• Journal of Applied Reliability
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• v.18 no.3
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• pp.271-279
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• 2018

Purpose: Probabilistic safety analysis was performed to enhance the safety and reliability of nuclear power plants because traditional deterministic approach has limitations in predicting the risk of failure by crack growth. The study introduces a probabilistic approach to establish a basis for probabilistic safety assessment of passive components. Methods: For probabilistic modeling of fatigue crack growth rate (FCGR), various FCGR tests were performed either under constant load amplitude or constant ${\Delta}K$ conditions by using heat treated X-750 at low temperature with adequate cathodic polarization. Bayesian inference was employed to update uncertainties of the FCGR model using additional information obtained from constant ${\Delta}K$ tests. Results: Four steps of Bayesian parameter updating were performed using constant ${\Delta}K$ test results. The standard deviation of the final posterior distribution was decreased by a factor of 10 comparing with that of the prior distribution. Conclusion: The method for developing a probabilistic crack growth model has been designed and demonstrated, in the paper. Alloy X-750 has been used for corrosion fatigue crack growth experiments and modeling. The uncertainties of parameters in the FCGR model were successfully reduced using the Bayesian inference whenever the updating was performed.

• Steel and Composite Structures
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• v.35 no.1
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• pp.77-92
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• 2020

The present paper outlined a procedure for geometrically nonlinear dynamic analysis of functionally graded graphene platelets-reinforced (GPLR-FG) nanocomposite cylinder subjected to mechanical shock loading. The governing equation of motion for large deformation problems is derived using meshless local Petrov-Galerkin (MLPG) method based on total lagrangian approach. In the MLPG method, the radial point interpolation technique is employed to construct the shape functions. A micromechanical model based on the Halpin-Tsai model and rule of mixture is used for formulation the nonlinear functionally graded distribution of GPLs in polymer matrix of composites. Energy dissipation in analyses of the structure responding to dynamic loads is considered using the Rayleigh damping. The Newmark-Newton/Raphson method which is an incremental-iterative approach is implemented to solve the nonlinear dynamic equations. The results of the proposed method for homogenous material are compared with the finite element ones. A very good agreement is achieved between the MLPG and FEM with very fine meshing. In addition, the results have demonstrated that the MLPG method is more effective method compared with the FEM for very large deformation problems due to avoiding mesh distortion issues. Finally, the effect of GPLs distribution on strength, stiffness and dynamic characteristics of the cylinder are discussed in details. The obtained results show that the distribution of GPLs changed the mechanical properties, so a classification of different types and volume fraction exponent is established. Indeed by comparing the obtained results, the best compromise of nanocomposite cylinder is determined in terms of mechanical and dynamic properties for different load patterns. All these applications have shown that the present MLPG method is very effective for geometrically nonlinear analyses of GPLR-FG nanocomposite cylinder because of vanishing mesh distortion issue in large deformation problems. In addition, since in proposed method the distributed nodes are used for discretization the problem domain (rather than the meshing), modeling the functionally graded media yields to more accurate results.

• Journal of the Institute of Convergence Signal Processing
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• v.12 no.1
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• pp.38-43
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• 2011

Cluster-based routing is high energy consumption of cluster head nodes. A recent approach to resolving the problem is the dynamic cluster technique that periodically re-selects cluster head nodes to distribute energy consumption of the sensor nodes. However, the dynamic clustering technique has a problem that repetitive construction of clustering consumes the more energies. This paper proposes a solution to the problems described above from the energy efficiency perspective. The round-robin cluster header(RRCH) technique, which fixes the initially structured cluster and sequentially selects cluster head nodes, is suggested for solving the energy consumption problem regarding repetitive cluster construction. A simulation result were compared with the performances of two of the most widely used conventional techniques, the LEACH(Low Energy Adaptive Clustering Hierarchy) and HEED(Hybrid, Energy Efficient, Distributed Clustering) algorithms, based on energy consumption, remaining energy for each node and uniform distribution. The evaluation confirmed that in terms of energy consumption, the technique proposed in this paper was 26.5% and 20% more efficient than LEACH and HEED, respectively.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.2 no.2
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• pp.75-82
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• 1990

A Wave transformation including wave breaking in shallow water region is a non-linear and discontinuous Phenomenon. Therefore, a so-called individual wave analysis (or a wave by wave analysis) rather than spectral approach seems to be adequate to investigate the wave transformation in such regions. In this study, a theoretical joint distribution of wave height, period and wave direction of zero-down crossing waves, which is required in the individual wave analysis in the shallow water region, is derived based on the hypothesis that sea surface is a Gaussian stochastic process and that a band-width of energy spectra is sufficiently narrow. The derived i oint distribution is found to be an effective measure to investigate characteristics of three-dimensional random wave field in shallow water through field measurements.

• Korean Journal of Remote Sensing
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• v.23 no.1
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• pp.33-42
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• 2007

In this paper, an iterative MAP approach using a Bayesian model based on the lognormal distribution for image intensity and a GRF for image texture is proposed for despeckling the SAR images that are corrupted by multiplicative speckle noise. When the image intensity is logarithmically transformed, the speckle noise is approximately Gaussian additive noise, and it tends to a normal probability much faster than the intensity distribution. MRFs have been used to model spatially correlated and signal-dependent phenomena for SAR speckled images. The MRF is incorporated into digital image analysis by viewing pixel types as slates of molecules in a lattice-like physical system defined on a GRF Because of the MRF-SRF equivalence, the assignment of an energy function to the physical system determines its Gibbs measure, which is used to model molecular interactions. The proposed Point-Jacobian Iterative MAP estimation method was first evaluated using simulation data generated by the Monte Carlo method. The methodology was then applied to data acquired by the ESA's ERS satellite on Nonsan area of Korean Peninsula. In the extensive experiments of this study, The proposed method demonstrated the capability to relax speckle noise and estimate noise-free intensity.

• Nuclear Engineering and Technology
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• v.56 no.2
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• pp.624-635
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• 2024

In two-fluid simulations of flow boiling, the modeling of the mean bubble diameter is a key parameter in the closure relations governing the intefacial transfer of mass, momentum, and energy. Monodispersed approach proved to be insufficient to describe the significant variation in bubble size during flow boiling in a heated pipe. A population balance model (PBM) has been employed to address these shortcomings. During nucleate boiling, vapor bubbles of a certain size are formed on the heated wall, detach and migrate into the bulk flow. These bubbles then grow, shrink or disintegrate by evaporation, condensation, breakage and aggregation. In this study, a parametric analysis of the PBM aggregation and breakage models has been performed to investigate their effect on the radial distribution of the mean bubble diameter and vapor volume fraction. The simulation results are compared with the DEBORA experiments (Garnier et al., 2001). In addition, the influence of PBM parameters on the local distribution of individual bubble size groups was also studied. The results have shown that the modeling of aggregation process has the largest influence on the results and is mainly dictated by the collisions due to flow turbulence.

• Journal of Electrical Engineering and Technology
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• v.9 no.2
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• pp.452-460
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• 2014

Due to increased concerns for rising oil prices and environmental problems, various solutions have been proposed for solving energy problems through tightening environmental regulations such as those regarding $CO_2$ reduction. Among them, Electrical Vehicles (EVs) are evaluated to be the most realistic and effective approach. Accordingly, research and development on EVs and charging infrastructures are mainly proceeding in developed countries. Since EVs operate using electric energy form a battery, they must be connected to the power system to charge the battery. If many EVs are connected during a short time, power quality problems can occur such as voltage sag, voltage unbalance and harmonics which are generated from power electronics devices. Therefore, when EVs are charged, it is necessary to analyze the effect of power quality on the distribution system, because EVs will gradually replace gasoline vehicles, and the number of EVs will be increased. In this paper, a battery for EVs and a PWM converter are modeled using an ElectroMagnetic Transient Program (EMTP). The voltage sag and unbalance are evaluated when EVs are connected to the distribution system of the Korea Electric Power Corporation (KEPCO). The simulation results are compared with IEEE standards.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.12
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• pp.33-42
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• 2020

The neoclassical economic supporters have suggested that foreign direct investment and raw material (e.g., coal, electricity, gas, and oil) are critical economic growth inputs. Few previous studies have analyzed the relationship between foreign direct investment and energy consumption on economic growth. However, existing studies usually have applied the frequentist inference. The limitation of the frequentist inference is that, if the coefficient of the independent variable is not yet significant, then conclusions might be unreliable. By applying the Bayesian approach, the main aim of this study is to revisit the impact of foreign direct investment, electricity consumption, and urbanization on economic growth in six ASEAN countries from 1980 to 2016. The obtained outcome shows that the impact of electricity consumption is evident and positive on economic growth in both frequentist and Bayesian inferences. However, the influence of foreign direct investment is not identified by frequentist inference, while Bayesian inference provides evidence that foreign direct investment is a moderately positive impact on economic growth. The empirical result from Bayesian inference contributes to the literature on foreign direct investment modeling and could be of significant importance for a more efficient foreign direct investment attracting and achieve sustainability in the long-term.

• Journal of Korea Society of Digital Industry and Information Management
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• v.4 no.4
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• pp.41-49
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• 2008

Sensor networks are often deployed in unattended environments, thus leaving these networks vulnerable to false data injection attacks in which an adversary injects forged reports into the network through compromised nodes. Such attacks by compromised sensors can cause not only false alarms but also the depletion of the finite amount of energy in a battery powered network. In order to reduce damage from these attacks, several security solutions have been proposed. Researchers have also proposed some techniques to increase the energy-efficiency of such security solutions. In this paper, we propose a CH(Cluster Header) selection algorithm to choose low power delivery method in sensor networks. The CNP(Contract Net Protocol), which is an approach to solve distribution problems, is applied to choose CHs for event sensing. As a result of employing CNP, the proposed method can prevent dropping of sensing reports with an insufficient number of message authentication codes during the forwarding process, and is efficient in terms of energy saving.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.9
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• pp.3148-3154
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• 2010

This paper presents the probabilistic analysis for fatigue life of Glass/Epoxy laminates with impact-induced damage. For this, a series of impact tests were perfomed on the Glass/Epoxy laminates using instrumented impact testing machine. Then, tensile and fatigue tests carried out so as to generate post-impact residual strength and fatigue life. Two Parameter Weibull distribution was used to fit the residual strength and fatigue life data of Glass/Epoxy composite laminates. The residual strength was affected by impact energy and their variance decreased with increasing of impact energy. The fatigue life of impacted laminates was greatly reduced by impact energy and this trend depended on applied stress amplitude. Additionally, the variation of fatigue life was gradually decreased with the applied stress amplitude.