A Computational Tool for the Reliable Prediction of Pavement Performance based on Temperature Data

A Computational Tool for the Reliable Prediction of Pavement Performance based on Temperature Data

Developed as a modular, open-source Python package with accompanying Jupyter notebook examples and hosted on GitHub, this tool provides a scalable approach to pavement condition monitoring. The research shows that temperature data collected from embedded thermocouples, when analyzed using advanced computational techniques, can serve as reliable indicators of pavement degradation, supporting more informed, data-driven infrastructure management decisions


Infrastructure Assets: Highway Assets, Pavement
Resource Types: Code or Software Tool
Capabilities: Tools & Technology
Management Processes: Monitoring & Adjustment
Publisher:
Center for Transportation Studies, University of Minnesota

Publication Year:
2025

External Link

Related Sites
TPM Portal