• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.4
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• pp.222-234
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• 2021

Airborne-pests can be introduced into Korea from overseas areas by wind, which can cause considerable damage to major crops. Meteorological models have been used to estimate the wind trajectories of airborne insects. The objective of this study is to analyze the effect of input settings on the prediction of areas where airborne pests arrive by wind. The wind trajectories were predicted using the HYbrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model. The HYSPLIT model was used to track the wind dispersal path of particles under the assumption that brown plant hopper (Nilaparvata lugens) was introduced into Korea from sites where the pest was reported in China. Meteorological input data including instantaneous and average wind speed were generated using meso-scale numerical weather model outputs for the domain where China, Korea, and Japan were included. In addition, the calculation time intervals were set to 1, 30, and 60 minutes for the wind trajectory calculation during early June in 2019 and 2020. It was found that the use of instantaneous and average wind speed data resulted in a considerably large difference between the arrival areas of airborne pests. In contrast, the spatial distribution of arrival areas had a relatively high degree of similarity when the time intervals were set to be 1 minute. Furthermore, these dispersal patterns predicted using the instantaneous wind speed were similar to the regions where the given pest was observed in Korea. These results suggest that the impact assessment of input settings on wind trajectory prediction would be needed to improve the reliability of an approach to predict regions where airborne-pest could be introduced.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.47 no.1
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• pp.26-34
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• 2019

In this paper, a coarse lunar soil model is developed using discrete element method and its computed physical properties are compared with those of the actual lunar soil for its validation. The surface of the actual moon consists of numerous craters and rocks of various sizes, and it is covered with fine dry soil which seriously affects the landing stability of the lunar lander. Therefore, in consideration of the environment of the lunar regolith, the lunar soil is realized using discrete element method. To validate the coarse model of lunar soil, the simulations of the indentation test and the direct shear test are performed to check the physical properties(indentation depth, cohesion stress, internal friction angle). To examine the performance of the proposed model, the drop simulation of finite element model of single-leg landing gear is performed on proposed soil models with different particle diameters. The impact load delivered to the strut of the lander is compared to test results.

• Fashion & Textile Research Journal
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• v.13 no.5
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• pp.790-796
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• 2011

This study was designed to investigate the influence of ratio of anionic/nonionic surfactant mixture on detergency of particulate soil under various solutions. The detergency of the particulate soil was determined by adhesion of particle to fabric and its removal from fabric separately. The PET fabric and ${\alpha}-Fe_2O_3$were used as materials of textile and model of particulate soil, respectively. The detergency was investigated as a function of surfactants concentration, ionic strength, kinds of electrolyte and mole numbers of oxyethylene ether of nonionic surfactant in different ratio of anionic/nonionic surfactant mixture. Although some deviations exist, the adhesion of particle to fabric generally increased with decreasing its removal from fabric. The detergency of particulate soil on PET fabric was relatively higher in anionic/nonionic surfactant mixed solution than in each single surfactant solution, but the influence of ratio of anionic/nonionic surfactant mixture on detergency of particulate soil was low. Generally the detergency of particulate soil on fabric was at its maximum at 0.1% surfactant concentration, $1{\times}10^{-3}$ ionic strength, $Na_5P_3O_{10}$ electrolytes and 10 mole numbers of oxyethylene ether of nonionic surfactant, regardless of ratio of anionic/nonionic surfactant mixture.

• Nuclear Engineering and Technology
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• v.52 no.11
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• pp.2479-2490
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• 2020

We performed experiments to measure a single-phase upward flow in a 5 × 5 rod bundle with spacer grids using a particle image velocimetry, focusing on the crossflow. The Reynolds number based on the hydraulic diameter and the bulk velocity is 10,000. The ratio of pitch between rods and rod diameter is 1.4 and spacer grid is installed periodically. The turbulence in the rod bundle results from the combination of a forced mixing and natural mixing. The forced mixing by the spacer grid persists up to 10D_h from the spacer grid, while the natural mixing is attributed to the crossflow between adjacent subchannels. The combined effects contribute to a sinusoidal distribution of the time-averaged stream-wise velocity along the lateral direction, which is relatively weak right behind the spacer grid as well as in the gap. The streamwise and lateral turbulence intensities are stronger right behind the spacer grid and in the gap. Based on these findings, we newly defined a modified mixing coefficient as the ratio of the lateral turbulence intensity to the time-averaged streamwise velocity, which shows a spatial variation. Finally, we compared the developed model with the measured data, which shows a good agreement with each other.

• Journal of Power Electronics
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• v.16 no.3
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• pp.1097-1109
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• 2016

Fault detection and isolation are related to system monitoring, identifying when a fault has occurred, and determining the type of fault and its location. Fault detection is utilized to determine whether a problem has occurred within a certain channel or area of operation. Fault detection and diagnosis have become increasingly important for many technical processes in the development of safe and efficient advanced systems for supervision. This paper presents an integrated technique for fault diagnosis and classification for open- and short-circuit faults in three-phase inverter circuits. Discrete wavelet transform and principal component analysis are utilized to detect the discontinuity in currents caused by a fault. The features of fault diagnosis are then extracted. A fault dictionary is used to acquire details about transistor faults and the corresponding fault identification. Fault classification is performed with a fuzzy logic system and relevance vector machine (RVM). The proposed model is incorporated with a set of optimization techniques, namely, evolutionary particle swarm optimization (EPSO) and cuckoo search optimization (CSO), to improve fault detection. The combination of optimization techniques with classification techniques is analyzed. Experimental results confirm that the combination of CSO with RVM yields better results than the combinations of CSO with fuzzy logic system, EPSO with RVM, and EPSO with fuzzy logic system.

• Journal of Information Processing Systems
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• v.15 no.3
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• pp.682-693
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• 2019

The traditional classification methods mostly assume that the data for class distribution is balanced, while imbalanced data is widely found in the real world. So it is important to solve the problem of classification with imbalanced data. In Mahalanobis-Taguchi system (MTS) algorithm, data classification model is constructed with the reference space and measurement reference scale which is come from a single normal group, and thus it is suitable to handle the imbalanced data problem. In this paper, an improved method of MTS-CBPSO is constructed by introducing the chaotic mapping and binary particle swarm optimization algorithm instead of orthogonal array and signal-to-noise ratio (SNR) to select the valid variables, in which G-means, F-measure, dimensionality reduction are regarded as the classification optimization target. This proposed method is also applied to the financial distress prediction of Chinese listed companies. Compared with the traditional MTS and the common classification methods such as SVM, C4.5, k-NN, it is showed that the MTS-CBPSO method has better result of prediction accuracy and dimensionality reduction.

• Current Optics and Photonics
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• v.6 no.5
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• pp.479-488
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• 2022

To account for the internal thermal effects of solid-state lasers, a method using a back propagation (BP) neural network integrated with a particle swarm optimization (PSO) algorithm is developed, which is a new wavefront distortion correction technique. In particular, by using a slab laser model, a series of fiber pumped sources are employed to form a controlled array to pump the gain medium, allowing the internal temperature field of the gain medium to be designed by altering the power of each pump source. Furthermore, the BP artificial neural network is employed to construct a nonlinear mapping relationship between the power matrix of the pump array and the thermally induced wavefront aberration. Lastly, the suppression of thermally induced wavefront distortion can be achieved by changing the power matrix of the pump array and obtaining the optimal pump light intensity distribution combined using the PSO algorithm. The minimal beam quality β can be obtained by optimally distributing the pumping light. Compared with the method of designing uniform pumping light into the gain medium, the theoretically computed single pass beam quality β value is optimized from 5.34 to 1.28. In this numerical analysis, experiments are conducted to validate the relationship between the thermally generated wavefront and certain pumping light distributions.

• Nuclear Engineering and Technology
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• v.55 no.12
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• pp.4395-4407
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• 2023

Bubble columns are widely encountered in several industries, especially in the field of nuclear safety. The Eulerian-Eulerian and the Eulerian-Lagrangian methods are commonly used to investigate bubble columns. Eulerian approaches require additional tasks such as strict volume conservation at the interface and a predefined well-structured grid. In contrast, the Lagrangian approach can be easily implemented. Hence, we introduce a fully Lagrangian approach for the simulation of bubble columns using the discrete bubble model (DBM) and moving particle semi-implicit (MPS) methods. Additionally, we propose a rigorous method to estimate the volume fraction accurately, and verified it through experimental data and analytical results. The MPS method was compared with the experimental data of Dambreak. The DBM was verified by analyzing the terminal velocity of a single bubble for each bubble size. It agreed with the analytical results for each of the four drag correlations. Additionally, the improved method for calculating the volume fraction showed agreement with the Ergun equation for the pressure drop in a packed bed. The implemented MPS-DBM was used to simulate the bubble column, and the results were compared with the experimental results. We demonstrated that the MPS-DBM was in quantitative agreement with the experimental data.

• Water Engineering Research
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• v.6 no.2
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• pp.49-61
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• 2005

This paper presents the numerical study to examine characteristics of fluid flow and solute transport in a rough fracture subject to effective normal stresses. The aperture distribution is generated by using the self-affine fractal model. In order to represent a nonlinear relationship between the supported normal stress and the fracture aperture, we combine a simple mechanical model with the local flow model. The solute transport is simulated using the random walk particle following algorithm. Results of numerical simulations show that the flow is significantly affected by the geometry of aperture distribution varying with the effective normal stress level while it is slightly affected by the fractal dimension that determines the degree of the fracture surface roughness. However, solute transport is influenced by the effective normal stress as well as the fracture surface roughness.

• Membrane Journal
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• v.12 no.4
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• pp.207-215
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• 2002

The hindered diffusion in confined spaces is an important phenomenon to understand in a micro-scale the filtration mechanism determined by the particle motion in membrane pores. Compared to the case of spherical colloids, both the theoretical investigations and the experiments on the hindered diffusion of polyelectrolytes is actually more difficult, due to lots of relevant parameters resulting from the complicated conformational properties of the polyelectrolyte chain. We have successfully performed the Brownian dynamics simulations upon a single polyeiectrolyte confined in a slit-like pore, where a coarse-grained bead-spring model incorporated with Debye-Huckel interaction is properly adopted. For the given sizes of both the polyelectrolyte and the pore width, the hindered diffusion coefficient decreases as the solution ionic concentration decreases. It is evident that a charge effect of the pore wall enhances the hindered diffusion of polyelectrolyte. Simulation results allow us to make sense of the diffusive transport through the micro-pore, which is restricted by the influences of the steric hindrance of polyelectrolytes as well as the electrostatic repulsion between the polyelectrolytes and pore wall.