Grant: Discovery Grants Program - Individual

Tire wear particles are a significant source of microplastic emissions that have been found to contribute to over 50% of microplastic emissions in some countries. Tire wear particles are composed of various materials, including Styrene-butadiene rubber, Butadiene rubber and natural rubber. The concentration of tire wear particles can vary depending on the road and traffic scenarios, with urban driving areas having higher concentrations compared to highways. Tire wear particles can be found in ambient air, water, and soil, posing potential ecotoxicological risks. While estimating tire wear particle emissions through chemical indicators and sampling may be inaccurate, capturing tire wear particles in real time provides more accurate estimates. Developing solutions to mitigate tire wear particle emissions is necessary to reduce the impact of microplastic pollution on the environment and human health. Currently, there is much research developed in the field of tire wear using experimental, analytical/numerical, and semi-empirical approaches. Reported studies on experimental and simulation methods are mostly focused on estimating tire wear for dynamics and control using sensors and repeated tests. These methods, however, do not permit direct estimates of tire wear particle emissions. During the current Discovery award, the applicant has successfully developed reliable simulation models of several truck tires and soils for the purpose of design, safety dynamics, and performance analyses. The rubber constituents of these tires were modeled using the Mooney Rivlin relation, which is non-distractive and not capable of predicting tire wear for rolling tires. In this DG program, an alternate rubber material model, such as non-linear, destructive, hyperplastic rubber called "Ogden" will be used for predicting tread wear (mass loss prediction) and possibly tread temperature distribution. It is proposed to investigate the Ogden model for estimating short- to medium-term tire wear. A more challenging hyperplastic material model will be employed in the long term to predict tire failure or blowup under severe operating conditions. In order to identify Ogden material model parameters, a tire standard specimen of the tread will be used to determine the stress-strain relationship to fit 3ed order Ogden material function and determine the coefficients that are needed for the FEA model. The candidate lab facility dynamometer will be used to determine tire wear rate under different operating conditions. The measured wear data will be used to calibrate the tire FEA model using the 3rd-order Ogden material model. This research program will be beneficial for the Canadian automotive industry and Environment Canada by reducing the time and monetary expenses involved in physical testing of tire wear and predictions of environmental Pollution due to rolling tires on the roads. In addition, several new HQPs will be trained in using advanced tire modeling models.