A Field-Based Polynomial Model for Estimating the ۲۸-Day Compressive Strength of Concrete from Slump, Temperature, and Density

Concrete is one of the most widely used materials in the construction industry. Quality control of ready-mixed concrete is important due to the many factors that influence its quality from the production phase to placement and curing. Slump, temperature, density, and compressive strength are commonly used tests for evaluating the quality of concrete. Since the compressive strength test requires ۲۸ days, predicting it using site-specific in situ tests can help engineers assess on-site conditions. To develop a prediction model for compressive strength, ۹۲ samples of ready-mixed concrete were collected in collaboration with the National Standard Organization of Iran in accordance with the relevant national standards. The samples were divided into two groups of training and testing datasets, including ۸۳ and nine randomly selected samples, respectively. According to the proposed model, compressive strength can be predicted from a twelve-term polynomial function in terms of powers of density, slump, and temperature, and their products. The performance of the model was assessed by calculating statistical indicators for the training samples as well as external validation with testing samples not used during model development. The model predicted the ۲۸-day compressive strength with a mean absolute error (MAE) of ۰.۸۴۹ MPa and a coefficient of determination (R²) of ۰.۷۴۴ for new samples.

Keywords:

Ready-mixed concrete , Slump , Temperature , density , Compressive strength , Prediction model