CenTiRe Project Spotlight: Modeling Snow Attributes for Tire Performance

CenTiRe is pleased to announce the successful completion of the research project “Characterization and Modeling of Different Snow Attributes for Tire Performance Simulation.”

This project set out to create a validated computational framework capable of accurately predicting tire traction on compacted snow—replicating conditions found in the ASTM F1805 snow traction test. The work aims to reduce reliance on costly field testing while improving understanding of snow–tire interaction and traction performance.

Key Outcomes

· Validated Snow Model: Developed and calibrated a compacted snow material model using laboratory shear and compression data.

· Advanced Simulation Methods: Evaluated several numerical approaches and identified a Hybrid SPH–FEM technique as the most accurate and efficient.

· Tire–Snow Interaction: Built and validated a finite element model of the Standard Reference Test Tire (SRTT) to simulate traction under realistic slip conditions.

· Tread Design Insights: Demonstrated how tread geometry and siping enhance traction on compacted snow.

Why It Matters

The resulting virtual validation framework will enable faster, more cost-effective, and sustainable winter tire development by reducing the need for physical prototypes and field tests. This simulation-driven approach directly supports CenTiRe’s mission to bridge academic research and industry innovation.

CenTiRe gratefully acknowledges Dr. Corina Sandu and Dr. Costin Untaroiu, faculty Principal Investigators at Virginia Tech, and graduate researcher Yogesh Surkutwar for their leadership and technical contributions throughout this project.