TY - GEN
T1 - Data-Driven Approaches Integrating SHM, WIM, and Digital Twin for Service Life Assessment of the Brooklyn-Queens Expressway (BQE)
AU - Na, Chaekuk
AU - Nassif, Hani
AU - Lou, Patrick
AU - Hanbay, Serap
AU - Braguim, Thales Couto
AU - Yang, Chan
AU - Harrison, Dawn
AU - Pandya, Tanvi
AU - Ozbay, Kaan
N1 - Publisher Copyright: © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.
PY - 2025
Y1 - 2025
N2 - Highway bridges are designed for specific loads but are increasingly subjected to overweight vehicles, causing significant infrastructure damage. Structural Health Monitoring (SHM) and Weigh-In-Motion (WIM) systems have become essential for assessing structural integrity and predicting future performance. SHM provides real-time structural data, while WIM records vehicle loads, enabling the development of site-specific live load models. Additionally, Finite Element Analysis (FEA) is utilized in the digital twin simulations to help estimate the remaining service life by integrating SHM and WIM data. This study employs SHM sensors, including accelerometers and strain gauges, with Wi-Fi connectivity to simplify installation. A WIM system near bridge approaches identifies truck load spectra. Short-term strain data linked to truck weights were used to calibrate the FEA, while accelerometers collected periodic data to analyze structural responses. Event-triggered thresholds guide long-term monitoring, correlating acceleration data with structural stiffness. Case studies with various geometries incorporate inspection reports, including rebar corrosion, petrographic analysis, and concrete core samples, to refine the FE models and material properties. These inputs are critical for predicting future conditions and estimating service life.
AB - Highway bridges are designed for specific loads but are increasingly subjected to overweight vehicles, causing significant infrastructure damage. Structural Health Monitoring (SHM) and Weigh-In-Motion (WIM) systems have become essential for assessing structural integrity and predicting future performance. SHM provides real-time structural data, while WIM records vehicle loads, enabling the development of site-specific live load models. Additionally, Finite Element Analysis (FEA) is utilized in the digital twin simulations to help estimate the remaining service life by integrating SHM and WIM data. This study employs SHM sensors, including accelerometers and strain gauges, with Wi-Fi connectivity to simplify installation. A WIM system near bridge approaches identifies truck load spectra. Short-term strain data linked to truck weights were used to calibrate the FEA, while accelerometers collected periodic data to analyze structural responses. Event-triggered thresholds guide long-term monitoring, correlating acceleration data with structural stiffness. Case studies with various geometries incorporate inspection reports, including rebar corrosion, petrographic analysis, and concrete core samples, to refine the FE models and material properties. These inputs are critical for predicting future conditions and estimating service life.
KW - Deterioration
KW - FEM
KW - SHM
KW - Service Life Prediction
KW - WIM
UR - https://www.scopus.com/pages/publications/105018105199
UR - https://www.scopus.com/pages/publications/105018105199#tab=citedBy
U2 - 10.1007/978-3-031-96110-6_100
DO - 10.1007/978-3-031-96110-6_100
M3 - Conference contribution
SN - 9783031961090
T3 - Lecture Notes in Civil Engineering
SP - 1007
EP - 1016
BT - Experimental Vibration Analysis for Civil Engineering Structures, EVACES 2025 - Volume 1
A2 - Cunha, Álvaro
A2 - Caetano, Elsa
PB - Springer Science and Business Media Deutschland GmbH
T2 - 11th International Conference on Experimental Vibration Analysis for Civil Engineering Structures, EVACES 2025
Y2 - 2 July 2025 through 4 July 2025
ER -