2291 A Fatigue Assessment Framework for Steel Bridges using Fiber Optic Sensors and Machine Learning

The main goal of the proposed research is to develop a machine learning (ML)assisted structural health monitoring (SHM) approach that employs fiber optic sensors (FOS) to enable (a) the assessment of the fatigue life of steel bridge details and (b) the accurate detection of the presence of damage under normal traffic loading conditions. In more detail, the proposed research aims at: -Constructing a monitoring system based on FOS to enable accurate strain quantification for efficient fatigue assessment and performance evaluation of steel bridge components. The FOS are chosen given their accuracy, low noise level, and durability. The developed monitoring system will be suitable for long-term field application under aggressive environmental conditions. -Formulating an approach that utilizes data from the FOS for damage detection in steel bridge components. The approach should detect and localize the damage without requiring detailed finite element modeling of the structure or detailed vehicular loading data. These requirements ensure its applicability for automated damage detection for existing bridges without the need for intensive post-processing data analysis. -Characterizing the effect of key operational parameters on the efficacy of the damage detection algorithm. These include the effect of loading conditions, temperature variations, type of damage, and boundary conditions. The proposed project will include the design of an instrumentation system for field application and validating its damage detection capabilities using large-scale laboratory testing.

Language

• English

Project

• Status: Active
• Funding: $305,000
• Contract Numbers:

  2291

  SPRY-0010(088)RS

• Sponsor Organizations:

  Oklahoma Department of Transportation

  200 NE 21st Street
  Oklahoma City, OK  United States  73105
• Managing Organizations:

  Oklahoma Department of Transportation

  200 NE 21st Street
  Oklahoma City, OK  United States  73105
• Project Managers:

  Peters, Walt

  Rice, Jerry

• Performing Organizations:

  Oklahoma State University, Stillwater

  School of Civil & Environmental Engineering
  Stillwater, OK  United States  74078
• Principal Investigators:

  Soliman, Mohamed

• Start Date: 20211001
• Expected Completion Date: 20240930
• Actual Completion Date: 0

Subject/Index Terms

• TRT Terms: Fiber optics; Machine learning; Steel bridges; Structural health monitoring
• Subject Areas: Bridges and other structures;

Filing Info

• Accession Number: 01830014
• Record Type: Research project
• Source Agency: Oklahoma Department of Transportation
• Contract Numbers: 2291, SPRY-0010(088)RS
• Files: RIP, STATEDOT
• Created Date: Dec 14 2021 11:51AM