• Steel and Composite Structures
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• v.33 no.3
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• pp.389-402
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• 2019

Reinforced concrete walls and buckling restrained braces are effective structural elements that are used to resist seismic loads. In this paper, the behavior of the reinforced concrete walls coupled with buckling restrained braces is investigated. In such a system, there is not any conventional reinforced concrete coupling beam. The coupling action is provided only by buckling restrained braces that dissipate energy and also cause coupling forces in the wall piers. The studied structures are 10-, 20- and 30-story ones designed according to the ASCE, ACI-318 and AISC codes. Wall nonlinear model is then prepared using the fiber elements in PERFORM-3D software. The responses of the systems subjected to the forward directivity near-fault (NF) and ordinary far-fault (FF) ground motions at maximum considered earthquake (MCE) level are studied. The seismic responses of the structures corresponding to the inter-story drift demand, curvature ductility of wall piers, and coupling ratio of the walls are compared. On average, the results show that the inter-story drift ratio for the examined systems subjected to the far-fault events at MCE level is less than allowable value of 3%. Besides, incremental dynamic analysis is used to examine the considered systems. Results of studied systems show that, the taller the structures, the higher the probability of their collapse. Also, for a certain peak ground acceleration of 1 g, the probability of collapse under NF records is more than twice this probability under FF records.

• Structural Engineering and Mechanics
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• v.83 no.6
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• pp.811-824
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• 2022

Despite its disadvantages, soft story can reduce the damage to the upper floors by concentrating drift in that specific story provided that large drifts are avoided. Gapped-Inclined Brace (GIB) with reduced P-delta effects and the control of soft story stiffness makes it possible to take advantage of the soft story in buildings and increase their capacity for energy dissipation. OpenSees software is used in this study to validate and modify the GIB model's shortcomings. Also, the analysis method for this element is changed for design. The modified element is evaluated in 3D analysis. Finally, to retrofit an existing building, this element is used. Based on the Iranian seismic code, a six-story reinforced concrete building is modelled and studied with 3D analysis. In this building, the construction shortcomings and elimination of infills on the ground floor cause the formation of a soft story. Results of nonlinear static analysis, nonlinear dynamic, and incremental dynamic analysis using both components of seismic acceleration applied to the structure at different angles and the fragility curves indicate the improvement of the retrofitted structure's performance using the modified element to reach the required performance level following the retrofit code.

• 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.

• Earthquakes and Structures
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• v.27 no.1
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• pp.31-39
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• 2024

The reliability-based seismic design of steel frames is a complex process that incorporates seismic demand with a structural capacity to attain safe buildings aligned with specified constraints. This paper introduces an efficient base shear force formulation to support the reliability-based design process of steel frames. The introduced base shear force equation combines the seismic demand statistics with the reliability objective to calculate a fictitious base shear force for linear static analysis. By concentrating on the seismic demand and promising to meet a certain level of reliability, the equation converts the reliability-based seismic design problem to a deterministic one. Two code-compliant real-size steel moment frames are developed according to different reliability objectives to demonstrate the competency of the proposed formula. The nonlinear dynamic analysis method is used to assess the seismic reliability of the constructed frames, and the numerical results validate the credibility of the suggested formulation. The base shear force calculation method regarding seismic reliability is the main finding of this study. The ease of use makes this approach a potent tool for design professionals and stakeholders to make rapid risk-informed decisions regarding steel moment frame design.

• Steel and Composite Structures
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• v.52 no.4
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• pp.461-473
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• 2024

This study focuses on the reliability of a transmission line under wind excitation and evaluates the failure probability using explicit data resources. The data-driven framework for calculating the failure probability of a transmission line subjected to wind loading is presented, and a probabilistic method for estimating the yearly extreme wind speeds in each wind direction is provided to compensate for the incompleteness of meteorological data. Meteorological data from the Xuwen National Weather Station are used to analyze the distribution characteristics of wind speed and wind direction, fitted with the generalized extreme value distribution. Then, the most vulnerable tower is identified to obtain the fragility curves in all wind directions based on uncertainty analysis. Finally, the failure probabilities are calculated based on the presented method. The simulation results reveal that the failure probability of the employed tower increases over time and that the joint probability distribution of the wind speed and wind direction must be considered to avoid overestimating the failure probability. Additionally, the mixed wind climates (synoptic wind and typhoon) have great influence on the estimation of structural failure probability and should be considered.

• Journal of the Earthquake Engineering Society of Korea
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• v.20 no.7_spc
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• pp.485-494
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• 2016

The risk-based assessment, also called time-based assessment of structure is usually performed to provide seismic risk evaluation of a target structure for its entire life-cycle, e.g. 50 years. The prediction of collapse probability is the estimator in the risk-based assessment. While the risk-based assessment is the key in the performance-based earthquake engineering, its application is very limited because this evaluation method is very expensive in terms of simulation and computational efforts. So the evaluation database for many archetype structures usually serve as representative of the specific system. However, there is no such an assessment performed for building stocks in Korea. Consequently, the performance objective of current building code, KBC is not clear at least in a quantitative way. This shortcoming gives an unresolved issue to insurance industry, socio-economic impact, seismic safety policy in national and local governments. In this study, we evaluate the comprehensive seismic performance of an low-rise residential buildings with discontinuous structural walls, so called piloti-type structure which is commonly found in low-rise domestic building stocks. The collapse probability is obtained using the risk integral of a conditioned collapse capacity function and regression of current hazard curve. Based on this approach it is expected to provide a robust tool to seismic safety policy as well as seismic risk analysis such as Probable Maximum Loss (PML) commonly used in the insurance industry.

• Earthquakes and Structures
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• v.20 no.2
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• pp.215-224
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• 2021

The carbon dioxide present in the atmosphere is one of the main reasons for the corrosion of bridges, buildings, tunnels, and other reinforced concrete (RC) structures in most industrialized countries. With the growing use of fossil fuels in the world since the Industrial Revolution, the amount of carbon dioxide in urban and industrial areas of the world has grown significantly, which increases the chance of corrosion caused by carbonation. The process of corrosion leads to a change in mechanical properties of rebars and concrete, and consequently, detrimentally impacting load-bearing capacity and seismic behavior of RC structures. Neglecting this phenomenon can trigger misleading results in the form of underestimating the seismic performance metrics. Therefore, studying the carbonation corrosion influence on the seismic behavior of RC structures in urban and industrial areas is of great significance. In this study, a 2D modern RC moment frame is developed to study and assess the effect of carbonation corrosion, in 5-year intervals, for a 50 years lifetime under two different environmental conditions. This is achieved using the nonlinear static and incremental dynamic analysis (IDA) to evaluate the reinforcement corrosion effects. The reduction in the seismic capacity and performance of the reinforced concrete frame, as well as the collapse probability over the lifetime for different corrosion scenarios, is examined through the capacity curves obtained from nonlinear static analysis and the fragility curves obtained from IDA.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.34 no.2
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• pp.77-84
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• 2021

A sampling-based approach was devised as a nuclear seismic probabilistic risk assessment (SPRA) method to account for the partially correlated relationships between components. However, since this method is based on sampling, there is a limitation that a large number of samples must be extracted to estimate the results accurately. Thus, in this study, we suggest an effective approach to improve the existing sampling method. The main features of this approach are as follows. In place of the existing Monte Carlo sampling (MCS) approach, the Latin hypercube sampling (LHS) method that enables effective sampling in multiple dimensions is introduced to the SPRA method. In addition, the degree of segmentation of the seismic intensity is determined with respect to the final seismic risk result. By applying the suggested approach to an actual nuclear power plant as an example, the accuracy of the results were observed to be almost similar to those of the existing method, but the efficiency was increased by a factor of two in terms of the total number of samples extracted. In addition, it was confirmed that the LHS-based method improves the accuracy of the solution in a small sampling region.

• Journal of the Korean GEO-environmental Society
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• v.23 no.2
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• pp.13-23
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• 2022

The ground-structure interaction of the bridge foundation has been pointed out as a major factor influencing the behavior of the bridge during earthquakes. In this study, the effect of characteristics of ground and bridge foundation on the earthquake vulnerability is investigated. From the pseudo-static analysis, it is confirmed that non-linearity becomes lesser and horizontal load becomes greater when surcharge is considered. It is also found that as the ground worsens and the size of foundation decreases, horizontal load reduces. To derive reasonable structural model for bridge foundation, fragility curve is obtained considering four conditions (fixed condition, equivalent linear condition, non-linear without surchage condition, non-linear with surcharge condition) and compared. Seismic analysis is performed on single pier with Opensees. From the earthquake vulnerability analysis, it is found that shallow foundation can be assumed as fixed condition. In conservative approach, stiffness of spring can be obtained based on Korean highway bridge design code for pile foundation which can consider the ground condition.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.32 no.2
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• pp.93-101
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• 2019

The objective of this study is to develop a model which can predict the seismic performance of the slope relatively accurately and efficiently by using artificial neural network(ANN) technique. The quantification of such the seismic performance of the slope is not easy task due to the randomness and the uncertainty of the earthquake input and slope model. Under these circumstances, probabilistic seismic fragility analyses of slope have been carried out by several researchers, and a closed-form equation for slope seismic performance was proposed through a multiple linear regression analysis. However, a traditional statistical linear regression analysis has shown a limit that cannot accurately represent the nonlinearistic relationship between the slope of various conditions and seismic performance. In order to overcome these problems, in this study, we attempted to apply the ANN to generate prediction models of the seismic performance of the slope. The validity of the derived model was verified by comparing this with the conventional multi-linear and multi-nonlinear regression models. As a result, the models obtained through the ANN basically showed excellent performance in predicting the seismic performance of the slope, compared to the models obtained by the statistical regression analyses of the previous study.