Predicting time to cracking of concrete composites under restrained shrinkage: A review with insights from statistical analysis and ensemble machine learning approaches

Restrained shrinkage cracking significantly undermines the performance of reinforced concrete and shortens the structures' lifespan. Standard methods have been established to examine restrained shrinkage cracking of cementitious composites, i.e., ASTM C1581, AASHTO T 334, AASHTO T 363, and RILEM TC 119-TCE. Deficiencies in testing methods for accommodating and evaluating different cementitious composites have been recognized. Nevertheless, the significance of the restrained shrinkage cracking factors and cracking vulnerability based on the degree of restraint provided by different testing methods remain unexplored. This article provides a critical review of testing methods and studies on restrained shrinkage cracking in cementitious composites, highlighting the limitations, advantages, and further capabilities. Comprehensive experimental test datasets associated with standard restrained shrinkage cracking test methods are compiled. Advanced statistical analysis and machine learning (ML) techniques are utilized to predict time-to-cracking (TTC) of cementitious composites subjected to various testing methods based on the cracking factors. Robust and precise ML's bagging and boosting algorithms such as random forest, gradient boosting machine, extreme gradient boosting, adaptive boosting, categorical gradient boosting, and stacking ensemble models are utilized to merge predictions of the various approaches on TTC. Despite the satisfactory performance of statistical modeling, stacking demonstrates the highest precision in forecasting TTC, achieving an R2 of 0.92 for the ASTM dataset and 0.65 for the AASHTO dataset. The derived statistical and ML models reveal the significance of drying shrinkage, binder content, and moist curing as the most important factors in TTC based on ASTM C1581 and AASHTO T 334 standard testing methods. Equations are derived to predict cracking vulnerability and design concrete composites that offer delayed TTC and prolonged service life. [Display omitted] •Restrained shrinkage testing methods are reviewed, their limitations, advantages, and further developments are elaborated.•Significant factors contributing to restrained shrinkage cracking are discussed.•Comprehensive experimental test datasets associated with standard restrained shrinkage cracking test methods are compiled.•Novel statistical analysis and machine learning techniques are employed to predict time-to-cracking of concrete composites.•Equations are derived to predict crac