Artificial Intelligence Prediction of Rutting and Fatigue Parameters in Modified Asphalt Binders

The complex shear modulus (G*) and phase angle (delta) are fundamental viscoelastic rheological properties used in the estimation of rutting and fatigue pavement distress in asphalt binder. In the tropical regions, rutting and fatigue cracking are major pavement distress affecting the serviceability...

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Veröffentlicht in:	Applied sciences 2020-11, Vol.10 (21), p.7764, Article 7764
Hauptverfasser:	Uwanuakwa, Ikenna D., Ali, Shaban Ismael Albrka, Hasan, Mohd Rosli Mohd, Akpinar, Pinar, Sani, Ashiru, Shariff, Khairul Anuar
Format:	Artikel
Sprache:	eng
Schlagworte:	Accuracy Aging Algorithms Artificial intelligence Asphalt Asphalt pavements Binders Binders (materials) Case studies Chemistry Chemistry, Multidisciplinary Concrete mixing Crack propagation Data points Developing countries Engineering Engineering, Multidisciplinary fatigue Fracture mechanics Gaussian process GPR Laboratory tests LDCs Machine learning Materials fatigue Materials Science Materials Science, Multidisciplinary modified binder Neural networks Parameter estimation Parameter modification Pavement design Pavements Phase shift Physical Sciences Physics Physics, Applied Prediction models Principal components analysis Recurrent neural networks Rheological properties rutting Science & Technology Shear modulus Support vector machines SVM Technology Thin films Tropical environment Tropical environments Viscoelasticity
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