Assessment of mechanical properties of C80 concrete prepared with different stone powder contents by a statistical analysis. (15th September 2022)

• Record Type: Journal Article
• Authors: Wu, Hongmei; Shen, Bo; Ma, Kejian; Xuan, Dongxing
• Is Part Of: Journal of building engineering. Volume 56(2022)
• Publication Date: 2022-09-15
• Subjects: Stone powder content -- M-sand concrete -- Standard value -- Mathematical statistics; Building -- Periodicals; 690.05
• DOI: 10.1016/j.jobe.2022.104754
• Languages: English
• ISSNs: 2352-7102

Abstract

Abstract: Machine-made rock sand (M-sand) as a replacement of river sand has been promoted as an environmental-friendly substitute in concrete. It is acknowledged that the stone powder in M-sand has an adverse influence on performance of concrete. This study investigated the influence of stone powder contents from 3% to 15% on mechanical properties of M-sand C80 concrete. As per experimental results, adopting the arithmetic mean method from experimental results hardly determined the optimum stone powder content for various mechanical properties of high-strength concrete due to high variation. A statistical analysis method was thus developed to verify the influence of stone powder content on mechanical properties of concrete. A new random variable was first constructed by considering the standard value, followed by the standard normal distribution. Meanwhile, the type I error in statistical hypothesis testing was further adopted. It was found that this developed statistical method can further verify experimental results through a standard value method, which can be used for practical engineering applications in accordance with specifications and provide a way to optimize the stone powder content in high strength concrete for experiment-oriented researches. Highlights: The influence of stone powder on mechanical properties of concrete was investigated. The standard values of properties were calculated from experimental results. A statistical analysis method was developed to evaluate the influence of stone powder. The optimal stone powder content was determined. A statistical way to optimize the powder content was put forward.