Numerical and experimental predictions of texture-related influences on rolling resistance

Mansura, Dmytro A.; Thom, Nicholas H.; Beckedahl, Hartmut J.

Abstract

To overcome rolling resistance (RR) a typical vehicle on average consumes 4152 MJ/119 L of fuel annually as a result of both
vehicle and pavement factors. A slight improvement in surface texture arrangement may therefore decrease fuel consumption
bringing substantial long-term socio-economic benefits. This aligns with ever-tighter limits on CO2 in the USA (163 g/km until 2025) fostering sustainable construction/exploitation of tires/pavements. This paper describes a multi-scale 3-D numerical methodology to calculate micro-distortional RR and contact indentations of surface aggregates into visco-elastic tread compound accounting for loading, velocity, temperature, and compound properties. It consists of a micro-scale tread block single aggregate model and a macro-scale car tire finite element model, rolling in steady-state mode over a rigid smooth surface. The surface texture is idealized in terms of hemispherical indenters. The micro-distortional RR estimates are based on contact force and energy lost per single stone. The computed contact/normal forces peak significantly due to visco-elastic effects at the beginning of the tire–surface contact phase, followed by a gradually relaxing stress region with a sudden release at the end of the interaction. The contact forces appear to be of a reasonable distribution and magnitude. It is found that microdistortional RR is higher on a rougher and sparsely packed surface compared with a smoother and more tightly packed case. To determine the total tire-related RR, macro-distortional RR can then be added. The predictions were qualitatively confirmed and adjusted against real bituminous mixes by experimental testing, showing a reasonable agreement.

Citation

Mansura, D. A., Thom, N. H., & Beckedahl, H. J. (2018). Numerical and experimental predictions of texture-related influences on rolling resistance. Transportation Research Record, doi:10.1177/0361198118776114

• Journal Article Type: Article
• Acceptance Date: Nov 1, 2017
• Online Publication Date: May 30, 2018
• Publication Date: May 30, 2018
• Deposit Date: Jan 31, 2019
• Publicly Available Date: Feb 1, 2019
• Publisher: SAGE Publications (UK and US)
• Peer Reviewed: Peer Reviewed
• DOI: https://doi.org/10.1177/0361198118776114
• Public URL: https://nottingham-repository.worktribe.com/output/1220118
• Publisher URL: https://journals.sagepub.com/doi/10.1177/0361198118776114