• International Journal of Aeronautical and Space Sciences
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• 제16권2호
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• pp.177-189
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• 2015

This paper presents an all-direct domain decomposition approach for large-scale structural analysis. The proposed approach achieves computational robustness and efficiency by enforcing the compatibility of the displacement field across the sub-domain boundaries via local Lagrange multipliers and augmented Lagrangian formulation (ALF). The proposed domain decomposition approach was compared to the existing FETI approach in terms of the computational time and memory usage. The parallel implementation of the proposed algorithm was described in detail. Finally, a preliminary validation was attempted for the proposed approach, and the numerical results of two- and three-dimensional problems were compared to those obtained through a dual-primal FETI approach. The results indicate an improvement in the performance as a result of the implementing the proposed approach.

• 한국산업융합학회 논문집
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• 제3권4호
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• pp.369-378
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• 2000

Conventional fractal image compression methods have many problems in searching time for matching domain block. Proposed method is an improved method of Fisher's Quadtree Decomposition in terms of time, compression ratio, and PSNR. This method determines range block in advance using QR algorithm. First, input image is partitioned to $4{\times}4$ range block and then recomposition is performed from bottom level to specified level. As a result, this proposed method achieves high encoding and decoding speed, high compression ratio, and high PSNR than Fisher's Quadtree Decomposition method.

• Structural Engineering and Mechanics
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• 제38권4호
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• pp.405-416
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• 2011

An efficient two-level domain decomposition parallel algorithm is suggested to solve large-DOF structural problems with nonlinear material models generating unsymmetric tangent matrices, such as a group of plastic-damage material models. The parallel version of the stabilized bi-conjugate gradient method is developed to solve unsymmetric coarse problems iteratively. In the present approach the coarse DOF system is solved parallelly on each processor rather than the whole system equation to minimize the data communication between processors, which is appropriate to maintain the computing performance on a non-supercomputer level cluster system. The performance test results show that the suggested algorithm provides scalability on computing performance and an efficient approach to solve large-DOF nonlinear structural problems on a cluster system.

• IEIE Transactions on Smart Processing and Computing
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• 제4권2호
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• pp.89-96
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• 2015

In this paper, time-frequency analysis algorithms, empirical mode decomposition and local mean decomposition, are reviewed and their applications to nonlinear and nonstationary real-world data are discussed. In addition, their generic extensions to complex domain are addressed for the analysis of multichannel data. Simulations of these algorithms on synthetic data illustrate the fundamental structure of the algorithms and how they are designed for the analysis of nonlinear and nonstationary data. Applications of the complex version of the algorithms to the synthetic data also demonstrate the benefit of the algorithms for the accurate frequency decomposition of multichannel data.

• 한국지반환경공학회 논문집
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• 제25권4호
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• pp.13-20
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• 2024

본 논문에서는 유동체를 해석할 수 있는 수치해석기법 중 하나인 SPH(Smoothed Particle Hydrodynamics)의 병렬해석 알고리즘이 소개된다. 무요소법(meshless method)의 SPH는 연속체 거동을 입자기반으로 표현하기 때문에 컴퓨팅하는데 높은 자원을 요구한다. 그래서 병렬해석 알고리즘은 SPH 시뮬레이션에서 필수적으로 고려되어야 한다. 계산영역을 일정한 간격으로 분할시켜 독립적으로 해석하는 영역분할 알고리즘은 병렬해석 알고리즘 중에 가장 대표적인 방법이다. 그리고 그 중 Cartesian 좌표계의 영역분할 방법은 입자들의 좌표를 빠르고 편리하게 검색할 수 있는 장점이 있어, DEM(Discrete Element Method)이나 MD(Molecular Dynamics)에서 대중적으로 사용되고 있다. 그러나 SPH의 경우 입자들이 smoothing 길이 이내의 주위 입자 정보가 필요하기 때문에 분할 영역 간의 입자정보 공유가 중요하다. 그리고 이에 따른 CPU의 로드밸런스가 중요하다. 본 연구에서는 직교 영역분할의 크기를 동적으로 미소화 시켜 잉여 CPU가 발생하지 않도록 하는 높은 병렬효율성의 알고리즘이 제안되었다. 그리고 수치해석 모델을 통하여 효율성을 검증하였다. 유동체 모델에 대해 총 30 CPU까지 제안된 방법의 병렬효율성을 검토하였고, 28개의 물리적 코어 수까지 90%의 병렬효율성을 얻을 수 있었다.

• 한국전산유체공학회지
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• 제3권1호
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• pp.22-29
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• 1998

Parallel implementation is conducted for a SIMPLER finite volume model. The present parallelism is based on domain decomposition and explicit message passing using MPI and SHMEM. Two parallel solvers to tridiagonal matrix equation are employed. The implementation is verified on the Cray T3E system for a benchmark problem of natural convection in a sidewall-heated cavity. The test results illustrate good scalability of the present parallel models. Performance issues are elaborated in view of convergence as well as conventional parallel overheads and single processor performance. The effectiveness of a localized matrix solution algorithm is demonstrated.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2000년도 춘계학술대회논문집
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• pp.269-273
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• 2000

This paper describes Active Noise Control (ANC) using Discrete Wavelet Transform (DWT) Domain Least Mean Square (LMS) Method. DWT-LMS is one of the transform domain input decorrelation LMS and improves the convergence speed of adaptive filter especially when the input signal is highly correlated. Conventional transform domain LMS's use Discrete Cosine Transform (DCT) because it offers linear band signal decomposition and fast transform algorithm. Wavelet transform can project the input signal into the several octave band subspace and offers more efficient sliding fast transform algorithm. In this paper, we propose Wavelet transform domain LMS algorithm and shows its performance is similar to DCT LMS in some cases using ANC simulation.

• Nuclear Engineering and Technology
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• 제48권3호
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• pp.635-641
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• 2016

Because of prohibitive data storage requirements in large-scale simulations, the memory problem is an obstacle for Monte Carlo (MC) codes in accomplishing pin-wise three-dimensional (3D) full-core calculations, particularly for whole-core depletion analyses. Various kinds of data are evaluated and quantificational total memory requirements are analyzed based on the Reactor Monte Carlo (RMC) code, showing that tally data, material data, and isotope densities in depletion are three major parts of memory storage. The domain decomposition method is investigated as a means of saving memory, by dividing spatial geometry into domains that are simulated separately by parallel processors. For the validity of particle tracking during transport simulations, particles need to be communicated between domains. In consideration of efficiency, an asynchronous particle communication algorithm is designed and implemented. Furthermore, we couple the domain decomposition method with MC burnup process, under a strategy of utilizing consistent domain partition in both transport and depletion modules. A numerical test of 3D full-core burnup calculations is carried out, indicating that the RMC code, with the domain decomposition method, is capable of pin-wise full-core burnup calculations with millions of depletion regions.

• 융합신호처리학회논문지
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• 제9권4호
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• pp.295-303
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• 2008

변환영역 적응필터는 시간영역 적응필터보다 일반직으로 수렴속도가 빠르지만 필터의 차수가 증가함에 따라 계산량이 크게 증가한다. 이러한 문제점은 변환영역 적응필터를 서브밴드 분해구조로 변경함으로써 해결할 수 있다. 이 논문에서는 일반화된 서브밴드 분해 FIR 적응 필터의 수렴속도 향상을 위해 웨이블릿 변환영역에서 다이아딕 희소인자 서브필터를 가지는 일반화된 서브밴드 분해 FTR 적응 필터의 구조를 설계하였다. 그리고 이 적응필터에서 변환영역의 일반화된 등가입력을 유도하고 이 입력을 이용하여 LMS 일고리듬에 대한 수렴특성을 해석 및 평가하였다. 이 서브밴드 FIR 적응필터를 이용하여 역 모델링 시스템과 주기성 잡음제거기를 구성하고 LMS 알고리듬 대한 이 시스템들의 수련속도를 이산푸리에 변환을 이용한 서브밴드 적응필터의 것과 컴퓨터 모의실험으로 비교하였다.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2000년도 하계종합학술대회 논문집(4)
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• pp.182-185
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• 2000

In this paper, we present a new adaptive filter structure which is based on polyphase decomposition of the filter to be adapted. This structure uses wavelet transform to acquire transform-domain coefficients of the input signal. With this coefficients RLS algorithm is used for adaptation. Particularly, using the polyphase parallel structure, we can trace the system which has very long impulse response with only increasing the subband, and show that computational savings can be achieved. The proposed structure was applied to system identification for performance estimation and compared with fullband adaptive filter.