408
Views
6
CrossRef citations to date
0
Altmetric
Articles

Evaluating the dynamic stabilities of asphalt concrete mixtures incorporating plasterboard wastes

, &
Pages 929-938 | Received 02 Dec 2013, Accepted 10 Sep 2014, Published online: 30 Oct 2014
 

Abstract

This study aims at investigating the impact of recycling by-product plasterboard wastes (gypsum and bassanite) with asphalt mixtures by replacing partly the filler portion of the asphalt mixtures with pulverised plasterboard wastes in order to contribute to non-toxic and good urban environment on one hand and improve, or at least retain, the design mechanical properties of the resulting asphalt concrete mixture on the other. The study was based on series of wheel tracking tests which successfully proved the possibility of mixing recycled plasterboard wastes with asphalt mixtures. The tests results showed that asphalt samples of 40% gypsum-filler ratio and asphalt samples of 40% bassanite-filler ratio as well gave the maximum resistance to plastic deformations and hence maximum dynamic stabilities. As a result, this research has shown that mixing of plasterboard wastes with asphalt concrete mixtures in specific quantities is promising.

Acknowledgements

The authors would like to express their gratitude to Mr Gaku Matsunaga, former M.Sc. student at Fukuoka University, for his help in carrying out the experimental work of this research.

Additional information

Funding

This work was supported by Nippo Asphalt Company/Fukuoka branch in Japan.

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 61.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 225.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.