• Nuclear Engineering and Technology
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• 제54권7호
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• pp.2670-2689
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• 2022

STREAM - a lattice transport calculation code with method of characteristics for the purpose of light water reactor analysis - has been developed by the Computational Reactor Physics and Experiment laboratory (CORE) of the Ulsan National Institute of Science and Technology (UNIST). Recently, efforts have been taken to develop a photon module in STREAM to assess photon heating and the influence of gamma photon transport on power distributions, as only neutron transport was considered in previous STREAM versions. A multi-group photon library is produced for STREAM based on the ENDF/B-VII.1 library with the use of the library-processing code NJOY. The developed photon solver for the computation of 2D and 3D distributions of photon flux and energy deposition is based on the method of characteristics like the neutron solver. The photon library and photon module produced and implemented for STREAM are verified on VERA pin and assembly problems by comparison with the Monte Carlo code MCS - also developed at UNIST. A short analysis of the impact of photon transport during depletion and thermal hydraulics feedback is presented for a 2D core also from the VERA benchmark.

• 대한기계학회논문집B
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• 제29권9호
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• pp.1057-1064
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• 2005

A conservative finite-volume numerical method using unstructured meshes, which is developed by the authors, is evaluated for its application to several 2-D benchmark problems using a variety of quadrilateral, triangular and hybrid meshes. The present pressure-based numerical method for unstructured mesh clearly demonstrates the same accuracy and robustness as that fur typical structured mesh.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2009년도 제40회 하계학술대회
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• pp.786_787
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• 2009

This paper proposes a novel multimodal optimization method, Coupling particles swarm optimization (PSO), to find all optima in design space. This method based on the conventional Particle Swarm Optimization with modifications. The Coupling method is applied to make a couple from main particle and then each couple of particles searches its own optimum by using non-stop-moving PSO. We tested out our method and other one, such as ClusteringParticle Swarm Optimization and Niche Particle Swarm Optimization, on three analytic functions. The Coupling Particle Swarm Optimization is also applied to solve a significant benchmark problem, the TEAM workshop benchmark problem 22

• 한국경영과학회지
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• 제26권2호
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• pp.59-68
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• 2001

The job shop scheduling problem is not only NP-hard, but is one of the well known hardest combinatorial optimization problems. The goal of this research is to develop an efficient scheduling method based on hybrid genetic algorithm to address job shop scheduling problem. In this scheduling method, generating method of initial population, new genetic operator, selection method are developed. The scheduling method based on genetic algorithm are tested on standard benchmark job shop scheduling problem. The results were compared with another genetic algorithm0-based scheduling method. Compared to traditional genetic, algorithm, the proposed approach yields significant improvement at a solution.

• KDI Journal of Economic Policy
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• 제40권2호
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• pp.23-52
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• 2018

Given the limited availability of data in South Korea, this study proposes a method by which to estimate regional capital stock by modifying the benchmark year method (BYM) and applies it to estimate regional net capital stock by sector in transport infrastructure. First, it estimates time-varying sectoral depreciation rates using the sectoral net capital stock and the investment amount for each period. Second, it estimates the net capital stock of each period using the net capital stock in the base year and the investment in each period. Third, in order to ensure that the sum of net capital stocks by region is equal to the nationwide estimate, the national estimates are allocated to each region according to the proportion of the values derived from the previous stage. The proposed method can alleviate well-known problems associated with conventional BYMs, specifically the upward bias and arbitrary choice of the depreciation rate.

• Structural Engineering and Mechanics
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• 제73권1호
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• pp.1-16
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• 2020

Finite elements based on the partition of unity (PU) approximation have powerful capabilities for p-adaptivity and solutions with high smoothness without remeshing of the domain. Recently, the PU approximation was successfully applied to the three-node shell finite element, properly eliminating transverse shear locking and showing excellent convergence properties and solution accuracy. However, the enrichment with the PU approximation results in a significant increase in the number of degrees of freedom; therefore, it requires greater computational cost, thus making it less suitable for practical engineering. To circumvent this disadvantage, we propose a new strategy to decrease the total number of degrees of freedom in the existing PU-based shell element, without loss of optimal convergence and accuracy. To alleviate the locking phenomenon, we use the method of mixed interpolation of tensorial components and perform convergence studies to show the accuracy and capability of the proposed shell element. The excellent performances of the new shell elements are illustrated in three benchmark problems.

• Nuclear Engineering and Technology
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• 제49권5호
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• pp.920-927
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• 2017

With ever-advancing computer technology, the Monte Carlo (MC) neutron transport calculation is expanding its application area to nuclear reactor transient analysis. Dynamic MC (DMC) neutron tracking for transient analysis requires efficient algorithms for delayed neutron generation, neutron population control, and initial condition modeling. In this paper, a new MC steady-state simulation method based on time-dependent MC neutron tracking is proposed for steady-state initial condition modeling; during this process, prompt neutron sources and delayed neutron precursors for the DMC transient simulation can easily be sampled. The DMC method, including the proposed time-dependent DMC steady-state simulation method, has been implemented in McCARD and applied for two-dimensional core kinetics problems in the time-dependent neutron transport benchmark C5G7-TD. The McCARD DMC calculation results show good agreement with results of a deterministic transport analysis code, nTRACER.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• 제25권3호
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• pp.93-106
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• 2021

In this paper, an efficient hybrid numerical method for solving two-asset option pricing problem is presented based on the Crank-Nicolson and the radial basis function methods. For this purpose, the two-asset Black-Scholes partial differential equation is considered. Also, the convergence of the proposed method are proved and implementation of the proposed hybrid method is specifically studied on Exchange and Call on maximum Rainbow options. In addition, this method is compared to the explicit finite difference method as the benchmark and the results show that the proposed method can achieve a noticeably higher accuracy than the benchmark method at a similar computational time. Furthermore, the stability of the proposed hybrid method is numerically proved by considering the effect of the time step size to the computational accuracy in solving these problems.

• Industrial Engineering and Management Systems
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• 제10권3호
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• pp.203-208
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• 2011

Job shop scheduling is well-known as one of the hardest combinatorial optimization problems and has been demonstrated to be NP-hard problem. In the past decades, several researchers have devoted their effort to develop evolutionary algorithms such as Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) for job shop scheduling problem. Differential Evolution (DE) algorithm is a more recent evolutionary algorithm which has been widely applied and shown its strength in many application areas. However, the applications of DE on scheduling problems are still limited. This paper proposes a one-stage differential evolution algorithm (1ST-DE) for job shop scheduling problem. The proposed algorithm employs random key representation and permutation of m-job repetition to generate active schedules. The performance of proposed method is evaluated on a set of benchmark problems and compared with results from an existing PSO algorithm. The numerical results demonstrated that the proposed algorithm is able to provide good solutions especially for the large size problems with relatively fast computing time.

• 한국원자력학회:학술대회논문집
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• 한국원자력학회 1996년도 춘계학술발표회논문집(1)
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• pp.142-147
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• 1996

The analytic function expansion nodal (AFEN) method has been successfully applied to two-group neutron diffusion problems. In this paper, the AFEN method is extended to solve general multigroup equations for any type of geometries. Also, a suite of new nodal codes based on the extended AFEN theory is developed for hexagonal-z geometry and applied to several benchmark problems. Numerical results obtained attest to their accuracy and applicability to practical problems.