• Journal of the Korea institute for structural maintenance and inspection
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• v.26 no.6
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• pp.33-38
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• 2022

As the intense heat continues, many cases of highway pavement blow up and bridge expansion joints damages have been inspected. Especially, Expansion joint closure of bridges is an important problem that can threat the safety of the bridge structure or reduce long-term durability. This paper proposed a structural analysis method for bridges having expansion joint closure and structural analysis was performed to verify the effects according to bridge types. Analysis bridges were divided into four types: concrete and steel bridges, shallow and piled foundations. To induce the situation of abutments and bridge decks are jammed, the following loads were additionally considered; lateral flow pressure, pavement expansion by alkali-aggregate reaction, creep settlement of backfill. The structural analysis method was verified by comparing the structural analysis results with the actually measured joint gap data. In addition, behavioral analysis due to joint closure was conducted to confirm the change in safety ratio by type of superstructure as the axial force increased.

• Structural Monitoring and Maintenance
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• v.10 no.1
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• pp.87-105
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• 2023

Seismic regulations have been updated from time to time to accommodate an increase in seismic hazards. Comparison of seismic fragility of the existing bridges in Indonesia from different historical periods since the era before 1990 will be the basis for seismic assessment of the bridge stock in Indonesia, most of which are located in earthquake-prone areas, especially those built many years ago with outdated regulations. In this study, seismic fragility curves were developed using incremental non-linear time history analysis and more holistically according to the actual strength of concrete and steel material in Indonesia to determine the uncertainty factor of structural capacity, βc. From the research that has been carried out, based on the current seismic load in SNI 2833:2016/Seismic Map 2017 (7% probability of exceedance in 75 years), the performance level of the bridge in the era before SNI 2833:2016 was Operational-Life Safety whereas the performance level of the bridge designed with SNI 2833:2016 was Elastic - Operational. The potential for more severe damage occurs in greater earthquake intensity. Collapse condition occurs at As = F_PGA x PGA value of bridge Era I = 0.93 g; Era II = 1.03 g; Era III = 1.22 g; Era IV = 1.54 g. Furthermore, the fragility analysis was also developed with geometric variations in the same bridge class to see the effect of these variations on the fragility, which is the basis for making bridge risk maps in Indonesia.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.1A
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• pp.237-246
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• 2006

In order to evaluate the seismic performance of damaged reinforced concrete members, particularly bridge piers, an inelastic time-dependent element is proposed. The proposed element enables increased characteristics due to structural intervention(i.e., repair or retrofitting) to be accurately reflected to the degraded strength and stiffness of the members. The inelastic time-dependent element having both birth and death time can freely be activated within the user-defined time intervals during static and dynamic time-history analysis. Comparative studies are carried out for reinforced concrete bridge piers that are repaired and retrofitted. Analytical predictions using the developed element show reasonable correlation with experimental results. Also conducted is a nonlinear time-history analysis of a reinforced concrete bridge under multiple earthquakes. The comparative analytical results prove the validation of current development. In all, it is concluded that the present element is capable of providing salient features for the healthy evaluation of seismic performance and hence seismic stability assessment of RC bridge piers being repaired and retrofitted.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.4A
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• pp.395-405
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• 2009

The purpose of this study was to investigate the performance of precast segmental PSC bridge columns with precast concrete footings. The proposed system can reduce work at a construction site and makes construction periods shorter. The precast concrete footings is intended to support precast segmental PSC bridge columns and provides an alternative to current cast-inplace systems, particularly for areas where reduced construction time is desired. Shortened construction time, in turn, leads to important safety and economic advantages when traffic disruption or rerouting is necessary. A model of precast segmental PSC bridge columns was tested under a constant axial load and a cyclically reversed horizontal load. In the companion paper, the experimental and analytical study for the performance assessment of precast segmental PSC bridge columns with precast concrete footings is performed.

• Journal of Environmental Impact Assessment
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• v.20 no.6
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• pp.857-866
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• 2011

This research categorized EIA target highways into following three types in order to minimize non-point source pollution from highway runoff. 1. Big drainage basin. 2. Small drainage basin. 3. Bridge section. The Natural, Filter and Swirl-Type devices were evaluated in terms of removal efficiency of TSS, BOD, COD, T-N, T-P, compatibility of site selection, economic feasibility, and maintenance convenience through which the final BMP was selected. According to the removal efficiency result, the area of Big and Small Drainage basin and bridge section had higher removal efficiency with natural facility than that of the Filter or Swirl-Type device. To make appropriate selection of highways'BMP for non-point source pollution, this study will aim to contribute to building more environmentally friendly highways by proposing the selection process that is made of 5 stages. 1. Selecting the target drainage basin. 2. Selecting the land for the mitigation facility. 3. Analysing the ease of maintenance. 4. Technically evaluating each installation. 5. Evaluating the effective implementation methods.

• Earthquakes and Structures
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• v.20 no.4
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• pp.389-403
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• 2021

Skewed bridges, being irregular structures with complicated dynamic behavior, are more susceptible to earthquake damage. Reliable seismic-resistant design of skewed bridges can be achieved by accurate determination of nonlinear seismic demands. However, the effect of geometric characteristics on the response modification factor (R-factor) is not accounted for in bridge design practices. This study attempts to investigate the effects of changes in the number of spans, skew angle and bearing stiffness on R-factor values and to assess the seismic fragility of skewed bridges. Results indicated that changes in the skew angle had no significant effect on R-factor values which were in consonance with code-prescribed R values. Also, unlike the increase in the number of spans that resulted in a decrease in the R-factor, the increase in bearing stiffness led to higher R-factor values. Findings of the fragility analysis implied that although the increase in the number of spans, as well as the increase in the skew angle, led to a higher failure probability, greater values of bearing stiffness reduced the collapse probability. For practicing design engineers, it is recommended that maximum demands on substructure elements to be calculated when the excitation angle is applied along the principal axes of skewed bridges.

• Earthquakes and Structures
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• v.25 no.6
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• pp.469-479
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• 2023

A probabilistic seismic damage analysis is an essential procedure to identify seismically vulnerable structures, prioritize the seismic retrofit, and ultimately minimize the overall seismic risk. To assess the seismic risk of multiple structures within a region, a large number of nonlinear time-history structural analyses must be conducted and studied. As a result, each assessment requires high computing resources. To overcome this limitation, we explore a deep learning-based metamodel to enable the prediction of the mean and the standard deviation of the seismic damage distribution of track-on steel-plate girder railway bridges in Korea considering the geometric variation. For machine learning training, nonlinear dynamic time-history analyses are performed to generate 800 high-fidelity datasets on the seismic response. Through intensive trial and error, the study is concentrated on developing an optimal machine learning architecture with the pre-identified variables of the physical configuration of the bridge. Additionally, the prediction performance of the proposed method is compared with a previous, well-defined, response surface model. Finally, the statistical testing results indicate that the overall performance of the deep-learning model is improved compared to the response surface model, as its errors are reduced by as much as 61%. In conclusion, the model proposed in this study can be effectively deployed for the seismic fragility and risk assessment of a region with a large number of structures.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1997.10a
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• pp.24-31
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• 1997

Recently, in Korea, demand for establishment of systematic risk assessment techniques for construction projects has increased, especially after the large construction failures occurred during construction such as New Haengju Bridge construction projects, subway construction projects, gas explosion accidents etc. Most of existing risk analysis modeling techniques such as Event Tree Analysis and Fault Tree Analysis may not be available for realistic risk assessment of construction projects because it is very complex and difficult to estimate occurrence frequency and failure probability precisely due to a lack of data related to the various risks inherent in construction projects like natural disasters, financial and economic risks, political risks, environmental risks as well as design and construction-related risks. Therefor the main objective of this paper is to suggest systematic probabilistic risk assessment model and demonstrate an approach for probabilistic risk assessment using advanced Event Tree Analysis introducing Fuzzy set theory concepts. It may be stated that the Fuzzy Event Tree AnaIysis may be very usefu1 for the systematic and rational risk assessment for real constructions problems because the approach is able to effectively deal with all the related construction risks in terms of the linguistic variables that incorporate systematically expert's experiences and subjective judgement.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.40 no.1
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• pp.69-76
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• 2020

Bridges which are components of road network consume large amounts of resources such as concrete and steel materials, which have large environmental impacts during construction. This causes a great environmental burden. In order to reduce the environmental impact caused by the construction of the bridge, the environmental impact should be reviewed based on reasonable data in the early design stage. The purpose of this study is to provide basic data for LCA-based environmental impact assessment in the process of selecting bridge type in the early design stage. For this purpose, design data for four types of PSC bridges (general PSC girder, IPC girder, e-Beam, DR girder) were collected and LCA was performed to analyze the basic unit value and impact factors of environmental load. The results of the analysis showed that the environmental impact of IPC girder was the smallest, and the environmental impact of e-Beam was 133.7% higher than that of IPC girder. In addition, concrete, reinforcement, PC strand, square timber, sheath pipe, and steel plate were derived as the main factors that generate 98.5% of the overall environmental impact of PSC girder.

• Smart Structures and Systems
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• v.21 no.5
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• pp.591-600
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• 2018

The probabilistic characterization of wind field characteristics is a significant task for fatigue reliability assessment of long-span railway bridges in wind-prone regions. In consideration of the effect of wind direction, the stochastic properties of wind field should be represented by a bivariate statistical model of wind speed and direction. This paper presents the construction of the bivariate model of wind speed and direction at the site of a railway arch bridge by use of the long-term structural health monitoring (SHM) data. The wind characteristics are derived by analyzing the real-time wind monitoring data, such as the mean wind speed and direction, turbulence intensity, turbulence integral scale, and power spectral density. A sequential quadratic programming (SQP) algorithm-based finite mixture modeling method is proposed to formulate the joint distribution model of wind speed and direction. For the probability density function (PDF) of wind speed, a double-parameter Weibull distribution function is utilized, and a von Mises distribution function is applied to represent the PDF of wind direction. The SQP algorithm with multi-start points is used to estimate the parameters in the bivariate model, namely Weibull-von Mises mixture model. One-year wind monitoring data are selected to validate the effectiveness of the proposed modeling method. The optimal model is jointly evaluated by the Bayesian information criterion (BIC) and coefficient of determination, $R^2$. The obtained results indicate that the proposed SQP algorithm-based finite mixture modeling method can effectively establish the bivariate model of wind speed and direction. The established bivariate model of wind speed and direction will facilitate the wind-induced fatigue reliability assessment of long-span bridges.