Evaluating and quantifying segregation in asphalt pavement construction: A state-of-the-practice survey

• Published in: Construction & building materials 2023-06, Vol.383, p.131205, Article 131205
• Main Authors: Shi, Jiachen, Gong, Hongren, Cong, Lin, Liang, Haimei, Ren, Minda
• Format: Article
• Language: English
• Subjects: Construction quality evaluation; Hot mix asphalt; Image processing; Segregation; Text mining
• ISSN: 0950-0618; 1879-0526
• DOI: 10.1016/j.conbuildmat.2023.131205

•Evaluation of segregation should be carried out in a representative area, but there is lacking principles to determine this area.•The aggregate's position, quantity, and orientation distributions partly represent segregation and unevenly impact the mixture's performance, so the segregation evaluation index (SEI) design needs a reasonable weight assignment for the above particle features.•Surface-based SEIs hardly quantify the segregation that occurs in three-dimensional space, and a correlation between surface and spatial segregation is an option to fill this gap.•The segregation results not only can evaluate the construction quality but also point out weak road sections for developing maintenance strategies. Asphalt pavement construction requires accurate, rapid, and continuous quality evaluation. As a primary defect appearing in construction, segregation significantly reduces the pavement's mechanical properties and service life, making it become a hot spot in asphalt pavement construction research. This review aims to provide a state-of-the-art review about evaluating and quantifying hot mix asphalt segregation and identify the opportunities and challenges in the quality evaluation of automatic asphalt pavement construction. This review contained text mining findings and critical surveys. Text mining was used to analyze the co-occurrence relationship of research keywords and the change of research heats. Based on the text mining findings, we critically reviewed the data collection, data processing, and quantification indexes of the subjective, direct-objective, and indirect-objective segregation evaluation methods. The remaining deficiencies and possible research directions have been discussed.