• Proceedings of the SAREK Conference
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• 2007.11a
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• pp.466-473
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• 2007

The comparison for the performance of heating systems, district heating and separate heating and power, is carried out in terms of energy consumption and environment on the basis of real operating data. The efficiency of boiler and the heat loss within the housing are assumed with reasonable manner due to the lack of reliable data regarding those quantities. The assessment for the established criteria of previous studies is performed and the new criteria for the analysis is proposed. It is shown that the district heating system is superior to the separate heating and power system from the point of view of reduction of energy use and environment improvement. The sensitivity study for those quantities with uncertainty such as the boiler efficiency and heat loss within the housing is carried out also and the reasons for the analysis results are discussed in detail.

• International Journal of Ocean System Engineering
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• v.3 no.2
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• pp.50-60
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• 2013

This paper presents a novel approach to the design of an adaptive fuzzy sliding mode controller for depth control of an autonomous underwater vehicle (AUV). So far, AUV's dynamics are highly nonlinear and the hydrodynamic coefficients of the vehicles are difficult to estimate, because of the variations of these coefficients with different operating conditions. These kinds of difficulties cause modeling inaccuracies of AUV's dynamics. Hence, we propose an adaptive fuzzy sliding mode control with novel fuzzy adaptation technique for regulating vertical positioning in presence of parametric uncertainty and disturbances. In this approach, two fuzzy approximator are employed in such a way that slope of the linear sliding surface is updated by first fuzzy approximator, to shape tracking error dynamics in the sliding regime, while second fuzzy approximator change the supports of the output fuzzy membership function in the defuzzification inference module of fuzzy sliding mode control (FSMC) algorithm. Simulation results shows that, the reaching time and tracking error in the approaching phase can be significantly reduced with chattering problem can also be eliminated. The effectiveness of proposed control strategy and its advantages are indicated in comparison with conventional sliding mode control FSMC technique.

• Journal of Korean Institute of Industrial Engineers
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• v.39 no.6
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• pp.577-586
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• 2013

In a shipyard, it is hard to predict block movement due to the uncertainty caused during the long period of shipbuilding operations. For this reason, block movement is rarely scheduled, while main operations such as assembly, outfitting and painting are scheduled properly. Nonetheless, the high operating costs of block movement compel task managers to attempt its management. To resolve this dilemma, this paper proposes a new block movement analysis framework consisting of the following operations: understanding the entire process, log clustering to obtain manageable processes, discovering the process model and detecting exceptional processes. The proposed framework applies fuzzy mining and trace clustering among the process mining technologies to find main process and define process models easily. We also propose additional methodologies including adjustment of the semantic expression level for process instances to obtain an interpretable process model, definition of each cluster's process model, detection of exceptional processes, and others. The effectiveness of the proposed framework was verified in a case study using real-world event logs generated from the Block Process Monitoring System (BPMS).

• Nuclear Engineering and Technology
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• v.48 no.6
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• pp.1412-1422
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• 2016

Austenitic stainless steels (ASSs) are widely used for nuclear pipes as they exhibit a good combination of mechanical properties and corrosion resistance. However, high tensile residual stresses may occur in ASS welds because postweld heat treatment is not generally conducted in order to avoid sensitization, which causes a stress corrosion crack. In this study, round robin analyses on stress intensity factors (SIFs) were carried out to examine the appropriateness of structural integrity assessment methods for ASS pipe welds with two types of circumferential cracks. Typical stress profiles were generated from finite element analyses by considering residual stresses and normal operating conditions. Then, SIFs of cracked ASS pipes were determined by analytical equations represented in fitness-for-service assessment codes as well as reference finite element analyses. The discrepancies of estimated SIFs among round robin participants were confirmed due to different assessment procedures and relevant considerations, as well as the mistakes of participants. The effects of uncertainty factors on SIFs were deducted from sensitivity analyses and, based on the similarity and conservatism compared with detailed finite element analysis results, the R6 code, taking into account the applied internal pressure and combination of stress components, was recommended as the optimum procedure for SIF estimation.

• Journal of the Korean Solar Energy Society
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• v.40 no.3
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• pp.1-20
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• 2020

In accordance with the Government's policy, renewable power generation is expanding very largely. This leads to increasing uncertainty in the power market and power system owing to the intermittent and fluctuating output characteristics of renewable power generators. Data on the acquisition of renewable power generators can be largely classified according to the operation of the power market and power system. Data on the settlement for the payment for the power amount are acquired in the power market, and real-time data for monitoring the status and output of the generators are acquired in the power system. However, renewable power generators operating in the power market have different acquisition cycles depending on the method of communication of the power meter. They acquire data only for settlement purposes and have no real-time data, which requires improvement. In this paper, the acquisition status is reviewed by classifying the data of renewable power generators into settlement and real-time data. In addition, measures and acquisition criteria for real-time data of renewable power generators for improving the acquisition method are proposed.

• Food Science of Animal Resources
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• v.41 no.5
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• pp.816-825
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• 2021

This study aims to validate a fast method of simultaneous analysis of 365 LCamenable and 142 GC-amenable pesticides in hen eggs by liquid chromatography-tandem mass spectrometry (LC-MS/MS) and gas chromatography-tandem mass spectrometry (GC-MS/MS), respectively, operating in multiple reaction monitoring (MRM) acquisition modes. The sample preparation was based on quick, easy, cheap, effective, rugged, and safe (QuEChERS) extraction. Key method performance parameters investigated were specificity, linearity, limit of quantification (LOQ), accuracy, precision and measurement uncertainty. The method was validated at two spiking levels (10 and 50 ㎍/kg), and good recoveries (70%-120%) and relative standard deviations (RSDs) (≤20) were achieved for 92.9% of LC-amenable and 86.6% of GC-amenable pesticide residues. The LOQs were ≤10 ㎍/kg for 94.2% of LC-amenable and 92.3% of GC-amenable pesticides. The validated method was further applied to 100 egg samples from caged hens, and none of the pesticides was quantified.

• Journal of Korea Society of Digital Industry and Information Management
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• v.18 no.2
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• pp.61-75
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• 2022

The purpose of this study is to analyze the impact of quality management system requirements, a management innovation technique, on business performance to secure the competitiveness of SMEs in an environment of increasing uncertainty in the global economy and intensifying competition. To this end, a survey was conducted on small and medium-sized enterprises (SMEs) operating a quality management system, and statistical analysis was performed through validity and reliability analysis, regression analysis, and group analysis using IBM SPSS 26.0. As a result of the study, it was found that planning, operation, support, and improvement, which are the core requirements of a quality management system, have a positive effect on business performance. In addition, through group analysis, it was found that the effect of quality management system requirements on business performance varies according to the level of the company. This means that the importance of quality management requirements required for strategy establishment varies according to the quality management introduction level of small and medium-sized manufacturers, and it can be used for small and medium-sized manufacturers to set strategic directions.

• Journal of the Korean Society of Safety
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• v.38 no.1
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• pp.87-92
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• 2023

The number of unmanned light rail train operators is continuously increasing in Korea. In a failure event during an operation due to the nature of the unmanned operation, recovery is performed based on the remote control. However, if remote recovery is not feasible, safety personnel arrive at the train to resume the train operation. There are regulations on safety personnel and the suspension time of the train operation. However, there is currently no rule for safety personnel deployment. Currently, railway operating organizations operate in three scenarios: safety personnel on board trains, stationed at stations, and deployed at major stations. Four major factors influence the downtime for each emergency response scenario. However, these four influencing factors vary too much to predict results with simple calculations. In this study, four influencing factors were considered as random variables with high uncertainty. In addition, the Monte Carlo method was applied to each scenario for the safety personnel deployment to predict train service downtime. This study found a 17% difference in train service suspension by safety personnel deployment scenario. The results of this study can be used in setting service goals, such as standards for future safety personnel placement and frequency of service interruptions.

• Nuclear Engineering and Technology
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• v.55 no.1
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• pp.238-247
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• 2023

The present work represents a technical guideline for decommissioning a disused teletherapy machine model Theratron-780 and contains category one ⁶⁰Co radioactive source. The first section predicts the dose rate from the source in case of normal and radiological emergency situations via FLUKA-MC simulation code. Moreover, the dose assessment for the occupational during the whole process is calculated and compared to the measured values. A suggested cordoned area for safety and security in a radiological emergency is simulated. The second section lists the whole process's technical procedures, including (preview, dismantle, securing, transport and storage) of the disused teletherapy machine. Results show that the maximum obtained accumulated dose for occupational were found to be 24.5 ± 4.9 μSv in the dismantle and securing process in addition to 3.5 ± 1.8 μSv during loading on the transport vehicle and unloading at the storage facility. It was found that the measured accumulated dose for workers is in good agreement with the estimated one by uncertainty not exceeding 5% in normal operating conditions.

• Nuclear Engineering and Technology
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• v.55 no.3
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• pp.814-826
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• 2023

Sensor faults in nuclear power plant instrumentation have the potential to spread negative effects from wrong signals that can cause an accident misdiagnosis by plant operators. To detect sensor faults and make accurate accident diagnoses, prior studies have developed a supervised learning-based sensor fault detection model and an accident diagnosis model with faulty sensor isolation. Even though the developed neural network models demonstrated satisfactory performance, their diagnosis performance should be reevaluated considering real-time connection. When operating in real-time, the diagnosis model is expected to indiscriminately accept fault data before receiving delayed fault information transferred from the previous fault detection model. The uncertainty of neural networks can also have a significant impact following the sensor fault features. In the present work, a pilot study was conducted to connect two models and observe actual outcomes from a real-time application with an integrated system. While the initial results showed an overall successful diagnosis, some issues were observed. To recover the diagnosis performance degradations, additive logics were applied to minimize the diagnosis failures that were not observed in the previous validations of the separate models. The results of a case study were then analyzed in terms of the real-time diagnosis outputs that plant operators would actually face in an emergency situation.