• Nuclear Engineering and Technology
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• 제53권10호
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• pp.3275-3285
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• 2021

A Nuclear Power Plant (NPP) is a complex dynamic system-of-systems with highly nonlinear behaviors. In order to control the plant operation under both normal and abnormal conditions, the different systems in NPPs (e.g., the reactor core components, primary and secondary coolant systems) are usually monitored continuously, resulting in very large amounts of data. This situation makes it possible to integrate relevant qualitative and quantitative knowledge with artificial intelligence techniques to provide faster and more accurate behavior predictions, leading to more rapid decisions, based on actual NPP operation data. Data-driven models (DDM) rely on artificial intelligence to learn autonomously based on patterns in data, and they represent alternatives to physics-based models that typically require significant computational resources and might not fully represent the actual operation conditions of an NPP. In this study, a feed-forward backpropagation artificial neural network (ANN) model was trained to simulate the interaction between the reactor core and the primary and secondary coolant systems in a pressurized water reactor. The transients used for model training included perturbations in reactivity, steam valve coefficient, reactor core inlet temperature, and steam generator inlet temperature. Uncertainties of the plant physical parameters and operating conditions were also incorporated in these transients. Eight training functions were adopted during the training stage to develop the most efficient network. The developed ANN model predictions were subsequently tested successfully considering different new transients. Overall, through prompt prediction of NPP behavior under different transients, the study aims at demonstrating the potential of artificial intelligence to empower rapid emergency response planning and risk mitigation strategies.

• Wind and Structures
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• 제23권5호
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• pp.449-464
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• 2016

Catastrophe models appraise the natural risk of the built-infrastructure simulating the interaction of its exposure and vulnerability with a hazard. Because of unique configurations and reduced number, mid/high-rise buildings present singular challenges to the assessment of their damage vulnerability. This paper presents a novel approach to estimate the vulnerability of mid/high-rise buildings (MHB) which is used in the Florida Public Hurricane Loss Model, a catastrophe model developed for the state of Florida. The MHB vulnerability approach considers the wind pressure hazard exerted over the building's height as well as accompanying rain. The approach assesses separately the damages caused by wind, debris impact, and water intrusion on building models discretized into typical apartment units. Hurricane-induced water intrusion is predicted combining the estimates of impinging rain with breach and pre-existing building defect size estimates. Damage is aggregated apartment-by-apartment and story-by-story, and accounts for vertical water propagation. The approach enables the vulnerability modeling of regular and complex building geometries in the Florida exposure and elsewhere.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제10권9호
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• pp.4367-4385
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• 2016

With millions of people across the globe suffering from Parkinson's disease (PD), an objective, confirmatory test for the same is yet to be developed. This research aims to develop a system which can assist the doctor in objectively saying whether the patient is normal or under risk of PD. The proposed work combines the eye-hand co-ordination behaviour with the DaTscan images in order to determine the risk of this disorder. Initially, eye-hand coordination level of the patient is assessed through a hardware module. Then, the DaTscan image is analysed and used to extract certain geometrical parameters which shall indicate the presence of PD. These parameters are then finally fed into a Multi-Layer Perceptron Neural Network using Levenberg-Marquardt (LM) Back propagation training algorithm. Experimental results indicate that the proposed system exhibits an accuracy of around 93%.

• 한국건축시공학회:학술대회논문집
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• 한국건축시공학회 2018년도 춘계 학술논문 발표대회
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• pp.45-46
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• 2018

The fire at the pilotis parking lot shows the fire propagation paths that are propagated to the ceiling materials and insulation materials and propagated through the external walls. In addition, there is a high risk of fire caused by vehicles with high combustion loads spreading throughout the parking lot. In particular, the omission of the ceiling materials at the parking lot in recent fire cases has contributed to the spread of the fire. In this study, the combustion performance of the ceiling materials between the insulation material and the vehicle is considered to prevent fire from spreading. Based on field research, the type of ceiling material used in the piloti structure showed that SMC ceiling materials have the highest percentage. Combustion performance test (KS F ISO 5660-1) was carried out on the SMC ceiling materials and the AL ceiling materials to review the fire safety of the ceiling finish based on the field investigation. The results of the test showed that the SMC ceiling materials has a THR 28.973[MJ/㎡] and peek HRR 273.93 [kW/㎡], while the AL ceiling material has a THR 0.584[MJ/㎡] and peek HRR 15.215[kW/㎡].

• Journal of Microbiology and Biotechnology
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• 제30권7호
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• pp.974-981
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• 2020

Sequence type 410 (ST410) of Escherichia coli is an extraintestinal pathogen associated with multi drug resistance. In this study, we aimed to investigate the horizontal propagation pathway of a high-risk clone of E. coli ST410 that produces Klebsiella pneumoniae carbapenemase (KPC). blaKPC-encoding E. coli and K. pneumoniae isolates were evaluated, and complete sequencing and comparative analysis of blaKPC-encoding plasmids from E. coli and K. pneumoniae, antimicrobial susceptibility tests, polymerase chain reaction, multilocus sequence typing, and conjugal transfer of plasmids were performed. Whole-genome sequencing was performed for plasmids mediating KPC-2 production in E. coli and K. pneumoniae clinical isolates. Strains E. coli CPEc171209 and K. pneumoniae CPKp171210 were identified as ST410 and ST307, respectively. CPEc171209 harbored five plasmids belonging to serotype O8:H21, which is in the antimicrobial-resistant clade C4/H24. The CPKp171210 isolate harbored three plasmids. Both strains harbored various additional antimicrobial resistance genes. The IncX3 plasmid pECBHS_9_5 harbored blaKPC-2 within a truncated Tn4401a transposon, which also contains blaSHV-182 with duplicated conjugative elements. This plasmid displayed 100% identity with the IncX3 plasmid pKPBHS_10_3 from the K. pneumoniae CPKp171210 ST307 strain. The genes responsible for the conjugal transfer of the IncX3 plasmid included tra/trb clusters and pil genes coding the type IV pilus. ST410 can be transmitted between patients, posing an elevated risk in clinical settings. The emergence of a KPC-producing E. coli strain (ST410) is concerning because the blaKPC-2-bearing plasmids may carry treatment resistance across species barriers. Transgenic translocation occurs among carbapenem-resistant bacteria, which may spread rapidly via horizontal migration.

• 한국안전학회지
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• 제17권3호
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• pp.81-89
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• 2002

The runaway reaction was analyzed experimently and theoretically at the batch styrene suspension polymerization process. In the experiments, the reaction temperature with time was measured at various experimental conditions. According to the experimental results, the risk of the runaway reaction was increased with increasing the ratio of the monomer(styrene, M) to the dispersion medium(water, W), the concentration of the initiator(BPO), and the monomer mass, respectively. And simulation results showed that the runaway reaction was significantly affected by the reaction rate constant of the propagation and that the phenomena of the runaway reaction occurred at about 70% conversion. Also, we found that the runaway reaction did not occur under the operating condition of below 0.5 for M/W, approximate 3 wt% BPO, and below 75$^{\circ}C$ for the cooling temperature.

• 한국군사과학기술학회지
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• 제14권5호
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• pp.805-811
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• 2011

Aircraft MLG and wing structures have been recognized as fatigue critical structures and exposed to the risk of fatigue crack initiation and propagation. Furthermore, these structures are frequently subjected to serious dynamic loading condition during a Hard Landing which may lead to their failure. Especially, structural integrity of MLG and wing components is decreased as the flight time increased because of the fatigue damage accumulated on the aircraft. In this study, the effects of Hard Landing on the MLG and wing components of aging aircraft were evaluated by using numerical approach. To achieve the aim, a finite element model has been developed and simulations were conducted by varying the landing conditions. As a result, it was revealed that the high stress concentration phenomenon was occurred at the lower Side Brace of MLG. Thereby, the intensified inspection for the lower Side Brace should be considered to prevent unexpected aircraft mishap.

• Smart Structures and Systems
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• 제6권2호
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• pp.147-165
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• 2010

Impact damage detection in composite structures has gained a considerable interest in many engineering areas. The capability to detect damage at the early stages reduces any risk of catastrophic failure. This paper compares two advanced signal processing methods for impact location in composite aircraft structures. The first method is based on a modified triangulation procedure and Genetic Algorithms whereas the second technique applies Artificial Neural Networks. A series of impacts is performed experimentally on a composite aircraft wing-box structure instrumented with low-profile, bonded piezoceramic sensors. The strain data are used for learning in the Neural Network approach. The triangulation procedure utilises the same data to establish impact velocities for various angles of strain wave propagation. The study demonstrates that both approaches are capable of good impact location estimates in this complex structure.

• 한국콘텐츠학회:학술대회논문집
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• 한국콘텐츠학회 2015년도 춘계 종합학술대회 논문집
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• pp.439-440
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• 2015

There has been a big need of Safety Education for the power plants with a high risk due to the Fukushima Daiichi nuclear disaster and the tragic accident of Sewol Ferry. The object of this research is for studying ways of developing contents for customized Power Plants Safety Education applied with 'Story Viewing' technology in order to improve the present format of Power Plant Safety Education based on hard copied documents so as to prevent human mistakes because of lack of system and ability of initial response which come from safety frigidity shown in the case of Sewol Accident. 'Story-viewing' applied to Power Plant Safety Education is the methodology to enhance information communicability utilizing IT/Visualization technology combined with Story Telling that is an effective propagation way.

• 한국철도학회논문집
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• 제10권2호
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• pp.131-136
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• 2007

In this paper, the methodology to predict the number of deaths and possible fire propagation scenarios will be described in case of fire on a train in a tunnel. We use a probabilistic analysis method for the evaluation of possibility for each scenario and the deaths tolls are calculated with the help of the passenger evacuation simulation program. The resulting safety of passengers is displayed on a F/N graph, which could be used in part as a guideline to predict the safety level of the tunnel in fire.