• Smart Structures and Systems
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• v.23 no.2
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• pp.185-194
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• 2019

The probabilistic tsunami risk assessment of large coastal areas is challenging because the inland propagation of a tsunami wave requires an accurate numerical model that takes into account the interaction between the ground, the infrastructures, and the wave itself. Classic mesh-based methods face many challenges in the propagation of a tsunami wave inland due to their ever-moving boundary conditions. In alternative, mesh-less based methods can be used, but they require too much computational power in the far-field. This study proposes a hybrid approach. A mesh-based method propagates the tsunami wave from the far-field to the near-field, where the influence of the sea floor is negligible, and a mesh-less based method, smooth particle hydrodynamic, propagates the wave onto the coast and inland, and takes into account the wave structure interaction. Nowadays, this can be done because the advent of general purpose GPUs made mesh-less methods computationally affordable. The method is used to simulate the inland propagation of the 2004 Indian Ocean tsunami off the coast of Indonesia.

• Journal of the Korean Society of Safety
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• v.36 no.2
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• pp.101-110
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• 2021

This paper presents the results of an initiating event analysis as part of a Level 1 probabilistic safety assessment (PSA) for at-power internal events for the Korea Research Reactor (KRR). The PSA methodology is widely used to quantitatively assess the safety of research reactors (RRs) in the domestic nuclear industry. Initiating event frequencies are required to conduct a PSA, and they considerably affect the PSA results. Because there is no domestic database for domestic trip events, the safety of RRs is usually assessed using foreign databases. In this paper, operating experience data from the KRR for trip events were collected and analyzed in order to determine the frequency of specific initiating events. These frequencies were calculated using two approaches according to the event characteristics and data availability: (1) based on KRR operating experience or (2) using generic data.

• Smart Structures and Systems
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• v.15 no.3
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• pp.751-767
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• 2015

A new procedure is proposed for assessing probabilistic condition of structures considering effect of measured data uncertainty. In this procedure, multiple Finite Element (FE) models are identified by using weighting vectors that represent the uncertainty conditions of measured data. The distribution of structural parameters is analysed using a Principal Component Analysis (PCA) in relation to uncertainty conditions, and the identified models are classified into groups according to their similarity by using a K-means method. The condition of a structure is then assessed probabilistically using FE models in the classified groups, each of which represents specific uncertainty condition of measured data. Yeondae bridge, a steel-box girder expressway bridge in Korea, is used as an illustrative example. Probabilistic condition of the bridge is evaluated by the distribution of load rating factors obtained using multiple FE models. The numerical example shows that the proposed method can quantify uncertainty of measured data and subsequently evaluate efficiently the probabilistic condition of bridges.

• Journal of the Korea institute for structural maintenance and inspection
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• v.6 no.4
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• pp.169-179
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• 2002

This paper presents an efficient algorithm for the estimation of damage location and severity in structure using Probabilistic Neural Network (PNN). Artificial neural network has been being used for damage assessment by many researchers, but there are still some barriers that must be overcome to improve its accuracy and efficiency. The major problems with the conventional neural network are the necessity of many training data for neural network learning and ambiguity in the relation of neural network architecture with convergence of solution. In this paper, PNN is used as a pattern classifier to overcome those problems in the conventional neural network. The basic idea of damage assessment algorithm proposed in this paper is that modal characteristics from a damaged structure are compared with the training patterns which represent the damage in specific element to determine how close it is to training patterns in terms of the probability from PNN. The training pattern that gives a maximum probability implies that the element used in producing the training pattern is considered as a damaged one. The proposed damage assessment algorithm using PNN is applied to a 2-span continuous beam model structure to verify the algorithm.

• Journal of the Earthquake Engineering Society of Korea
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• v.18 no.3
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• pp.151-160
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• 2014

Probabilistic tsunami hazard analysis (PTHA) is based on the approach of probabilistic seismic hazard analysis (PSHA) which is performed using various seismotectonic models and ground-motion prediction equations. The major difference between PTHA and PSHA is that PTHA requires the wave parameters of tsunami. The wave parameters can be estimated from tsunami propagation analysis. Therefore, a tsunami simulation analysis was conducted for the purpose of evaluating the wave parameters required for the PTHA of Uljin nuclear power plant (NPP) site. The tsunamigenic fault sources in the western part of Japan were chosen for the analysis. The wave heights for 80 rupture scenarios were numerically simulated. The synthetic tsunami waveforms were obtained around the Uljin NPP site. The results show that the wave heights are closely related with the location of the fault sources and the associated potential earthquake magnitudes. These wave parameters can be used as input data for the future PTHA study of the Uljin NPP site.

• Earthquakes and Structures
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• v.15 no.5
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• pp.487-498
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• 2018

Buckling-restrained braces are passive control devices with high level of energy dissipation ability. However, they suffer from low post-yield stiffness which makes them vulnerable to severe ground motions, especially near-field earthquakes. Among the several methods proposed to improve resistance of BRB frames, mega-brace configuration can be a solution to increase frame lateral strength and stiffness and improve distribution of forces to prevent large displacement in braces. Due to the limited number of research regarding the performance of such systems, the current paper aims to assess seismic performance of BRB frames with mega-bracing arrangement under near-field earthquakes via a detailed probabilistic framework. For this purpose, a group of multi-story mega-BRB frames were modelled by OpenSEES software platform. In the first part of the paper, simplified procedures including nonlinear pushover and Incremental Dynamic Analysis were conducted for performance evaluation. Two groups of near-fault seismic ground motions (Non-pulse and Pulse-like records) were considered for analyses to take into account the effects of record-to-record uncertainties, as well as forward directivity on the results. In the second part, seismic reliability analyses are conducted in the context of performance based earthquake engineering. Two widely-known EDP-based and IM-based probabilistic frameworks are employed to estimate collapse potential of the structures. Results show that all the structures can successfully tolerate near-field earthquakes with a high level of confidence level. Therefore, mega-bracing configuration can be an effective alternative to conventional BRB bracing to withstand near-field earthquakes.

• Computational Structural Engineering
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• v.2 no.4
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• pp.89-98
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• 1989

In order to take account of the statistical properties of random variables used in the structural analysis, the conventional approach usually adopts the safety factor based on past experiences for the qualitative assessment of structural safety problem. Recently, new approach based on the probabilistic concept has been applied to the assessment of structural safety in order to circumvent the difficulties of the conventional approach in choosing the appropriate safety factor. Thus, computer program called "Probabilistic finite element method" is developed by incorporating the probabilistic concept into the conventional matrix method in order to investigate the effects of the random variables on the final output of the structural analysis. From the comparison of some examples, it can be concluded that the PFEM developed in this study deals consistently with the uncertainty of random variables and provides the rational tool for the assessment of structural safety of plane frame.

• Earthquakes and Structures
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• v.13 no.4
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• pp.421-427
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• 2017

Seismic safety evaluation of weir structure is significant considering the catastrophic economical consequence of operational disruption. In recent years, the seismic probabilistic risk assessment (SPRA) has been issued as a key area of research for the hydraulic system to mitigate and manage the risk. The aim of this paper is to assess the seismic probabilistic risk of weir structures employing the seismic hazard and the structural fragility in Korea. At the first stage, probabilistic seismic hazard analysis (PSHA) approach is performed to extract the hazard curve at the weir site using the seismic and geological data. Thereafter, the seismic fragility that defines the probability of structural collapse is evaluated by using the incremental dynamic analysis (IDA) method in accordance with the four different design limit states as failure identification criteria. Consequently, by combining the seismic hazard and fragility results, the seismic risk curves are developed that contain helpful information for risk management of hydraulic structures. The tensile stress of the mass concrete is found to be more vulnerable than other design criteria. The hazard deaggregation illustrates that moderate size and far source earthquakes are the most likely scenario for the site. In addition, the annual loss curves for two different hazard source models corresponding to design limit states are extracted.

• Journal of Environmental Impact Assessment
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• v.20 no.4
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• pp.497-507
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• 2011

This research studied human health risk assessment of benzene from industrial complexes of Chungcheong Province (Seosan industrial complex) and Jeonla Province (Iksan industrial complex and Yeosoo industrial complex). The residents near the industrial complexes areas can be often exposed to volatile organic compounds (e.g., benzene, toluene, xylenes) through a number of exposure pathways, including inhalation of the organic pollutant via various environmental matrices (air, water and soil), contaminated water, and soil intake. Benzene is well known to be a common carcinogenic and toxic compound that is produced from industrial and oil refinery complexes. In this study, a number of samples from water, air, and soil were taken from the residential settings and public school zones located near the industrial complex sites. Based on the carcinogenic risk assessment, the risk estimates were slightly above $10{\times}10^{-6}$ at all three industrial sites. According to deterministic risk assessment, inhalation was the most important route. The distribution of benzene in the environment would be dependent on vapor pressure, and the physical property influencing the extent of the potential risks. Non-carcinogenic risk assessment of benzene shows that the values of Hazard Index(HI) were much lower than 1.0 at all industrial complexes. Therefore, benzene was not a cause of concern in terms of non-carcinogenic risk posed to the residents near the sites. When compared to probabilistic risk assessment, the CTE(central tendency exposure) cancer risk values of deterministic risk assessment were close to the mean values predicted by the probabilistic risk assessment. The RME(reasonable maximum exposure) values fell within the range of 95% to 99.9% estimated by the probabilistic risk assessment. Since the values of carcinogenic risk assessment were higher than $10{\times}10^{-6}$, further detailed monitoring and refined risk assessment for benzene may be warranted to estimate more reliable and potential inhalation risks to receptors near the industrial complexes.

• Journal of the Earthquake Engineering Society of Korea
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• v.25 no.2
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• pp.53-58
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• 2021

Nuclear power plant's safety against seismic events is evaluated as risk values by probabilistic seismic safety assessment. The risk values vary by the seismic failure correlation between the structures, systems, and components (SSCs). However, most probabilistic seismic safety assessments idealized the seismic failure correlation between the SSCs as entirely dependent or independent. Such a consideration results in an inaccurate assessment result not reflecting real physical phenomenon. A nuclear power plant's seismic risk should be calculated with the appropriate seismic failure correlation coefficient between the SSCs for a reasonable outcome. An accident scenario that has an enormous impact on a nuclear power plant's seismic risk was selected. Moreover, the probabilistic seismic response analyses of a nuclear power plant were performed to derive appropriate seismic failure correlations between SSCs. Based on the analysis results, the seismic failure correlation coefficient between SSCs was derived, and the seismic fragility curve and core damage frequency of the loss of essential power event were calculated. Results were compared with the seismic fragility and core damage frequency of assuming the seismic failure correlations between SSCs were independent and entirely dependent.