Advancing Rail Infrastructure Asset Management and Hazard Mitigation: Educational Tools and Practitioner Decision Support Systems
As rail infrastructure ages and faces intensifying system stressors (e.g., flooding, icing, and extreme heat), agencies need to identify pathways to enhance the durability and operational reliability of their physical assets. However, there is a significant gap in available training material regarding Rail Infrastructure Asset Management (IAM) for both university students and current practitioners. Building upon the researcher’s ongoing research into adaptive capacity and international rail best practices, this project will translate rigorous research findings into accessible educational and research tools and practical decision-support systems. The project focuses on three primary technology transfer and workforce development initiatives: (1) Interactive Rail Asset Management Platform: The team will develop a web-based, interactive learning module (utilizing platforms such as Tigyog) targeting students and practitioners. This resource will cover the principles of IAM, condition assessment, and decision-making under uncertainty. It will feature "gamified" scenarios and narrative case studies drawn from the team's research, contrasting infrastructure failures (e.g., the East Palestine, Ohio derailment) with successful engineering adaptations (e.g., the Shinkansen automatic braking systems in Japan). Users will engage with a "build-your-own" asset management framework to apply these concepts in real-time. (2) University Teaching Packets: To address the lack of specialized rail engineering curricula, the team will create comprehensive teaching modules for instructors. These packets will draw from the team's six-country comparative analysis (U.S., Australia, Spain, Japan, Ghana, Argentina), providing lecture slides, assignment materials, and case-study evaluations. Topics will focus on identifying key asset vulnerabilities, institutional barriers to maintenance, and successful infrastructure hardening strategies. (3) Practitioner Decision Matrix: The team will develop a "Rail Hazard Mitigation Decision Matrix" for state agencies and rail operators. This tool will synthesize data on geographic hazards, system ownership models, and cost-benefit ratios to help managers prioritize physical infrastructure improvements.
Language
- English
Project
- Status: Active
- Funding: $120,000.00
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Contract Numbers:
DOT 69A3552348319
DOT 69A3552344814
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Sponsor Organizations:
Office of the Assistant Secretary for Research and Technology
University Transportation Centers Program
Department of Transportation
Washington, DC United States 20590National Center for Sustainable Transportation
University of California, Davis
Davis, CA United StatesGeorgia Institute of Technology, Atlanta
790 Atlantic Drive
Atlanta, GA United States 30332-0355 -
Managing Organizations:
National Center for Sustainable Transportation
University of California, Davis
Davis, CA United StatesUniversity of California, Davis
1 Shields Ave
Davis, California United States 95616Georgia Institute of Technology, Atlanta
790 Atlantic Drive
Atlanta, GA United States 30332-0355 -
Project Managers:
Cliff, Sydney
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Performing Organizations:
National Center for Sustainable Transportation
University of California, Davis
Davis, CA United StatesGeorgia Institute of Technology, Atlanta
790 Atlantic Drive
Atlanta, GA United States 30332-0355 -
Principal Investigators:
Garrett, Adair
- Start Date: 20260401
- Expected Completion Date: 20270331
- Actual Completion Date: 0
- USDOT Program: University Transportation Centers
Subject/Index Terms
- TRT Terms: Asset management; Best practices; Decision support systems; Education and training; Maintenance of way; Railroad transportation
- Subject Areas: Education and Training; Maintenance and Preservation; Planning and Forecasting; Railroads;
Filing Info
- Accession Number: 01985466
- Record Type: Research project
- Source Agency: National Center for Sustainable Transportation
- Contract Numbers: DOT 69A3552348319, DOT 69A3552344814
- Files: UTC, RIP
- Created Date: Apr 12 2026 11:25PM