• Architectural research
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• v.15 no.3
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• pp.151-158
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• 2013

Offshore oil and gas process plants are exposed to hazardous accidents such as explosion and fire, so that the structural components should resist such accidental loads. Given the possibilities of thousands of different scenarios for the occurrence of an accidental hazard, the best way to predict a reasonable size of a specific accidental load would be the employment of a probabilistic approach. Having the fact that a specific procedure for probabilistic accidental hazard analysis has not yet been established especially for explosion and fire hazards, it is widely accepted that engineers usually take simple and conservative figures in assuming uncertainties inherent in the procedure, resulting either in underestimation or more likely in overestimation in the topside structural design for offshore plants. The variation in the results of a probabilistic approach is determined by the assumptions accepted in the procedures of explosion probability computation, explosion analysis, and structural analysis. A design overpressure load for a sample offshore plant is determined according to the proposed probabilistic approach in this study. CFD analysis results using a Flame Acceleration Simulator, FLACS_v9.1, are utilized to create an overpressure hazard curve. Moreover, the negative impulse and frequency contents of a blast wave are considerably influencing structural responses, but those are completely ignored in a widely used triangular form of blast wave. An idealistic blast wave profile deploying both negative and positive pulses is proposed in this study. A topside process module and piperack with blast wall are 3D FE modeled for structural analysis using LS-DYNA. Three different types of blast wave profiles are applied, two of typical triangular forms having different impulse and the proposed load profile. In conclusion, it is found that a typical triangular blast load leads to overestimation in structural design.

• Nuclear Engineering and Technology
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• v.54 no.8
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• pp.2924-2932
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• 2022

Motivated by learning from experience and exploiting existing knowledge in civil nuclear operations, we have developed in-house generic Probabilistic Safety Assessment (PSA) models for pressurized and boiling water reactors. The models are computationally light, handy, transparent, user-friendly, and easily adaptable to account for major plant-specific differences. They cover the common internal initiating events, frontline and support systems reliability and dependencies, human-factors, common-cause failures, and account for new factors typically overlooked in many PSAs. For quantification, the models use generic US reliability data, precursor analysis reports, the ETHZ Curated Nuclear Events Database, and experts' opinions. Moreover, uncertainties in the most influential basic events are addressed. The generated results show good agreement with assessments available in the literature with detailed PSAs. We envision the models as an unbiased framework to measure nuclear operational risk with the same "ruler", and hence support inter-plant risk comparisons that are usually not possible due to differences in plant-specific PSA assumptions and scopes. The models can be used for initial risk screening, order-of-magnitude precursor analysis, and other research/pedagogic applications especially when no plant-specific PSAs are available. Finally, we are using the generic models for large-scale precursor analysis that will generate big picture trends, lessons, and insights.

• Nuclear Engineering and Technology
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• v.49 no.2
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• pp.313-326
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• 2017

The systematic management of plant risk is crucial for enhancing the safety of nuclear power plants and for designing new nuclear power plants. Accident sequence precursor (ASP) analysis may be able to provide risk significance of operational experience by using probabilistic risk assessment to evaluate an operational event quantitatively in terms of its impact on core damage. In this study, an ASP methodology for two operation mode, full power and low power/shutdown operation, has been developed and applied to significant accident precursors that may occur during the operation of nuclear power plants. Two operational events, loss of feedwater and steam generator tube rupture, are identified as ASPs. Therefore, the ASP methodology developed in this study may contribute to identifying plant risk significance as well as to enhancing the safety of nuclear power plants by applying this methodology systematically.

• Nuclear Engineering and Technology
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• v.53 no.3
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• pp.967-973
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• 2021

In 2011, an earthquake and subsequent tsunami hit the Fukushima Daiichi Nuclear Power Plant, causing simultaneous accidents in several reactors. This accident shows us that if there are several reactors on site, the seismic risk to multiple units is important to consider, in addition to that to single units in isolation. When a seismic event occurs, a seismic-failure correlation exists between the nuclear power plant's structures, systems, and components (SSCs) due to their seismic-response and seismic-capacity correlations. Therefore, it is necessary to evaluate the multi-unit seismic risk by considering the SSCs' seismic-failure-correlation effect. In this study, a methodology is proposed to obtain the seismic-response-correlation coefficient between SSCs to calculate the risk to multi-unit facilities. This coefficient is calculated from a probabilistic multi-unit seismic-response analysis. The seismic-response and seismic-failure-correlation coefficients of the emergency diesel generators installed within the units are successfully derived via the proposed method. In addition, the distribution of the seismic-response-correlation coefficient was observed as a function of the distance between SSCs of various dynamic characteristics. It is demonstrated that the proposed methodology can reasonably derive the seismic-response-correlation coefficient between SSCs, which is the input data for multi-unit seismic probabilistic safety assessment.

• Nuclear Engineering and Technology
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• v.46 no.1
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• pp.11-26
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• 2014

The analyses carried out within the Seismic Probabilistic Risk Assessments (SPRAs) of Nuclear Power Plants (NPPs) are affected by significant aleatory and epistemic uncertainties. These uncertainties have to be represented and quantified coherently with the data, information and knowledge available, to provide reasonable assurance that related decisions can be taken robustly and with confidence. The amount of data, information and knowledge available for seismic risk assessment is typically limited, so that the analysis must strongly rely on expert judgments. In this paper, a Dempster-Shafer Theory (DST) framework for handling uncertainties in NPP SPRAs is proposed and applied to an example case study. The main contributions of this paper are two: (i) applying the complete DST framework to SPRA models, showing how to build the Dempster-Shafer structures of the uncertainty parameters based on industry generic data, and (ii) embedding Bayesian updating based on plant specific data into the framework. The results of the application to a case study show that the approach is feasible and effective in (i) describing and jointly propagating aleatory and epistemic uncertainties in SPRA models and (ii) providing 'conservative' bounds on the safety quantities of interest (i.e. Core Damage Frequency, CDF) that reflect the (limited) state of knowledge of the experts about the system of interest.

• Food Science of Animal Resources
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• v.39 no.4
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• pp.565-575
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• 2019

This study evaluated Campylobacter jejuni risk in ground meat products. The C. jejuni prevalence in ground meat products was investigated. To develop the predictive model, survival data of C. jejuni were collected at $4^{\circ}C-30^{\circ}C$ during storage, and the data were fitted using the Weibull model. In addition, the storage temperature and time of ground meat products were investigated during distribution. The consumption amount and frequency of ground meat products were investigated by interviewing 1,500 adults. The prevalence, temperature, time, and consumption data were analyzed by @RISK to generate probabilistic distributions. In 224 samples of ground meat products, there were no C. jejuni-contaminated samples. A scenario with a series of probabilistic distributions, a predictive model and a dose-response model was prepared to calculate the probability of illness, and it showed that the probability of foodborne illness caused by C. jejuni per person per day from ground meat products was $5.68{\times}10^{-10}$, which can be considered low risk.

• Journal of the Earthquake Engineering Society of Korea
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• v.23 no.2
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• pp.101-108
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• 2019

The seismic safety of nuclear power plants has always been emphasized by the effects of accidents. In general, the seismic safety evaluation of nuclear power plants carries out a seismic probabilistic safety assessment. The current probabilistic safety assessment assumes that damage to the structure, system, and components (SSCs) occurs independently to each other or perfect dependently to each other. In case of earthquake events, the failure event occurs with the correlation due to the correlation between the seismic response of the SSCs and the seismic performance of the SSCs. In this study, the EEMS (External Event Mensuration System) code is developed which can perform the seismic probabilistic safety assessment considering correlation. The developed code is verified by comparing with the multiplier n, which is for calculating the joint probability of failure, which is proposed by Mankamo. It is analyzed the changes in seismic fragility curves and seismic risks with correlation. As a result, it was confirmed that the seismic fragility curves and seismic risk change according to the failure correlation coefficient. This means that it is important to select an appropriate failure correlation coefficient in order to perform a seismic probabilistic safety assessment. And also, it was confirmed that carrying out the seismic probabilistic safety assessment in consideration of the seismic correlation provides more realistic results, rather than providing conservative or non-conservative results comparing with that damage to the SSCs occurs independently.

• Journal of Navigation and Port Research
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• v.33 no.4
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• pp.255-261
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• 2009

Prediction of the stability for ships is very complex in reality. In this paper, risk based approach is applied to predict the probability of capsize for a certified ship, which is effected by the forces of sea especially the wave loading Safety assessment and risk analysis process are also applied for the probabilistic prediction of stability for ships. The probability of shipsencountering different waves at sea is calculated by the existed statistics data and risk based models. Finally, ship capsizing probability is calculated according to single degree of freedom(SDF) rolling differential equation and basin erosion theory of nonlinear dynamics. Calculation results show that the survival probabilities of ship excited by the forces of the seas, especially in the beam seas status, can be predicted by the risk based method.

• Nuclear Engineering and Technology
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• v.52 no.9
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• pp.1983-1989
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• 2020

The human reliability analysis is a method by which, in general terms, the human impact to the safety and risk of a nuclear power plant operation can be modelled, quantified and analysed. It is an indispensable element of the PSA process within the nuclear industry nowadays. The paper herein presents a sensitivity study of the human reliability analysis performed on a real nuclear power plant-specific probabilistic safety assessment model. The analysis is performed on a pre-selected set of post-initiator operator actions. The purpose of the study is to investigate the impact of these operator actions on the plant risk by altering their corresponding human error probabilities in a wide spectrum. The results direct the fact that the future effort should be focused on maintaining the current human reliability level, i.e. not letting it worsen, rather than improving it.

• Nuclear Engineering and Technology
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• v.50 no.8
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• pp.1372-1386
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• 2018

Despite recent advances in multi-hazard analysis, the complexity and inherent nature of such problems make quantification of the landslide effect in a probabilistic safety assessment (PSA) of NPPs challenging. Therefore, in this paper, a practical approach was presented for performing an earthquake-induced landslide PSA for NPPs subject to seismic hazard. To demonstrate the effectiveness of the proposed approach, it was applied to Korean typical NPP in Korea as a numerical example. The assessment result revealed the quantitative probabilistic effects of peripheral slope failure and subsequent run-out effect on the risk of core damage frequency (CDF) of a NPP during the earthquake event. Parametric studies were conducted to demonstrate how parameters for slope, and physical relation between the slope and NPP, changed the CDF risk of the NPP. Finally, based on these results, the effective strategies were suggested to mitigate the CDF risk to the NPP resulting from the vulnerabilities inherent in adjacent slopes. The proposed approach can be expected to provide an effective framework for performing the earthquake-induced landslide PSA and decision support to increase NPP safety.