Improved sorptivity models for mortar and concrete based on significant process parameters. (15th April 2022)

• Record Type: Journal Article
• Authors: Hanumanthu, Korakuti; Sarkar, Kaustav
• Is Part Of: Journal of building engineering. Volume 47(2022)
• Publication Date: 2022-04-15
• Subjects: ANOVA -- Concrete -- Mortar -- Sorptivity -- Taguchi analysis; Building -- Periodicals; 690.05
• DOI: 10.1016/j.jobe.2021.103912
• Languages: English
• ISSNs: 2352-7102

Abstract

Abstract: Sorptivity of cementitious composites serves as a reliable measure of durability and extensive research on the factors influencing sorptivity is available. However, the literature lacks a robust model based on statistically significant process parameters for the prediction of this important parameter. This work combines experiments designed through Taguchi's method with ANOVA to rank the effects of cement type, coarse-to-fine aggregate ratio, water-to-cement ratio, curing age, and test temperature on sorptivity. The water-to-cement ratio has been found to be the most influencing factor as is also indicated by Washburn's law. The significant parameters have been used to develop new empirical models for sorptivity of initially dry mortar and concrete. The validation results based on data obtained from literature show that the models perform robustly despite of the wide range of mix-design. The model parameters could be further refined using the delineated algorithm requiring only nine experimental runs based on a 3 2 design. Highlights: Taguchi's design and ANOVA have been adopted to study sorptivity. Cement type, w/c, curing age, and temperature affect sorptivity significantly. The developed model unifies the effects of significant factors. The predictions are satisfactory for a wide range of mix design.