Statistical Models Supporting the High-Performance Self-Compacting Concrete (HPSCC) Design Process for High Strength

Materials (Basel). 2022 Jan 17;15(2):690. doi: 10.3390/ma15020690.

Abstract

The type of test ingredients used for obtaining self-compacting high-performance concrete (HPSCC) has been carefully selected to be universal. For this purpose, an extensive statistical analysis of the obtained results of the literature research was carried out. Then, universal and adapted to the typical range, highly fit statistical models are presented that can support the HPSCC design process for achieving high strength. For this purpose, a broad plan of statistical research was used, namely multivariate selection of sidereal points, which allowed the use of as many as five variable factors at three levels of variability. The sidereal points were equal to the respective minimum and maximum input values. Additionally, based on the analysis of variance (ANOVA) for factorial systems with the interaction of the obtained test results, the significance of the impact of the tested material factors on the compressive strength of the HPSCC tested was determined.

Keywords: ANOVA; HPSCC; compressive strength; high-performance self-compacting concrete.