Method to Estimate Functional Obsolescence of Colorado Bridges
Bridges serve as critical components of a transportation infrastructure, ensuring the safe and efficient movement of people and goods. In the state of Colorado, as in many parts of the United States, there exists a substantial inventory of bridges that were designed and constructed in previous decades. Over time, these bridges may become functionally obsolete due to changing traffic patterns, revised design standards, and evolving transportation needs. Therefore, it is imperative to recognize and rectify functional obsolescence in bridges that no longer conform to current design standards. To address this challenge, this research proposal aims to address the pressing issue of functional obsolescence in bridges across Colorado. The primary objective is to develop a comprehensive guideline for the Colorado Department of Transportation (CDOT) to efficiently assess and address the issue of functional obsolescence in bridges. Additionally, the potential of utilizing advanced data analysis methods, such as machine learning and deep learning, to predict the functional obsolescence of bridges over the next decade will be explored. This assessment will help prioritize maintenance, rehabilitation, or replacement efforts and allocate resources effectively. This research proposal aims to develop a tailored guideline for the Colorado Department of Transportation (CDOT) to assess bridge functional obsolescence, and explore the feasibility of utilizing data analysis techniques for predicting future bridge obsolescence to enhance proactive infrastructure management. The research will begin with a systematic review of existing literature and guidelines related to bridge functional obsolescence, with a focus on best practices. This review will inform the development of tailored guidelines specific to CDOT's needs and Colorado's infrastructure characteristics. Simultaneously, data-driven approaches, including machine learning and deep learning, will be explored to create predictive models. These models aim to assist CDOT in anticipating and managing bridge functional obsolescence, enabling proactive resource allocation and infrastructure maintenance. This research project will contribute to the preservation and enhancement of Colorado's bridge infrastructure, ensuring its continued effectiveness and safety in a rapidly changing transportation landscape.
Language
- English
Project
- Status: Programmed
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Sponsor Organizations:
Colorado Department of Transportation
Applied Research and Innovation Branch
Denver, CO United States 80204 -
Managing Organizations:
Colorado Department of Transportation
Applied Research and Innovation Branch
Denver, CO United States 80204 -
Project Managers:
Tran, Thien
- Performing Organizations: Mississippi State, MS United States 39762
- Start Date: 20250601
- Expected Completion Date: 0
- Actual Completion Date: 0
Subject/Index Terms
- TRT Terms: Bridge management systems; Data analysis; Machine learning; Maintenance management; Predictive models
- Geographic Terms: Colorado
- Subject Areas: Bridges and other structures; Data and Information Technology; Highways; Maintenance and Preservation; Planning and Forecasting;
Filing Info
- Accession Number: 01930633
- Record Type: Research project
- Source Agency: Colorado Department of Transportation
- Files: RIP, STATEDOT
- Created Date: Sep 16 2024 9:17AM