Fundamental characterisation of dry process crumb rubber modified asphalt mixtures
Professor G.D. Airey (NTEC) - Principal Investigator
Professor A.C. Collop (formerly NTEC) - Co-investigor
M. Rahman - Research Assistant
Sponsored by EPSRC, Highways Agency, Shell Bitumen, Foster Yeomen, Charles Lawrence Recycling Ltd, Scrap Tyre Working Group, Scott Wilson Pavement Engineering
Background
Scrap tyres form a major part of the world’s solid waste management problem. Each year UK produces around 30million waste tyres with 1 billion are produced globally. Almost half of them are used for landfill or stockpile and rest of them are recycled. New European legislation will prohibit using scrap tyre as a landfill by 2006. Within the expending recycling market, only two, to date, have shown the potential to use a significant number of scrap tyres, (i) fuel for combustion and (ii) crumb rubber modified (CRM) material for asphalt paving. Although combustion can consume millions of tyres, but it is not an ideal environmental solution. The only remaining potential market for using scrap tyres is crumb rubber modified material for asphalt paving. Modified asphalt paving products with crumb rubber can be made by several techniques, including wet process (binder modification by finely ground rubber) and dry process (part of aggregate replaced by rubber crumb).
Aims and objectives
In this research project the use of crumb rubber in the dry process technology will be investigated to improve the design method and also to gain fundamental knowledge to produce a number of practical recommendations for the production of dry process CRM technology in UK.
The overall aims of the project are to;
- Perform literature review
- Investigate the chemical and physical interaction of the crumb rubber & bitumen in the dry process
- Investigate the mechanical interaction of rubber-bitumen composites
- Investigate the mechanical properties of the mixtures
- Validation of results by performing larger scale testing
- Mixture design guidelines and performance prediction