• 충청수학회지
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• 제34권2호
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• pp.157-168
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• 2021

This study uses the benchmark interest rate of the Federal Open Market Committee (FOMC) to predict gold futures prices. For the predictions, we used the support vector machine (SVM) (a machine-learning model) and the long short-term memory (LSTM) deep-learning model. We found that the LSTM method is more accurate than the SVM method. Moreover, we applied the Boruta algorithm to demonstrate that the FOMC benchmark interest rates correlate with gold futures.

• 한국음향학회:학술대회논문집
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• 한국음향학회 1996년도 제11회 수중음향학 학술발표회 논문집 11th Underwater Acoustics Symposium Proceedings
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• pp.64-68
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• 1996

수중음파전달 모델은 benchmark 시험을 통해 정확도, 적용범위, 계산시간 등의 성능을 평가받는다. 본 논문에서는 analytic 모델, 정상 모드 모델(normal mode model), 포물선 방정식 모델(parabolic equation model), 가우시안 빔 모델(Gaussian beam model), 스펙트럼 모델(spectral model) 등 거리의존 모델에 대해 benchmark 시험을 수행하였으며, benchmark 시험은 다음과 같은 세 가지 거리의존 해양환경으로 나누어 실시했다 : 1) 해수면과 해저면이 Dirichlet 경계조건인 이상 쐐기 문제(ideal wedge problem), 2) 해수면은 앞서 말한 Dirichlet 경계조건이나 해저면은 전달 손실이 있는 손실 통과 해저면 쐐기 문제(penetrable lossy bottom wedge problem), 3) 해수면은 앞서 말한 Dirichlet 경계조건이고 해저면은 Neumann 경계조건으로 서로 평행이면 음파전달 속도가 거리방향 의존인 경우, 경우 1은 anaytic 모델을 사용하고 경우 2는 정상 모드 모델, 포물선 방정식 모델, 스펙트럼 모델을 사용하였으며, 경우 3에 대해서는 가우시안 빔 모델과 포물선 방정식 모델을 사용하였다.

• Nuclear Engineering and Technology
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• 제56권8호
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• pp.2948-2957
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• 2024

High-order harmonic techniques can be used to recreate neutron flux distributions in reactor cores using the neutron diffusion equation. However, traditional source iteration and source correction iteration techniques have sluggish convergence rates and protracted calculation periods. The correctness of the implicitly restarted Arnoldi method (IRAM) in resolving the eigenvalue problems of the one-dimensional and two-dimensional neutron diffusion equations was confirmed by computing the benchmark problems SLAB_1D_1G and two-dimensional steady-state TWIGL using IRAM. By integrating Galerkin projection with Proper Orthogonal Decomposition (POD) techniques, a POD-Galerkin reduced-order model was developed and the IRAM model was used as the full-order model. For 14 macroscopic cross-section values, the TWIGL benchmark problem was perturbed within a 20% range. We extracted 100 sample points using the Latin hypercube sampling method, and 70% of the samples were used as the testing set to assess the performance of the reduced-order model The remaining 30% were utilized as the training set to develop the reduced-order model, which was employed to rebuild the TWIGL benchmark problem. The reduced-order model demonstrates good flexibility and can efficiently and accurately forecast the effective multiplication factor and neutron flux distribution in the core. The reduced-order model predicts k_eff and neutron flux distribution with a high degree of agreement compared to the full-order model. Additionally, the reduced-order model's computation time is only 10.18% of that required by the full-order model.The neutron flux distribution of the steady-state TWIGL benchmark was recreated using the reduced-order model. The obtained results indicate that the reduced-order model can accurately predict the k_eff and neutron flux distribution of the steady-state TWIGL benchmark.Overall, the proposed technique not only has the potential to accurately project neutron flux distributions in transient settings, but is also relevant for reconstructing neutron flux distributions in steady-state conditions; thus, its applicability is bound to increase in the future.

• Nuclear Engineering and Technology
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• 제13권2호
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• pp.73-84
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• 1981

B$\Phi$rrensen은 3차원적 노심분석에 긴 시간이 요구되는 유한차분법의 대안으로서 경수형 원자로의 전체출력분포를 계산하는데 한가지의 coarse mesh 방법을 제안하였다. 이 방법은 계산시간이 매우 짧은 것으로 알려져 있지만. 그 계산의 정확도에 대한 것은 아직까지 알려져 있지 않다. 본 논문에서는 B$\Phi$rrensen의 방법을 IAEA benchmark 문제와 RIS$\Phi$ benchmark 문제에 적용시켜서 계산시간과 정확도에 대해서 고찰하였다. 두 문제에서 노심-반사체와의 경계조건과 B$\Phi$rrensen의 모델상수들의 개선으로 출력분포 계산의 정확도를 상당히 높힐 수 있었다.

• Smart Structures and Systems
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• 제10권4_5호
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• pp.411-426
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• 2012

The Canton Tower (formerly named Guangzhou New TV Tower) of 610 m high has been instrumented with a long-term structural health monitoring (SHM) system consisting of over 700 sensors of sixteen types. Under the auspices of the Asian-Pacific Network of Centers for Research in Smart Structures Technology (ANCRiSST), an SHM benchmark problem for high-rise structures has been developed by taking the instrumented Canton Tower as a host structure. This benchmark problem aims to provide an international platform for direct comparison of various SHM-related methodologies and algorithms with the use of real-world monitoring data from a large-scale structure, and to narrow the gap that currently exists between the research and the practice of SHM. This paper first briefs the SHM system deployed on the Canton Tower, and the development of an elaborate three-dimensional (3D) full-scale finite element model (FEM) and the validation of the model using the measured modal data of the structure. In succession comes the formulation of an equivalent reduced-order FEM which is developed specifically for the benchmark study. The reduced-order FEM, which comprises 37 beam elements and a total of 185 degrees-of-freedom (DOFs), has been elaborately tuned to coincide well with the full-scale FEM in terms of both modal frequencies and mode shapes. The field measurement data (including those obtained from 20 accelerometers, one anemometer and one temperature sensor) from the Canton Tower, which are available for the benchmark study, are subsequently presented together with a description of the sensor deployment locations and the sensor specifications.

• Smart Structures and Systems
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• 제10권4_5호
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• pp.443-458
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• 2012

The structural health monitoring (SHM) benchmark study on optimal sensor placement problem for the instrumented Canton Tower has been launched. It follows the success of the modal identification and model updating for the Canton Tower in the previous benchmark study, and focuses on the optimal placement of vibration sensors (accelerometers) in the interest of bettering the SHM system. In this paper, the sensor placement problem for the Canton Tower and the benchmark model for this study are first detailed. Then an information entropy based sensor placement method with the purpose of damage detection is proposed and applied to the benchmark problem. The procedure that will be implemented for structural damage detection using the data obtained from the optimal sensor placement strategy is introduced and the information on structural damage is specified. The information entropy based method is applied to measure the uncertainties throughout the damage detection process with the use of the obtained data. Accordingly, a multi-objective optimal problem in terms of sensor placement is formulated. The optimal solution is determined as the one that provides equally most informative data for all objectives, and thus the data obtained is most informative for structural damage detection. To validate the effectiveness of the optimally determined sensor placement, damage detection is performed on different damage scenarios of the benchmark model using the noise-free and noise-corrupted measured information, respectively. The results show that in comparison with the existing in-service sensor deployment on the structure, the optimally determined one is capable of further enhancing the capability of damage detection.

• Nuclear Engineering and Technology
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• 제51권1호
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• pp.13-30
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• 2019

This paper presents the recent improvements in the DeCART code for HTGR analysis. A new 190-group DeCART cross-section library based on ENDF/B-VII.0 was generated using the KAERI library processing system for HTGR. Two methods for the eigen-mode adjoint flux calculation were implemented. An azimuthal angle discretization method based on the Gaussian quadrature was implemented to reduce the error from the azimuthal angle discretization. A two-level parallelization using MPI and OpenMP was adopted for massive parallel computations. A quadratic depletion solver was implemented to reduce the error involved in the Gd depletion. A module to generate equivalent group constants was implemented for the nodal codes. The capabilities of the DeCART code were improved for geometry handling including an approximate treatment of a cylindrical outer boundary, an explicit border model, the R-G-B checker-board model, and a super-cell model for a hexagonal geometry. The newly improved and implemented functionalities were verified against various numerical benchmarks such as OECD/MHTGR-350 benchmark phase III problems, two-dimensional high temperature gas cooled reactor benchmark problems derived from the MHTGR-350 reference design, and numerical benchmark problems based on the compact nuclear power source experiment by comparing the DeCART solutions with the Monte-Carlo reference solutions obtained using the McCARD code.

• 한국컴퓨터정보학회논문지
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• 제25권2호
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• pp.31-39
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• 2020

본 논문에서는 시계열 데이터를 기반으로 합성 벤치마크를 생성하는 기법을 소개한다. IoT 기기에서 측정되는 많은 데이터는 시간에 따른 수치 변화를 측정하는 시계열적 특성이 있다. 하지만 긴 기간 동안 측정되는 데이터를 일반화된 시계열 데이터로 모델링하기 힘든 문제점이 존재한다. 이런 문제를 개선하기 위해 본 논문에서는 BST-IGT 모델을 소개한다. BST-IGT 모델은 전체 데이터를 시계열 모델링이 쉬운 구간으로 분리하여 생성 데이터를 템플릿으로 수집하고 이를 기반으로 특성을 공유하거나 변형되는 새로운 합성 벤치마크를 생성한다. 제안된 모델링 기법을 이용하여 신규 벤치마크를 생성한 결과, 기존 데이터의 통계적 특성을 유지하는 합성 벤치마크와 다른 벤치마크와의 혼합으로 여러 특성을 가지는 벤치마크의 생성을 수행할 수 있었다.

• 전력전자학회:학술대회논문집
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• 전력전자학회 2003년도 춘계전력전자학술대회 논문집(1)
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• pp.446-450
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• 2003

This paper makes more stronger than original model about sending station fault and saves total construction cost to replace established six-pulse bridge by each six thyristor for DC-transmission. Also, varying of controller for sending station has a robust characteristics for harmonics and unbalanced faults. This paper is verified by simulation using EMTDC program. Comparing with the results of original model, this paper is proved superiority.

• 대한원격탐사학회지
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• 제39권4호
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• pp.459-466
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• 2023

In the last decade, artificial intelligence's dramatic advancement with the development of various deep learning techniques has significantly contributed to remote sensing fields and satellite image applications. Among many prominent areas, super-resolution research has seen substantial growth with the release of several benchmark datasets and the rise of generative adversarial network-based studies. However, most previously published remote sensing benchmark datasets represent spatial resolution within approximately 10 meters, imposing limitations when directly applying for super-resolution of small objects with cm unit spatial resolution. Furthermore, if the dataset lacks a global spatial distribution and is specialized in particular land covers, the consequent lack of feature diversity can directly impact the quantitative performance and prevent the formation of robust foundation models. To overcome these issues, this paper proposes a method to generate benchmark datasets by simulating the modulation transfer functions of the sensor. The proposed approach leverages the simulation method with a solid theoretical foundation, notably recognized in image fusion. Additionally, the generated benchmark dataset is applied to state-of-the-art super-resolution base models for quantitative and visual analysis and discusses the shortcomings of the existing datasets. Through these efforts, we anticipate that the proposed benchmark dataset will facilitate various super-resolution research shortly in Korea.