SHM-based Bridge Element Deterioration Modeling and Prediction

The transportation legislation MAP-21 and the FAST Act have advanced the integration of performance-based asset management into transportation decision-making across federal, state, and local levels. Through Transportation Asset Management (TAM), agencies are establishing systematic processes to operate, maintain, and preserve infrastructure assets throughout their lifecycle. The objective of the project described herein is to support these goals by developing a methodology for predicting bridge element deterioration using long-term Structural Health Monitoring (SHM) data. Current approaches rely on periodic inspections and NDT/NDE methods, which miss real-time changes and pose safety risks. By combining SHM data with traditional models (Markov chains, Weibull distributions) and advanced algorithms, this research aims to produce accurate, time-based deterioration curves for bridge elements. Using high-resolution data from the BEAST lab at Rutgers University, the models will be calibrated and validated to reflect real-world deterioration mechanisms. This work supports NCIT’s mission to improve durability and extend the life of transportation infrastructure. It directly addresses the topical pillars of Infrastructure Durability, Resiliency, and Technology, offering tools for predictive maintenance, life-cycle cost management, and improved safety. The outcome will aid bridge owners in making data-driven decisions that enhance long-term performance and resilience.

Language

• English

Project

• Status: Active
• Funding: $150,000.00
• Contract Numbers:

  69A3552344813

  69A3552348318

• Sponsor Organizations:

  Office of the Assistant Secretary for Research and Technology

  University Transportation Centers Program
  Department of Transportation
  Washington, DC  United States  20590
• Managing Organizations:

  National Center for Infrastructure Transformation

  Prairie View A&M University
  Prairie View, TX  United States  77446
• Performing Organizations:

  National Center for Infrastructure Transformation

  Prairie View A&M University
  Prairie View, TX  United States  77446
• Principal Investigators:

  Morgese, Maurizio

  Maher, Ali

• Start Date: 20260201
• Expected Completion Date: 20270131
• Actual Completion Date: 20270131
• USDOT Program: University Transportation Centers
• Source Data: 03-37-RU

Subject/Index Terms

• TRT Terms: Asset management; Markov chains; Predictive models; Structural health monitoring; Weibull distributions
• Subject Areas: Bridges and other structures; Data and Information Technology; Safety and Human Factors;

Filing Info

• Accession Number: 02001913
• Record Type: Research project
• Source Agency: National Center for Infrastructure Transformation
• Contract Numbers: 69A3552344813, 69A3552348318
• Files: UTC, RIP
• Created Date: Sep 10 2026 8:40AM