KSCE Journal of Civil and Environmental Engineering Research
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v.28
no.1C
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pp.31-40
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2008
This study presents the assessment of pseudostatic approach for obtaining the internal response of Single Column/Shaft subjected to earthquake loading. In numerical procedure, various lateral load transfer characteristics (p-y curve and Bi-linear curve) were used to model the nonlinear behavior of soil reactions including soil-pile interaction. The analysis using nonlinear soil model could estimate the seismic performance of soil-pile system, despite its relative simplicity. It was found that lateral behavior of single column/shaft obtained from the response displacement method was larger than those by seismic intensity method. To investigate the effects of soil-pile rigidity and pile head condition on the internal pile response, parametric studies were carried out for various soil models. The results from numerical analysis showed that lateral deflection was decreased with fixed condition of pile head and decreasing the soil-pile rigidity. The seismic analysis using Bi-linear model of JRA could reasonably predict the lateral behavior of Single Column/Shaft.
International conference on construction engineering and project management
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2015.10a
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pp.339-343
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2015
To rapidly recover ceased functionality of a facility after a catastrophic seismic event, critical decisions on facility repair works are made within a limited period of time. However, prolonged damage assessment of facilities, due to massive damage in the surrounding region and the complicated damage judgment procedures, may impede restoration planning. To assist reliable structural damage estimation without a deep knowledge and rapid interactive analysis among facility damage and restoration operations during the approximate restoration project planning phase, we developed a prototype of distributed facility restoration simulations through the use of high-level architecture (HLA) (IEEE 1516). The simulation prototype, in which three different simulations (including a seismic data retrieval technique, a structural response simulator, and a restoration simulation module) interact with each other, enables immediate damage estimation by promptly detecting earthquake intensity and the restoration operation analysis according to estimated damage. By conducting case simulations and experiments, research outcomes provide key insights into post-disaster restoration planning, including the extent to which facility damage varies according to disaster severity, facility location, and structures. Additional insights arise regarding the extent to which different facility damage patterns impact a project's performance, especially when facility damage is hard to estimate by observation. In particular, an understanding of required type and amount of repair activities (e.g., demolition works, structural reinforcement, frame installation, or finishing works) is expected to support project managers in approximate work scheduling or resource procurement plans.
Satyam Tiwari;Sarat K. Das;Madhumita Mohanty;Prakhar
Geomechanics and Engineering
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v.37
no.5
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pp.475-498
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2024
The prediction of the susceptibility of soil to liquefaction using a limited set of parameters, particularly when dealing with highly unbalanced databases is a challenging problem. The current study focuses on different ensemble learning classification algorithms using highly unbalanced databases of results from in-situ tests; standard penetration test (SPT), shear wave velocity (Vs) test, and cone penetration test (CPT). The input parameters for these datasets consist of earthquake intensity parameters, strong ground motion parameters, and in-situ soil testing parameters. liquefaction index serving as the binary output parameter. After a rigorous comparison with existing literature, extreme gradient boosting (XGBoost), bagging, and random forest (RF) emerge as the most efficient models for liquefaction instance classification across different datasets. Notably, for SPT and Vs-based models, XGBoost exhibits superior performance, followed by Light gradient boosting machine (LightGBM) and Bagging, while for CPT-based models, Bagging ranks highest, followed by Gradient boosting and random forest, with CPT-based models demonstrating lower Gmean(error), rendering them preferable for soil liquefaction susceptibility prediction. Key parameters influencing model performance include internal friction angle of soil (ϕ) and percentage of fines less than 75 µ (F75) for SPT and Vs data and normalized average cone tip resistance (qc) and peak horizontal ground acceleration (amax) for CPT data. It was also observed that the addition of Vs measurement to SPT data increased the efficiency of the prediction in comparison to only SPT data. Furthermore, to enhance usability, a graphical user interface (GUI) for seamless classification operations based on provided input parameters was proposed.
The high-speed railway system is mainly composed of tunnel, bridge, and viaduct to meet the straightness needed for keeping the high speed up to 400 km/s. Seismic fragility for the high-speed railway infrastructure can be assessed as two ways: one way is studying each element of infrastructure analytically or numerically, but it requires lots of research efforts due to wide range of railway system. On the other hand, empirical method can be used to access the fragility of an entire system efficiently, which requires case history data. In this study, we collect the 2004 MW 6.6 Niigata earthquake case history data to develop empirical seismic fragility function for a railway system. Five types of intensity measures (IMs) and damage levels are assigned to all segments of target system for which the unit length is 200 m. From statistical analysis, probability of exceedance for a certain damage level (DL) is calculated as a function of IM. For those probability data points, log-normal CDF is fitted using MLE method, which forms fragility function for each damage level of exceedance. Evaluating fragility functions calculated, we observe that T=3.0 spectral acceleration (SAT3.0) is superior to other IMs, which has lower standard deviation of log-normal CDF and low error of the fit. This indicates that long-period ground motion has more impacts on railway infrastructure system such as tunnel and bridge. It is observed that when SAT3.0 = 0.1 g, P(DL>1) = 2%, and SAT3.0 = 0.2 g, P(DL>1) = 23.9%.
As the frequency and intensity of catastrophic disasters increase, there is widespread public sentiment that government capacity for disaster response and recovery is fundamentally limited, and that the involvement of civil society and the private sector is ever more vital. That is, in order to strengthen national disaster response capacity, governments need to build disaster systems that are more participatory and function through the channels of civil society, rather than continuing themselves to bear sole responsibility for these "wicked problems." With the advancement of smart mobile technology and social media, government and society as a whole have been called upon to apply these new information and communication technologies to address the current shortcomings of government-led disaster management. As illustrated in such catastrophic disasters as the 2011 Tohoku earthquake and tsunami in Japan, the 2010 Haitian earthquake, and Hurricane Katrina in the United States in 2005, the realization of participatory potential of smart technologies for better disaster response has enabled citizen participation via new smart technologies during disasters and resulted in positive impact on the management of such disasters. In this context, this study focuses on the South Korean context, and aims to analyze Korean government officials' readiness for public participation using smart technologies. On this basis, it aims to offer policy suggestions aimed at promoting smart technology-enabled citizen participation. For this purpose, it proposes a particular model, termed SMART (System, Motivation, Ability, Response, and Technology).
Journal of the Computational Structural Engineering Institute of Korea
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v.27
no.6
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pp.517-524
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2014
The ultimate goal of seismic design is to reduce the probable losses or damages occurred during an expected earthquake event. To achieve this goal, this study represents a procedure that can estimate annual loss probability of a structure damaged by strong ground motion. First of all, probabilistic seismic performance assessment should be performed using seismic fragility analyses that are presented by a cumulative distribution function of the probability in each exceedance structural damage state. A seismic hazard curve is then derived from an annual frequency of exccedance per each ground motion intensity. An annual loss probability function is combined with seismic fragility analysis results and seismic hazard curves. In this paper, annual loss probabilities are estimated by the structural fragility curve of steel moment-resisting frames(SMRFs) in San Francisco Bay, USA, and are compared with loss estimation results obtained from the HAZUS methodology. It is investigated from the comparison that seismic losses of the SMRFs calculated from the HAZUS method are conservatively estimated. The procedure presented in this study could be effectively used for future studies related with structural seismic performance assessment and annual loss probability estimation.
Journal of the Korea Academia-Industrial cooperation Society
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v.20
no.7
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pp.203-210
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2019
A recent earthquake on the Korean Peninsula caused much damage to masonry buildings, and research on performance evaluation has been underway. A masonry building is generally constructed using wet construction and is affected by temperature, which reduces the efficiency of the construction. In this study, we propose a dry construction technique for assembling concrete blocks without using mortar and evaluated its performance through experimental and analytical research. To evaluate the performance, experiments were carried out for the prismatic compressive strength, direct terminal strength, and diagonal tensile strength of the dry construction wall. The adequacy of the cross section shape was also reviewed through FEM analysis. The results show that the compressive strength and diagonal tensile strength could exert a certain intensity or higher. Furthermore, the H-type module of a key block acted as a shear key for the entire concrete block, which resulted in excellent shear strength performance. In addition, the shape and thickness of the main block have a major effect on the strength performance of each block. Therefore, an optimal shape and the proposed dry construction method could be applied to replace the wet method by studying the construction or seismic performance of the proposed method.
In the recent period, there have been numerous earthquakes both domestically and internationally, and buildings in South Korea are particularly vulnerable to seismic design and earthquake damage. Therefore, the objective of this study is to discover an effective method for assessing the seismic vulnerability of buildings and conducting a density analysis of high-risk structures. The aim is to model this approach and validate it using data from pilot area(Seoul). To achieve this, two modeling techniques were employed, of which the predictive accuracy of the statistical analysis technique was 87%. Among the machine learning techniques, Random Forest Model exhibited the highest predictive accuracy, and the accuracy of the model on the Test Set was determined to be 97.1%. As a result of the analysis, the district rating revealed that Gwangjin-gu and Songpa-gu were relatively at higher risk, and the density analysis of at-risk buildings predicted that Seocho-gu, Gwanak-gu, and Gangseo-gu were relatively at higher risk. Finally, the result of the statistical analysis technique was predicted as more dangerous than those of the machine learning technique. However, considering that about 18.9% of the buildings in Seoul are designed to withstand the Seismic intensity of 6.5 (MMI), which is the standard for seismic-resistant design in South Korea, the result of the machine learning technique was predicted to be more accurate. The current research is limited in that it only considers buildings without taking into account factors such as population density, police stations, and fire stations. Considering these limitations in future studies would lead to more comprehensive and valuable research.
The present study investigates the non-linear soil-pile interaction using three-dimensional (3D) non-linear finite element models. The numerical models were validated by using the results of extensive pile load and shaking table tests. The pile performance in liquefiable and non-liquefiable soil has been studied by analyzing the liquefaction ratio, pile lateral displacement (LD), pile bending moment (BM), and frictional resistance (FR) results. The pile models have been developed for the different ground conditions. The study reveals that the results obtained during the pile load test and shaking cycles have good agreement with the predicted pile and soil response. The soil density, peak ground acceleration (PGA), slenderness ratio (L/D), and soil condition (i.e., dry and saturated) are considered during modeling. Four ground motions are used for the non-linear time history analyses. Consequently, design charts are proposed depended on the analysis results to be used for design practice. Eleven models have been used to validate the capability of these charts to capture the soil-pile response under different seismic intensities. The results of the present study demonstrate that L/D ratio slightly affects the lateral displacement when compared with other parameters. Also, it has been observed that the increasing in PGA and decreasing L/D decreases the excess pore water pressure ratio; i.e., increasing PGA from 0.1 g to 0.82 g of loose sand model, decrease the liquefaction ratio by about 50%, and increasing L/D from 15 to 75 of the similar models (under Kobe earthquake), increase this ratio by about 30%. This study reveals that the lateral displacement increases nonlinearly under both dry and saturated conditions as the PGA increases. Similarly, it is observed that the BM increases under both dry and saturated states as the L/D ratio increases. Regarding the acceleration histories, the pile BM was reduced by reducing the acceleration intensity. Hence, the pile BM decreased to about 31% when the applied ground motion switched from Kobe (PGA=0.82 g) to Ali Algharbi (PGA=0.10 g). This study reveals that the soil conditions affect the relationship pattern between the FR and the PGA. Also, this research could be helpful in understanding the threat of earthquakes in different ground characteristics.
Purpose: The dynamic behavior of a bridge structure under seismic loading depends on many uncertainties, such as the nature of the seismic waves and the material and geometric properties. However, not all uncertainties have a significant impact on the dynamic behavior of a bridge structure. Since probabilistic seismic performance evaluation considering even low-impact uncertainties is computationally expensive, the uncertainties should be identified by considering their impact on the dynamic behavior of the bridge. Therefore, in this study, a global sensitivity analysis was performed to identify the main parameters affecting the dynamic behavior of bridges with I-curved girders. Method: Considering the uncertainty of the earthquake and the material and geometric uncertainty of the curved bridge, a finite element analysis was performed, and a surrogate model was developed based on the analysis results. The surrogate model was evaluated using performance metrics such as coefficient of determination, and finally, a global sensitivity analysis based on the surrogate model was performed. Result: The uncertainty factors that have the greatest influence on the stress response of the I-curved girder under seismic loading are the peak ground acceleration (PGA), the height of the bridge (h), and the yield stress of the steel (fy). The main effect sensitivity indices of PGA, h, and fy were found to be 0.7096, 0.0839, and 0.0352, respectively, and the total sensitivity indices were found to be 0.9459, 0.1297, and 0.0678, respectively. Conclusion: The stress response of the I-shaped curved girder is dominated by the uncertainty of the input motions and is strongly influenced by the interaction effect between each uncertainty factor. Therefore, additional sensitivity analysis of the uncertainty of the input motions, such as the number of input motions and the intensity measure(IM), and a global sensitivity analysis considering the structural uncertainty, such as the number and curvature of the curved girders, are required.
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