• Steel and Composite Structures
• /
• v.49 no.1
• /
• pp.81-89
• /
• 2023

A simplified calculation method of natural vibration characteristics of high-speed railway multi-span bridge-longitudinal ballastless track system is proposed. The rail, track slab, base slab, main beam, bearing, pier, cap and pile foundation are taken into account, and the multi-span longitudinal ballastless track-beam-bearing-pier-cap-pile foundation integrated model (MBTIM) is established. The energy equation of each component of the MBTIM based on Timoshenko beam theory is constructed. Using the improved Fourier series, and the Rayleigh-Ritz method and Hamilton principle are combined to obtain the extremum of the total energy function. The simplified calculation formula of the natural vibration frequency of the MBTIM under the influence of vertical and longitudinal vibration is derived and verified by numerical methods. The influence law of the natural vibration frequency of the MBTIM is analyzed considering and not considering the participation of each component of the MBTIM, the damage of the track interlayer component and the stiffness change of each layer component. The results show that the error between the calculation results of the formula and the numerical method in this paper is less than 3%, which verifies the correctness of the method in this paper. The high-order frequency of the MBTIM is significantly affected considering the track, bridge pier, pile soil and pile cap, while considering the influence of pile cap on the low-order and high-order frequency of the MBTIM is large. The influence of component damage such as void beneath slab, mortar debonding and fastener failure on each order frequency of the MBTIM is basically the same, and the influence of component damage less than 10m on the first fourteen order frequency of the MBTIM is small. The bending stiffness of track slab and rail has no obvious influence on the natural frequency of the MBTIM, and the bending stiffness of main beam has influence on the natural frequency of the MBTIM. The bending stiffness of pier and base slab only has obvious influence on the high-order frequency of the MBTIM. The natural vibration characteristics of the MBTIM play an important guiding role in the safety analysis of high-speed train running, the damage detection of track-bridge structure and the seismic design of railway bridge.

• Journal of the Korea institute for structural maintenance and inspection
• /
• v.25 no.6
• /
• pp.1-11
• /
• 2021

As the aging of large domestic SOC facilities accelerates, facility maintenance is also changing from safety evaluation based on the current condition to performance-oriented preventive and preemptive maintenance based on the prediction of the level of future obsolescence. In particular, in the case of bridges, class 1 and 2 bridges are systematically managed along with many studies, but for small and medium-sized class 3 bridges there is no collection and utilization of historical data presenting performance degradation during their service life. Therefore, in this study, 3D model-based demonstration DB system was designed and developed to intuitively check the damage change rate at the damage location by registering the maintenance history by life cycle for each member's exterior damage in the 3D bridge object and to enable API-based comprehensive performance evaluation.

• Journal of Korean Society of Steel Construction
• /
• v.24 no.1
• /
• pp.119-128
• /
• 2012

In this study, experimental vibration tests are performed on a real full-scale railway steel plate girder bridge, which resides in open-space environments. Using experimental modal analysis techniques, the modal parameters of the railway steel plate girder bridge yielded by the modal testing of the impact hammer are compared and investigated with the natural frequencies and mode shapes obtained by finite element analysis. This work focuses on the application of model updating techniques to measured experimental data and output-only data from an analytical vibration study that takes into account various geometric and material properties of the bridge members. A finite element model of the railway bridge structure is used to verify the modal experimental results. It is subsequently updated using the corresponding modal identification technique. The basic database is provided to evaluate damage, which can be determined based on the changes in the element properties, resulting from the process of updating the finite element model benchmark and experimental data.

• Journal of KIBIM
• /
• v.8 no.4
• /
• pp.13-22
• /
• 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
• /
• v.10 no.2
• /
• pp.131-154
• /
• 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
• /
• v.30 no.6
• /
• pp.673-686
• /
• 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.

• Computers and Concrete
• /
• v.16 no.5
• /
• pp.723-740
• /
• 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
• /
• v.51 no.5
• /
• pp.809-821
• /
• 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.

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

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