• Nuclear Engineering and Technology
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• v.41 no.10
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• pp.1275-1284
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• 2009

A directly heated $SO_3$ decomposer for the sulfur-iodine and hybrid-sulfur processes has been introduced and analyzed using the computational fluid dynamics (CFD) code CFX 11. The use of a directly heated decomposition reactor in conjunction with a very high temperature reactor (VHTR) allows for higher decomposition reactor operating temperatures. However, the high temperatures and strongly corrosive operating conditions associated with $SO_3$ decomposition present challenges for the structural materials of decomposition reactors. In order to resolve these problems, we have designed a directly heated $SO_3$ decomposer using RA330 alloy as a structural material and have performed a CFD analysis of the design based on the finite rate chemistry model. The CFD results show the maximum temperature of the structural material could be maintained sufficiently below 1073 K, which is considered the target temperature for RA 330. The CFD simulations also indicated good performance in terms of $SO_3$ decomposition for the design parameters of the present study.

• Journal of Microbiology and Biotechnology
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• v.34 no.9
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• pp.1867-1875
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• 2024

Identification of the biochemical metabolic pathway for lignin decomposition and the responsible degradative enzymes is needed for the effective biotechnological valorization of lignin to renewable chemical products. In this study, we investigated the decomposition of kraft lignin by the soil bacterium Pseudomonas kribbensis CHA-19, a strain that can utilize kraft lignin and its main degradation metabolite, vanillic acid, as growth substrates. Gel permeation chromatography revealed that CHA-19 decomposed polymeric lignin and degraded dehydrodivanillin (a representative lignin model compound); however, the degradative enzyme(s) and mechanism were not identified. Quantitative polymerase chain reaction with mRNAs from CHA-19 cells induced in the presence of lignin showed that the putative genes coding for two laccase-like multicopper oxidases (LMCOs) and three dye-decolorizing peroxidases (DyPs) were upregulated by 2.0- to 7.9-fold compared with glucose-induced cells, which indicates possible cooperation with multiple enzymes for lignin decomposition. Computational homology analysis of the protein sequences of LMCOs and DyPs also predicted their roles in lignin decomposition. Based on the above data, CHA-19 appears to initiate oxidative lignin decomposition using multifunctional LMCOs and DyPs, producing smaller metabolites such as vanillic acid, which is further degraded via ortho- and meta-ring cleavage pathways. This study not only helps to better understand the role of bacteria in lignin decomposition and thus in terrestrial ecosystems, but also expands the biocatalytic toolbox with new bacterial cells and their degradative enzymes for lignin valorization.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2004.10a
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• pp.422-425
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• 2004

This paper develops an octree-based algorithm for machining simulation. Most commercial machining simulators are based on the Z map model, which has several limitations in terms of achieving a high level of precision in five-axis machining simulation. Octree representation being a three-dimensional (3D) decomposition method, an octree-based algorithm is expected to be able to overcome such limitations. With the octree model, storage requirement is reduced. Moreover, recursive subdivision is processed in the boundaries, which reduces useless computations. The supersampling method is the most common form of antialiasing and is typically used with polygon mesh rendering in computer graphics. The supersampling technique is being used to advance the efficiency of the octree algorithm..

• Journal of Information Processing Systems
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• v.13 no.4
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• pp.863-875
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• 2017

The traditional text similarity measurement methods based on word frequency vector ignore the semantic relationships between words, which has become the obstacle to text similarity calculation, together with the high-dimensionality and sparsity of document vector. To address the problems, the improved singular value decomposition is used to reduce dimensionality and remove noises of the text representation model. The optimal number of singular values is analyzed and the semantic relevance between words can be calculated in constructed semantic space. An inverted index construction algorithm and the similarity definitions between vectors are proposed to calculate the similarity between two documents on the semantic level. The experimental results on benchmark corpus demonstrate that the proposed method promotes the evaluation metrics of F-measure.

• Korean Journal of Mathematics
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• v.31 no.4
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• pp.419-431
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• 2023

In this paper, we propose an iterative method for a symmetric interior penalty Galerkin method for heterogeneous elliptic problems. The iterative method consists mainly of two parts based on a non-overlapping domain decomposition approach. One is an intermediate preconditioner constructed by understanding the properties of the discontinuous finite element functions and the other is a preconditioning related to the dual-primal finite element tearing and interconnecting (FETI-DP) methodology. Numerical results for the proposed method are presented, which demonstrate the performance of the iterative method in terms of various parameters associated with the elliptic model problem, the finite element discretization, and non-overlapping subdomain decomposition.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.160-163
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• 1996

This paper deals with MCMBPC(Multivariable Constrained Model Based Predictive Controller) for nonlinear boiler system with noise and disturbance. MCMBPC is designed by linear state space model obtained from some operating point of nonlinear boiler system and Kalman filter is used to estimate the state with noise and disturbance. The solution of optimization of the cost function constrained on input and/or output variables is achieved using quadratic programming, viz. singular value decomposition (SVD). The controller designed is shown to have excellent tracking performance via simulation applied to nonlinear dynamic drum boiler turbine model for 16OMW unit.

• Journal of Multimedia Information System
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• v.2 no.2
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• pp.215-222
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• 2015

Epileptic Seizure is a popular brain disease in the world. It affects the nervous system and the activities of brain function that make a person who has seizure signs cannot control and predict his actions. Based on the Electroencephalography (EEG) signals which are recorded from human or animal brains, the scientists use many methods to detect and recognize the abnormal activities of brain. Tucker model is investigated to solve this problem. Tucker decomposition is known as a higher-order form of Singular Value Decomposition (SVD), a well-known algorithm for decomposing a matric. It is widely used to extract good features of a tensor. After decomposing, the result of Tucker decomposition is a core tensor and some factor matrices along each mode. This core tensor contains a number of the best information of original data. In this paper, we used Tucker decomposition as a way to obtain good features. Training data is primarily applied into the core tensor and the remained matrices will be combined with the test data to build the Tucker base that is used for testing. Using core tensor makes the process simpler and obtains higher accuracies.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.16 no.2
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• pp.125-130
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• 2016

The proposal of this study is a fast version of the conventional extreme learning machine (ELM), called pseudoinverse matrix decomposition based incremental ELM (PDI-ELM). One of the main problems in ELM is to determine the number of hidden nodes. In this study, the number of hidden nodes is automatically determined. The proposed model is an incremental version of ELM which adds neurons with the goal of minimization the error of the ELM network. To speed up the model the information of pseudoinverse from previous step is taken into account in the current iteration. To show the ability of the PDI-ELM, it is applied to few benchmark classification datasets in the University of California Irvine (UCI) repository. Compared to ELM learner and two other versions of incremental ELM, the proposed PDI-ELM is faster.

• Nuclear Engineering and Technology
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• v.55 no.8
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• pp.2835-2843
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• 2023

After an emergency shutdown of a lead-bismuth fast reactor, thermal stratification occurs in the upper Plenum, which negatively impacts the integrity of the reactor structure and the residual heat removal capacity of natural circulation flow. The research on thermal stratification of reactors has mainly been conducted using an experimental method, a system program, and computational fluid dynamics (CFD). However, the equipment required for the experimental method is expensive, accuracy of the system program is unpredictable, and resources and time required for the CFD approach are extensive. To overcome the defects of thermal stratification analysis, a high-precision full-order thermal stratification model based on CFD technology is prepared in this study. Furthermore, a reduced-order model has been developed by combining proper orthogonal decomposition (POD) with Galerkin projection. A comparative analysis of thermal stratification with the proposed full-order model reveals that the reduced-order thermal stratification model can well simulate the temperature distribution in the upper plenum and rapidly elucidate the thermal stratification interface characteristics during the lead-bismuth fast reactor accident. Overall, this study provides an analytical tool for determining the thermal stratification mechanism and reducing thermal stratification.

• Nuclear Engineering and Technology
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• v.51 no.6
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• pp.1487-1503
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• 2019

The methods and performance of a pin-level nuclear reactor core thermal-hydraulics (T/H) code ESCOT employing the drift-flux model are presented. This code aims at providing an accurate yet fast core thermal-hydraulics solution capability to high-fidelity multiphysics core analysis systems targeting massively parallel computing platforms. The four equation drift-flux model is adopted for two-phase calculations, and numerical solutions are obtained by applying the Finite Volume Method (FVM) and the Semi-Implicit Method for Pressure-Linked Equation (SIMPLE)-like algorithm in a staggered grid system. Constitutive models involving turbulent mixing, pressure drop, and vapor generation are employed to simulate key phenomena in subchannel-scale analyses. ESCOT is parallelized by a domain decomposition scheme that involves both radial and axial decomposition to enable highly parallelized execution. The ESCOT solutions are validated through the applications to various experiments which include CNEN $4{\times}4$, Weiss et al. two assemblies, PNNL $2{\times}6$, RPI $2{\times}2$ air-water, and PSBT covering single/two-phase and unheated/heated conditions. The parameters of interest for validation include various flow characteristics such as turbulent mixing, spacer grid pressure drop, cross-flow, reverse flow, buoyancy effect, void drift, and bubble generation. For all the validation tests, ESCOT shows good agreements with measured data in the extent comparable to those of other subchannel-scale codes: COBRA-TF, MATRA and/or CUPID. The execution performance is examined with a mini-sized whole core consisting of 89 fuel assemblies and for an OPR1000 core. It turns out that it is about 1.5 times faster than a subchannel code based on the two-fluid three field model and the axial domain decomposition scheme works as well as the radial one yielding a steady-state solution for the OPR1000 core within 30 s with 104 processors.