• Journal of KIBIM
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• v.8 no.4
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• pp.13-22
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• 2018

Future performance prediction of bridges is challenging task for structural engineers. Well-organized information from design, construction and operation stages is essential for the assessment of structures. Digital twin model is a new concept to realize more reliable data platform for management of infrastructures. Damage history including degradation of material, cracking, corrosion, etc. needs to be accumulated in the digital model. The digital model is linked to the analysis model for the assessment of structural performance considering changed mechanical properties of structural components. In this paper, initial definition digital twin model of a PSC-I girder bridge is proposed.

• Smart Structures and Systems
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• v.10 no.2
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• pp.131-154
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• 2012

In this paper, it is aimed to determine the seismic behaviour of highway bridges by nondestructive testing using ambient vibration measurements. Eynel Highway Bridge which has arch type structural system with a total length of 216 m and located in the Ayvaclk county of Samsun, Turkey is selected as an application. The bridge connects the villages which are separated with Suat U$\breve{g}$urlu Dam Lake. A three dimensional finite element model is first established for a highway bridge using project drawings and an analytical modal analysis is then performed to generate natural frequencies and mode shapes in the three orthogonal directions. The ambient vibration measurements are carried out on the bridge deck under natural excitation such as traffic, human walking and wind loads using Operational Modal Analysis. Sensitive seismic accelerometers are used to collect signals obtained from the experimental tests. To obtain experimental dynamic characteristics, two output-only system identification techniques are employed namely, Enhanced Frequency Domain Decomposition technique in the frequency domain and Stochastic Subspace Identification technique in time domain. Analytical and experimental dynamic characteristic are compared with each other and finite element model of the bridge is updated by changing of boundary conditions to reduce the differences between the results. It is demonstrated that the ambient vibration measurements are enough to identify the most significant modes of highway bridges. After finite element model updating, maximum differences between the natural frequencies are reduced averagely from 23% to 3%. The updated finite element model reflects the dynamic characteristics of the bridge better, and it can be used to predict the dynamic response under complex external forces. It is also helpful for further damage identification and health condition monitoring. Analytical model of the bridge before and after model updating is analyzed using 1992 Erzincan earthquake record to determine the seismic behaviour. It can be seen from the analysis results that displacements increase by the height of bridge columns and along to middle point of the deck and main arches. Bending moments have an increasing trend along to first and last 50 m and have a decreasing trend long to the middle of the main arches.

• Smart Structures and Systems
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• v.30 no.6
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• pp.673-686
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• 2022

Deep learning algorithms for Structural Health Monitoring (SHM) have been extracting the interest of researchers and engineers. These algorithms commonly used loss functions and evaluation indices like the mean square error (MSE) which were not originally designed for SHM problems. An updated loss function which was specifically constructed for deep-learning-based structural damage detection problems has been proposed in this study. By tuning the coefficients of the loss function, the weights for damage localization and quantification can be adapted to the real situation and the deep learning network can avoid unnecessary iterations on damage localization and focus on the damage severity identification. To prove efficiency of the proposed method, structural damage detection using convolutional neural networks (CNNs) was conducted on a truss bridge model. Results showed that the validation curve with the updated loss function converged faster than the traditional MSE. Data augmentation was conducted to improve the anti-noise ability of the proposed method. For reducing the training time, the normalized modal strain energy change (NMSEC) was extracted, and the principal component analysis (PCA) was adopted for dimension reduction. The results showed that the training time was reduced by 90% and the damage identification accuracy could also have a slight increase. Furthermore, the effect of different modes and elements on the training dataset was also analyzed. The proposed method could greatly improve the performance for structural damage detection on both the training time and detection accuracy.

• Structural Monitoring and Maintenance
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• v.8 no.4
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• pp.379-402
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• 2021

Traditional approaches for structural health monitoring (SHM) seldom take ambient uncertainty (temperature, humidity, ambient vibration) into consideration, while their impacts on structural responses are substantial, leading to a possibility of raising false alarms. A few predictors model-based approaches deal with these uncertainties through complex numerical models running online, rendering the SHM approach to be compute-intensive, slow, and sometimes not practical. Also, with model-based approaches, the imperative need for a precise understanding of the structure often poses a problem for not so well understood complex systems. The present study employs a data-based approach coupled with Empirical mode decomposition (EMD) to correlate recorded response time histories under varying temperature conditions to corresponding damage scenarios. EMD decomposes the response signal into a finite set of intrinsic mode functions (IMFs). A two-dimensional Convolutional Neural Network (2DCNN) is further trained to associate these IMFs to the respective damage cases. The use of IMFs in place of raw signals helps to reduce the impact of sensor noise while preserving the essential spatio-temporal information less-sensitive to thermal effects and thereby stands as a better damage-sensitive feature than the raw signal itself. The proposed algorithm is numerically tested on a single span bridge under varying temperature conditions for different damage severities. The dynamic strain is recorded as the response since they are frame-invariant and cheaper to install. The proposed algorithm has been observed to be damage sensitive as well as sufficiently robust against measurement noise.

• Computers and Concrete
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• v.16 no.5
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• pp.723-740
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• 2015

In this study, the seismic performance of skewed highway bridges has been assessed by using fragility function methodology. Incremental Dynamic Analysis (IDA) has been used to prepare complete information about the different damage states of a 30 degree skewed highway bridge. A three dimensional model of a skewed highway bridge is presented and incremental dynamic analysis has been applied. The details of the full nonlinear procedures have also been presented. Different spectral intensity measures are studied and the effects of the period on the fragility curves are shown in different figures. The efficiency, practicality and proficiency of these different spectral intensity measures are compared. A suite of 20 earthquake ground motions are considered for nonlinear time history analysis. It has been shown that, considering different intensity measures (IM) leads us to overestimate or low estimate the damage probability which has been discussed completely.

• Structural Engineering and Mechanics
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• v.51 no.5
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• pp.809-821
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• 2014

The truss based steel bridge structures usually consists of gusset plates which lose their load carrying capacity and rigidity under the effect of repeated and dynamics loads. This paper is focused on modeling the nonlinear material behavior of the gusset plates of the Truss Based Bridges subjected to dynamics loads. The nonlinear behavior of material is characterized by a damage coupled elsto-plastic material models. A truss bridge finite element model is established in Abaqus with the details of the gusset plates and their connections. The nonlinear finite element analyses are performed to calculate stress and strain states in the gusset plates under different loading conditions. The study indicates that damage initiation occurred in the plastic deformation localized region of the gusset plates where all, diagonal, horizontal and vertical, truss member met and are critical for shear type of failure due tension and compression interaction. These findings are agreed with the analytical and experimental results obtained for the stress distribution of this kind gusset plate.

• Journal of the Earthquake Engineering Society of Korea
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• v.15 no.4
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• pp.13-21
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• 2011

Seismic structure pounding between adjacent superstructures may induce the destruction of pier and bridge superstructures and cause local damage that leads to the collapse of the whole bridge system. The pounding problem is related to the expansion of joints, gap distance and seismic response of the abutments. In this research, methods of the contact element approach, the linear spring model, the Kelvin-Voigt model and the Hertz model were studied to analyse the pounding characteristics. The shaking table test for a model specimen such as a bridge superstructure with elastomeric bearings was performed to evaluate the contact element approach methods. Relationships between the time history response from the numerical analysis results and the measured response from the shaking table test are compared. The experimental results were not well matched with the numerical analysis results using the existing pounding stiffness models. Therefore, in this study, coefficients are proposed to calculate the appropriate pounding stiffness ratio.

• Journal of the Korean Geotechnical Society
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• v.37 no.11
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• pp.61-69
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• 2021

In this study, scale down model bridge piers were fabricated and non-destructive experiments conducted with an impact load to determine scours in the ground adjacent to the bridge piers using the natural frequency of the bridge piers. Three scale-model bridge piers with different heights were fabricated, and they penetrated the ground at a depth of 0.35 m. The scours around the bridge piers were simulated as a side scour and foundation scour. The experiments were conducted in 13 steps, in which scouring around the model bridge piers was performed in 0.05 m excavation units. To derive the natural frequency, the impact load was measured with three accelerometers attached to the model bridge piers. The impact load was applied with an impact hammer, and the top of the model bridge pier was struck perpendicularly to the bridge axis. The natural frequency according to the scour progress was calculated with a fast Fourier transform. The results demonstrated that the natural frequency of each bridge pier tended to decrease with scour progress. The natural frequency also decreased with increasing pier height. With scour progress, a side scour occurred at 70% or higher of the initial natural frequency, and a foundation scour occurred at less than 70%.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.12
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• pp.150-156
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• 2017

This study examined the stress recovery length due to the local damage of a 7-wire strand, which is applied widely to PSC (Post Tensioned Concrete) bridges and cable-stayed bridges. The 7-wire strand is a multiple stranded steel of PC prestressing strand. Owing to the nature of the material, it is damaged continuously after completion with corrosion being the main cause of damage. On the other hand, due to its structural characteristics, it is difficult to grasp the degree of damage inside the cable and the pattern of stress variation. In the case of cables applied to bridges, the parts that are susceptible to corrosion are generated depending on the water supply and installation shape, which may cause local damage. This study analyzed the tendency of performance degradation and stress recovery length according to local damage of a 7-wire strand, which is applied mainly to bridge post-tensioning or stay cables. This study developed a computer-based simulation model that was validated with experimental results. The model developed in this study can be used to evaluate the safety level and estimate the remaining life span of P SC bridges or cable-stayed bridges.

• Smart Structures and Systems
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• v.24 no.1
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• pp.127-139
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• 2019

Residual drifts after an earthquake can incur huge repair costs and might need to replace the infrastructure because of its non-reparability. Proper functioning of bridges is also essential in the aftermath of an earthquake. In order to mitigate pounding and unseating damage of bridges subjected to earthquakes, a self-adaptive Ni-Ti shape memory alloy (SMA)-cable-based frictional sliding bearing (SMAFSB) is proposed considering self-adaptive centering, high energy dissipation, better fatigue, and corrosion resistance from SMA-cable component. The developed novel bearing is associated with the properties of modularity, replaceability, and earthquake isolation capacity, which could reduce the repair time and increase the resilience of highway bridges. To evaluate the super-elasticity of the SMA-cable, pseudo-static tests and numerical simulation on the SMA-cable specimens with a diameter of 7 mm are conducted and one dimensional (1D) constitutive hysteretic model of the SMAFSB is developed considering the effects of gap, self-centering, and high energy dissipation. Two types of the SMAFSB (i.e., movable and fixed SMAFSBs) are applied to a two-span continuous reinforced concrete (RC) bridge. The seismic vulnerabilities of the RC bridge, utilizing movable SMAFSB with the constant gap size of 60 mm and the fixed SMAFSBs with different gap sizes (e.g., 0, 30, and 60 mm), are assessed at component and system levels, respectively. It can be observed that the fixed SMAFSB with a gap of 30 mm gained the most retrofitting effect among the three cases.