• Journal of the Korean Society of Combustion
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• v.13 no.1
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• pp.31-43
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• 2008

Oxy-fuel flame has a significantly different structure from that of air-fuel flame because of its high temperature. This study is aimed to find out the difference of the oxy-fuel flame structure in order to understand reaction mechanism closely, which is crucial to design real-scale oxy-fuel combustion system. By examining pictures of counterflow flame and LIF images, we found that oxy-fuel flame had two-zone structure: fuel decomposition region and distributed CO oxidation region. In the oxy-fuel flame, OH radical was distributed intensely through the whole flame due to its higher flame temperature than crossover temperature. For showing those features of the oxy-fuel flame, 1 MW scale IFRF oxy-natural gas burner was simulated by conditional moment closure(CMC) model. Calculation results were compared with experimental data, and showed agreements in trend. In the simulated distributions of fuel decomposition/CO oxidation rates, CO oxidation region was also separated from fuel decomposition zone considerably, which showed the two-zone structure in the oxy-fuel flame.

• Journal of Electrical Engineering and Technology
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• v.10 no.3
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• pp.709-718
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• 2015

Traditional transmission planning usually caters for rated wind power output. Due to the low occurrence probability of nominal capacity of wind power and huge investment in transmission, these planning methods will leads to low utilization rates of transmission lines and poor economic efficiency. This paper provides a novel transmission expansion planning method for integrating large-scale wind power. The wind power distribution characteristics of large-scale wind power output and its impact on transmission planning are analyzed. Based on the wind power distribution characteristics, this paper proposes a flexible and economic transmission planning model which saves substantial transmission investment through spilling a small amount of peak output of wind power. A methodology based on Benders decomposition is used to solve the model. The applicability and effectiveness of the model and algorithm are verified through a numerical case.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.44 no.4
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• pp.98-105
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• 2021

Using the frequency-based decomposition, I decompose the consumption growth to explain well-known patterns of stock returns in the Korean market. To be more specific, the consumption growth is decomposed by its half-life of shocks. The component over four years of half-life is called the business-cycle consumption component, and the components with half-lives under four years are short-run components. I compute the long-run and short-run components of stock excess returns as well and use component-by-component sensitivities to price stock portfolios. As a result, the business-cycle consumption risk with half-life of over four years is useful in explaining the cross-section of size-book-to-market portfolios and size-momentum portfolios in the Korean stock market. The short-run components have their own pricing abilities with mixed direction, so that the restricted one short-term factor model is rejected. The explanatory power with short- and long-run components is comparable to that of the Fama-French three-factor model. The components with one- to four-year half-lives are also helpful in explaining the returns. The results about the long-run components emphasize the importance of long-run component in consumption growth to explain the asset returns.

• Nuclear Engineering and Technology
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• v.55 no.3
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• pp.827-838
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• 2023

Centrifugal pump is a key part of nuclear power plant systems, and its health status is critical to the safety and reliability of nuclear power plants. Therefore, fault diagnosis is required for centrifugal pump. Traditional fault diagnosis methods have difficulty extracting fault features from nonlinear and non-stationary signals, resulting in low diagnostic accuracy. In this paper, a new fault diagnosis method is proposed based on the improved particle swarm optimization (IPSO) algorithm-based variational modal decomposition (VMD) and relevance vector machine (RVM). Firstly, a simulation test bench for rotor faults is built, in which vibration displacement signals of the rotor are also collected by eddy current sensors. Then, the improved particle swarm algorithm is used to optimize the VMD to achieve adaptive decomposition of vibration displacement signals. Meanwhile, a screening criterion based on the minimum Kullback-Leibler (K-L) divergence value is established to extract the primary intrinsic modal function (IMF) component. Eventually, the factors are obtained from the primary IMF component to form a fault feature vector, and fault patterns are recognized using the RVM model. The results show that the extraction of the fault information and fault diagnosis classification have been improved, and the average accuracy could reach 97.87%.

• The Korean Journal of Applied Statistics
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• v.24 no.6
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• pp.995-1006
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• 2011

A time series can be decomposed into simple components with a multiscale method. Empirical mode decomposition(EMD) is a recently invented multiscale method in Huang et al. (1998). It is natural to apply a classical prediction method such a vector autoregressive(AR) model to the obtained simple components instead of the original time series; in addition, a prediction procedure combining a classical prediction model to EMD and Hilbert spectrum is proposed in Kim et al. (2008). In this paper, we suggest to adopt principal component analysis(PCA) to the prediction procedure that enables the efficient selection of input variables among obtained components by EMD. We discuss the utility of adopting PCA in the prediction procedure based on EMD and Hilbert spectrum and analyze the daily worm account data by the proposed PCA adopted prediction method.

• Proceedings of the IEEK Conference
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• 2007.07a
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• pp.301-302
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• 2007

A speech enhancement algorithm based on both a decomposition of speech into deterministic and stochastic components and a psychoacoustic model is proposed. Noisy speech is decomposed into deterministic and stochastic components, and then each component is enhanced preserving its individual characteristics. A psychoacoustic model is taken into account when enhancing the stochastic component. Simulation results show that the proposed algorithm performs better than some of the more popular algorithms.

• Journal of Power Electronics
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• v.13 no.5
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• pp.884-895
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• 2013

In this paper, the Fourier-based PLL (Phase-locked Loop) is introduced with a new structure, capable of selective harmonic detection in single and three-phase systems. The application of the FB-PLL to harmonic detection is discussed and a new model applicable to three-phase systems is introduced. An analysis of the convergence of the FB-PLL based on a linear model is presented. Simulation and experimental results are included for performance analysis and to support the theoretical development. The decomposition of an input signal in its harmonic components using the Fourier theory is based on previous knowledge of the signal fundamental frequency, which cannot be easily implemented with input signals with varying frequencies or subjected to phase-angle jumps. In this scenario, the main contribution of this paper is the association of a phase-locked loop system, with a harmonic decomposition and reconstruction method, based on the well-established Fourier theory, to allow for the tracking of the fundamental component and desired harmonics from distorted input signals with a varying frequency, amplitude and phase-angle. The application of the proposed technique in three-phase systems is supported by results obtained under unbalanced and voltage sag conditions.

• Journal of applied mathematics & informatics
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• v.41 no.4
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• pp.861-868
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• 2023

Nonlinear network creates complex homotopy structural communication in wireless network medium because of complex distribution approach. Due to this multicast topological connection structure, the queuing probability was non regular principles to create routing structures. To resolve this problem, we propose a Co-cluster homotopy queuing model (Co-CHQT) for Nonlinear Algebraic Topological Structure (NLTS-) for improving poison distribution network communication. Initially this collects the routing propagation based on Nonlinear Distance Theory (NLDT) to estimate the nearest neighbor network nodes undernon linear at x_(a,b)→ax²+bx² = c. Then Quillen Network Decomposition Theorem (QNDT) was applied to sustain the non-regular routing propagation to create cluster path. Each cluster be form with co variance structure based on Two unicast 2(n+1)-Z2(n+1)-Z network. Based on the poison distribution theory X_(a,b) ≠ µ(C), at number of distribution routing strategies weights are estimated based on node response rate. Deriving shorte;'l/st path from behavioral of the node response, Hilbert -Krylov subspace clustering estimates the Cluster Head (CH) to the routing head. This solves the approximation routing strategy from the nonlinear communication depending on Max- equivalence theory (Max-T). This proposed system improves communication to construction topological cluster based on optimized level to produce better performance in distance theory, throughput latency in non-variation delay tolerant.

• Journal of Internet Computing and Services
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• v.9 no.1
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• pp.103-113
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• 2008

Vast amount of XML documents raise interests in how they will be used and how far their usage can be expanded, This paper has two central goals: 1) easy and fast retrieval of XML documents or relevant elements; and 2) efficient and stable management of large-size XML documents, The keys to develop such a practical system are how to segment a large XML document to smaller fragments and how to store them. In order to achieve these goals, we designed SCOF(Service-centric Object Fragmentation) model, which is a semi-decomposition method based on conversion rules provided by XML database managers. Keyword-based search using SCOF model then retrieves the specific elements or attributes of XML documents, just as typical XML query language does. Even though this approach needs the wisdom of managers in XML document collection, SCOF model makes it efficient both retrieval and management of massive XML documents.

• Journal of Broadcast Engineering
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• v.19 no.1
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• pp.64-74
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• 2014

The primary and ambient signal decomposition of a stereo sound is a key step to the stereo upmix. The principal component analysis (PCA) is one of the most widely used methods of primary-ambient signal decomposition. However, previous PCA-based decomposition algorithms assume that stereo sound sources are only amplitude-panned without any consideration of phase difference. So it occurs some performance degradation in case of live recorded stereo sound. In this paper, we propose a new PCA-based stereo decomposition algorithm that can consider the phase difference between the channel signals. The proposed algorithm overcomes limitation of conventional signal model using PCA with phase alignment. The phase alignment is realized by using inter-channel phase difference (IPD) which is widely used in parametric stereo coding. Moreover, Enhanced Modified PCA(EMPCA) is combined to solve the problem of conventional PCA caused by Primary to Ambient energy Ratio(PAR) and panning angle dependency. The simulation results are presented to show the improvements of the proposed algorithm.