Developing SonReb models to predict the compressive strength of concrete using different percentage of recycled brick aggregate

The study was conducted to obtain the relationship between non-destructive and destructive tests in concrete cubes using different ratios of normal stone and recycled brick as a coarse aggregate. Variations in the grade of concrete, density, and age were considered to make the model prediction more efficient in places where uses of recycled brick aggregate are common. Normal concrete M20, M25, and M30 grades were considered having density variation by replacing stone into recycled brick aggregate, and age by testing concrete strength at 7, 28, and 84 days. The regression model was created using artificial neural networks and multiple regression analysis. The study shows that the regression model developed using an artificial neural network predicted better results. The obtained models from the experiment were compared with other models provided by different authors. The study also considers the effect of using recycled brick aggregate in nondestructive tests and modulus of concrete.The accepted manuscript in pdf format is listed with the files at the bottom of this page. The presentation of the authors' names and (or) special characters in the title of the manuscript may differ slightly between what is listed on this page and what is listed in the pdf file of the accepted manuscript; that in the pdf file of the accepted manuscript is what was submitted by the author