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ICTD 2025

Data Sensing & Analytics

POSTER RECEPTION (View list of posters here)

Integrated Field Data Collection System to Determine Bridge Dynamic Impact Factor

Tuesday, June 10, 2025
4:45 PM – 6:00 PM MT

    Presenter(s)

  • KP

    Kundan Raj Parajulee, n/a

    Graduate Assistant
    Oklahoma State University
    Stillwater, Oklahoma, United States

    • Co-Author(s)

  • FA

    Fatemeh Ansari, n/a

    PhD Student
    Oklahoma State University
    Stillwater, Oklahoma, United States

  • Kaustav Chatterjee (he/him/his)

    PhD Student
    Oklahoma State University
    Stillwater, OK, United States

  • AP

    Akrit Pradhan, n/a

    Graduate Assistant
    Oklahoma State University
    Stillwater, Oklahoma, United States

    • Primary Author(s)

  • JL

    Joshua Q. Li

    Associate Professor
    Oklahoma State University
    Stillwater, OK, United States

    • Co-Author(s)

  • JL

    Joshua Q. Li

    Associate Professor
    Oklahoma State University
    Stillwater, OK, United States

  • LL

    Lin Li, n/a

    Postdoctoral Researcher
    Oklahoma State University
    Stillwater, Oklahoma, United States

  • WP

    Walt Peters

    Assistant Bridge Engineer - Maintenance
    Oklahoma Department of Transportation
    Oklahoma City, OK, United States

    • Submitter(s)

  • KP

    Kundan Raj Parajulee, n/a

    Graduate Assistant
    Oklahoma State University
    Stillwater, Oklahoma, United States

Abstract: The Bridge Impact Factor (IM) measures dynamic interactions between bridges and vehicles. Conducting network-level field tests for IM is challenging due to cost, labor, and efficiency constraints, while AASHTO’s IM guidelines are often considered conservative. This study introduces an integrated data collection system for determining dynamic IM on a bridge at SH-177 in Oklahoma. Using a highway longitudinal profiler, International Roughness Index (IRI) data were collected at 1-ft intervals to capture bridge bumps and dynamic impacts. Instrumentation sensors, including strain gauges, accelerometers, and an Inertial Measurement Unit (IMU), were installed on bridge girders of the first span to measure strain and acceleration under vehicular loading. Portable Weigh-in-Motion (WIM) systems at the bridge approach and on the first span measured both “static” and “dynamic” truck weights. A high-resolution camera recorded passing vehicles to validate WIM truck measurements and exclude the presence of multiple vehicles on the deck. Data from these sensors were processed with digital signal techniques to develop IM estimation equations based on deck smoothness and other significant parameters. This approach provides a rapid, efficient method for assessing bridge IM and load rating without traffic control.

Keywords: Impact Factor, Strain Gauge, Inertial Measurement Unit (IMU), Weigh-in-Motion (WIM), Digital Signal Processing

Learning Objectives:

Attendees can expect to learn the following from this session:
  • Upon completion, participant will be able to utilize different sensors to quantify the vehicle-road interaction and its effect
  • Upon completion, participant will be able to develop Impact factor based on the sensor data
  • Upon completion, participant will be able to derive the interrelationship between IRI and the Impact factor without disrupting traffic flow