This study investigates the risk reduction effect and identifies the optimal capacity of Multi-barrier Accident Coping Strategy (MACST) facilities for nuclear power plants (NPPs) under seismic hazard. The efficacy of MACST facilities in OPR1000 and APR1400 NPP systems is evaluated by utilizing the Improved Direct Quantification of Fault Tree with Monte Carlo Simulation (I-DQFM) method. The analysis encompasses a parametric study of the seismic capacity of two MACST facilities: the 1.0 MW large-capacity mobile generator and the mobile low-pressure pump. The results demonstrate that the optimal seismic capacity of MACST facilities for both NPP systems is 1.5g, which markedly reduces the probability of core damage. In particular, the core damage risk is reduced by approximately 23% for the OPR1000 system, with the core damage fragility reduced by approximately 72% at 1.0g seismic intensity. For the APR1400 system, the implementation of MACST is observed to reduce the core damage risk by approximately 17% and the core damage fragility by approximately 44% under the same conditions. These results emphasize the significance of integrating MACST facilities to enhance the resilience and safety of NPPs against seismic hazard scenarios, highlighting the necessity for continuous adaptation of safety strategies to address evolving natural threats.

Seismic fragility curves present the conditional probability of damage to target structures due to external seismic load and are widely used in various ways. When constructing such a seismic fragility curve, it is essential to consider various types and numbers of ground motions. In general, the earthquake occurrence characteristics of an area where the target structure of the seismic fragility curve exists are analyzed, and based on this, appropriate ground motions are selected to derive the seismic fragility curve. If the number of selected ground motions is large, the diversity of ground motions is considered, but a large amount of computational time is required. Conversely, if the number of ground motions is too small, the diversity of ground motions cannot be considered, which may distort the seismic fragility curve. Therefore, this study analyzed the relationship between the number of ground motions considered when deriving the seismic fragility curve and the parameters of the seismic fragility curve. Using two example structures, numerical analysis was performed by selecting a random number of ground motions from a total of two hundred, and a seismic fragility curve was derived based on the results. Analysis of the relationship of the parameter of the seismic fragility curve and the number of selected ground motions was performed. As the number of ground motions considered increases, uncertainty in ground motion selection decreases, and when deriving seismic fragility curves considering the same number of ground motions, uncertainty increases relatively as the degree of freedom of the target structure increases. However, considering a relatively large number of ground motions, uncertainty appeared insignificant regardless of increased degrees of freedom. Finally, it is possible that the increase in the number of ground motions could lower the epistemic uncertainty and thus improve the reliability of the results.

Strong ground motions at specific sites can cause severe damage to structures. Understanding the influence of site characteristics on the dynamic response of structures is crucial for evaluating their seismic performance and mitigating the potential damage caused by site effects. This study investigates the impact of the average shear wave velocity, as a site characteristic, on the seismic response of low-to-medium-rise reinforced concrete buildings. To explore them, one-dimensional soil column models were generated using shear wave velocity profile from California, and nonlinear site response analyses were performed using bedrock motions. Nonlinear dynamic structural analyses were conducted for reinforced concrete moment-resisting frame models based on the regional information. The effect of shear wave velocity on the structural response and surface ground motions was examined. The results showed that strong ground motions tend to exhibit higher damping on softer soils, reducing their intensity, while on stiffer soils, the ground motion intensity tends to amplify. Consequently, the structural response tended to increase on stiffer soils compared to softer soils.

The damage to structures during an earthquake can be varied depending on the frequency characteristics of seismic waves and the geological properties of the ground. Therefore, considering such attributes in the design ground motions is crucial. The Korean seismic design standard (KDS 17 10 00) provides design response spectra for various ground classifications. If required for time-domain analysis, ground motion time series can be either selected and adjusted from motions recorded at rock sites in intraplate regions or artificially synthesized. Ground motion time series at soil sites should be obtained from site response analysis. However, in practice, selecting suitable ground motion records is challenging due to the overall lack of large earthquakes in intraplate regions, and artificially synthesized time series often leads to unrealistic responses of structures. As an alternative approach, this study provides a case study of generating ground motion time series based on the hybrid broadband ground motion simulation of selected scenario earthquakes at sites in the Nakdonggang delta region. This research is significant as it provides a novel method for generating ground motion time series that can be used in seismic design and response analysis. For large-magnitude earthquake scenarios close to the epicenter, the simulated response spectra surpassed the 1000-year design response spectra in some specific frequency ranges. Subsequently, the acceleration time series at each location were used as input motions to perform nonlinear 1D site response analysis through the PySeismoSoil Package to account for the site response characteristics at each location. The results of the study revealed a tendency to amplify ground motion in the mid to long-period range in most places within the study area. Additionally, significant amplification in the short-period range was observed in some locations characterized by a thin soil layer and relatively high shear wave velocity soil near the upper bedrock.

High-rise buildings are equipped with TMD (Tuned Mass Damper), a vibration control device that ensure the stability and usability of the building. In this study, the seismic response control performance was evaluated by selecting the design variables of the TMD based on the installation location of the twisted irregular building. To this end, we selected analysis models of 60, 80, and 100 floors with a twist angle of 1 degree per floor, and performed time history analysis by applying historical seismic loads and resonant harmonic loads. The total mass ratio of TMDs was set to 1.0%, and the distributed installation locations of TMDs were selected through mode analysis. The analysis results showed that the top-floor displacement responses of all analysis models increased, but the maximum story drift ratio decreased. In order to secure the seismic response control performance by distributed installation of TMDs in twisted irregular buildings, it is judged that the mass ratio distribution of TMDs will act as a key variable.

Dynamic responses of nuclear power plant structure subjected to earthquake loads should be carefully investigated for safety. Because nuclear power plant structure are usually constructed by material of reinforced concrete, the aging deterioration of R.C. have no small effect on structural behavior of nuclear power plant structure. Therefore, aging deterioration of R.C. nuclear power plant structure should be considered for exact prediction of seismic responses of the structure. In this study, a machine learning model for seismic response prediction of nuclear power plant structure was developed by considering aging deterioration. The OPR-1000 was selected as an example structure for numerical simulation. The OPR-1000 was originally designated as the Korean Standard Nuclear Power Plant (KSNP), and was re-designated as the OPR-1000 in 2005 for foreign sales. 500 artificial ground motions were generated based on site characteristics of Korea. Elastic modulus, damping ratio, poisson’s ratio and density were selected to consider material property variation due to aging deterioration. Six machine learning algorithms such as, Decision Tree (DT), Random Forest (RF), Support Vector Machine (SVM), K-Nearest Neighbor (KNN), Artificial Neural Networks (ANN), eXtreme Gradient Boosting (XGBoost), were used t o construct seispic response prediction model. 13 intensity measures and 4 material properties were used input parameters of the training database. Performance evaluation was performed using metrics like root mean square error, mean square error, mean absolute error, and coefficient of determination. The optimization of hyperparameters was achieved through k-fold cross-validation and grid search techniques. The analysis results show that neural networks present good prediction performance considering aging deterioration.

원전 내 전기기기의 내진성능 평가는 안전성 확보에 매우 중요하다. 이 연구에서는 원전에 설치되는 전기기기의 동특성 및 현장조사 결과를 참고하여 모형 캐비닛과 앵커기초를 설계 및 제작하였다. 제작된 모형 캐비닛을 대상으로 진동대실험을 수행하였다. 실험 결과를 바탕으로 유한요소모델을 작성하고 지진응답해석을 수행하였다. 입력지진동이 커짐에 따른 실험 및 해석 결과를 비교하여 모형 캐비닛의 지진거동특성을 분석하였다. 두 결과에 대한 모형 캐비닛의 지진거동은 다르며 내진성능에 큰 차이가 발생할 수 있다. 따라서 캐비닛과 콘크리트 기초 사이의 상호작용을 고려할 수 없는 경우 캐비닛의 지진거동 특성은 실험적으로 평가하는 것이 적절할 것으로 판단하였다.

In the seismic evaluation of underground utility tunnels, selecting an analytical method is critical to estimating reasonable seismic responses. In simplified pseudo-static analysis methods widely applied to typical seismic design and evaluation of underground tunnels in practice, it is essential to check whether the methods provide valid results for cut-and-cover tunnels buried in shallow to medium depth. The differences between the two simplified pseudo-static methods are discussed in this study, and the analysis results are compared to those obtained from FLAC models. In addition to the analysis methods, seismic site classification, overburden soil depth, and sectional configuration are considered variables to examine their effects on the seismic response of underground utility tunnels. Based on the analysis results, the characteristics derived from the concepts and details of each simplified model are discussed. Also, general observations are made for the application of simplified analysis methods.

Existing reinforced concrete (RC) building frames constructed before the seismic design was applied have seismically deficient structural details, and buildings with such structural details show brittle behavior that is destroyed early due to low shear performance. Various reinforcement systems, such as fiber-reinforced polymer (FRP) jacketing systems, are being studied to reinforce the seismically deficient RC frames. Due to the step-by-step modeling and interpretation process, existing seismic performance assessment and reinforcement design of buildings consume an enormous amount of workforce and time. Various machine learning (ML) models were developed using input and output datasets for seismic loads and reinforcement details built through the finite element (FE) model developed in previous studies to overcome these shortcomings. To assess the performance of the seismic performance prediction models developed in this study, the mean squared error (MSE), R-square (R2), and residual of each model were compared. Overall, the applied ML was found to rapidly and effectively predict the seismic performance of buildings according to changes in load and reinforcement details without overfitting. In addition, the best-fit model for each seismic performance class was selected by analyzing the performance by class of the ML models.

This study investigated the impact of soil-structure interaction on multi-degree-of-freedom structures using the shallow-foundation Winkler model, known as the BNWF model. The model’s period was determined through eigenvalue analysis and compared to results obtained from FEMA’s formula. Results indicated that considering the soil, the structure’s period increased by up to 8.7% compared to the fixed-base model, aligning with FEMA’s calculations. Furthermore, with adequate ground acceleration, roof displacement increased by 3.4% to 3.8%, while base shear decreased by 4% to 10%. However, roof displacement and base shear increased in some earthquake scenarios due to spectral shape effects in regions with extended structural periods. Foundation damping effects, determined through the foundation’s moment-rotation history, grew with higher ground acceleration. This suggests that accounting for period elongation and foundation damping can enhance the seismic design of multi-degree-of-freedom structures.

최근 원자력 지진 PSA(Probabilistic Safety Assessment)를 토대로 산업시설물의 지진 PSA를 수행하는 연구가 진행되었다. 해당 연 구는 원자력 발전소와 산업시설물의 차이를 파악하고, 최종적으로 운영정지를 목표로 하는 고장수목(Fault Tree)를 구축한 후 시각적 확률도구인 베이지안 네트워크(Bayesian Network, BN)으로 변환하였다. 본 연구는 선행연구를 기반으로 지진으로 유발된 구조손상 으로 인해 발생 가능한 화재･폭발에 대해 PSA를 수행하고자 하였다. 이를 위해 화재･폭발을 사건수목(Event Tree)으로 표현하고, BN 으로 변환하였다. 변환된 BN은 화재･폭발 모듈로서 선행연구에서 제시된 고장수목 기반 BN과 연계되어 최종적으로 지진 유발 화재･ 폭발 PSA를 수행할 수 있는 BN 기반 방법론이 개발되었다. 개발된 BN을 검증하기위해 수치예제로서 가상의 가스플랜트 Plot Plan을 생성하였고, 가스플랜트의 설비 종류가 구체적으로 반영된 대규모 BN을 구축하였다. 해당 BN을 이용하여 지진 규모에 따른 전체시 스템의 운영정지 확률 및 하위시스템들의 고장확률 산정과 더불어 역으로 전체시스템이 운영 정지되었을 때 하위시스템들의 영향도 분석과 화재･폭발 가능성을 산정하여 다양한 의사결정을 수행할 수 있음을 제시함으로써 그 우수성을 확인하였다.

지반운동의 입사방향 변화에 따라 구조물의 지진응답도 그 방향에 따라 변화할 것이다. 지반운동의 입사되는 방향에 따른 예제교 량의 지진응답의 영향을 분석하기 위하여 다양한 입사각에 대하여 구한 1초 주기에 대응하는 가속도응답스펙트럼을 구하였다. 이를 이용하여 5가지 종류의 백분위수에 해당하는 1쌍의 직교하는 수평성분 지진파를 40세트 생성하였다. 지반운동의 입사방향에 따른 예 제교량의 지진응답을 구하여 교각에 대한 지진취약도 해석을 수행하였다. 5가지 종류의 백분위수에 대응하는 지진파에 대한 지진취 약도 해석을 분석하여 지진파의 입사방향에 따라서 지진취약도 곡선의 중앙값이 약 1.2~2.6배 정도 차이가 남을 알 수 있었다. 다시 말 하면 지진파의 입사방향에 따라서 교량 구조물의 손상정도가 약 1.2~2.6배 정도 차이가 날 수 있음을 의미한다.

In this paper, machine learning models were applied to predict the seismic response of steel frame structures. Both geometric and material nonlinearities were considered in the structural analysis, and nonlinear inelastic dynamic analysis was performed. The ground acceleration response of the El Centro earthquake was applied to obtain the displacement of the top floor, which was used as the dataset for the machine learning methods. Learning was performed using two methods: Decision Tree and Random Forest, and their efficiency was demonstrated through application to 2-story and 6-story 3-D steel frame structure examples.

Machine learning is widely applied to various engineering fields. In structural engineering area, machine learning is generally used to predict structural responses of building structures. The aging deterioration of reinforced concrete structure affects its structural behavior. Therefore, the aging deterioration of R.C. structure should be consider to exactly predict seismic responses of the structure. In this study, the machine learning based seismic response prediction model was developed. To this end, four machine learning algorithms were employed and prediction performance of each algorithm was compared. A 3-story coupled shear wall structure was selected as an example structure for numerical simulation. Artificial ground motions were generated based on domestic site characteristics. Elastic modulus, damping ratio and density were changed to considering concrete degradation due to chloride penetration and carbonation, etc. Various intensity measures were used input parameters of the training database. Performance evaluation was performed using metrics like root mean square error, mean square error, mean absolute error, and coefficient of determination. The optimization of hyperparameters was achieved through k-fold cross-validation and grid search techniques. The analysis results show that neural networks and extreme gradient boosting algorithms present good prediction performance.

Phayathonzu temple in Myanmar was made of masonry bricks, and so it was vulnerable to lateral load such as earthquake. Especially, it has many difficulties in structural modeling and dynamic analysis because the discontinuous characteristics of masonry structure should be considered. So, it is necessary to provide the seismic performance evaluation technology through the inelastic dynamic modeling and analysis under earthquake loads for the safety security of masonry brick temple. Therefore, this study analyzes the seismic behavior characteristics and evaluates the seismic performance for the 479 structure with many cracks and deformations. Through the evaluation results, we found out the structural weak parts on earthquake loads.

This study aims to investigate the seismic response of a large span thin shell structures and assess their displacement under seismic loads. The study employs finite element analysis to model a thin shell structure subjected to seismic excitation. The analysis includes eigenvalue analysis and time history analysis to evaluate the natural frequencies and displacement response of the structure under seismic loads. The findings show that the seismic response of the large span thin shell structure is highly dependent on the frequency content of the seismic excitation. The eigenvalue analysis reveals that the tenth mode of vibration of the structure corresponds to a large-span mode. The time history analysis further demonstrates, with 5% damping, that the displacement response of the structure at the critical node number 4920 increases with increasing seismic intensity, reaching a maximum displacement of 49.87mm at 3.615 seconds. Nevertheless, the maximum displacement is well below the allowable limit of the thin shell. The results of this study provide insight into the behaviour of complex large span thin shell structures as elevated foundations for buildings under seismic excitation, based on the displacement contours on different modes of eigenvalues. The findings suggest that the displacement response of the structure is significant for this new application of thin shell, and it is recommended to enhance the critical displacement area in the next design phase to align with the findings of this study to resist the seismic impact.

Recent earthquakes in Korea, like Gyeongju and Pohang, have highlighted the need for accurate seismic hazard assessment. The lack of substantial ground motion data necessitates stochastic simulation methods, traditionally used with a simplistic point-source assumption. However, as earthquake magnitude increases, the influence of finite faults grows, demanding the adoption of finite faults in simulations for accurate ground motion estimates. We analyzed variations in simulated ground motions with and without the finite fault method for earthquakes with magnitude (Mw) ranging from 5.0 to 7.0, comparing pseudo-spectral acceleration. We also studied how slip distribution and hypocenter location affect simulations for a virtual earthquake that mimics the Gyeongju earthquake with Mw 5.4. Our findings reveal that finite fault effects become significant at magnitudes above Mw 5.8, particularly at high frequencies. Notably, near the hypocenter, the virtual earthquake’s ground motion significantly changes using a finite fault model, especially with heterogeneous slip distribution. Therefore, applying finite fault models is crucial for simulating ground motions of large earthquakes (Mw ≥ 5.8 magnitude). Moreover, for accurate simulations of actual earthquakes with complex rupture processes having strong localized slips, incorporating finite faults is essential even for more minor earthquakes.

Piloti-type structures with vertical irregularity are vulnerable to earthquakes due to the soft structure of the first story. Structural characteristics of buildings can significantly affect the seismic loss function, calculated based on seismic fragility, and therefore need to be considered. This study investigated the effects of the number of stories and core locations on the seismic loss function of piloti-type buildings in Korea. Twelve analytical models were developed considering two variations: three stories (4-story, 5-story, and 6-story) and four core locations (center core, x-eccentric core, y-eccentric core, and xy-eccentric core). The interstory drift ratio and peak floor acceleration were assessed through incremental dynamic analysis using 44 earthquake records, and seismic fragility was derived. Seismic loss functions were calculated and compared using the derived seismic fragility and repair cost ratio of each component. The results indicate that the seismic loss function increases with more stories and when the core is eccentrically located in the piloti-type structure model. Therefore, the uncertainty due to the number of stories and core location should be considered when deriving the seismic loss function of piloti-type structures.

There are growing concerns that the recently implemented Earthquake Early Warning service is overestimating the rapidly provided earthquake magnitudes (M). As a result, the predicted damages unnecessarily activate earthquake protection systems for critical facilities and lifeline infrastructures that are far away. This study is conducted to improve the estimation accuracy of M by incorporating the observed S-wave seismograms in the near source region after removing the site effects of the seismograms in real time by filtering in the time domain. The ensemble of horizontal S-wave spectra from at least five seismograms without site effects is calculated and normalized to a hypocentric target distance (21.54 km) by using the distance attenuation model of Q(f)=348f0.52 and a cross-over distance of 50 km. The natural logarithmic mean of the S-wave ensemble spectra is then fitted to Brune’s source spectrum to obtain the best estimates for M and stress drop (SD) with the fitting weight of 1/standard deviation. The proposed methodology was tested on the 18 recent inland earthquakes in South Korea, and the condition of at least five records for the near-source region is sufficiently fulfilled at an epicentral distance of 30 km. The natural logarithmic standard deviation of the observed S-wave spectra of the ensemble was calculated to be 0.53 using records near the source for 1~10 Hz, compared to 0.42 using whole records. The result shows that the root-mean-square error of M and ln(SD) is approximately 0.17 and 0.6, respectively. This accuracy can provide a confidence interval of 0.4~2.3 of Peak Ground Acceleration values in the distant range.

유체-구조물-지반 상호작용을 고려한 액체저장탱크의 유한요소 모형을 제시하고, 비선형 지진응답 해석기법을 정식화한다. 탱크 구조물은 기하 및 재료 비선형 거동을 고려할 수 있는 쉘 요소로 모델링한다. 유체의 거동은 acoustic 요소로 구현하고, interface 요소 를 사용하여 구조물과 결합한다. 지반-구조물 상호작용을 고려하기 위해 지반의 근역과 원역을 각각 solid 요소와 perfectly matched discrete layer로 모델링한다. 예제 20만 kl급 액체저장탱크의 지진취약도 해석에 적용하여, 유연한 지반에 구조물이 놓인 경우 부지에 서의 암반노두운동의 증폭 및 필터링으로 인해 지진취약도의 중앙값과 대수 표준편차가 감소하는 것을 관찰할 수 있다.