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Virginia Tech

Material Characterization and Numerical Techniques for Accurate Prediction of Snow-Tire Interactions

Abstract

dc:description.abstract

Snow traction is a critical performance parameter for tire manufacturers, typically evaluated using standardized methods such as ASTM F1805-20. However, physical testing presents substantial limitations, including limited access to winter proving grounds, difficulties in maintaining consistent test conditions and high prototyping costs. This dissertation addresses these challenges by developing advanced numerical simulations for snow-tire interactions. In this study, a systematic approach was established to characterize compacted snow with a density of 500 kg/m³. Material parameters for the Drucker-Prager Cap (DPC) plasticity model were derived from Direct Shear Tests (DST) and Confined Compression Tests (CCT). These parameters were validated through numerical simulations, which closely matched experimental results. The effectiveness of different numerical methods including Arbitrary Lagrangian-Eulerian (ALE), Smoothed Particle Hydrodynamics (SPH), and a hybrid SPH-FEM was evaluated. Simulations of in-situ devices such as the CTI penetrometer, Clegg hammer, and vane-cone device compared method performance in terms of accuracy, stability, and computational efficiency. The hybrid SPH-FEM method demonstrated the best performance. Additionally, a finite element analysis (FEA) model of the Standard Reference Test Tire (SRTT) 225/60R16 was developed and validated against experimental data with different inflation pressure. Using validated tire and snow models, traction simulations were conducted at various slip ratios and validated against in-situ test data. Additionally, the impact of tire tread design and sipes on traction was investigated by comparing a SRTT tire model to a blank-rib tire model under identical slip conditions. This research provides tire manufacturers with a reliable virtual validation method, significantly reducing the development time and prototype testing costs while improving traction performance of winter tires.

Degree

thesis:*
Name thesis:degree_name
Doctor of Philosophy
Level thesis:degree_level
doctoral
Discipline thesis:degree_discipline
Mechanical Engineering
Department dc:contributor.department
Mechanical Engineering
Grantor dc:publisher
Virginia Tech
Year dc:date.issued
2025

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Surkutwar, Yogesh Vitthalrao
Chairs dc:contributor.committeechair
  • Untaroiu, Costin D.
  • Sandu, Corina
Committee members dc:contributor.committeemember
  • Untaroiu, Alexandrina
  • Taheri, Saied

Subjects

dc:subject × 7

Rights

dc:rights
Statement dc:rights
  • In Copyright
Language dc:language.iso
en

Identifiers

dc:identifier.*
Dc Identifier Other
vt_gsexam:43692
OAI identifier oai:identifier
oai:vtechworks.lib.vt.edu:10919/135445

Chain of custody

source
Harvested from
Virginia Tech
Base URL
vtechworks.lib.vt.edu/oai/request
Last updated
2026-07-22
Source record
OAI-PMH GetRecord
citation

Surkutwar, Yogesh Vitthalrao. Material Characterization and Numerical Techniques for Accurate Prediction of Snow-Tire Interactions. doctoral thesis, Virginia Tech, 2025. https://hdl.handle.net/10919/135445