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Öğe A New Approach to Compressive Strength Assessment of Concrete: Image Processing Technique(Amer Inst Physics, 2012) Başyiğit, Celalettin; Çomak, Bekir; Kılınçarslan, ŞemsettinIn this study, the compressive strength levels of different concrete classes were estimated using an image processing technique. A series of different concretes were prepared by applying different water/cement ratios. The percentages of cement matrix, aggregate, and air void were calculated by processing the images obtained from the surfaces of hardened concretes. The relation between the parameters that were calculated via image processing and the compressive strengths of the concretes produced were examined. By this means, the compressive strength levels of concretes were estimated one by one via the developed image processing software and ImageJ. It was found that the compressive strength levels of concretes can be estimated with a high level of correlation by using the values obtained via the image processing technique. The developed software can be used to estimate the compressive strength levels of concretes. In addition, in considering concrete age, cure conditions, and relative humidity, the method used in this study can be used together with destructive and non-destructive test methods.Öğe Modeling Marshall stability of light asphalt concretes fabricated using expanded clay aggregate with artificial neural networks(2012) Morova, Nihat; Karahançer, Şebnem Sargın; Terzi, Serdal; Saltan, Mehmet; Serin, SercanIn this study, an Artificial Neural Network (ANN) model has been developed to estimate Marshall Stability (MS) of lightweight asphalt concrete containing expanded clay. In the model, amount of bitumen (%), transition speed of ultrasound (?s), unit weight (gr/cm 3) were used as inputs and Marshall Stability (kg) was used as output. Developed ANN model results and the experimental results were compared and good relationship was found. © 2012 IEEE.
