Cultivating a Culture of Entrepreneurial Mindset and Undergraduate Research

Kun Zhang

Research Interests:

  • Recycling of pavement materials and industrial by-products
  • Intelligent and functional materials for transportation infrastructure
  • Advanced numerical modeling (CFD, DEM, and FEM) for engineering applications
  • Pavement evaluation and preservation

CURE-E Course: Transportation Engineering (CIVL 441), first introduced with CURE-E Fall 2021

Project Title: Analyze long-term pavement performance (LTPP) database to develop prediction models for pavement distresses.

Rutting and cracking are common distresses occurred in asphalt pavements, which significantly affect driving safety and pavement performance. The maintenance strategies (e.g. the selection of appropriate pavement preservation treatments) at the road network level are highly needed based on the models that could predict the condition of a road according to the pavement structure, pavement materials, local climate, and traffic data. This will assist transportation agencies to make informed decisions on the maintenance strategy. Therefore, research is highly needed to develop prediction models for pavement distresses by using the FHWA Long-Term Pavement Performance (LTPP) database, which contains pavement performance data as well as climatic and traffic data of in-service roads’ sections across the U.S. and Canada. This laboratory course implements course-based undergraduate research experiences (CUREs) and Entrepreneurial Mindset (EM) to allow students to explore the LTPP database and develop prediction models for pavement distresses in a Region or State.

Portrait of Kun Zhang