario as well as of the material composition variables, which could be used in serviceability limit state design calculations as well as quantify its influence on material durability parameters with the purpose of evaluating the kinetics of degradation mechanisms. The final aim of the study is to propose, also through suitably built design charts, a straightforward input-output model to quickly predict.