• Journal of the Earthquake Engineering Society of Korea
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• v.22 no.5
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• pp.271-280
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• 2018

This paper presents a framework for developing aftershock fragility curves for reinforced concrete bridges initially damaged by mainshocks. The presented aftershock fragility is a damage-dependent fragility function, which is conditioned on an initial damage state resulting from mainshocks. The presented framework can capture the cumulative damage of as-built bridges due to mainshock-aftershock sequences as well as the reduced vulnerability of bridges repaired with CFRP pier jackets. To achieve this goal, the numerical model of column jackets is firstly presented and then validated using existing experimental data available in literature. A four-span concrete box-girder bridge is selected as a case study to examine the application of the presented framework. The aftershock fragility curves are derived using response data from back-to-back nonlinear dynamic analyses under mainshock-aftershock sequences. The aftershock fragility curves for as-built bridge columns are firstly compared with different levels of initial damage state, and then the post-repair effect of FRP pier jacket is examined through the comparison of aftershock fragility curves for as-built and repaired piers.

• Structural Engineering and Mechanics
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• v.29 no.6
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• pp.689-707
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• 2008

This study presents a method to evaluate the seismic risk of an extradosed bridge with seismic isolators of lead rubber bearings (LRBs), and also to show the effectiveness of the LRB isolators on the extradosed bridge, which is one of the relatively flexible and lightly damped structures in terms of seismic risk. Initially, the seismic vulnerability of a structure is evaluated, and then the seismic hazard of a specific site is rated using an earthquake data set and seismic hazard maps in Korea. Then, the seismic risk of the structure is assessed. The nonlinear seismic analyses are carried out to consider plastic deformation of bridge columns and the nonlinear characteristics of soil foundation. To describe the nonlinear behaviour of a column, the ductility demand is adopted, and the moment-curvature relation of a column is assumed to be bilinear hysteretic. The fragility curves are represented as a log-normal distribution function for column damage, movement of superstructure, and cable yielding. And the seismic hazard at a specific site is estimated using the available seismic hazard maps. The results show that in seismically-isolated extradosed bridges under earthquakes, the effectiveness of the isolators is much more noticeable in the columns than the cables and girders.

• Earthquakes and Structures
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• v.14 no.3
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• pp.203-214
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• 2018

Predictive demand and collapse fragility functions are two essential components of the probabilistic seismic demand analysis that are commonly developed based on statistics with enormous, costly and time consuming data gathering. Although this approach might be justified for research purposes, it is not appealing for practical applications because of its computational cost. Thus, in this paper, Bayesian regression-based demand and collapse models are proposed to eliminate the need of time-consuming analyses. The demand model developed in the form of linear equation predicts overall maximum inter-story drift of the lowto mid-rise regular steel moment resisting frames (SMRFs), while the collapse model mathematically expressed by lognormal cumulative distribution function provides collapse occurrence probability for a given spectral acceleration at the fundamental period of the structure. Next, as an application, the proposed demand and collapse functions are implemented in a seismic fragility analysis to develop fragility and consequently seismic demand curves of three example buildings. The accuracy provided by utilization of the proposed models, with considering computation reduction, are compared with those directly obtained from Incremental Dynamic analysis, which is a computer-intensive procedure.

• Earthquakes and Structures
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• v.19 no.4
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• pp.261-272
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• 2020

Recent severe earthquakes in and around the vital public places worldwide indicate the severe vulnerability of ground excitation to be assailed. Reducing the effect of seismic lateral load in structural design is an important conception. Essentially, seismic isolation is required to shield the superstructure in such a way that the building superstructure would not move when the ground is shaking. This study explores the effectiveness, design, and practical feasibility of base isolation systems to reduce seismic demands on buildings of varying elevations. Thus, static and dynamic analyses were conducted based on site-specific bi-directional earthquakes for base-isolated as well as fixed-based buildings. Remarkably, it was discovered that isolators used in low-rise to high-rise structures tend to significantly decrease the structural responses of seismic prone buildings. The higher allowable horizontal displacement induces structural flexibility and ensure good structural health of the building stories. Reinforcement from vertical and horizontal members can be reduced in significant amounts for BI buildings. Thus, although incorporating base isolators increases the initial outlay, it considerably diminishes the total structural cost.

• Journal of the Earthquake Engineering Society of Korea
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• v.8 no.1
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• pp.77-86
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• 2004

This paper introduces a shape memory alloy-restrainer-damper(SMA-RD) to protect multiple span continuous steel bridges from seismic loads. The type of bridges has only one fixed bearing condition on a pier and expansion bearings are located on the other piers and abutments. Due to this state and a big mass of the deck, these bridges are usually very vulnerable to column's damage on which fixed bearings are located and large deformation of abutments in passive action. Two types of SMA-RDs are developed, and their effect is inspected for protecting the bridges through seismic analyses. Conventional steel restrainer cables are also used to reduce the seismic vulnerability of the bridge and the results are compared to those of the SMA-RDs.

• Earthquakes and Structures
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• v.6 no.5
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• pp.473-494
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• 2014

Progressive collapse, which is referred to as the collapse of the entire building under local damages, is a common failure mode happened by earthquakes. The collapse process highly depends on the whole structural system. Since, asymmetry of the building plan leads to the local damage concentration; it may intensify the progressive collapse mechanism of asymmetric buildings. In this research the progressive collapse of regular and irregular 6-story RC ordinary moment resisting frame buildings are studied in the presence of the earthquake loads. Collapse process and collapse propagation are investigated using nonlinear time history analyses (NLTHA) in buildings with 5%, 15% and 25% mass asymmetry with respect to the number of collapsed hinges and story drifts criteria. Results show that increasing the value of mass eccentricity makes the asymmetric buildings become unstable earlier and in the early stages with lower number of the collapsed hinges. So, with increasing the mass eccentricity in building, instability and collapse of the entire building occurs earlier, with lower potential of the progressive collapse. It is also demonstrated that with increasing the mass asymmetry the decreasing trend of the number of collapsed beam and column hinges is approximately similar to the decreasing trend in the average story drifts of the mass centers and stiff edges. So, as an alternative to a much difficult-to-calculate local response parameter of the number of collapsed hinges, the story drift, as a global response parameter, measures the potential of progressive collapse more easily.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.12
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• pp.1679-1685
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• 2015

This paper examines the effect of the magnetization pattern on the partial demagnetization of a permanent magnet (PM) machine that uses a ferrite magnet. Although the use of halbach-magnetized PM (HMPM) arrays in PM machines has been dramatically increasing because of their attractive features, the demagnetization characteristics of HMPM arrays have not yet been examined. In this study, two analyses of the demagnetization characteristics of HMPM arrays and parallel magnetized PMs (PMPMs) are performed, with the demagnetization characteristics being analyzed using a finite element method. According to our results, partial demagnetization occurred dramatically in the HMPM arrays. Thus, it is important to consider the vulnerability of HMPM arrays when designing PM machines.

• Coupled systems mechanics
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• v.7 no.6
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• pp.731-753
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• 2018

The recent seismic events have led to concerns on safety and vulnerability of Reinforced Concrete Moment Resisting Frame "RC-MRF" buildings. The seismic design demands are greatly dependent on the computational tools, the inherent assumptions and approximations introduced in the modeling process. Thus, it is essential to assess the relative importance of implementing different modeling approaches and investigate the computed response sensitivity to the corresponding modeling assumptions. Many parameters and assumptions are to be justified for generation effective and accurate structural models of RC-MRF buildings to simulate the lateral response and evaluate seismic design demands. So, the present study aims to develop reliable finite element model through many refinements in modeling the various structural components. The effect of finite element modeling assumptions, analysis methods and code provisions on seismic response demands for the structural design of RC-MRF buildings are investigated. where, a series of three-dimensional finite element models were created to study various approaches to quantitatively improve the accuracy of FE models of symmetric buildings located in active seismic zones. It is shown from results of the comparative analyses that the use of a calibrated frame model which was made up of line elements featuring rigid offsets manages to provide estimates that match best with estimates obtained from a much more rigorous modeling approach involving the use of shell elements.

• International conference on construction engineering and project management
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• 2009.05a
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• pp.83-90
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• 2009

Natural disasters, such as the recent floods in the Midwest, Hurricane Ike in the Gulf coast region (U.S.), and the earthquake in Sichuan (China), cause severe damage to the infrastructure as well as the associated industries and communities that rely on the infrastructure. The estimated damages due to Hurricane Ike in 2008 were a staggering $27 billion, the third worst in U.S. history. In addition, the worst earthquake in three decades in Sichuan resulted in about 90,000 people dead or missing and $20 billion of the estimated loss. A common observation in the analyses of these natural disaster events is the inadequacy of critical infrastructure to withstand the forces of natural calamities and the lack of mitigation strategies when they occur on the part of emergency-related organizations, industries, and communities. If the emergency-related agencies could identify and fortify the vulnerable critical infrastructure in the preparedness stage, the damage and impacts can be significantly reduced. Therefore, it is important to develop a decision support system (DSS) for identifying region-specific mitigation strategies based on the inter-relationships between the infrastructure and associated industries and communities in the affected region. To establish effective mitigation strategies, relevant data were collected from the affected areas with respect to the technical, social, and economic impact levels. The data analysis facilitated identifying the major factors, such as vulnerability, criticality, and severity, for developing a DSS. Customized mitigation strategies that will help agencies prepare, respond, and recover according to the disaster response were suggested.

• International Journal of Computer Science & Network Security
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• v.23 no.7
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• pp.202-209
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• 2023

Android malware is now on the rise, because of the rising interest in the Android operating system. Machine learning models may be used to classify unknown Android malware utilizing characteristics gathered from the dynamic and static analysis of an Android applications. Anti-virus software simply searches for the signs of the virus instance in a specific programme to detect it while scanning. Anti-virus software that competes with it keeps these in large databases and examines each file for all existing virus and malware signatures. The proposed model aims to provide a machine learning method that depend on the malware detection method for Android inability to detect malware apps and improve phone users' security and privacy. This system tracks numerous permission-based characteristics and events collected from Android apps and analyses them using a classifier model to determine whether the program is good ware or malware. This method used the machine learning techniques KNN-SVM, DBN, and GRU in which help to find the accuracy which gives the different values like KNN gives 87.20 percents accuracy, SVM gives 91.40 accuracy, Naive Bayes gives 85.10 and DBN-GRU Gives 97.90. Furthermore, in this paper, we simply employ standard machine learning techniques; but, in future work, we will attempt to improve those machine learning algorithms in order to develop a better detection algorithm.