0 Datasets
0 Files
Get instant academic access to this publication’s datasets.
Join our academic network to download verified datasets and collaborate with researchers worldwide.
Get Free AccessTire rubber waste is globally accumulated every year. Therefore, a solution to this problem should be found since, if landfilled, it is not biodegradable and causes environmental issues. One of the most effective ways is recycling those wastes or using them as a replacement for normal aggregate in the concrete mixture, which has high impact resistance and toughness; thus, it will be a good choice. In this study, 135 data were collected from previous literature to develop a model for the prediction of rubberized concrete compressive strength; the database comprised different mixture proportions, the maximum size of the rubber (1-40 mm), and the rubber percentage (0-100%) replacing natural fine and coarse aggregates were among the input parameters in addition to cement content (380-500 kg/m
Dilshad Kakasor Ismael Jaf, Aso A. Abdalla, Ahmed Salih Mohammed, Payam Ismael Abdulrahman, Rawaz Kurda, Azad A. Mohammed (2024). Hybrid nonlinear regression model versus MARS, MEP, and ANN to evaluate the effect of the size and content of waste tire rubber on the compressive strength of concrete. , 10(4), DOI: https://doi.org/10.1016/j.heliyon.2024.e25997.
Datasets shared by verified academics with rich metadata and previews.
Authors choose access levels; downloads are logged for transparency.
Students and faculty get instant access after verification.
Type
Article
Year
2024
Authors
6
Datasets
0
Total Files
0
Language
en
DOI
https://doi.org/10.1016/j.heliyon.2024.e25997
Access datasets from 50,000+ researchers worldwide with institutional verification.
Get Free AccessYes. After verification, you can browse and download datasets at no cost. Some premium assets may require author approval.
Files are stored on encrypted storage. Access is restricted to verified users and all downloads are logged.
Yes, message the author after sign-up to request supplementary files or replication code.
Join 50,000+ researchers worldwide. Get instant access to peer-reviewed datasets, advanced analytics, and global collaboration tools.
✓ Immediate verification • ✓ Free institutional access • ✓ Global collaboration