Machine learning-based prediction of resilient modulus for blends of tire-derived aggregates and demolition wastes
Download
Download
Download
Full text for this resource is not available from the Research Repository.
Export
Ghorbani, Behnam 
ORCID: 0000-0002-8651-4402, Yaghoubi, Ehsan ORCID: 0000-0003-0639-0225, Wasantha, PLP, van Staden, Rudi ORCID: 0000-0002-7339-7702, Guerrieri, Maurice ORCID: 0000-0001-7916-7003 and Fragomeni, Salvatore ORCID: 0000-0002-0733-4770
(2023)
Machine learning-based prediction of resilient modulus for blends of tire-derived aggregates and demolition wastes.
Road Materials and Pavement Design, 25 (4).
pp. 694-715.
ISSN 1468-0629
Dimensions Badge
Altmetric Badge
| Item type | Article |
| URI | https://vuir.vu.edu.au/id/eprint/47982 |
| DOI | 10.1080/14680629.2023.2222176 |
| Official URL | https://www.tandfonline.com/doi/full/10.1080/14680... |
| Subjects | Current > FOR (2020) Classification > 4005 Civil engineering Current > Division/Research > Institute for Sustainable Industries and Liveable Cities |
| Keywords | construction and demolition waste; recycled materials; waste tires; sustainable materials; pavement structure; geotechnical engineering |
| Download/View statistics | View download statistics for this item |
CORE (COnnecting REpositories)