Cracking performance evaluation and modelling of RAP mixtures containing different recycled materials using deep neural network model

M Khorshidi, M Ameri, A Goli - Road Materials and Pavement …, 2024 - Taylor & Francis
This study evaluates the cracking resistance of recycled asphalt pavement (RAP) mixtures
including waste engine oil (WEO), crumb rubber (CR), and steel slag aggregates using the …

Data-driven approach for investigating and predicting rutting depth of asphalt concrete containing reclaimed asphalt pavement

HL Nguyen, VQ Tran - Construction and Building Materials, 2023 - Elsevier
The aim of this paper is to investigate and predict the rutting depth of asphalt concrete
containing Reclaimed Asphalt Pavement (RAP) content by the data-driven approach with …

Autonomous soil vision scanning system for intelligent subgrade compaction

X Wang, T Wang, J Zhang, G Ma - Automation in Construction, 2024 - Elsevier
The wide application of intelligent compaction in subgrade construction is limited by the
evaluation accuracy. The current practice assumes the compacted site as a homogeneous …

Development of a balanced cracking index for asphalt mixtures tested in semi-circular bending with load-LLD measurements

H Majidifard, B Jahangiri, P Rath, WG Buttlar - Measurement, 2021 - Elsevier
In this study, a new Semi-Circular Bending (SCB) Balanced Cracking Index (BCI), is
introduced as an alternative cracking index to the FI and CRI, which are based on the IL …

Aggregate boundary recognition of asphalt mixture CT images based on convolutional neural networks

Y Peng, H Yang - Road Materials and Pavement Design, 2024 - Taylor & Francis
This study aims to propose an intelligent aggregate boundary segmentation algorithm based
on convolutional neural networks (CNNs) and watershed algorithm for quickly recognising …

[HTML][HTML] Predictive models for flexible pavement fatigue cracking based on machine learning

AJ Alnaqbi, W Zeiada, G Al-Khateeb, A Abttan… - Transportation …, 2024 - Elsevier
Pavement performance prediction is crucial for ensuring the longevity and safety of road
networks. In our extensive study, we employ a diverse array of techniques to enhance …

[HTML][HTML] Deep learning techniques for multi-class classification of asphalt damage based on hamburg-wheel tracking test results

JA Guzmán-Torres, LA Morales-Rosales… - Case Studies in …, 2023 - Elsevier
In recent years, advancements in deep learning (DL) have been leveraged in civil
engineering, but further exploration is necessary to apply DL techniques to asphalt research …

Application of deep learning for characterizing microstructures in SBS modified asphalt

E Zhang, L Shan, Y Guo, S Liu - Materials and Structures, 2024 - Springer
Microstructures in asphalt, often resembling bee structures, are pivotal in influencing asphalt
performance and, by extension, sustainable fuel production. This study employs deep …

A data-driven rutting depth short-time prediction model with metaheuristic optimization for asphalt pavements based on RIOHTrack

Z Li, I Korovin, X Shi, S Gorbachev… - IEEE/CAA Journal of …, 2023 - ieeexplore.ieee.org
Rutting of asphalt pavements is a crucial design criterion in various pavement design
guides. A good road transportation base can provide security for the transportation of oil and …

Studying the impact of aggregates and mix volumetric properties on the moisture resistance of asphalt concrete using a feed-Forward artificial neural network

MA Dalhat, SA Osman - Road Materials and Pavement Design, 2023 - Taylor & Francis
Several studies have reported the effect of various additives on the moisture resistance of
AC, but limited studies explored the impact of aggregate's properties on the moisture …