• Nuclear Engineering and Technology
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• v.51 no.6
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• pp.1540-1553
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• 2019

A nuclear power plant (NPP) is a highly complex system-of-systems as manifested through its internal systems interdependence. The negative impact of such interdependence was demonstrated through the 2011 Fukushima Daiichi nuclear disaster. As such, there is a critical need for new strategies to overcome the limitations of current risk assessment techniques (e.g. the use of static event and fault tree schemes), particularly through simulation of the nonlinear dynamic feedback mechanisms between the different NPP systems/components. As the first and key step towards developing an integrated NPP dynamic probabilistic risk assessment platform that can account for such feedback mechanisms, the current study adopts a system dynamics simulation approach to model the thermal dynamic processes in: the reactor core; the secondary coolant system; and the pressurized water reactor. The reactor core and secondary coolant system parameters used to develop system dynamics models are based on those of the Palo Verde Nuclear Generating Station. These three system dynamics models are subsequently validated, using results from published work, under different system perturbations including the change in reactivity, the steam valve coefficient, the primary coolant flow, and others. Moving forward, the developed system dynamics models can be integrated with other interacting processes within a NPP to form the basis of a dynamic system-level (systemic) risk assessment tool.

• International Journal of Naval Architecture and Ocean Engineering
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• v.11 no.1
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• pp.22-32
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• 2019

On offshore platforms, oil and gas leaks are apt to be the initial events of major accidents that may result in significant loss of life and property damage. To prevent accidents induced by leakage, it is vital to perform a case-specific and accurate risk assessment. This paper presents an integrated method of Ddynamic Qquantitative Rrisk Aassessment (DQRA)-using the Decision Making Trial and Evaluation Laboratory (DEMATEL)-Bayesian Network (BN)-for evaluation of the system vulnerabilities and prediction of the occurrence probabilities of accidents induced by leakage. In the method, three-level indicators are established to identify factors, events, and subsystems that may lead to leakage, fire, and explosion. The critical indicators that directly influence the evolution of risk are identified using DEMATEL. Then, a sequential model is developed to describe the escalation of initial events using an Event Tree (ET), which is converted into a BN to calculate the posterior probabilities of indicators. Using the newly introduced accident precursor data, the failure probabilities of safety barriers and basic factors, and the occurrence probabilities of different consequences can be updated using the BN. The proposed method overcomes the limitations of traditional methods that cannot effectively utilize the operational data of platforms. This work shows trends of accident risks over time and provides useful information for risk control of floating marine platforms.

• Journal of Trauma and Injury
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• v.34 no.4
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• pp.299-304
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• 2021

Atypical hemolytic uremic syndrome (aHUS) is a rare, progressive, life-threatening condition of thrombotic microangiopathy characterized by thrombocytopenia, microangiopathic hemolytic anemia, and renal impairment. The mechanisms underlying aHUS remain unclear. Herein, we present the first case in the literature of aHUS after a traumatic injury. A 55-year-old male visited the emergency department after a traumatic injury caused by a tree limb. Abdominal computed tomography revealed a rectal wall defect with significant air density in the perirectal space and preperitoneum, implying rectal perforation. Due to the absence of intraperitoneal intestinal perforation, we performed diverting sigmoid loop colostomy. An additional intermittent simple repair was performed due to perianal and anal injuries. One day postoperatively, his urine output abruptly decreased and serum creatinine level increased. His platelet level decreased, and a spiking fever occurred after 2 days. The patient was diagnosed with acute renal failure secondary to aHUS and was treated with fresh frozen plasma replacement. Continuous renal replacement therapy (CRRT) was also started for oliguria and uremic symptoms. The patient received CRRT for 3 days and intermittent hemodialysis thereafter. After hemodialysis and subsequent supportive treatment, his urine output and renal function improved. The hemolytic anemia and thrombocytopenia also gradually improved. Dialysis was terminated on day 22 of admission and the patient was discharged after recovery. This case suggests that that a traumatic event can trigger aHUS, which should be considered in patients who have thrombocytopenia and acute renal failure with microangiopathic hemolytic anemia. Early diagnosis and appropriate management are critical for favorable outcomes.

• Journal of the Korea Society of Computer and Information
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• v.27 no.3
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• pp.1-12
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• 2022

In the event of a maritime distress accident, rapid search and rescue operations using rescue assets are very important to ensure the safety and life of drowning person's at sea. In this paper, we analyzed the surface layer current in the northwest sea area of Ulleungdo by applying machine learning such as multiple linear regression, decision tree, support vector machine, vector autoregression, and LSTM to the meteorological information collected from the maritime observation buoy. And we predicted the drowning person's route at sea based on the predicted current direction and speed information by constructing each prediction model. Comparing the various machine learning models applied in this paper through the performance evaluation measures of MAE and RMSE, the LSTM model is the best. In addition, LSTM model showed superior performance compared to the other models in the view of the difference distance between the actual and predicted movement point of drowning person.

• Journal of the Korea Convergence Society
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• v.12 no.11
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• pp.91-97
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• 2021

This paper uses a data extension technique originally designed for the rule refinement problem to handling incomplete data. This technique is characterized in that each event can have a weight indicating importance, and each variable can be expressed as a probability value. Since the key problem in this paper is to find the probability that is closest to the missing value and replace the missing value with the probability, three different algorithms are used to find the probability for the missing value and then store it in this data structure format. And, after learning to classify each information area with the SVM classification algorithm for evaluation of each probability structure, it compares with the original information and measures how much they match each other. The three algorithms for the imputation probability of the missing value use the same data structure, but have different characteristics in the approach method, so it is expected that it can be used for various purposes depending on the application field.

• Journal of the Korea institute for structural maintenance and inspection
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• v.12 no.3
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• pp.175-182
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• 2008

In this paper, through the study and consideration of the recently prominent monitoring of cable stayed-bridge, practical but reasonable suggested for the evaluation of the probabilistic safety of the bridges using probable measured data from monitoring measurement system. It is shown in the paper that the live load effects can be evaluated using measured data of cable-stayed bridge and this the realistic probabilistic safety of the cable-stayed bridge could be assessed in term of element reliability and system reliability. As a practical method for the evalution of the system reliability of system cable-stayed bridges partial ETA method is uesd, which can find the critical failure path including combined failure modes of cable, deck and pylon. Compared with the conventional safety analysis method, the propsed approach may be considered as the practical method that shows the considerably actual and reasonable results the system redundancy of the structure.

• Journal of Internet of Things and Convergence
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• v.10 no.4
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• pp.27-33
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• 2024

As of 2023, the number of accident victims in the domestic construction industry is 26,829, ranking second only to other businesses (service industries). The accident types of casualties in all industries were falls (29,229 people), followed by falls (14,357 people). Based on the above data, this study attaches sensors to hard hats and insoles to predict fall accidents that frequently occur at construction sites, and proposes smart safety equipment that applies a random forest algorithm based on the data collected through this. The random forest model can determine fall accidents in real time with high accuracy by generating multiple decision trees and combining the predictions of each tree. This model classifies whether a worker has had a fall accident and the type of behavior through data collected from the MPU-6050 sensor attached to the hard hat. Fall accidents that are primarily determined from hard hats are secondarily predicted through sensors attached to the insole, thereby increasing prediction accuracy. It is expected that this will enable rapid response in the event of an accident, thereby reducing worker deaths and accidents.

• 한국균학회소식:학술대회논문집
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• 2014.05a
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• pp.27-28
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• 2014

Beauveria bassiana (Cordycipitaceae, Hypocreales, Ascomycota) is an anamorphic fungus having a potential to be used as a biological control agent because it parasitizes a wide range of arthropod hosts including termites, aphids, beetles and many other insects. A number of bioactive secondary metabolites (SMs) have been isolated from B. bassiana and functionally verified. Among them, beauvericin and bassianolide are cyclic depsipeptides with antibiotic and insecticidal effects belonging to the enniatin family. Non-ribosomal peptide synthetases (NRPSs) play a crucial role in the synthesis of these secondary metabolites. NRPSs are modularly organized multienzyme complexes in which each module is responsible for the elongation of proteinogenic and non-protein amino acids, as well as carboxyl and hydroxyacids. A minimum of three domains are necessary for one NRPS elongation module: an adenylation (A) domain for substrate recognition and activation; a tholation (T) domain that tethers the growing peptide chain and the incoming aminoacyl unit; and a condensation (C) domain to catalyze peptide bond formation. Some of the optional domains include epimerization (E), heterocyclization (Cy) and oxidation (Ox) domains, which may modify the enzyme-bound precursors or intermediates. In the present study, we analyzed genomes of B. bassiana and its allied species in Hypocreales to verify the distribution of NRPS-encoding genes involving biosynthesis of beauvericin and bassianolide, and to unveil the evolutionary processes of the gene clusters. Initially, we retrieved completely or partially assembled genomic sequences of fungal species belonging to Hypocreales from public databases. SM biosynthesizing genes were predicted from the selected genomes using antiSMASH program. Adenylation (A) domains were extracted from the predicted NRPS, NRPS-like and NRPS-PKS hybrid genes, and used them to construct a phylogenetic tree. Based on the preliminary results of SM biosynthetic gene prediction in B. bassiana, we analyzed the conserved gene orders of beauvericin and bassianolide biosynthetic gene clusters among the hypocrealean fungi. Reciprocal best blast hit (RBH) approach was performed to identify the regions orthologous to the biosynthetic gene cluster in the selected fungal genomes. A clear recombination pattern was recognized in the inferred A-domain tree in which A-domains in the 1st and 2nd modules of beauvericin and bassianolide synthetases were grouped in CYCLO and EAS clades, respectively, suggesting that two modules of each synthetase have evolved independently. In addition, inferred topologies were congruent with the species phylogeny of Cordycipitaceae, indicating that the gene fusion event have occurred before the species divergence. Beauvericin and bassianolide synthetases turned out to possess identical domain organization as C-A-T-C-A-NM-T-T-C. We also predicted precursors of beauvericin and bassianolide synthetases based on the extracted signature residues in A-domain core motifs. The result showed that the A-domains in the 1st module of both synthetases select D-2-hydroxyisovalerate (D-Hiv), while A-domains in the 2nd modules specifically activate L-phenylalanine (Phe) in beauvericin synthetase and leucine (Leu) in bassianolide synthetase. antiSMASH ver. 2.0 predicted 15 genes in the beauvericin biosynthetic gene cluster of the B. bassiana genome dispersed across a total length of approximately 50kb. The beauvericin biosynthetic gene cluster contains beauvericin synthetase as well as kivr gene encoding NADPH-dependent ketoisovalerate reductase which is necessary to convert 2-ketoisovalarate to D-Hiv and a gene encoding a putative Gal4-like transcriptional regulator. Our syntenic comparison showed that species in Cordycipitaceae have almost conserved beauvericin biosynthetic gene cluster although the gene order and direction were sometimes variable. It is intriguing that there is no region orthologous to beauvericin synthetase gene in Cordyceps militaris genome. It is likely that beauvericin synthetase was present in common ancestor of Cordycipitaceae but selective gene loss has occurred in several species including C. militaris. Putative bassianolide biosynthetic gene cluster consisted of 16 genes including bassianolide synthetase, cytochrome P450 monooxygenase, and putative Gal4-like transcriptional regulator genes. Our synteny analysis found that only B. bassiana possessed a bassianolide synthetase gene among the studied fungi. This result is consistent with the groupings in A-domain tree in which bassianolide synthetase gene found in B. bassiana was not grouped with NRPS genes predicted in other species. We hypothesized that bassianolide biosynthesizing cluster genes in B. bassiana are possibly acquired by horizontal gene transfer (HGT) from distantly related fungi. The present study showed that B. bassiana is the only species capable of producing both beauvericin and bassianolide. This property led to B. bassiana infect multiple hosts and to be a potential biological control agent against agricultural pests.

• Journal of Korean Society of Environmental Engineers
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• v.33 no.6
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• pp.439-446
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• 2011

In this research, enhanced land-cover classification methods using high-resolution satellite image (HRSI) and GIS in terms of practicality and accuracy was proposed. It aims for understanding non-point pollutant origin/loading, assessment the efficiency of rainfall storage/infiltration facilities and sounds water-environment management. The result of applying enhanced land-cover classification methods to the urban region verifies that roof and road area are including various vegetations such as roof garden, flower bed in the median strip and street tree. This accounts for 3% of total study area, and more importantly it was counted as impervious area by GIS alone or conventional indoor work. The feasibility of the method was assessed by applying to rainfall-runoff analysis for three weak rainfall in the range of 7.1-10.5 mm events in 2000, Chiba, Japan. A good agreement between simulated and observed runoff hydrograph was obtained. In comparison, the hydrograph simulated with land-use parameters by the detailed land-use information of 10m grid had an error between 31%~71%, while enhanced method showed 4% to 29%, and showed the improvement particularly for reproducing observed peak and recession flow rate of hydrograph in weak rainfall condition.

• Journal of the Korean Institute of Gas
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• v.20 no.5
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• pp.9-16
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• 2016

Buried pipe system is subject to leak or rupture due to internal and external defects with age. Especially, if the pipeline is designed for pressurized gas, the leak can wreak a devastating on its surrounding area. The current method of setting up underground gas pipeline is based on OGP criteria of applying one tenth of the inner pipe pressure. The criteria is applied irrespective of their burial depth or pipe's properties. At times, even the whole safety measures are totally ignored. Considering the magnitude of possible damage from a gas leakage, a precise analytical tool for the risk assessment is urgently needed. The study was conducted to assess possible scenarios of gas accidents and to develop a computer model to minimize the damage. The data from ETA was analyzed intensively, and the model was developed. The model is capable of predicting jet fire influence area with comprehensive input parameters, such as burial depth. The model was calibrated and verified by the historic accident data from Edison Township, New Jersey, the United States. The statistical model was also developed to compare the results of the model in this study and the existing OGP model. They were in good agreement with respect to damage predictions, such as radiation heat coming from 10 meters away from the heat source of gas flame.