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- Utilizing artificial neural networks to predict the asphalt pavement profile temperature in western Europe. In: Case Studies in Construction Materials, v. 18 (July 2023). (2023):
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- Use of a machine learning-based framework to approximate the input features of an intrinsic cohesive zone model of recycled asphalt mixes tested at low temperatures. In: Construction and Building Materials, v. 373 (April 2023). (2023):
- Assessing the potential of application of titanium dioxide for photocatalytic degradation of deposited soot on asphalt pavement surfaces. In: Construction and Building Materials, v. 350 (October 2022). (2022):
- Validation of a model to predict the effect of short-term aging on the rheological properties of asphalt binders. In: Construction and Building Materials, v. 278 (April 2021). (2021):
- Utilizing deep learning and advanced image processing techniques to investigate the microstructure of a waxy bitumen. In: Construction and Building Materials, v. 313 (December 2021). (2021):
- Identification of the viscoelastic properties of an asphalt mixture using a scanning laser Doppler vibrometer. In: Materials and Structures, v. 53, n. 6 (16 October 2020). (2020):
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