Linear Regression Model for Sustainable Concrete Compressive Strength: A Partial Replacement of Agricultural Byproduct Ash to Portland Cement

This paper intends to assess the effects of substituting agricultural byproduct ash for cement in concrete making. Cement is a non-renewable resource and faces the potential of being depleted as it is one of the most consumed materials in the world. Moreover, the production of cement has adverse effects on the environment. As such, this study aims to find a sustainable partial replacement for cement. The researchers created concrete cylinders of varying mix ratios that partially replaced cement from 1% to 35%. A compression test was conducted using a Universal Testing Machine (UTM) to gather the experiment results. For the statistical treatment of the data, a linear regression machine learning was used by the researchers. A linear regression is used to visualize the relationship of the variables in a straight line. Machine learning can be utilized in predicting future values of the variables based on the linear regression used to treat the data. The study concluded that the compressive strength of the concrete with the agricultural byproduct ash was reduced as the percentage of cement replaced increased. Also, the study concluded that the compressive strength of concrete with agricultural byproduct ash peaked at 2% cement replacement with a mean compressive strength of 28.3 MPa.