Baseline Model Updating during Bridge Construction Using Measured Strains

Sanayei, Masoud; Brenner, Brian; Santini‐Bell, Erin; Sipple, Jesse D.; Phelps, John E.; Lefebvre, P. J.

doi:10.1061/41130(369)66

Cited by 3 publications

(2 citation statements)

References 4 publications

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“…of a significant change in the system performance due to likely damage to determine the need for more costly actions, either through a targeted visual inspection for areas of potential damage or model updating and parameter estimation depending on the available data (Santini-Bell et al, 2007;Sanayei et al, 2011).…”

Section: Real-time Condition Assessment For Operational Decision-makimentioning

confidence: 99%

Diagnostic Testing of a Vertical Lift Truss Bridge for Model Verification and Decision-Making Support

Shahsavari

Mashayekhi

Mehrkash

et al. 2019

Front. Built Environ.

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A practical long term structural health monitoring program must be based on reasonable field capabilities, the needs of the bridge owner, and the anticipated structural behavior unique to the structure. Each sensor installed as part of the monitoring program should provide information directly in response to operational needs related to the structure's short term and long term performance. A thoughtfully considered instrumentation plan developed in cooperation with the bridge designer, bridge manager, bridge maintenance operator and academic researchers will provide data to enhance both the state of the practice and state of the art for the bridge structural design, management and maintenance. Monitoring a bridge's structural response has the potential to (a) detect the presence of structural changes for condition assessment, (b) inform the bridge manger to assist in daily operational decision-making and (c) validate the structural design assumptions and (d) refine a structural model of the bridge to be used for performance prediction. The excitation for these responses typically comes from traffic or environmental demands. Vertical lift bridges provide a unique opportunity for structural health monitoring based on the dynamic response due to the frequent and repeated impact imparted on the structure each time the lift span opens and closes. In this paper, a structural health monitoring system designed to provide valuable information for design verification, structural model calibration, fatigue monitoring, and operational decision-making support for the reconstructed Memorial Bridge carrying US Route 1 between Portsmouth, New Hampshire and Kittery, Maine. This paper will detail the development of the sensor layout including input from stakeholders, accessibility issues and complementary and contradicting objectives. A set of structural models with varying degrees on complexity were created based on the structural performance objectives. The data collected during a pseudo-static truck load test was used to calibrate the structural models of the bridge and to select the appropriate model for each post-processing and decision-making tools related to structural performance.

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Section: Real-time Condition Assessment For Operational Decision-makimentioning

confidence: 99%

Diagnostic Testing of a Vertical Lift Truss Bridge for Model Verification and Decision-Making Support

Shahsavari

Mashayekhi

Mehrkash

et al. 2019

Front. Built Environ.

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“…As per bridge design specifications, bridges are modeled as 'simply supported', assuming no lateral demands on the bridge girder or slab. It is common knowledge that due to extreme temperature variations, horizontal displacements in a bridge can be significant (Helmicki et al, 1999;Rohrmann et al, 2000;Catbas et al, 2008;Bell and Sipple, 2009;Sanayei et al, 2011). Wipf et al noted the tilt of the piers of a bridge located in Iowa, US.…”

Section: Introductionmentioning

confidence: 99%

Efficient bridge steel bearing health monitoring using laser displacement sensors and wireless accelerometers

Waqas,

Sahil,

Riaz

et al. 2024

Front. Built Environ.

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Steel bearings have been commonly used to counteract induced loading from thermal and traffic conditions in numerous bridges. However, their effectiveness has been compromised due to aging and maintenance limitations, potentially impacting the overall bridge system performance. Existing monitoring techniques for detecting malfunctioning steel bearings lack automation and precision, making them inadequate for long-term and real-time bridge dynamics assessment. This study proposes a response-based approach to identify bearing malfunction by analyzing the traffic-induced response in the bearing vicinity. To implement this approach, laser displacement sensors and wireless acceleration sensors were employed to monitor both malfunctioning and well-functioning steel bridge bearings. Significant differences in bearing performance were observed through response analysis and comparison. Laser sensor measurements revealed larger vertical deflections in the girder at malfunctioned bearing under traffic loading. Moreover, the investigation of the acceleration response in the bearing locality indicated that bearing malfunction could alter the vibrational characteristics of the vicinity, significantly affecting Cross Power Spectral Density (CPSD) and cross-correlation. To quantitatively evaluate the performance of steel bearings, a Condition Score (CS) was introduced. The CS exhibited a strong correlation with bearing damage, providing valuable insights for maintenance and decision-making processes in bridge asset management. This study offers a comprehensive and automated method for identifying steel bridge bearing malfunction by utilizing advanced monitoring techniques and introducing the CS for assessment. The results obtained from this approach can enhance bridge maintenance strategies and contribute to effective bridge asset management.

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Construction monitoring and control for Jiaomen River arch bridge in Guangzhou

Zhu

Yan

et al. 2017

IABSE Symposium, Vancouver 2017: Engineering the Future

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<p>For novel arch rib, it is difficult to control the accuracy of the segments and whole bridge, especially for special shape bridge. It is also hard to balance the maximum lateral displacement (MLD) of arch rib and the maximum axis force (MAF) of jigs when removing temporary supports at high altitude. To address these issues, firstly, the derrick arch bridge with a total span of 231 meters is taken as the research object. Following the establishment of the finite element (FE) model of the bridge, an innovative criterion is proposed to consider both axis position and inclination angle, in which the error during the closure stage of the bridge is controlled availably. Secondly, among three potential plans modeled with FE model, one was chosen to remove the jigs, which effectively reducing the MAF and the MLD. Finally, the field monitor tests were proofread with FE model results to ensure the reasonable state of the bridge.</p>

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Baseline Model Updating during Bridge Construction Using Measured Strains

Cited by 3 publications

References 4 publications

Diagnostic Testing of a Vertical Lift Truss Bridge for Model Verification and Decision-Making Support

Diagnostic Testing of a Vertical Lift Truss Bridge for Model Verification and Decision-Making Support

Efficient bridge steel bearing health monitoring using laser displacement sensors and wireless accelerometers

Construction monitoring and control for Jiaomen River arch bridge in Guangzhou

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