Comparison of small and large-scale wheel tracking devices
This paper presents a comparison of results from two wheel tracking devices. It is part of a larger on-going collaborative research project between the University of Nottingham in the UK, Delft University of Technology in The Netherlands and LCPC in France on the development and Finite Element (FE) implementation of a non-linear elasto-visco-plastic constitutive model for asphalt. Two devices, a large scale and small scale device, encompassed by the European Standard and the former British Standard were used. Rutting evaluation at the same temperature, on two different materials for pavement surface layers was tested under the same conditions allowing the evaluation of the rutting rate to be determined which was found to be very close from one test to another but sensitive to mixture type. In addition to rutting results, the contact dimensions and pressures from the two devices are evaluated in both the static case and during motion using a flat force transducer on the surface of the slab. The stresses induced in the slabs were calculated using finite element simulations and the measured contact conditions. For different pressure distributions under the wheel the isotropic and deviatoric stresses at the centre of the slab were compared which showed the importance of a good understanding of the wheel/slab contact conditions. The paper provides experimental rutting results obtained at the same temperatures for two characteristic materials on two devices. For future mechanical modelling the wheel print was found to be smaller during the motion than static prints. For wheels using inflated tyres a constant pressure over and elliptic area was found to be appropriate. For hard rubber wheels a rectangular area with an elliptic pressure distribution is more realistic.
Citation : Bodin, D., Grenfell, J.R.A. and Collop, A.C. (2009) Comparison of small and large-scale wheel tracking devices. Road Materials and Pavement Design (Special Issue), 10 (Sup. 1) pp. 295-325
ISSN : 1468-0629
Research Group : DIGITS
Research Institute : Institute of Artificial Intelligence (IAI)