Development of truck tire-terrain finite element analysis models.
| dc.contributor.advisor | El-Gindy, Moustafa | |
| dc.contributor.author | Dhillon, Ranvir Singh | |
| dc.date.accessioned | 2014-01-02T20:10:16Z | |
| dc.date.accessioned | 2022-03-25T19:03:01Z | |
| dc.date.available | 2014-01-02T20:10:16Z | |
| dc.date.available | 2022-03-25T19:03:01Z | |
| dc.date.issued | 2013-12-01 | |
| dc.degree.discipline | Electrical and Computer Engineering | |
| dc.degree.level | Master of Applied Science (MASc) | |
| dc.description.abstract | Heavy vehicles require tires which can withstand extreme loads while maintaining control, delivering performance and minimizing fuel consumption, particularly on soft soils. Recent advances in finite element analysis and computational efficiency have opened doors to highperformance, highly complex simulations which were not possible just a few years ago. This research aims to model two tires using non-linear finite element analysis code and validate them using static and dynamic tests, including response to steering input. Soils are modeled using both traditionally-meshed FEA techniques as well as a newer mesh-less smoothed particle hydrodynamics method. Soils are validated and the accuracy of the SPH and FEA models are compared. The tires and soils are used together to estimate the rolling resistance of the tire over various terrains. The developed soil models are sufficient to model soils behaving like clay. The SPH soil models behave closer to actual soils, providing superior penetration and shear properties. This causes the SPH soil models to exhibit rolling resistance closer to experimental data. | en |
| dc.description.sponsorship | University of Ontario Institute of Technology | en |
| dc.identifier.uri | https://hdl.handle.net/10155/373 | |
| dc.language.iso | en | en |
| dc.subject | FEA | en |
| dc.subject | SPH | en |
| dc.subject | Tires | en |
| dc.subject | Soils | en |
| dc.subject | Rolling resistance | en |
| dc.title | Development of truck tire-terrain finite element analysis models. | en |
| dc.type | Thesis | en |
| thesis.degree.discipline | Electrical and Computer Engineering | |
| thesis.degree.grantor | University of Ontario Institute of Technology | |
| thesis.degree.name | Master of Applied Science (MASc) |
