Mr. Reza Baghaei-Naeini Profile

Reza Baghaei-Naeini

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Publications (3)

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Proceedings Article | 20 April 2011 Paper

Utilization of strong motion data for damage assessment of reinforced concrete bridges

Reza Baghaei, Maria Feng

Proceedings Volume 7983, 79832P (2011) https://doi.org/10.1117/12.880727

KEYWORDS: Bridges, Earthquakes, Time-frequency analysis, Optimization (mathematics), Genetic algorithms, Data modeling, Stochastic processes, Mathematical modeling, Error analysis, Calibration

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This study investigates the performance of a vibration-based technique for damage assessment of reinforced concrete bridges from non-stationary and incomplete acceleration response measurements during high amplitude earthquakes. The proposed damage assessment technique is targeted to be used in the aftermath of a major earthquake event to rapidly and remotely assess the functionality status of the bridge and identify potential hazards to the public safety. As the first step of the procedure, time-frequency representation of the response of the bridge is achieved by applying stochastic subspace system identification technique to successive and overlapping windows of the response measurements. The timefrequency representation is then used to identify the longest ending segment of the response with relatively stable modal properties. Post-earthquake experimental modal properties of the bridge are subsequently extracted from the identified stable portion of the response. These properties are used to estimate the amount of degradation in stiffness of the structural elements through an optimization-based finite element model updating technique. The Genetic Algorithm optimization technique is used to update the stiffness properties of the structural elements by minimizing the error between analytical and experimental modal properties of the bridge. The proposed damage assessment procedure is applied to experimental data from a large-scale shake table test during which a quarter-scale model of a reinforced concrete bridge was subjected to a series of earthquake and low-amplitude white noise base excitations. The meaningful agreement between the stiffness correction factors identified from both types of motions at the same damage state of the bridge demonstrates that the proposed procedure can effectively be applied for post-earthquake damage assessment of the bridges from nonlinear responses during high amplitude earthquakes.

Proceedings Article | 20 April 2011 Paper

Residual capacity estimation of bridges using structural health monitoring data

Reza Baghaei, Maria Feng, Marco Torbol

Proceedings Volume 7983, 79833I (2011) https://doi.org/10.1117/12.880728

KEYWORDS: Bridges, Earthquakes, Motion models, Data modeling, Databases, Structural health monitoring, Nonlinear response, Structural engineering, Analytical research, Modal analysis

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In this study, a vibration-based procedure for residual capacity estimation of bridges after damaging earthquake events is proposed. The procedure starts with estimation of collapse capacity of the intact bridge using incremental dynamic analysis (IDA) curves. The collapse capacity is defined as the median intensity level of the earthquakes that cause global or local collapse within the structure. A database of post-earthquake modal properties is created by calculating the analytical modal properties of the bridge after each nonlinear response history analysis performed for generation IDA curves. After the damaging event, experimental modal properties of the bridge are identified from vibration measurements of the bridge. These properties along with the modal properties database are used to find ground motionintensity pairs that can drive nonlinear FE model of the structure to the current damage state of the bridge. The IDA curves corresponding to the damaged FE model of the bridge are subsequently used to estimate amount of loss in collapse capacity of the damaged structure. Estimated loss in capacity of the bridge besides the bridge-site-specific seismic hazard curves are used to update the functionality status of the bridge. Proposed procedure is applied to experimental data from a large-scale shake table test on a quarter-scale model of a short-span reinforced concrete bridge. The bridge was subjected to a series of earthquake ground motions introducing progressive seismic damage to the bridge which finally led to the failure of one of the bents. Residual collapse capacity and functionality status of the bridge are updated at different stages of the experiment using the proposed procedure.

Proceedings Article | 9 April 2010 Paper

Damage assessment of the bridge structures using a hybrid optimization strategy

Reza Baghaei, Maria Feng

Proceedings Volume 7649, 76491N (2010) https://doi.org/10.1117/12.848855

KEYWORDS: Bridges, Data modeling, Optimization (mathematics), Signal to noise ratio, Earthquakes, Calibration, Matrices, Motion models, Error analysis, Interference (communication)

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Vibration based damage assessment of structures can be formulated as an optimization problem with the objective of minimizing the error between the measured and simulated responses of the structure by updating analytical model parameters. In this study, genetic algorithm (GA) and pattern search technique are combined in a hybrid optimization framework for finite element (FE) model updating using two objective functions defined in time and modal domains. The proposed model updating techniques have been applied to experimental data recorded during a shake table test on a quarter-scale model of a two span reinforced concrete bridge. The bridge was subjected to a series of seismic base excitations with increasing intensities introducing progressive real damage to the structure. Bridge responses to intermediate low amplitude white noise excitations are used for the purpose of modal identification and damage assessment. The FE model parameters are updated at different stages of the experiment. This study shows that damage throughout the structure can be accurately and consistently detected, located and quantified using the proposed model updating techniques.

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