• Fire Science and Engineering
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• v.31 no.1
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• pp.26-35
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• 2017

Since the Northridge earthquake (1994) and Kobe earthquake (1995), the concept of performance-based design has been actively introduced to design major structures and buildings. Recently, the seismic design code was established for fire protection facilities. Therefore, the important fire protection facilities should be designed and constructed according to the seismic design code. Accordingly, uniform hazard spectra (UHS), with annual exceedance probabilities, corresponding to the performance level, such as operational, immediate occupancy, life safety, and collapse prevention, are required for performance-based design. Using the method of probabilistic seismic hazard analysis (PSHA), the uniform hazard spectra for 5 major cities in Korea with a recurrence period of 500, 1,000, and 2,500 years corresponding to frequencies of (0.5, 1.0, 2.0, 5.0, 10.0)Hz and PGA, were analyzed. The expert panel was comprised of 10 members in seismology and tectonics. The ground motion prediction equations and several seismo tectonic models suggested by 10 expert panel members in seismology and tectonics were used as the input data for uniform hazard spectrum analysis. According to sensitivity analysis, the parameter of spectral ground motion prediction equations has a greater impact on the seismic hazard than seismotectonic models. The resulting uniform hazard spectra showed maximum values of the seismic hazard at a frequency of 10Hz and also showed the shape characteristics, which are similar to previous studies and related technical guides for nuclear facilities.

• Earthquakes and Structures
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• v.7 no.2
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• pp.141-157
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• 2014

The Conditional Mean Spectrum represents a powerful link between the seismic hazard information and the selection of strong ground motion records at a particular site. The scope of the paper is to apply for the city of Bucharest for the first time the method to obtain the Conditional Mean Spectrum (CMS) presented by Baker (2011) and to select, on the basis of the CMS, a suite of strong ground motions for performing elastic and inelastic dynamic analyses of buildings and structures with fundamental periods of vibration in the vicinity of 1.0 s. The major seismic hazard for Bucharest and for most of Southern and Eastern Romania is dominated by the Vrancea subcrustal seismic source. The ground motion prediction equation developed for subduction-type earthquakes and soil conditions by Youngs et al. (1997) is used for the computation of the Uniform Hazard Spectrum (UHS) and the CMS. The disaggregation of seismic hazard is then performed in order to determine the mean causal values of magnitude and source-to-site distance for a particular spectral ordinate (for a spectral period T = 1.0 s in this study). The spectral period of 1.0 s is considered to be representative for the new stock of residential and office reinforced concrete (RC) buildings in Bucharest. The differences between the Uniform Hazard Spectrum (UHS) and the Conditional Mean Spectrum (CMS) are discussed taking into account the scarcity of ground motions recorded in the region of Bucharest and the frequency content characteristics of the recorded data. Moreover, a record selection based on the criteria proposed by Baker and Cornell (2006) and Baker (2011) is performed using a dataset consisting of strong ground motions recorded during seven Vrancea seismic events.

• 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 (V_s) 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 V_s-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 G_mean(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 V_s data and normalized average cone tip resistance (q_c) and peak horizontal ground acceleration (a_max) for CPT data. It was also observed that the addition of V_s 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.

• Computational Structural Engineering
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• v.3 no.4
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• pp.143-148
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• 1990

The modal parameter estimations of linear multi-degree-of-freedom structural dynamic systems are carried out in time domain. For this purpose, the equation of motion is transformed into the auto regressive and moving average model with auxiliary stochastic input(ARMAX) model. The parameters of the ARMAX model are estimated by using the sequential prediction error method. Then the modal parameters of the system are obtained thereafter. Experimental results are given for a 3-story budding model subject to ground exitations.

• Earthquakes and Structures
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• v.14 no.2
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• pp.129-142
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• 2018

The current paper introduces a new approach for development of damage index to obtain the maximum damage in the reinforced concrete frames caused by as-recorded single and consecutive earthquakes. To do so, two sets of strong ground motions are selected based on maximum and approximately maximum peak ground acceleration (PGA) from "PEER" and "USGS" centers. Consecutive earthquakes in the first and second groups, not only occurred in similar directions and same stations, but also their real time gaps between successive shocks are less than 10 minutes and 10 days, respectively. In the following, a suite of six concrete moment resisting frames, including 3, 5, 7, 10, 12 and 15 stories, are designed in OpenSees software and analyzed for more than 850 times under two groups of as-recorded strong ground motion records with/without seismic sequences phenomena. The idealized multilayer artificial neural networks, with the least value of Mean Square Error (MSE) and maximum value of regression (R) between outputs and targets were then employed to generate the empirical charts and several correction equations for design utilization. To investigate the effectiveness of the proposed damage index, calibration of the new approach to existing real data (the result of Park-Ang damage index 1985), were conducted. The obtained results show good precision of the developed ANNs-based model in predicting the maximum damage of regular reinforced concrete frames.

• Earthquakes and Structures
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• v.26 no.4
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• pp.311-326
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• 2024

Transmission tower structures are particularly susceptible to damage and even collapse under strong seismic ground motions. Conventional seismic analyses of transmission towers are usually performed by considering only ground motion uncertainty while ignoring structural uncertainty; consequently, the performance evaluation and failure prediction may be inaccurate. In this context, the present study numerically investigates the seismic responses and failure mechanism of transmission towers by considering multiple sources of uncertainty. To this end, an existing transmission tower is chosen, and the corresponding three-dimensional finite element model is created in ABAQUS software. Sensitivity analysis is carried out to identify the relative importance of the uncertain parameters in the seismic responses of transmission towers. The numerical results indicate that the impacts of the structural damping ratio, elastic modulus and yield strength on the seismic responses of the transmission tower are relatively large. Subsequently, a set of 20 uncertainty models are established based on random samples of various parameter combinations generated by the Latin hypercube sampling (LHS) method. An uncertainty analysis is performed for these uncertainty models to clarify the impacts of uncertain structural factors on the seismic responses and failure mechanism (ultimate bearing capacity and failure path). The numerical results show that structural uncertainty has a significant influence on the seismic responses and failure mechanism of transmission towers; different possible failure paths exist for the uncertainty models, whereas only one exists for the deterministic model, and the ultimate bearing capacity of transmission towers is more sensitive to the variation in material parameters than that in geometrical parameters. This research is expected to provide an in-depth understanding of the influence of structural uncertainty on the seismic demand assessment of transmission towers.

• Structural Engineering and Mechanics
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• v.90 no.2
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• pp.189-208
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• 2024

Artificial intelligence is one of the efficient methods that can be developed to simulate nonlinear behavior and predict the response of building structures. In this regard, an adaptive method based on optimization algorithms is used to train the TSK model of the fuzzy inference system to estimate the seismic behavior of building structures based on analytical data. The optimization algorithm is implemented to determine the parameters of the TSK model based on the minimization of prediction error for the training data set. The adaptive training is designed on the feedback of the results of previous time steps, in which three training cases of 2, 5, and 10 previous time steps were used. The training data is collected from the results of nonlinear time history analysis under 100 ground motion records with different seismic properties. Also, 10 records were used to test the inference system. The performance of the proposed inference system is evaluated on two 3 and 20-story models of nonlinear steel moment frame. The results show that the inference system of the TSK model by combining the optimization method is an efficient computational method for predicting the response of nonlinear structures. Meanwhile, the multi-vers optimization (MVO) algorithm is more accurate in determining the optimal parameters of the TSK model. Also, the accuracy of the results increases significantly with increasing the number of previous steps.

• Journal of the Earthquake Engineering Society of Korea
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• v.27 no.5
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• pp.221-230
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• 2023

This study proposes a methodology for assessing seismic liquefaction hazard by implementing high-resolution three-dimensional (3D) ground models with high-density/high-precision site investigation data acquired in an area of interest, which would be linked to geotechnical numerical analysis tools. It is possible to estimate the vulnerability of earthquake-induced geotechnical phenomena (ground motion amplification, liquefaction, landslide, etc.) and their triggering complex disasters across an area for urban development with several stages of high-density datasets. In this study, the spatial-ground models for city development were built with a 3D high-precision grid of 5 m × 5 m × 1 m by applying geostatistic methods. Finally, after comparing each prediction error, the geotechnical model from the Gaussian sequential simulation is selected to assess earthquake-induced geotechnical hazards. In particular, with seven independent input earthquake motions, liquefaction analysis with finite element analyses and hazard mappings with LPI and LSN are performed reliably based on the spatial geotechnical models in the study area. Furthermore, various phenomena and parameters, including settlement in the city planning area, are assessed in terms of geotechnical vulnerability also based on the high-resolution spatial-ground modeling. This case study on the high-precision 3D ground model-based zonations in the area of interest verifies the usefulness in assessing spatially earthquake-induced hazards and geotechnical vulnerability and their decision-making support.

• Journal of the Earthquake Engineering Society of Korea
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• v.14 no.2
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• pp.49-56
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• 2010

In general, the seismic intensity deduced from instrumental data has been evaluated from the empirical relation between the intensity and the PGA. From the point of view that the degree of earthquake damage is more closely associated with the seismic intensity than with the observed PGA, JMA developed the instrumental seismic intensity (JMA instrumental intensity) meter that estimate the real-time seismic intensity from the observed strong motion data to obtain a more correct estimate of earthquake damage. The purpose of the present study is to propose a practical application of the JMA instrumental intensity in Korea. Since the occurrence of strong earthquakes is scarce in the Korean Peninsula, there is an insufficiency of strong motion data. As a result, strong motion data were synthesized by a stochastic procedure to satisfy the characteristics of a seismic source and crustal attenuation of the Peninsula. Six engineering ground motion parameters, including the JMA instrumental intensity, were determined from the synthesized strong motion data. The empirical relations between the ground motion parameters were then analyzed. Cluster analysis to classify the parameters into groups was also performed. The result showed that the JMA acceleration ($a_0$) could be classified into similar group with the spectrum intensity and the relatively distant group with the CAV (Cumulative Absolute Velocity). It is thought that the $a_0$ or JMA intensity can be used as an alternative criterion in the evaluation of seismic damage. On the other hand, attenuation relation equations for PGA and $a_0$ to be used in the prediction of seismic hazard were derived as functions of the moment magnitude and hypocentral distance.

• Earthquakes and Structures
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• v.8 no.3
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• pp.681-697
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• 2015

Iran as one of the countries located on the Alpine-Himalayan seismic belt has recently experienced a few number of catastrophic earthquakes. A well-known index of how buildings are affected by earthquakes is through assessment of probable Peak Ground Acceleration (PGA) and structures' response spectra. In this research, active faults around Kerman and Birjand, two major cities in eastern parts of Iran, have been considered. Seismic catalogues are gathered to categorize effects of surrounding faults on seismicity of the region. These catalogues were further refined with respect to time and space based on Knopoff-Gardner algorithm in order to increase statistical independency of events. Probabilistic Seismic Hazard Analysis (PSHA) has been estimated for each of cities regarding 50, 100, 200 and 500 years of structures' effective life-span. These results subsequently have been compared with Deterministic Seismic Hazard Analysis (DSHA). It has been observed that DSHA not necessarily suggests upper bound of PSHA results. Furthermore, based on spectral Ground Motion Prediction Equations (GMPEs), Uniform Hazard Spectra (UHS) and spectral acceleration were provided for 2% and 10% levels of probability of exceedance. The results show that increasing source-to-site distance leads to spectral acceleration reduction regarding each fault. In addition, the spectral acceleration rate of variation would increase if the source-to-site distance decreases.