Predicting The Complex Modulus of Magnetic Activated Carbon Modified Bitumen Using Artificial Neural Networks

Abstract

In this study, the rheological properties of the bitumen modified with Magnetic Activated Carbon (MAC) were investigated and the results were predicted with artificial neural networks. Within the scope of the study, modified bitumens were obtained by adding 5%, 10% and 15% MAC to the B160/220 penetration grade bituminous binder. Then, a frequency sweep test at ten different frequencies (0.01-10Hz) and four different temperatures (40 °, 50 °, 60 °, 70 ° C) was carried out on original and modified bitumens with the Dynamic Shear Rheometer (DSR) device. The results showed that the addition of magnetic activated carbon improves the elastic properties of the binder by increasing the complex modulus and decreasing the phase angle values. Then, complex modulus and phase angle values, which vary depending on the frequency, addition content and temperature value, were predicted by artificial neural networks. The results showed that complex modulus and phase angle values of the bitumen can be obtained with very high accuracy and low error with artificial neural networks.

Keywords

• Rheology
• Magnetic activated carbon
• Modification
• Artificial neural networks

Manyetik Aktif Karbon Modifiyeli Bitümün Kompleks Modül Değerlerinin Yapay Sinir Ağlarıyla Tahmini

Abstract

Bu çalışmada Manyetik Aktif Karbon (MAK) ile modifiye edilmiş bitümlü bağlayıcının reolojik özellikleri araştırılmış ve sonuçlar yapar sinir ağları ile tahmin edilmiştir. Çalışma kapsamında B160/220 penetrasyon sınıfı bitümlü bağlayıcıya %5, %10 ve %15 oranlarında MAK ilave edilerek modifiye bitümler elde edilmiş, ardından bitümler üzerinde Dinamik Kayma Reometresi (DSR) cihazı ile on farklı frekansta (0.01-10Hz) ve dört farklı sıcaklıkta (40°,50°,60°,70°C) frekans taraması testi gerçekleştirilmiştir. Sonuçlar, MAK ilavesinin kompleks modül değerlerini artırıp, faz açısı değerlerini azaltarak bitümlü bağlayıcının elastik özelliklerini geliştirdiğini göstermiştir. Daha sonra frekans, katkı oranı ve sıcaklık değerlerine bağlı olarak değişen kompleks modül ve faz açısı değerleri yapay sinir ağları yöntemi ile tahmin edilmiştir. Sonuçlar, kompleks modül ve faz açısı değerlerinin oldukça yüksek doğrulukta düşük hata ile elde edilebileceğini göstermiştir.

Keywords

• Bitüm
• Reoloji
• Manyetik aktif karbon
• Modifikasyon
• Yapay sinir ağları

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