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A Field-Based Polynomial Model for Estimating the 28-Day Compressive Strength of Concrete from Slump, Temperature, and Density | ||
| Civil Engineering and Applied Solutions | ||
| مقالات آماده انتشار، پذیرفته شده، انتشار آنلاین از تاریخ 28 اردیبهشت 1405 | ||
| نوع مقاله: Original Article | ||
| شناسه دیجیتال (DOI): 10.22080/ceas.2026.31362.1081 | ||
| نویسندگان | ||
| Aliakbar Yahyaabadi* ؛ Seyyed Ghasem Rostami؛ Masood Mohammadi | ||
| Faculty of Engineering, University of Bojnord, Bojnord, Iran | ||
| تاریخ دریافت: 03 اسفند 1404، تاریخ بازنگری: 11 فروردین 1405، تاریخ پذیرش: 22 اردیبهشت 1405 | ||
| چکیده | ||
| 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 28 days, predicting it using site-specific in situ tests can help engineers assess on-site conditions. To develop a prediction model for compressive strength, 92 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 83 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 28-day compressive strength with a mean absolute error (MAE) of 0.849 MPa and a coefficient of determination (R²) of 0.744 for new samples. | ||
| کلیدواژهها | ||
| Ready-mixed concrete؛ Slump؛ Temperature؛ Density؛ Compressive strength؛ Prediction model | ||
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آمار تعداد مشاهده مقاله: 7 |
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