Title

Structural Identification For Performance Prediction Considering Uncertainties: Case Study Of A Movable Bridge

Keywords

Bridge; Finite-element model; Load rating; Prediction; Reliability; Structural health monitoring (SHM); Structural identification (St-Id); Uncertainty

Abstract

Structural identification (St-Id) can be described simply as estimating the properties of a structural system based on a correlation of inputs and outputs for decision making. For a complete St-Id process, establishing the decision-making needs, developing analytical and numerical models, and conducting field measurements, along with parameter identification using the experimental data for model calibration, are carried out. One important consideration is evaluation of the limitations and adequacy of using a single calibrated model before leveraging it for decision making, such as the reliability of the structural system for the remainder of its design life. The uncertainties in the data collected, determined by means of intermittent testing or monitoring; the limitations of the models; and the nonstationary nature of structural behavior need to be considered. These uncertainties can be incorporated by using of a family of parent and offspring models. The objective of this paper is to illustrate the use of a family of models that incorporates the uncertainties and makes predictions in terms of load rating and system-level reliability with the help of structural health monitoring (SHM) data. First, a finite-element (FE) model of a movable bridge is calibrated with SHM data, and parent FE models are created to best represent the measurements. At the same time, uncertainties in critical structural parameters such as boundary conditions are considered by offspring models. The family-of-models approach is employed to estimate load rating and system reliability by considering the probability of failure of the system with different correlations among the safety margins of the components. Finally, future performance of the movable bridge in the case of damage and deterioration is estimated for demonstration of structural identification for performance prediction by considering uncertainties. Such results are expected to provide a set of solutions for the performance of a structure for optimal decision making. © 2013 American Society of Civil Engineers.

Publication Date

10-1-2013

Publication Title

Journal of Structural Engineering (United States)

Volume

139

Issue

10

Number of Pages

1703-1715

Document Type

Article

Personal Identifier

scopus

DOI Link

https://doi.org/10.1061/(ASCE)ST.1943-541X.0000601

Socpus ID

84885012757 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/84885012757

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