• Nuclear Engineering and Technology
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• v.45 no.2
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• pp.211-218
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• 2013

Large quantities of irradiated graphite waste from graphite-moderated nuclear reactors exist and are expected to increase in the case of High Temperature Reactor (HTR) deployment [1,2]. This situation indicates the need for a graphite waste management strategy. Of greatest concern for long-term disposal of irradiated graphite is carbon-14 ($^{14}C$), with a half-life of 5730 years. Fachinger et al. [2] have demonstrated that thermal treatment of irradiated graphite removes a significant fraction of the $^{14}C$, which tends to be concentrated on the graphite surface. During thermal treatment, graphite surface carbon atoms interact with naturally adsorbed oxygen complexes to create $CO_x$ gases, i.e. "gasify" graphite. The effectiveness of this process is highly dependent on the availability of adsorbed oxygen compounds. The quantity and form of adsorbed oxygen complexes in pre- and post-irradiated graphite were studied using Time of Flight Secondary Ion Mass Spectrometry (ToF-SIMS) and Xray Photoelectron Spectroscopy (XPS) in an effort to better understand the gasification process and to apply that understanding to process optimization. Adsorbed oxygen fragments were detected on both irradiated and unirradiated graphite; however, carbon-oxygen bonds were identified only on the irradiated material. This difference is likely due to a large number of carbon active sites associated with the higher lattice disorder resulting from irradiation. Results of XPS analysis also indicated the potential bonding structures of the oxygen fragments removed during surface impingement. Ester- and carboxyl-like structures were predominant among the identified oxygen-containing fragments. The indicated structures are consistent with those characterized by Fanning and Vannice [3] and later incorporated into an oxidation kinetics model by El-Genk and Tournier [4]. Based on the predicted desorption mechanisms of carbon oxides from the identified compounds, it is expected that a majority of the graphite should gasify as carbon monoxide (CO) rather than carbon dioxide ($CO_2$). Therefore, to optimize the efficiency of thermal treatment the graphite should be heated to temperatures above the surface decomposition temperature increasing the evolution of CO [4].

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.10
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• pp.4661-4680
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• 2016

Cognitive radio (CR) technology is an effective solution to the spectrum scarcity issue. Collaborative spectrum sensing is known as a promising technique to improve the performance of spectrum sensing in cognitive radio networks (CRNs). However, collaborative spectrum sensing is vulnerable to spectrum data falsification (SSDF) attack, where malicious users (MUs) may send false sensing data to mislead other secondary users (SUs) to make an incorrect decision about primary user (PUs) activity, which is one of the key adversaries to the performance of CRNs. In this paper, we propose a coalition based malicious users detection (CMD) algorithm to detect the malicious user in CRNs. The proposed CMD algorithm can efficiently detect MUs base on the Geary'C theory and be modeled as a coalition formation game. Specifically, SSDF attack is one of the key issues to affect the resource allocation process. Focusing on the security issues, in this paper, we analyze the power allocation problem with MUs, and propose MUs detection based power allocation (MPA) algorithm. The MPA algorithm is divided into two steps: the MUs detection step and the optimal power allocation step. Firstly, in the MUs detection step, by the CMD algorithm we can obtain the MUs detection probability and the energy consumption of MUs detection. Secondly, in the optimal power allocation step, we use the Lagrange dual decomposition method to obtain the optimal transmission power of each SU and achieve the maximum utility of the whole CRN. Numerical simulation results show that the proposed CMD and MPA scheme can achieve a considerable performance improvement in MUs detection and power allocation.

• Journal of the Korean Society of Propulsion Engineers
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• v.25 no.3
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• pp.56-61
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• 2021

In this study, Al₂O₃ and H-ZSM-5 were coated on the inner wall of the stainless steel tube for the stable use of liquid hydrocarbon fuel and an endothermic catalyst used as coolant for hypersonic flying vehicles. Coke production is inevitable by the endothermic decomposition reaction of the liquid hydrocarbon fuel, and Fe, Ni metals induce the production of the filamentous coke by using a stainless steel tube reactor as a cooling channel. By coating the stainless steel with H-ZSM-5, Fe and Ni metals are prevented from being directly exposed to the liquid hydrocarbon fuel, and the formation of the filamentous coke is inhibited. In addition, Al₂O₃ is coated between the stainless steel and H-ZSM-5 to enhance adhesion bond strength.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.4
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• pp.565-571
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• 2021

In this paper, a compensation scheme of frequency selective IQ mismatch for high-performance radar systems based on commercial RFIC's is proposed. Besides, an optimization model and its solution based on the dimension reduction scheme using singular value decomposition are also proposed to design the optimal IQ mismatch compensation digital filter with complex coefficients. The performance of the proposed method had been analyzed through experiments using the IQ mismatch measurement and compensation system implemented on an FPGA board with a target RFIC and compared with the previous method. The experiment result showed a performance improvement of the proposed method over the existing one without noticeable increments in complexities. These performance analysis results showed that the limitation of using commercial RFIC's in high-performance radar systems due to the undesirable maximum SNR cap caused by their IQ mismatches could be overcome by employing the proposed method.

• Journal of the Korea Society of Computer and Information
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• v.27 no.5
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• pp.77-84
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• 2022

In this paper, we propose a novel unsupervised feature selection method. Conventional unsupervised feature selection method defines virtual label and uses a regression analysis that projects the given data to this label. However, since virtual labels are generated from data, they can be formed similarly in the space. Thus, in the conventional method, the features can be selected in only restricted space. To solve this problem, in this paper, features are selected using orthogonal projections and low-rank approximations. To solve this problem, in this paper, a virtual label is projected to orthogonal space and the given data set is also projected to this space. Through this process, effective features can be selected. In addition, projection matrix is restricted low-rank to allow more effective features to be selected in low-dimensional space. To achieve these objectives, a cost function is designed and an efficient optimization method is proposed. Experimental results for six data sets demonstrate that the proposed method outperforms existing conventional unsupervised feature selection methods in most cases.

• Nuclear Engineering and Technology
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• v.54 no.5
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• pp.1825-1834
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• 2022

Performing high-fidelity computational fluid dynamics (HF-CFD) to predict the flow and heat transfer state of the coolant in the reactor core is expensive, especially in scenarios that require extensive parameter search, such as uncertainty analysis and design optimization. This work investigated the performance of utilizing a multi-fidelity reduced-order model (MF-ROM) in PWR rod bundles simulation. Firstly, basis vectors and basis vector coefficients of high-fidelity and low-fidelity CFD results are extracted separately by the proper orthogonal decomposition (POD) approach. Secondly, a surrogate model is trained to map the relationship between the extracted coefficients from different fidelity results. In the prediction stage, the coefficients of the low-fidelity data under the new operating conditions are extracted by using the obtained POD basis vectors. Then, the trained surrogate model uses the low-fidelity coefficients to regress the high-fidelity coefficients. The predicted high-fidelity data is reconstructed from the product of extracted basis vectors and the regression coefficients. The effectiveness of the MF-ROM is evaluated on a flow and heat transfer problem in PWR fuel rod bundles. Two data-driven algorithms, the Kriging and artificial neural network (ANN), are trained as surrogate models for the MF-ROM to reconstruct the complex flow and heat transfer field downstream of the mixing vanes. The results show good agreements between the data reconstructed with the trained MF-ROM and the high-fidelity CFD simulation result, while the former only requires to taken the computational burden of low-fidelity simulation. The results also show that the performance of the ANN model is slightly better than the Kriging model when using a high number of POD basis vectors for regression. Moreover, the result presented in this paper demonstrates the suitability of the proposed MF-ROM for high-fidelity fixed value initialization to accelerate complex simulation.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.13 no.2
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• pp.73-84
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• 1993

In this research, configuration design optimization of plane truss structure has been tested by using decomposition technique. In the first level, the problem of transferring the nonlinear programming problem to linear programming problem has been effectively solved and the number of the structural analysis necessary for doing the sensitivity analysis can be decreased by developing stress constraint into member stress approximation according to the design space approach which has been proved to be efficient to the sensitivity analysis. And the weight function has been adopted as cost function in order to minimize structures. For the design constraint, allowable stress, buckling stress, displacement constraint under multi-condition and upper and lower constraints of the design variable are considered. In the second level, the nodal point coordinates of the truss structure are used as coordinating variable and the objective function has been taken as the weight function. By treating the nodal point coordinates as design variable, unconstrained optimal design problems are easy to solve. The decomposition method which optimize the section areas in the first level and optimize configuration variables in the second level was applied to the plane truss structures. The numerical comparisons with results which are obtained from numerical test for several truss structures with various shapes and any design criteria show that convergence rate is very fast regardless of constraint types and configuration of truss structures. And the optimal configuration of the truss structures obtained in this study is almost the identical one from other results. The total weight couldbe decreased by 5.4% - 15.4% when optimal configuration was accomplished, though there is some difference.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.33 no.3
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• pp.171-178
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• 2020

In this study, we develop MPI-OpenMP hybrid parallelization for multibody peridynamic simulations. Peridynamics is suitable for analyzing complicated dynamic fractures and various discontinuities. However, compared with a conventional finite element method, nonlocal interactions in peridynamics cost more time and memory. In multibody peridynamic analysis, the costs increase due to the additional interactions that occur when computing the nonlocal contact and ghost interlayer models between adjacent bodies. The costs become excessive when further refinement and smaller time steps are required in cases of high-velocity impact fracturing or similar instances. Thus, high computational efficiency and performance can be achieved by parallelization and optimization of multibody peridynamic simulations. The analytical code is developed using an Intel Fortran MPI compiler and OpenMP in NURION of the KISTI HPC center and parallelized through MPI-OpenMP hybrid parallelization. Further parallelization is conducted by hybridizing with OpenMP threads in each MPI process. We also try to minimize communication operations by model-based decomposition of MPI processes. The numerical results for the impact fracturing of multiple bodies show that the computing performance improves significantly with MPI-OpenMP hybrid parallelization.

• Korean Journal of Optics and Photonics
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• v.31 no.6
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• pp.281-289
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• 2020

This paper reports a slim mobile lens design using a hybrid refractive/diffractive optical element. Conventionally a wide field of view (FOV) camera-lens design adopts a retrofocus type having a negative (-) lens at the forefront, so that it improves in imaging performance over the wide FOV, but with the sacrifice of longer total track length (TTL). However, we chose a telephoto type as a baseline design layout having a positive (+) lens at the forefront, to achieving slimness, based on the specification analysis of 23 reported optical designs. Following preliminary optimization of a baseline design and aberration analysis based on Zernike-polynomial decomposition, we applied a hybrid refractive/diffractive element to effectively reduce the residual chromatic spherical aberration. The optimized optical design consists of 6 optical elements, including one hybrid element. It results in a very slim telephoto ratio of 1.7, having an f-number of 2.0, FOV of 90°, effective focal length of 2.23 mm, and TTL of 3.7 mm. Compared to a comparable conventional lens design with no hybrid elements, the hybrid design improved the value of the modulation transfer function (MTF) at a spatial frequency of 180 cycles/mm from 63% to 71-73% at zero field (0 F), and about 2-3% at 0.5, 0.7, and 0.9 fields. It was also found that a design with a hybrid lens with only two diffraction zones at the stop achieved the same performance improvement.

• Journal of the Korean Crystal Growth and Crystal Technology
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• v.33 no.2
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• pp.54-60
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• 2023

In this study, microstructure and basic property analysis of DG (Desulfurization gypsum) and CCMs (Carbondioxide conversion capture materials) made by reacting CO₂ with DG were conducted to analyze applicability as a cement admixture. The main crystalline phases of DG were CaO and CaSO₄, and CCMs were CaSO₄, CaCO₃, Ca(OH)₂ and CaSO₄·H₂O. As a result of particle size analysis, the difference in average particle sizes between the two materials was about 7 ㎛. No major heavy metals were detected in the CCMs, and as a result o f TGA, the CO₂ decomposition of CCMs was more than twice as high as that of DG. Therefore, it was judged that CCMs could be used as a cement admixture through optimization of manufacturing conditions. As a results of measuring the strength behavior of DG and CCMs mixture ratios, the long-term strength of CCMs-mixed mortar was higher, and this is due to the filler effect of CaCO₃ in CCMs.