• Nuclear Engineering and Technology
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• v.54 no.1
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• pp.49-60
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• 2022

Motivated by the high-resolution properties of high-order Weighted Essentially Non-Oscillatory (WENO) and flux limiter (FL) for steep-gradient problems and the robust convergence of Jacobian-free Newton-Krylov (JFNK) methods for nonlinear systems, the preconditioned JFNK fully implicit high-order WENO and FL schemes are proposed to solve the transient two-phase two-fluid models. Specially, the second-order fully-implicit BDF2 is used for the temporal operator and then the third-order WENO schemes and various flux limiters can be adopted to discrete the spatial operator. For the sake of the generalization of the finite-difference-based preconditioning acceleration methods and the excellent convergence to solve the complicated and various operational conditions, the random vector instead of the initial condition is skillfully chosen as the solving variables to obtain better sparsity pattern or more positions of non-zero elements in this paper. Finally, the WENO_JFNK and FL_JFNK codes are developed and then the two-phase steep-gradient problem, phase appearance/disappearance problem, U-tube problem and linear advection problem are tested to analyze the convergence, computational cost and efficiency in detailed. Numerical results show that WENO_JFNK and FL_JFNK can significantly reduce numerical diffusion and obtain better solutions than traditional methods. WENO_JFNK gives more stable and accurate solutions than FL_JFNK for the test problems and the proposed finite-difference-based preconditioning acceleration methods based on the random vector can significantly improve the convergence speed and efficiency.

• Nuclear Engineering and Technology
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• v.54 no.6
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• pp.2135-2146
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• 2022

A nuclear energy facility is one of the most critical facilities to be safely protected during and after operation because the physical destruction of its barriers by an external attack could release radioactivity into the environment and can cause harmful effects. The barrier walls of nuclear energy facilities should be sufficiently robust to protect essential facilities from external attack or sabotage. Physical protection system (PPS) vulnerability assessment of a typical small nuclear research reactor was carried out by simulating an external attack with a tri-nitro toluene (TNT) shaped charge and results are presented. The reinforced concrete (RC) barrier wall of the research reactor located at a distance of 50 m from a TNT-shaped charge was the target of external attack. For the purpose of the impact assessment of the RC barrier wall, a finite element method (FEM) is utilized to simulate the destruction condition. The study results showed that a hole-size of diameter 342 mm at the front side and 364 mm at the back side was created on the RC barrier wall as a result of a 143.35 kg TNT-shaped charge. This aperture would be large enough to let at least one person can pass through at a time. For the purpose of the PPS vulnerability assessment, an Estimate of Adversary Sequence Interruption (EASI) model was used, which enabled the determination of most vulnerable path to the target with a probability of interruption equal to 0.43. The study showed that the RC barrier wall is vulnerable to a TNT-shaped charge impact, which could in turn reduce the effectiveness of the PPS.

• Nuclear Engineering and Technology
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• v.54 no.6
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• pp.2107-2119
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• 2022

Accurate remaining useful life (RUL) prediction for critical components of nuclear power equipment is an important way to realize aging management of nuclear power equipment. The electric gate valve is one of the most safety-critical and widely distributed mechanical equipment in nuclear power installations. However, the electric gate valve's extended service in nuclear installations causes aging and degradation induced by crack propagation and leakages. Hence, it is necessary to develop a robust RUL prediction method to evaluate its operating state. Although the particle filter(PF) algorithm and its variants can deal with this nonlinear problem effectively, they suffer from severe particle degeneracy and depletion, which leads to its sub-optimal performance. In this study, we combined the whale algorithm with regularized particle filtering(RPF) to rationalize the particle distribution before resampling, so as to solve the problem of particle degradation, and for valve RUL prediction. The valve's crack propagation is studied using the RPF approach, which takes the Paris Law as a condition function. The crack growth is observed and updated using the root-mean-square (RMS) signal collected from the acoustic emission sensor. At the same time, the proposed method is compared with other optimization algorithms, such as particle swarm optimization algorithm, and verified by the realistic valve aging experimental data. The conclusion shows that the proposed method can effectively predict and analyze the typical valve degradation patterns.

• Smart Structures and Systems
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• v.30 no.6
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• pp.613-626
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• 2022

Guaranteeing the quality and integrity of structural health monitoring (SHM) data is very important for an effective assessment of structural condition. However, sensory system may malfunction due to sensor fault or harsh operational environment, resulting in multiple types of data anomaly existing in the measured data. Efficiently and automatically identifying anomalies from the vast amounts of measured data is significant for assessing the structural conditions and early warning for structural failure in SHM. The major challenges of current automated data anomaly detection methods are the imbalance of dataset categories. In terms of the feature of actual anomalous data, this paper proposes a data anomaly detection method based on data-level and deep learning technique for SHM of civil engineering structures. The proposed method consists of a data balancing phase to prepare a comprehensive training dataset based on data-level technique, and an anomaly detection phase based on a sophisticatedly designed network. The advanced densely connected convolutional network (DenseNet) and Transformer encoder are embedded in the specific network to facilitate extraction of both detail and global features of response data, and to establish the mapping between the highest level of abstractive features and data anomaly class. Numerical studies on a steel frame model are conducted to evaluate the performance and noise immunity of using the proposed network for data anomaly detection. The applicability of the proposed method for data anomaly classification is validated with the measured data of a practical supertall structure. The proposed method presents a remarkable performance on data anomaly detection, which reaches a 95.7% overall accuracy with practical engineering structural monitoring data, which demonstrates the effectiveness of data balancing and the robust classification capability of the proposed network.

• Clean Technology
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• v.16 no.4
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• pp.297-303
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• 2010

Effect of interconnect structure on the cell performance in anode-supported tubular solid oxide fuel cell (SOFC) has been investigated in this study, employing the Fluent CFD solver. For the robust and reliable theoretical analysis corroborating experimental results, it is of great importance to elucidate the role of interconnect which is electrically connected with electrodes on the cell characteristics. From the fact that the thin interconnect provides the enhanced cell performance, it is revealed that the interconnect thickness is a key parameter that is able to effectively control the ohmic resistance. Under the constant thickness condition, the cell performance does not considerably change with the variation of interconnect width. This is because the current passage along with circumferential direction is not effectively altered by the change of interconnect width in tubular SOFC system.

• The Journal of Korean Institute of Next Generation Computing
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• v.13 no.5
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• pp.39-50
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• 2017

Moving object tracking techniques can be considered as one of the most essential technique in the video understanding of which the importance is much more emphasized recently. However, irregularity of light condition in the video, variations in shape and size of object, camera motion, and occlusion make it difficult to tracking moving object in the video. Swarm based methods are developed to improve the performance of Kalman filter and particle filter which are known as the most representative conventional methods, but these methods also need to consider dynamic property of moving object. This paper proposes adaptive parameter control method which can dynamically change weight value among parameters in particle swarm optimization. The proposed method classifies each particle to 3 groups, and assigns different weight values to improve object tracking performance. Experimental results show that our scheme shows considerable improvement of performance in tracking objects which have nonlinear movements such as occlusion or unexpected movement.

• Journal of Advanced Technology Convergence
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• v.2 no.2
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• pp.9-14
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• 2023

This study is shown the result of the first year to develop an export 1050MPa-class lightweight ductile iron castings Austempered control arm through the research process to obtain the following results. First, the structure of the optimal design Layout design and development of the component, and then achieve them through the Control Arm rigidity and optimal structure design and robust design of the focus areas of the expected stress Control Arm. Second, to develop a Control Arm reflects the high rigidity and high performance lightweight structures. Control Arm them developed to meet the design and rigidity as required by the consumer through the hollow, and to develop a process for the Core. Third, through optimum alloy composition and heat treatment methods will be derived to derive the amount of iron alloy (Cu, Ni, Mo) and Austempered heat treated and tempered condition. Fourth, through the development of optimum molding technology development component to develop the optimum ADI for the low-stiffness, high-rigidity component development, it attempts to develop a high-strength casting forming technology..

• Korean Journal of Materials Research
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• v.34 no.2
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• pp.85-94
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• 2024

The optimization of deacetylation process parameters for producing chitosan from isolated chitin shrimp shell waste was investigated using response surface methodology with central composite design (RSM-CCD). Three independent variables viz, NaOH concentration (X₁), radiation power (X₂), and reaction time (X₃) were examined to determine their respective effects on the degree of deacetylation (DD). The DD of chitosan was also calculated using the baseline approach of the Fourier Transform Infrared (FTIR) spectra of the yields. RSM-CCD analysis showed that the optimal chitosan DD value of 96.45 % was obtained at an optimized condition of 63.41 % (w/v) NaOH concentration, 227.28 W radiation power, and 3.34 min deacetylation reaction. The DD was strongly controlled by NaOH concentration, irradiation power, and reaction duration. The coefficients of correlation were 0.257, 0.680, and 0.390, respectively. Because the procedure used microwave radiation absorption, radiation power had a substantial correlation of 0.600~0.800 compared to the two low variables, which were 0.200~0.400. This independently predicted robust quadratic model interaction has been validated for predicting the DD of chitin.

• Journal of the Earthquake Engineering Society of Korea
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• v.10 no.6 s.52
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• pp.79-91
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• 2006

A new methodology of guided wave based nondestructive testing (NDT) is developed to detect crack damage in civil infrastructures such as steel bridges without using prior baseline data. In conventional guided wave based techniques, damage is often identified by comparing the "current" data obtained from a potentially damaged condition of a structure with the "past" baseline data collected at the pristine condition of the structure. However, it has been reported that this type of pattern comparison with the baseline data can lead to increased false alarms due to its susceptibility to varying operational and environmental conditions of the structure. To develop a more robust damage diagnosis technique, a new concept of NDT is conceived so that cracks can be detected without direct comparison with previously obtained baseline data. The proposed NDT technique utilizes the polarization characteristics of the piezoelectric wafers attached on the both sides of the thin metal structure. Crack formation creates Lamb wave mode conversion due to a sudden change in the thickness of the structure. Then, the proposed technique instantly detects the appearance of the crack by extracting this mode conversion from the measured Lamb waves even at the presence of changing operational and environmental conditions. Numerical and experimental results are presented to demonstrate the applicability of the proposed technique to crack detection.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.38 no.2
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• pp.249-259
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• 2018

More than half of annual rainfall occurs in summer season in Korea due to its climate condition and geographical location. A frequency analysis is mostly adopted for designing hydraulic structure under the such concentrated rainfall condition. Among the various distributions, univariate Gumbel distribution has been routinely used for rainfall frequency analysis in Korea. However, the distributional changes in extreme rainfall have been globally observed including Korea. More specifically, the univariate Gumbel distribution based rainfall frequency analysis is often fail to describe multimodal behaviors which are mainly influenced by distinct climate conditions during the wet season. In this context, we purposed a Gumbel mixture distribution based rainfall frequency analysis with a Bayesian framework, and further the results were compared to that of the univariate. It was found that the proposed model showed better performance in describing underlying distributions, leading to the lower Bayesian information criterion (BIC) values. The mixed Gumbel distribution was more robust for describing the upper tail of the distribution which playes a crucial role in estimating more reliable estimates of design rainfall uncertainty occurred by peak of upper tail than single Gumbel distribution. Therefore, it can be concluded that the mixed Gumbel distribution is more compatible for extreme frequency analysis rainfall data with two or more peaks on its distribution.