UROP Project
***Pavement Performance Simulation
Fatigue Cracking, Pavement Performance, Predictive Models
Research Mentor: Dr. Michael Elwardany, He/him/his
Department, College, Affiliation: Civil and Environmental Engineering, FAMU-FSU College of Engineering
Contact Email: melwardany@fsu.edu
Research Assistant Supervisor (if different from mentor):
Research Assistant Supervisor Email:
Faculty Collaborators:
Faculty Collaborators Email:
Department, College, Affiliation: Civil and Environmental Engineering, FAMU-FSU College of Engineering
Contact Email: melwardany@fsu.edu
Research Assistant Supervisor (if different from mentor):
Research Assistant Supervisor Email:
Faculty Collaborators:
Faculty Collaborators Email:
Looking for Research Assistants: Yes
Number of Research Assistants: 2
Relevant Majors: Civil Engineering, Computer Engineering, Computer Science, and Other Engineering Majors
Project Location: FAMU-FSU College of Engineering
Research Assistant Transportation Required: FSU Buss Services Remote or In-person: Partially Remote
Approximate Weekly Hours: 8 hours a week, Flexible schedule (Combination of business and outside of business. TBD between student and research mentor.)
Roundtable Times and Zoom Link:
Not participating in the roundtable
Number of Research Assistants: 2
Relevant Majors: Civil Engineering, Computer Engineering, Computer Science, and Other Engineering Majors
Project Location: FAMU-FSU College of Engineering
Research Assistant Transportation Required: FSU Buss Services Remote or In-person: Partially Remote
Approximate Weekly Hours: 8 hours a week, Flexible schedule (Combination of business and outside of business. TBD between student and research mentor.)
Roundtable Times and Zoom Link:
Not participating in the roundtable
Project Description
As machine learning increasingly becomes a transformative tool in engineering research, high-quality datasets are essential for training robust, predictive models. In pavement engineering, predictive models can significantly improve decision-making related to design, performance, and maintenance. However, there is currently a lack of comprehensive datasets capturing the effects of material properties and environmental conditions on pavement cracking behavior.This project aims to use FlexPAVE, a finite element-based pavement analysis software, to simulate cracking performance in flexible pavements constructed with various asphalt mixtures. The primary objective is to systematically run simulations across a wide matrix of material and environmental conditions to generate a large and consistent dataset for future machine learning applications. While the long-term goal involves predictive modeling, the current focus is solely on simulation design, execution, and structured data collection.
Research Tasks: Literature review
Data analysis
Documentation and reporting of outcomes
Skills that research assistant(s) may need: Required:
Basic research skills
Basic data analysis skills
Basic Excel
Recommended:
Coding skills