• Nuclear Engineering and Technology
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• 제52권5호
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• pp.956-963
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• 2020

Dose optimization for Radioactive Occupational Personal (ROP) is an important subject in nuclear and radiation safety field. The geometric environment of a nuclear facility is complex and the work area is radioactive, so traditional navigation model and radioactive data field cannot form an effective environment model for dose assessment and dose optimization. The environment model directly affects dose assessment and indirectly affects dose optimization, this is an urgent problem needed to be solved. Therefore, this paper focuses on an environment model used for Dose Assessment and Dose Optimization (DA&DO). We designed a multi-layer radiation field coupling modeling method, and then explored the influence of the environment model to DA&DO by virtual simulation. Then, a simulation test is done, the multi-layer radiation field coupling model for nuclear facilities is demonstrated to be effective for dose assessment and dose optimization through the experiments and analysis.

• 한국해양공학회지
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• 제35권2호
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• pp.121-130
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• 2021

In this study, a computational fluid dynamics (CFD) simulation based on an Eulerian-Eulerian approach was used to evaluate the mixing performance of a mud agitator through the distribution of bulk particles. Firstly, the commercial CFD software Star-CCM+ was verified by performing numerical simulations of single-phase water mixing problems in an agitator with various turbulence models, and the simulation results were compared with an experiment. The standard model was selected as an appropriate turbulence model, and a grid convergence test was performed. Then, a simulation of the liquid-solid multi-phase mixing in an agitator was simulated with different multi-phase interaction models, and lift and drag models were selected. In the case of the lift model, the results were not significantly affected, but Syamlal and O'Brien's drag model showed more reasonable results with respect to the experiment. Finally, with the properly determined simulation conditions, a multi-phase flow simulation of a mud agitator was performed to predict the mixing time and spatial distribution of solid particles. The applicability of the CFD multi-phase simulation for the practical design of a mud agitator was confirmed.

• Journal of Power Electronics
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• 제19권4호
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• pp.980-988
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• 2019

When compared with traditional power frequency generators, the frequency of a super high-speed permanent magnet generator (SHSPMG) is a lot higher. In order to study the influence of frequency on the electromagnetic field of SHSPMGs, a 60000rpm, 117kW SHSPMG was taken as a research object. The two-dimensional finite element model of the generator was established, and the two-dimensional transient field of the generator was simulated. In addition, a test platform of the generator was set up and tested. The reliability of the simulation was verified by comparing the experiment data with that of the simulation. Then the generator electromagnetic field under different frequencies was studied, and the influence mechanism of frequency on the generator electromagnetic field was revealed. The generator loss, voltage regulation rate, torque and torque ripple were analyzed under the rated active power load and different frequencies. The influences of frequency on the eddy current density, loss, voltage regulation rate and torque ripple of the generator were obtained. These conclusions can provide some reference for the design and optimization of SHSPMGs.

• Geomechanics and Engineering
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• 제17권6호
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• pp.565-572
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• 2019

Spatial variability is an inherent characteristic of soil, and auto-correlation length (ACL) is a very important parameter in the reliability or probabilistic analyses of geotechnical engineering that consider the spatial variability of soils. Current methods for estimating the ACL need a large amount of laboratory or in-situ experiments, which is a great obstacle to the application of random field theory to geotechnical reliability analysis and design. To estimate the ACL reasonably and efficiently, we propose a micro-structure based numerical simulation method. The quartet structure generation set algorithm is used to generate stochastic numerical micro-structure of soils, and scanning electron microscope test of soil samples combined with digital image processing technique is adopted to obtain parameters needed in the QSGS algorithm. Then, 2-point correlation function is adopted to calculate the ACL based on the generated numerical micro-structure of soils. Results of a case study shows that the ACL can be estimated efficiently using the proposed method. Sensitivity analysis demonstrates that the ACL will become stable with the increase of mesh density and model size. A model size of $300{\times}300$ with a grid size of $1{\times}1$ is suitable for the calculation of the ACL of clayey soils.

• 자동차안전학회지
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• 제11권2호
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• pp.29-34
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• 2019

This paper presents a new method for construction of a static obstacle map. A static obstacle is important since it is utilized to path planning and decision. Several established approaches generate static obstacle map by grid method and counting algorithm. However, these approaches are occasionally ineffective since the density of LiDAR layer is low. Our approach solved this problem by applying probability theory. First, we converted all LiDAR point to Gaussian distribution to considers an uncertainty of LiDAR point. This Gaussian distribution represents likelihood of obstacle. Second, we modeled dynamic transition of a static obstacle map by adopting the Hidden Markov Model. Due to the dynamic characteristics of the vehicle in relation to the conditions of the next stage only, a more accurate map of the obstacles can be obtained using the Hidden Markov Model. Experimental data obtained from test driving demonstrates that our approach is suitable for mapping static obstacles. In addition, this result shows that our algorithm has an advantage in estimating not only static obstacles but also dynamic characteristics of moving target such as driving vehicles.

• Nuclear Engineering and Technology
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• 제51권5호
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• pp.1218-1230
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• 2019

A sub-channel solver, named ${\underline{S}}teady$ and ${\underline{T}}ransient$ ${\underline{A}}nalyzer$ for ${\underline{R}}eactor$ ${\underline{T}}hermal$ hydraulics (START), has been developed using the homogenous model for two-phase conditions of light water reactors. The code is developed as a fast and accurate TH-solver for coupled and multi-physics calculations. START has been validated against the NUPEC PWR Sub-channel and Bundle Test (PSBT) database. Tests like single-channel quality and void-fraction for steady state, outlet fluid temperature for steady state, rod-bundle quality and void-fraction for both steady state and transient conditions have been analyzed and compared with experimental values. Results reveal a good accuracy of solution for both steady state and transient scenarios. Axially different values for turbulent mixing coefficient are used based on different grid-spacer types. This provides better results as compared to using a single value of turbulent mixing coefficient. Code-to-code evaluation of PSBT results by the START code compares well with other industrial codes. The START code has been parallelized with the OpenMP algorithm and its numerical performance is evaluated with a large whole PWR core. Scaling study of START shows a good parallel performance.

• 한국기계가공학회지
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• 제20권1호
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• pp.95-102
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• 2021

Analysis of the fracture surface is one of the most important methods for determining the cause of equipment structural failure. Whether structural failure is caused by impact or fatigue is necessary information in industrial fields. For ferrous and non-ferrous metal materials, two fracture phenomena are generated on the fracture surface: ductile and brittle fractures. In this study, machine learning predicts whether the fracture is based on ductile or brittle when structurural failure is caused by impact. The K-means algorithm calculates this ratio by clustering the brittle and ductile fracture data from a photograph of the impact fracture surface, unlike the existing method, which calculates the fracture surface ratio by comparison with the grid type or the reference fracture surface shape.

• 천문학회지
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• 제53권6호
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• pp.169-179
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• 2020

Emission features formed through Raman scattering with atomic hydrogen provide unique and crucial information to probe the distribution and kinematics of a thick neutral region illuminated by a strong far-ultraviolet radiation source. We introduce a new 3-dimensional Monte-Carlo code in order to describe the radiative transfer of line photons that are subject to Raman and Rayleigh scattering with atomic hydrogen. In our Sejong Radiative Transfer through Raman and Rayleigh Scattering (STaRS) code, the position, direction, wavelength, and polarization of each photon is traced until escape. The thick neutral scattering region is divided into multiple cells with each cell being characterized by its velocity and density, which ensures flexibility of the code in analyzing Raman-scattered features formed in a neutral region with complicated kinematics and density distribution. To test the code, we revisit the formation of Balmer wings through Raman scattering of the far-UV continuum near Lyβ and Lyγ in a static neutral region. An additional check is made to investigate Raman scattering of O vi in an expanding neutral medium. We find a good agreement of our results with previous works, demonstrating the capability of dealing with radiative transfer modeling that can be applied to spectropolarimetric imaging observations of various objects including symbiotic stars, young planetary nebulae, and active galactic nuclei.

• Nuclear Engineering and Technology
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• 제53권8호
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• pp.2708-2715
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• 2021

The Multi-Purpose Overload Robot (CMOR) is a key subsystem of China Fusion Engineering Test Reactor (CFETR) remote handling system. Due to the long cantilever and large loads of the CMOR, it has a large rigid-flexible coupling deformation that results in a poor position accuracy of the end-effector. In this study, based on the Levenberg-Marquardt algorithm, the spatial grid, and the linearized variable load principle, a variable parameter compensation model was designed to identify the parameters of the CMOR's kinematics models under different loads and at different poses so as to improve the trajectory tracking accuracy. Finally, through Adams-MATLAB/Simulink, the trajectory tracking accuracy of the CMOR's rigid-flexible coupling model was analyzed, and the end position error exceeded 0.1 m. After the variable parameter compensation model, the average position error of the end-effector became less than 0.02 m, which provides a reference for CMOR error compensation.

• International Journal of Internet, Broadcasting and Communication
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• 제14권3호
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• pp.285-291
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• 2022

The number of people enrolling in universities is rising due to the simplicity of applying and the benefit of earning a bachelor's degree. However, the on-time graduation rate has declined since plenty of students fail to complete their courses and take longer to get their diplomas. Even though there are various reasons leading to the aforementioned problem, it is crucial to emphasize the cause originating from the management and care of learners. In fact, understanding students' difficult situations and offering timely Number of Test data and advice would help prevent college dropouts or graduate delays. In this study, we present a machine learning-based method for early detection at-risk students, using data obtained from graduates of the Faculty of Information Technology, Dainam University, Vietnam. We experiment with several fundamental machine learning methods before implementing the parameter optimization techniques. In comparison to the other strategies, Random Forest and Grid Search (RF&GS) and Random Forest and Random Search (RF&RS) provided more accurate predictions for identifying at-risk students.