[HTML][HTML] Prediction of rheological properties and ageing performance of recycled plastic modified bitumen using Machine learning models

S Salehi, M Arashpour, EM Golafshani… - Construction and Building …, 2023 - Elsevier
Recycled plastics can be used to improve the rheological properties of neat bitumen. The
rheological properties of recycled plastic modified bitumen (RPMB) depend on multiple …

An eXtreme Gradient Boosting model for predicting dynamic modulus of asphalt concrete mixtures

Y Ali, F Hussain, M Irfan, AS Buller - Construction and Building Materials, 2021 - Elsevier
Dynamic modulus (DM)—an important stiffness property and a basic input parameter in the
design of flexible pavements—is often obtained through expensive, laborious, and time …

The influence of SBS modification on the rheological property of asphalt before and after regeneration

N Zhang, G Fan, S Lv, F He, X Fan, X Peng… - … and Building Materials, 2021 - Elsevier
In this article, the author intends to explore the different aging process of SBS modified
asphalt, and the influence of chemical components on the rheological property by adding …

Improved predictions of asphalt concretes' dynamic modulus and phase angle using decision-tree based categorical boosting model

F Rondinella, F Daneluz, B Hofko, N Baldo - Construction and Building …, 2023 - Elsevier
The most suitable parameter to summarize the viscoelastic response of asphalt concrete
(AC) mixtures is the complex modulus, defined by means of its two main components: the …

Gradient optimization method for tunnel resistivity and chargeability joint inversion based on deep learning

P Jiang, B Liu, Y Tang, Z Liu, Y Pang - Tunnelling and Underground Space …, 2024 - Elsevier
The water inrush hazards have become one of the bottleneck problems that constrain tunnel
construction. Ahead geological prospecting is the major tool to avoid geo-hazards and …

Machine learning applications for developing sustainable construction materials

H Adel, MI Ghazaan, AH Korayem - Artificial Intelligence and Data Science …, 2022 - Elsevier
Consuming a huge proportion of raw materials and resources, the construction industry
could significantly affect the environment. In addition, the production of cement, the most …

Viscoelasticity of asphalt mixture based on the dynamic modulus test

L Ma, H Wang, Y Ma - Journal of Materials in Civil Engineering, 2024 - ascelibrary.org
This study comprehensively describes the viscoelastic behavior of high-elasticity modified
asphalt mixtures under varying strain conditions. The commonly used sigmoidal model …

A multidimensional framework for asphalt pavement evaluation based on multilayer network representation learning: A case study in RIOHTrack

H Liu, J Cao, W Huang, X Shi, X Zhou, Z Li - Expert Systems with …, 2024 - Elsevier
Pavement evaluation using multiple performance indicators has been a critical challenge in
the field due to limitations in relying on pavement engineers to simultaneously assess …

[HTML][HTML] Neural network approach for GO-modified asphalt properties estimation

HGT Hoang, TA Nguyen, HL Nguyen, HB Ly - Case Studies in Construction …, 2022 - Elsevier
This paper presents an innovative development process of Artificial Neural Network (ANN)
to predict four properties of Graphene Oxide (GO) modified asphalt, including penetration …

Quantifying the differential phase angle behaviour of asphalt concrete mixtures using artificial neural networks

F Hussain, Y Ali, M Irfan - International Journal of Pavement Research and …, 2022 - Springer
Phase angle is an important property of asphalt concrete (AC) mixtures that can aid in
proper material selection and thereby assist in accurate design of flexible pavements. In …