• Journal of the Korean Society of Systems Engineering
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• v.19 no.2
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• pp.32-45
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• 2023

Implementing Severe Accident Management (SAM) strategies is crucial for enhancing a nuclear power plant's resilience and safety against severe accidents conditions represented in the analysis of Station Blackout (SBO) event. Among these critical approaches, the In-Vessel Retention (IVR) through External Reactor Vessel Cooling (IVR-ERVC) strategy plays a key role in preventing vessel failure. This work is designed to evaluate the efficacy of the IVR strategy for a high-power density reactor APR1400. The APR1400's plant is represented and simulated under steady-state and transient conditions for a station blackout (SBO) accident scenario using the computer code, ASYST. The APR1400's thermal-hydraulic response is analyzed to assess its performance as it progresses toward a severe accident scenario during an extended SBO. The effectiveness of emergency operating procedures (EOPs) and severe accident management guidelines (SAMGs) are systematically examined to assess their ability to mitigate the accident. A group of associated key phenomena selected based on Phenomenon Identification and Ranking Tables (PIRT) and uncertain parameters are identified accordingly and then propagated within DAKOTA Uncertainty Quantification (UQ) framework until a statistically representative sample is obtained and hence determine the uncertainty bands of key system parameters. The Systems Engineering methodology is applied to direct the progression of work, ensuring systematic and efficient execution.

• Tunnel and Underground Space
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• v.17 no.4
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• pp.285-294
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• 2007

Material properties of geomaterials are usually heterogeneous. And the limitted number of investigation for the subsurface material properties in terms of boreholes are not sufficient enough for identifying the heterogeneity. In most civil engineering work, pre-investigation results can be different from those by in-situ inspection during the construction work. With these points of view, a new analysis concept aiming to evaluate the uncertainty resulted from the heterogeneity of the geomaterial properties as well as to enhance a construction workability and design qualify by a prompt feedback of in-situ conditions was proposed. It was accomplished by linking the Element Free analysis and pre-developed stochastic methods represented by Karhunen-Loeve expansion. Simple ID problem was solved by the developed method, and its validity as well as the characteristic results by different stochastic methods were clarified.

• Journal of Radiation Protection and Research
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• v.36 no.1
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• pp.16-23
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• 2011

Accurate measurement of uranium enrichment is very important in nuclear material accountability. The analysis uncertainty of the uranium enrichment measurement with gamma-ray analysis was studied in the present work. FRAM (Fixed energy Response function Analysis with Multiple efficiencies) code was used to determine the uranium enrichment. If the shield materials were placed between the detector and the sample, the error was measured and analyzed. Measurement time was varied and the dependency of the analysis uncertainty on the measurement time was studied. Transmitted gamma-ray intensities and FWHMs of the peaks in the energy spectrum were measured as the shield thickness was varied. The transmitted gamma-ray intensity follows shape of the exponential function, and the FWHM was almost independent of the shield thickness. The uncertainty of FRAM analysis was studied when the thick shield material was placed between the detector and the sample. Our work could be helpful in analysis of the fissile material in uranium sample.

• Journal of the Korean Society for Precision Engineering
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• v.24 no.9
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• pp.68-75
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• 2007

The pitch and orthogonality of two-dimensional (2D) gratings have been measured by using a metrological atomic force microscope (MAFM) and measurement uncertainty has been analyzed. Gratings are typical standard artifacts for the calibration of precision microscopes. Since the magnification and orthogonality in two perpendicular axes of microscopes can be calibrated simultaneously using 2D gratings, it is important to certify the pitch and orthogonality of 2D gratings accurately for nano-metrology using precision microscopes. In the measurement of 2D gratings, the MAFM can be used effectively for its nanometric resolution and uncertainty, but a new measurement scheme was required to overcome some limitations of current MAFM such as nonnegligible thermal drift and slow scan speed. Two kinds of 2D gratings, each with the nominal pitch of 300 nm and 1000 nm, were measured using line scans for the pitch measurement of each direction. The expanded uncertainties (k = 2) of measured pitch values were less than 0.2 nm and 0.4 nm for each specimen, and those of measured orthogonality were less than 0.09 degree and 0.05 degree respectively. The experimental results measured using the MAFM and optical diffractometer were coincident with each other within the expanded uncertainty of the MAFM. As a future work, we also proposed another scheme for the measurements of 2D gratings to increase the accuracy of calculated peak positions.

• Korean Journal of Optics and Photonics
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• v.20 no.2
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• pp.110-117
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• 2009

This work introduces the uncertainty evaluation formulation on color measurement of light sources and display devices, such as CIE 1931 (x, y) chromaticity, CIE 1960 (u, v) chromaticity, correlated color temperature, and distribution temperature. All the mentioned quantities are reduced from spectral data in the visible range, for which uncertainties are strongly correlated between different wavelengths. Using matrix algebra we have formulated the uncertainty propagation from the SI- traceable spectral irradiance standard to the individual color related measurement quantities taking the correlation between wavelengths into account. As a result, we have demonstrated uncertainty evaluation examples of 3 types of light sources: CIE illuminant A, LED white light, and LCD white light. This method can be applied to any other quantities based on spectral measurement such as solar irradiance, material color measurement, etc.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.23 no.12
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• pp.1406-1411
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• 2012

An energy detection based spectrum sensing has been found to be vulnerable to the noise power uncertainty. A cooperative spectrum sensing with an energy detector has appeared as one of the solutions to alleviate this difficulty. However, its performance analysis in a fading environment has not been reported yet in the literature. Motivated by this, this paper presents the performance analysis of the scheme by extending our previous work on evaluating the performance of an energy detector in the presence of noise power uncertainty. The analysis shows that the false alarm probability and detection probability gets higher as the sensing time and/or the number of the secondary users in the OR based cooperative spectrum sensing scheme increase when the noise power uncertainty exists.

• Computers and Concrete
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• v.23 no.6
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• pp.433-444
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• 2019

As rice husk ash (RHA) is not produced in controlled manufacturing process like cement, its properties vary significantly even within the same lot. In fact, properties of Rice Husk Ash Based Concrete (RHABC) are largely dictated by uncertainty leading to huge deviations from their expected values. This paper proposes a Robust Cost Optimization (RCO) procedure for RHABC, which minimizes such unwanted deviation due to uncertainty and provides guarantee of achieving desired strength and workability with least possible cost. The RCO simultaneously minimizes cost of RHABC production and its deviation considering feasibility of attaining desired strength and workability in presence of uncertainty. RHA related properties have been modeled as uncertain-but-bounded type as associated probability density function is not available. Metamodeling technique is adopted in this work for generating explicit expressions of constraint functions required for formulation of RCO. In doing so, the Moving Least Squares Method is explored in place of conventional Least Square Method (LSM) to ensure accuracy of the RCO. The efficiency by the proposed MLSM based RCO is validated by experimental studies. The error by the LSM and accuracy by the MLSM predictions are clearly envisaged from the test results. The experimental results show good agreement with the proposed MLSM based RCO predicted mix properties. The present RCO procedure yields RHABC mixes which is almost insensitive to uncertainty (i.e., robust solution) with nominal deviation from experimental mean values. At the same time, desired reliability of satisfying the constraints is achieved with marginal increment in cost.

• Nuclear Engineering and Technology
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• v.55 no.9
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• pp.3423-3440
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• 2023

In this work, a multivariate time-series machine learning meta-model is developed to predict the transient response of a typical nuclear power plant (NPP) undergoing a steam generator tube rupture (SGTR). The model employs Recurrent Neural Networks (RNNs), including the Long Short-Term Memory (LSTM), Gated Recurrent Unit (GRU), and a hybrid CNN-LSTM model. To address the uncertainty inherent in such predictions, a Bayesian Neural Network (BNN) was implemented. The models were trained using a database generated by the Best Estimate Plus Uncertainty (BEPU) methodology; coupling the thermal hydraulics code, RELAP5/SCDAP/MOD3.4 to the statistical tool, DAKOTA, to predict the variation in system response under various operational and phenomenological uncertainties. The RNN models successfully captures the underlying characteristics of the data with reasonable accuracy, and the BNN-LSTM approach offers an additional layer of insight into the level of uncertainty associated with the predictions. The results demonstrate that LSTM outperforms GRU, while the hybrid CNN-LSTM model is computationally the most efficient. This study aims to gain a better understanding of the capabilities and limitations of machine learning models in the context of nuclear safety. By expanding the application of ML models to more severe accident scenarios, where operators are under extreme stress and prone to errors, ML models can provide valuable support and act as expert systems to assist in decision-making while minimizing the chances of human error.

• The Journal of the Korea institute of electronic communication sciences
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• v.19 no.1
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• pp.241-248
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• 2024

Socially, organizations are required to effectively manage their information resources, both in terms of acquiring information from external sources and safeguarding against potential breaches by insiders. While information security policies and technologies implemented by organizations contribute to achieving internal security, an overly complex or disorganized security structure can create uncertainty among employees. In this study, we identify factors of structural information security (IS)-related uncertainty within organizations and propose that they contribute to non-compliance. We develop a research model and hypotheses based on previous studies on the information security environment and test these hypotheses using structural equation modeling. Our findings indicate that uncertainties related to IS policy, technology, and communication decrease employees' IS role identity and their intention to comply with IS measures. By addressing these uncertainties, organizations can improve their IS environment and work towards achieving there IS goals.

• Korean Journal of Construction Engineering and Management
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• v.2 no.4 s.8
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• pp.48-61
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• 2001

This study aims at improving work reliability. It proposes a way to overcome the limitations of current scheduling methods by providing a new framework, CPAM(Construction Process Analysis Model) based on the lean principles. It suggests methods which improve work reliability and production effectiveness with variability control methods. Also it suggests methods which reduce inventories of materials and equipment and WIP(Work In Process) using two techniques; Lookahead Schedule and Weekly Work Plan. The contribution of this research also includes that it assumes planning as a process of reducing uncertainty and maximizing throughput, counter-posing plan reliability to resource redundancy as alternative strategies for managing in conditions of uncertain work flow.