University of Utah Research Pioneering Sustainable Infrastructure Design in Utah

Revolutionizing Maintenance Data Collection for Better Planning


Civil & Environmental Engineering faculty member Dr. Juan Medina’s work is optimizing Utah’s transportation infrastructure through in-depth cost analysis. His team’s research emphasizes the importance of considering long-term maintenance costs alongside initial construction and installation expenses.

In partnership with the Upper Great Plains Transportation Institute, Dr. Medina’s recent work offers practical solutions that balance upfront construction costs with long-term maintenance needs, ultimately paving the way for more efficient statewide transportation planning.

The report, published by the Upper Great Plains Transportation Institute, presents a comprehensive review of ten years’ worth of barrier-related work order data and transactional expenses and provides the foundation for a big-picture analysis of barrier systems. The case study provided valuable insights into the challenges and opportunities in maintenance data collection and asset cost tracking over time. These findings are crucial for conducting comprehensive life-cycle cost analyses and evaluating alternative design options.

Dr. Medina’s research not only contributes to a deeper understanding of infrastructure maintenance and cost management but also offers practical solutions to enhance data collection practices. These improvements are vital for the accurate evaluation of design alternatives, ensuring that planners can make informed decisions that balance upfront costs with long-term sustainability.

Dr. Richard Porter, a former faculty member of the University of Utah, also played a significant role in this study. Their combined efforts are paving the way for more efficient and cost-effective transportation infrastructure design, ultimately benefiting the entire state of Utah. Read the abstract here.

 


Transportation Engineering at the University of Utah

Researchers in Transportation Engineering use state-of-the-art technology such as AI and machine-learning to make innovative advancements in the planning, design, operations, maintenance, and assessment of transportation systems.

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