• International Journal of Safety
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• v.2 no.1
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• pp.50-56
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• 2003

There are a lot of uncertainties in the severe accident phenomena and scenarios in nuclear power plants (NPPs) and one of the major issues for severe accident management is the reduction of these uncertainties. The severe accident management aid system using Probabilistic Safety Assessments (PSA) technology is developed for the management staff in order to reduce the uncertainties. The developed system includes the graphical display for plant and equipment status, previous research results by a knowledge-base technique, and the expected plant behavior using PSA. The plant model used in this paper is oriented to identify plant response and vulnerabilities via analyzing the quantified results, and to set up a framework for an accident management program based on these analysis results. Therefore the developed system may playa central role of information source for decision-making for severe accident management, and will be used as a training tool for severe accident management.

• Nuclear Engineering and Technology
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• v.46 no.2
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• pp.207-216
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• 2014

This paper revisits the Fukushima accident to draw lessons in the aspect of nuclear safety considering the fact that the Fukushima accident resulted in core damage for three nuclear power plants simultaneously and that there is a high possibility of a failure of the integrity of reactor vessel and primary containment vessel. A brief review on the accident progression at Fukushima nuclear power plants is discussed to highlight the nature and characteristic of the event. As the severe accident management measures at the Fukushima Daiich nuclear power plants seem to be not fully effective, limitations of current severe accident management strategy are discussed to identify the areas for the potential improvements including core cooling strategy, containment venting, hydrogen control, depressurization of primary system, and proper indication of event progression. The gap between the Fukushima accident event progression and current understanding of severe accident phenomenology including the core damage, reactor vessel failure, containment failure, and hydrogen explosion are discussed. Adequacy of current safety goals are also discussed in view of the socio-economic impact of the Fukushima accident. As a conclusion, it is suggested that an investigation on a coherent integrated safety principle for the severe accident and development of innovative mitigation features is necessary for robust and resilient nuclear power system.

• Nuclear Engineering and Technology
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• v.53 no.10
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• pp.3298-3313
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• 2021

The objective of this study is to estimate the occurrence probabilities of severe accident phenomena based on a fuzzy elicitation technique. Normally, it is difficult to determine these probabilities due to the lack of information on severe accident progression and the highly uncertain values currently in use. In this case, fuzzy set theory (FST) can be best exploited. First, questions were devised for expert elicitation on technical issues of severe accident phenomena. To deal with ambiguities and the imprecision of previously developed (reference) probabilities, fuzzy aggregation methods based on FST were employed to derive the occurrence probabilities of severe accidents via four phases: 1) choosing experts, 2) quantifying weighting factors for the experts, 3) aggregating the experts' opinions, and 4) defuzzifying the fuzzy numbers. In this way, this study obtained expert elicitation results in the form of updated occurrence probabilities of severe accident phenomena in the OPR-1000 plant, after which the differences between the reference probabilities and the newly acquired probabilities using fuzzy aggregation were compared, with the advantages of the fuzzy technique over other approaches explained. Lastly, the impact of applying the updated severe accident probabilities on containment integrity was quantitatively investigated in a Level 2 PSA model.

• Nuclear Engineering and Technology
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• v.47 no.1
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• pp.74-84
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• 2015

If a transient occurs in a nuclear power plant (NPP), operators will try to protect the NPP by estimating the kind of abnormality and mitigating it based on recommended procedures. Similarly, operators take actions based on severe accident management guidelines when there is the possibility of a severe accident occurrence in an NPP. In any such situation, information about the occurrence time of severe accident-related events can be very important to operators to set up severe accident management strategies. Therefore, support systems that can quickly provide this kind of information will be very useful when operators try to manage severe accidents. In this research, the occurrence times of several events that could happen during a severe accident were predicted using support vector machines with short time variations of plant status variables inputs. For the preliminary step, the break location and size of a loss of coolant accident (LOCA) were identified. Training and testing data sets were obtained using the MAAP5 code. The results show that the proposed algorithm can correctly classify the break location of the LOCA and can estimate the break size of the LOCA very accurately. In addition, the occurrence times of severe accident major events were predicted under various severe accident paths, with reasonable error. With these results, it is expected that it will be possible to apply the proposed algorithm to real NPPs because the algorithm uses only the early phase data after the reactor SCRAM, which can be obtained accurately for accident simulations.

• Clinical and Experimental Pediatrics
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• v.53 no.6
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• pp.694-700
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• 2010

Purpose: To assess the validity of individual and combined prognostic effects of severe bronchopulmonary dysplasia (BPD), brain injury, retinopathy of prematurity (ROP), and parenteral nutrition associated cholestasis(PNAC). Methods: We retrospectively analyzed the medical records of 80 extremely low birthweight (ELBW) infants admitted to the neonatal intensive care unit (NICU) of the Severance Children's Hospital, and who survived to a postmenstrual age of 36 weeks. We analyzed the relationship between 4 neonatal morbidities (severe BPD, severe brain injury, severe ROP, and severe PNAC) and poor outcome. Poor outcome indicated death after a postmenstrual age of 36 weeks or survival with neurosensory impairment (cerebral palsy, delayed development, hearing loss, or blindness) between 18 and 24 months of corrected age. Results: Each neonatal morbidity correlated with poor outcome on univariate analysis. Multiple logistic regression analysis revealed that the odds ratios (OR) were 4.9 (95% confidence interval [CI], 1.0-22.6; $P$=0.044) for severe BPD, 13.2 (3.0-57.3; $P$<.001) for severe brain injury, 5.3 (1.6-18.1; $P$=0.007) for severe ROP, and 3.4 (0.5-22.7; $P$=0.215) for severe PNAC. Severe BPD, brain injury, and ROP were significantly correlated with poor outcome, but not severe PNAC. By increasing the morbidity count, the rate of poor outcome was significantly increased (OR 5.2; 95% CI, 2.2-11.9; $P$<.001). In infants free of the above-mentioned morbidities, the rate of poor outcome was 9%, while the corresponding rates in infants with 1, 2, and more than 3 neonatal morbidities were 46%, 69%, and 100%, respectively. Conclusion: In ELBW infants 3 common neonatal mornidifies, severe BPD, brain injury and ROP, strongly predicts the risk of poor outcome.

• BMB Reports
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• v.55 no.1
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• pp.11-19
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• 2022

The coronavirus disease 2019 (COVID-19) is an ongoing global pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Patients with severe COVID-19 exhibit hyper-inflammatory responses characterized by excessive activation of myeloid cells, including monocytes, macrophages, and neutrophils, and a plethora of pro-inflammatory cytokines and chemokines. Accumulating evidence also indicates that hyper-inflammation is a driving factor for severe progression of the disease, which has prompted the development of anti-inflammatory therapies for the treatment of patients with COVID-19. Corticosteroids, IL-6R inhibitors, and JAK inhibitors have demonstrated promising results in treating patients with severe disease. In addition, diverse forms of exosomes that exert anti-inflammatory functions have been tested experimentally for the treatment of COVID-19. Here, we briefly describe the immunological mechanisms of the hyper-inflammatory responses in patients with severe COVID-19. We also summarize current anti-inflammatory therapies for the treatment of severe COVID-19 and novel exosome-based therapeutics that are in experimental stages.

• Tuberculosis and Respiratory Diseases
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• v.87 no.3
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• pp.213-220
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• 2024

The continuously increasing prevalence of severe asthma has imposed an increasing burden worldwide. Despite the emergence of novel therapeutic agents, management of severe asthma remains challenging. Insights garnered from big data may be helpful in the effort to determine the complex nature of severe asthma. In the field of asthma research, a vast amount of big data from various sources, including electronic health records, national claims data, and international cohorts, is now available. However, understanding of the strengths and limitations is required for proper utilization of specific datasets. Use of big data, along with advancements in artificial intelligence techniques, could potentially facilitate the practice of precision medicine in management of severe asthma.

• Journal of The Korean Society of Clinical Toxicology
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• v.17 no.1
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• pp.7-13
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• 2019

Purpose: Owing to the increased agricultural use of the herbicide glufosinate ammonium (GLA), the incidence of GLA poisoning has recently increased. Therefore, we investigated the possible predictive factors associated with severe complications following GLA poisoning. Methods: A retrospective analysis of medical records was conducted based on 76 patients who had visited our regional emergency medical center with GLA poisoning from 2006 to 2017. Severe complications were defined as respiratory failure requiring intubation, systolic blood pressure less than 90 mmHg, Glasgow Coma Scale (GCS) less than 8, and presence of seizure. Results: Age, ingested amount and ingested amount per weight were significantly greater in the severe group (p<0.001). PSS grade 2 or higher was more common in the severe group (p<0.001), and In addition, the APACHE II score was significantly higher in the severe group (p<0.001), as were the SOFA scores (p=0.002). Serum ammonia levels were significantly higher in the severe group (p=0.007), while MDRD-GFR was smaller in the severe group (p=0.002). The spot urine protein levels were significantly higher in the severe group (p=0.005), as was the urine protein to creatinine ratio (p=0.001). Upon multivariate analysis, the amount ingested per weight and PSS grade 2 or higher were identified as significant predictors. Conclusion: Our study showed that MDRD-GFR was significantly lower in the severe group after GLA poisoning. PSS grade 2 or higher and ingested amount per weight may be useful to evaluate the severity of complications after GLA poisoning.

• Nuclear Engineering and Technology
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• v.41 no.5
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• pp.617-648
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• 2009

Under the government supported long-term nuclear R&D program, the severe accident research program at KAERI is directed to investigate unresolved severe accident issues such as core debris coolability, steam explosions, and hydrogen combustion both experimentally and numerically. Extensive studies have been performed to evaluate the in-vessel retention of core debris through external reactor vessel cooling concept for APR1400 as a severe accident management strategy. Additionally, an improvement of the insulator design outside the vessel was investigated. To address steam explosions, a series of experiments using a prototypic material was performed in the TROI facility. Major parameters such as material composition and void fraction as well as the relevant physics affecting the energetics of steam explosions were investigated. For hydrogen control in Korean nuclear power plants, evaluation of the hydrogen concentration and the possibility of deflagration-to-detonation transition occurrence in the containment using three-dimensional analysis code, GASFLOW, were performed. Finally, the integrated severe accident analysis code, MIDAS, has been developed for domestication based on MELCOR. The data transfer scheme using pointers was restructured with the modules and the derived-type direct variables using FORTRAN90. New models were implemented to extend the capability of MIDAS.

• Atmosphere
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• v.27 no.4
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• pp.377-384
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• 2017

The effective management of call centers under special circumstances is critical to improve customer satisfaction. In order to effectively respond to call center counseling demand, this paper aims to identify factors having the greatest impact on the number of Korea Meteorological Administration (KMA) call center counseling. To do so, we propose to combine call center data with severe weather announcement data and investigate how the severe weather announcement affects the number of KMA call center counseling. A time lag analysis is conducted and it is found that the severe weather announcement takes about an hour to be reflected in the number of KMA call center counseling. Based on the result of the time lag analysis, we conduct a comparative analysis according to time and season using the data collected from 1 January 2012, to 29 June 2016. The results show that the number of KMA call center counseling increases at lunchtime and decreases during nighttime, and the average rate of change in call center counseling demand tends to be larger under the severe weather announcement. For the comparative analysis according to the season, there are significant differences in the effect of severe weather announcement on the number of KMA call center counseling in spring, fall and winter.