• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.247-247
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• 2021

국내외적으로 하도 내의 흐름을 해석하기 위해 다양한 2차원 흐름해석 모형이 적용되고 있다. 2차원 흐름해석 모형은 기존의 1차원 흐름 해석 모형에서 해석하기 어려운 확산형 홍수파 해석에 강점을 가지고 있어 도심 하천의 외수 범람 예측 등에도 사용되고 있다. 하지만 복잡한 지형 형상을 어떻게 격자로 구성하는가에 따라 해석의 효율성과 정확성이 크게 좌우된다. 초기의 2차원 흐름해석 모형은 주로 정형격자 기반의 단순한 셀을 제작하여 구동되었다. 하지만 매우 빠른 유속과 복잡한 형상을 반영하기 위해서는 전체 격자를 조밀하게 구성할 필요가 있으므로 계산 효율이 떨어지는 문제점이 있다. 그렇기 때문에 대안으로 삼각망과 혼합망 등 비정형 격자를 사용하여 필요한 구역만 격자를 조밀하게 구성하는 방법을 사용하고 있지만 이 방법 또한 추가적인 계산 과정에 따른 계산 시간의 증가가 필연적이다. 따라서 최근에는 정형격자와 비정형격자에 대하여 wet-dry front matrix 최적화, 절점제거법 등 다양한 기법을 통하여 계산 효율을 향상시키고 있는 실정이다. 따라서 본 연구에서는 HLLC Rimann solver와 2차 정확도 기법인 MUSCL-Hancock Method를 적용한 유한체적기반 천수방정식을 기반으로 다양한 격자 구성에 따른 2차원 흐름해석 모형의 효율성 분석을 수행하고, 이를 통해 최적의 흐름해석 방안을 제시하고자 한다.

• Educational Technology International
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• v.13 no.2
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• pp.283-312
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• 2012

Problem-solving ability is one of the most important learning outcomes for students to compete and accomplish in a knowledge-based society. It has been empirically proven that visualization plays a central role in problem-solving. The best performing problem-solver might have a strong visualization tendency. However, there is little research as to what factors of visualization tendency primarily related to problem-solving ability according to phases of problem-solving. The purpose of this study is to identify the relationship between visualization tendency and problem-solving ability, to determine which factors of visualization tendency influence problem-solving ability in each phase of problem-solving, and to examine different problem-solving ability from the perspective of the levels of visualization tendency. This study has found out that visualization tendency has a significant correlation with problem-solving ability. Especially, Generative Visualization and Spatial-Motor Visualization as sub-visualization tendency were more strongly related to each phase of problem-solving. It indicates that visualization tendency to generate and operate mental processing can be considered a major cognitive skill to improve problem-solving ability. Furthermore, students who have high visualization tendency also have significantly higher problem-solving ability than students with low visualization tendency. It shows that the levels of visualization tendency can predict variables related to students' problem-solving ability.

• Computers and Concrete
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• v.32 no.4
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• pp.399-410
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• 2023

This study proposes a novel use of backpropagated Levenberg-Marquardt neural networks based on computational intelligence heuristics to comprehend the examination of hybrid nanoparticles on the flow of dusty liquid via stretched cylinder. A two-phase model is employed in the present work to describe the fluid flow. The use of desulphated nanoparticles of silver and molybdenum suspended in water as base fluid. The mathematical model represented in terms of partial differential equations, Implementing similarity transformationsis model is converted to ordinary differential equations for the analysis . By adjusting the particle mass concentration and curvature parameter, a unique technique is utilized to generate a dataset for the proposed Levenberg-Marquardt neural networks in various nanoparticle circumstances on the flow of dusty liquid via stretched cylinder. The intelligent solver Levenberg-Marquardt neural networks is trained, tested and verified to identify the nanoparticles on the flow of dusty liquid solution for various situations. The Levenberg-Marquardt neural networks approach is applied for the solution of the hybrid nanoparticles on the flow of dusty liquid via stretched cylinder model. It is validated by comparison with the standard solution, regression analysis, histograms, and absolute error analysis. Strong agreement between proposed results and reference solutions as well as accuracy provide an evidence of the framework's validity.

• Corrosion Science and Technology
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• v.23 no.2
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• pp.93-103
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• 2024

In the present work, a phase-field model for dendritic solidification is applied to hot-dip ZnAlMg coatings to elucidate the morphology of zinc dendrites and the solute segregation leading to the formation of eutectics. These aspects define the microstructure that conditions the corrosion resistance and the mechanical behaviour of the coating. Along with modelling phase transformation and solute diffusion, the implemented model is partially coupled with the tracking of crystal orientation in solid grains, thus allowing the effects of surface tension anisotropy to be considered in multi-dendrite simulations. For this purpose, the composition of a hot-dip ZnAlMg coating is assimilated to a dilute pseudo-binary system. 1D and 2D simulations of isothermal solidification are performed in a finite element solver by introducing nuclei as initial conditions. The results are qualitatively consistent with existing analytical solutions for growth velocity and concentration profiles, but the spatial domain of the simulations is limited by the required mesh refinement.

• Nuclear Engineering and Technology
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• v.56 no.3
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• pp.1002-1012
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• 2024

To remove insoluble fission products, which could possibly cause reactor instability and significantly reduce heat transfer efficiency from primary system of molten salt reactor, a helium bubbling method is employed into a passive molten salt fast reactor. In this regard, two-phase flow behavior of molten salt and helium bubbles was investigated experimentally because the helium bubbles highly affect the circulation performance of working fluid owing to an additional drag force. As the helium flow rate is controlled, the change of key thermal-hydraulic parameters was analyzed through a two-phase experiment. Simultaneously, to assess the applicability of numerical model for the analysis of two-phase flow behavior, the numerical calculation was performed using the OpenFOAM 9.0 code. The accuracy of the numerical analysis code was evaluated by comparing it with the experimental data. Generally, numerical results showed a good agreement with the experiment. However, at the high helium injection rates, the prediction capability for void fraction of helium bubbles was relatively low. This study suggests that the multiphaseEulerFoam solver in OpenFOAM code is effective for predicting the helium bubbling but there exists a room for further improvement by incorporating the appropriate drag flux model and the population balance equation.

• Nuclear Engineering and Technology
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• v.55 no.12
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• pp.4431-4446
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• 2023

A Multiphysics coupling framework, MPCORE, has been developed to analyze safety parameters using the best estimate codes. The framework contains neutron kinetics (NK), thermal hydraulics (TH), and fuel performance (FP) codes to analyze fuel burnup, radial power distribution, and coolant temperature (T_bc). Shuffling and rotation capabilities have been verified on the Watts Bar reactor for three cycles. This study focuses on two coupling approaches for TH and FP modules. The one-way coupling approach involves coupling the FP code with the NK code, providing no data to the TH modules but getting T_bc as boundary condition from TH module. The two-way coupling approach exchanges information from FP to TH modules, so that the simplified heat conduction solver of the TH module is not used. The power profile in both approaches does not differ significantly, but there is an impact on coolant and cladding parameters. The one-way coupling approach tends to over-predict the cladding hydrogen concentration (CHC). This research highlights the difference between one-way and two-way coupling on critical boron concentration, T_bc, CHC, oxide surface temperature, and pellet centerline temperature. Overall, MPCORE framework with two-way coupling provides a more accurate and reliable analysis of safety parameters for nuclear reactors.

• Journal of applied mathematics & informatics
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• v.42 no.5
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• pp.1195-1210
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• 2024

This research aims to determine an optimal (best) solution for transporting the logistics at a minimum cost from various sources to various destinations. We proposed a new algorithm for the initial basic feasible solution (IBFS). Developing a new IBFS is the first step towards finding the optimal solution. A new approach for the initial basic feasible solution that reduces iterations and produces the best answer in the initial process of the transportation issue. Different IBFS approaches have been generated in the literature review. Some statistical fundamentals, such as normal distribution and the root mean square technique, are employed to find new IBFS. A TP is transformed into a normal distribution, and penalties are determined using the root mean square method. Excel Solver is used to calculate normal distribution values. The second step involves using a stepping-stone approach to compute the optimum solution. The results of our study were calculated using numerical examples and contrasted with a few other methodologies, such as Vogel's approximation, the Continuous Allocation Method (CAM), the Supply Demand Repair Method (SDRM), and the Karagul-Sahin Approximation Method (KSAM). The conclusion of our proposed method gives more accurate results than the existing approach.

• Journal of the Korean Society of Visualization
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• v.22 no.2
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• pp.44-54
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• 2024

This study investigates the effectiveness of using a plasma actuator for active control of turbulent flow around a finite square cylinder. The primary objective is to analyze the impact of plasma actuators on flow separation and wake region characteristics, which are critical for reducing drag and suppressing vortex-induced vibrations. Direct Numerical Simulation (DNS) was employed to explore the flow dynamics at various operational parameters, including different actuation frequencies and voltages. The proposed methodology employs a neural network trained using the Proximal Policy Optimization (PPO) algorithm to determine optimal control policies for plasma actuators. This network is integrated with a computational fluid dynamics (CFD) solver for real-time control. Results indicate that this deep reinforcement learning (DRL)-based strategy outperforms existing methods in controlling flow, demonstrating robustness and adaptability across various flow conditions, which highlights its potential for practical applications.

• International Journal of Advanced Culture Technology
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• v.12 no.3
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• pp.471-479
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• 2024

Recent advancements in cloud computing have significantly increased its importance across various sectors. As sensors, devices, and customer demands have become more diverse, workloads have become increasingly variable and difficult to predict. Cloud providers, connected to multiple physical servers to support a range of applications, often over-provision resources to handle peak workloads. This approach results in inconsistent services, imbalanced energy usage, waste, and potential violations of service level agreements. In this paper, we propose a novel engine equipped with a scheduler based on the Hot-Threshold concept, aimed at optimizing resource usage and improving energy efficiency in cloud environments. We developed this engine to employ both proactive and reactive methods. The proactive method leverages workload estimate-based provisioning, while the reactive Hot-Cold Scheduler consists of a Predictor, Solver, and Processor, which together suggest an intelligent migration flow. We demonstrate that our approach effectively addresses existing challenges in terms of cost and energy consumption. By intelligently managing resources based on past user statistics, we provide significant improvements in both energy efficiency and service consistency.

• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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• v.22 no.1
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• pp.1-7
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• 2024

In this research, a detailed analysis of the decay heat contributions of both actinides and non-actinides (fission fragments) from spent nuclear fuel (SNF) was made after 50 GWd·tHM^-1 burnup of fresh uranium fuel with 4.5% enrichment lasted for 1,350 days. The calculations were made for a long storage period of 300 years divided into four sections 1, 10, 100, and 300 years so that we could study the decay heat and physical disposal ratios of radioactive waste in medium- and long-term storage periods. Fresh fuel burnup calculations were made using the code MCNP, while isotopic content and then decay heat were calculated using the built-in stiff equation solver in the MATLAB code. It is noted that only around 12 isotopes contribute more than 90% of the decay heat at all times. It is also noted that the contribution of actinides persists and is the dominant ether despite decreasing decay heat, while the effect of fission products decreases at a very rapid rate after about 40 years of storage.