Predicting the strength characteristics of alkali activated concrete with environment friendly precursors using statistical methods

Abstract

Over the recent twenty years, utilization of ordinary Portland cement (OPC) has expanded dramatically, making it the world’s most mass-produced product. OPC manufacture is energy demanding, uses non-renewable naturally available resources, and is a major contributor to global warming (responsible for nearly 8 percent of global CO2 exhalations). A substitute to OPC concrete (OPCC) is Alkali Activated Concrete (AAC), in which precursors (raw materials) such as Blast Furnace Slag (GGBS), Fly Ash (FA) and other residues are activated with an activator solution. Statistical analysis is preferred for concrete related experiments incorporating a large number of samples and data in order to save time, money and work labour. The current work deals with developing statistical models for anticipating the compressive behaviour of AAC. Regression analysis is performed to determine the significant impact of variables on the compression behaviour and also to develop several linear regression models to predict the compressive strength of AAC at the age of 28 days. In the present work, collection of data base regarding mix proportions and mechanical properties of AAC is done through an extensive literature survey. This study identifies JASP as one of the most effective online tools for generating regression models.