• Smart Structures and Systems
• /
• v.30 no.6
• /
• pp.571-582
• /
• 2022

Optimal life-cycle management is a challenging issue for deteriorating regional bridges. Due to the complexity of regional bridge structural conditions and a large number of inspection and maintenance actions, decision-makers generally choose traditional passive management strategies. They are less efficiency and cost-effectiveness. This paper suggests a deep reinforcement learning framework employing double-deep Q-networks (DDQNs) to improve the life-cycle management of deteriorating regional bridges to tackle these problems. It could produce optimal maintenance plans considering restrictions to maximize maintenance cost-effectiveness to the greatest extent possible. DDQNs method could handle the problem of the overestimation of Q-values in the Nature DQNs. This study also identifies regional bridge deterioration characteristics and the consequence of scheduled maintenance from years of inspection data. To validate the proposed method, a case study containing hundreds of bridges is used to develop optimal life-cycle management strategies. The optimization solutions recommend fewer replacement actions and prefer preventative repair actions when bridges are damaged or are expected to be damaged. By employing the optimal life-cycle regional maintenance strategies, the conditions of bridges can be controlled to a good level. Compared to the nature DQNs, DDQNs offer an optimized scheme containing fewer low-condition bridges and a more costeffective life-cycle management plan.

• Smart Structures and Systems
• /
• v.29 no.1
• /
• pp.105-116
• /
• 2022

Stay cables play an essential role in cable-stayed bridges. Severe vibrations and/or harsh environment may result in cable failures. Therefore, an efficient structural health monitoring (SHM) solution for cable damage detection is necessary. This study proposes a data-driven method for immediately detecting cable damage from measured cable forces by recognizing pattern transition from the intact condition when damage occurs. In the proposed method, pattern recognition for cable damage detection is realized by time series classification (TSC) using a deep learning (DL) model, namely, the long short term memory fully convolutional network (LSTM-FCN). First, a TSC classifier is trained and validated using the cable forces (or cable force ratios) collected from intact stay cables, setting the segmented data series as input and the cable (or cable pair) ID as class labels. Subsequently, the classifier is tested using the data collected under possible damaged conditions. Finally, the cable or cable pair corresponding to the least classification accuracy is recommended as the most probable damaged cable or cable pair. A case study using measured cable forces from an in-service cable-stayed bridge shows that the cable with damage can be correctly identified using the proposed DL-TSC method. Compared with existing cable damage detection methods in the literature, the DL-TSC method requires minor data preprocessing and feature engineering and thus enables fast and convenient early detection in real applications.

• Structural Monitoring and Maintenance
• /
• v.11 no.1
• /
• pp.57-70
• /
• 2024

Masonry arch bridges as a vital infrastructure were not designed for seismic loads. Given that masonry arch bridges are made up of various components, their contribution under the seismic actions can be very undetermined and each of these structural components can play a different role in energy dissipation. Iran is known as a high-risk area in terms of seismic excitations and according to the seismic hazard zoning classification of Iran, most of these railway infrastructures are placed in the high and very high seismicity zones or constructed near the major faults. Besides, these ageing structures are deteriorated and thus in recent years, some of these bridges using various retrofitting approaches, including sprayed concrete technique are strengthened. Therefore, investigating the behavior of these restored structures with new characteristics is very significant. The aim of this study is to investigate the cyclic in-plane performance of masonry arch bridges retrofitted by sprayed concrete technique through the finite element simulation. So, by considering the fill-arch interaction, the nonlinear behavior of a bridge has been investigated. Finally, by extracting the hysteresis and enveloping curves of the retrofitted and non-retrofitted bridge, the effect of strengthening on energy absorption and degradation of material has been investigated.

• Journal of Korean Society of Steel Construction
• /
• v.22 no.1
• /
• pp.55-65
• /
• 2010

To effectively secure and execute the national budget, it is very important to estimate the reasonable construction cost of each process in the construction of public facilities and works. The construction cost is generally estimated at the time when the design of the targeted structures has been completed. Without detailed sectional drawings and with only simple information on bridge structures in the planning stage or in the early design stage. it would be very difficult to predict the approximate construction cost. In this study, a more efficient and appropriate approximate construction cost estimation model in the planning stage and in the early design stage is presented and verified as reliable by analyzing the construction cost data of 61 existing steel box girder bridges from previous studies. The results of this study show that when the construction cost that was predicted using the construction cost estimation model in the design stage was compared with the cost from the conventional standards, the suggested model in this study produced results with a very high confidence level.

• Smart Structures and Systems
• /
• v.21 no.1
• /
• pp.53-64
• /
• 2018

Nondestructive testing methods are required to assess the condition of civil structures and formulate their maintenance programs. Axial force identification is required for several structural members of truss bridges, pipe racks, and space roof trusses. An accurate evaluation of in situ axial forces supports the safety assessment of the entire truss. A considerable redistribution of internal forces may indicate structural damage. In this paper, a novel compressive force identification method for prismatic members implemented using static deflections is applied to steel beams. The procedure uses the Euler-Bernoulli beam model and estimates the compressive load by using the measured displacement along the beam's length. Knowledge of flexural rigidity of the member under investigation is required. In this study, the deflected shape of a compressed steel beam is subjected to an additional vertical load that was short-term measured in several laboratory tests by using fiber Bragg grating-differential settlement measurement (FBG-DSM) sensors at specific cross sections along the beam's length. The accuracy of midspan deflections offered by the FBG-DSM sensors provided excellent force estimations. Compressive load detection accuracy can be improved if substantial second-order effects are induced in the tests. In conclusion, the proposed method can be successfully applied to steel beams with low slenderness under real conditions.

• Journal of the Korean Society of Safety
• /
• v.33 no.5
• /
• pp.120-126
• /
• 2018

The traffic accident types are largely classified into vehicle to vehicle accident, vehicle-to-person accident and single-vehicle. Especially, the single-vehicle accident types are severe when the vehicle crashed into road facilities such as bridge, piers, utility poles. The severity of single-vehicle accidents are ten times higher than that of all other accidents types. It is needed to consider to reduce accident severity. This study was conducted to develop crash worthy safety design facility to ensure the vehicle occupant safety. The simulation and the crash tests were conducted for assessment of the safety performance to check the criteria of CC2(Crash Cushion 2) level. THIV(Theoretical Head Impact Velocity) and PHD(Post-impact Head Deceleration) were used to assess occupant impact severity for crashes. The non-redirection collision test conditions for 900 kg and 1,300 kg-head on crash tests, 900 kg-1/4 offset crash tests, 1,300 kg-head on crash test with $15^{\circ}$angle were conducted. The simulation and experiment test result showed that THIV values were below 44 km/h criterion, PHD values were below the 20G. The development non-redirective crash cushion is expected to be used for the fixed object such as bridge piers for assuring occupant safety.

• Journal of the Earthquake Engineering Society of Korea
• /
• v.12 no.6
• /
• pp.1-12
• /
• 2008

As internal and external seismic experiment results, the seismic performance of RC bridge piers is largely dependent on the ratio of lap-spliced bars to all longitudinal reinforcing bars in plastic hinge regions, and confining effects of transverse reinforcements. Capacity and displacement ductility of non-seismically designed existing RC piers are reduced by lap splices in plastic hinge regions. The provision for the lap splice of longitudinal reinforcing bars was not specified in KBDS (Korean Bridge Design Specifications) before the implementation of 1992 seismic design code, but the ratio of lap-spliced bars to all longitudinal reinforcing bars in plastic hinge regions is restricted to 50% in the 2005 version of KBDS. This paper presents a seismic assessment of RC piers at lap-splicing ratios of 0%, 50%, and 100%. Through a comparison of experimental and analytic results of RC piers, we introduce an appropriate ultimate strain of confined concrete in plastic hinge regions with lap-splices, and propose a method for estimating displacement ductility ratios of non-seismically designed existing RC piers using fiber element analysis.

• Smart Structures and Systems
• /
• v.17 no.3
• /
• pp.471-489
• /
• 2016

Modal identification based on ambient vibration data has attracted extensive attention in the past few decades. Since the excitation for ambient vibration tests is mainly from the environmental effects such as wind and traffic loading and no artificial excitation is applied, the signal to noise (s/n) ratio of the data acquired plays an important role in mode identifiability. Under ambient vibration conditions, certain modes may not be identifiable due to a low s/n ratio. This paper presents a study on the mode identifiability of an instrumented cable-stayed bridge with the use of acceleration response data measured by a long-term structural health monitoring system. A recently developed fast Bayesian FFT method is utilized to perform output-only modal identification. In addition to identifying the most probable values (MPVs) of modal parameters, the associated posterior uncertainties can be obtained by this method. Likewise, the power spectral density of modal force can be identified, and thus it is possible to obtain the modal s/n ratio. This provides an efficient way to investigate the mode identifiability. Three groups of data are utilized in this study: the first one is 10 data sets including six collected under normal wind conditions and four collected during typhoons; the second one is three data sets with wind speeds of about 7.5 m/s; and the third one is some blind data. The first two groups of data are used to perform ambient modal identification and help to estimate a critical value of the s/n ratio above which the deficient mode is identifiable, while the third group of data is used to perform verification. A couple of fundamental modes are identified, including the ones in the vertical and transverse directions respectively and coupled in both directions. The uncertainty and s/n ratio of the deficient mode are investigated and discussed. A critical value of the modal s/n ratio is suggested to evaluate the mode identifiability of the deficient mode. The work presented in this paper could provide a base for the vibration-based condition assessment in future.

• Proceedings of the Korea Concrete Institute Conference
• /
• 2008.11a
• /
• pp.101-104
• /
• 2008

Recently, the serious damage by earthquakes is increased around the world. SOC fo city is established to minimize the loss of lives and assets by earthquakes, which an objective standard is required. Generally, bridges damage by earthquakes occurred the inelastic hinge under the column. Nonlinear element model of inelastic hinge have been used to Bilinear model, but Takeda model for material characterization of concrete is a little. In this study, railway bridge was performed seismic fragility analysis for Takeda model and Bilinear model comparatively. This analysis shows that damage probability of Takeda model is larger than Bilinear model. And analysis of Takeda model in longitudinal direction and transverse direction are different. Therefore developed analysis for concrete column of bridge is expected to apply to material characterization.

• Journal of the Korea institute for structural maintenance and inspection
• /
• v.16 no.5
• /
• pp.29-39
• /
• 2012

The main objective is to predict the future degradation and maintenance budget for a suspension bridge system. Bayesian inference is applied to find the posterior probability density function of the source parameters (damage indices and serviceability), given ten years of maintenance data. The posterior distribution of the parameters is sampled using a Markov chain Monte Carlo method. The simulated risk prediction for decreased serviceability conditions are posterior distributions based on prior distribution and likelihood of data updated from annual maintenance tasks. Compared with conventional linear prediction model, the proposed quadratic model provides highly improved convergence and closeness to measured data in terms of serviceability, risky factors, and maintenance budget for bridge components, which allows forecasting a future performance and financial management of complex infrastructures based on the proposed quadratic stochastic regression model.