• 소성∙가공
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• 제22권6호
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• pp.310-316
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• 2013

Recently, numerical predictions of surface deflection based on curvature analysis have been developed. In the current study, a measure of surface deflection is proposed as the maximum variation of curvature difference between the panel and the tool in order to account for surfaces that have high curvature. The current study focused on the assessment of accuracy for the surface deflection prediction with the consideration of planar anisotropy. As an example, a shallow rectangular drawn part with rectangular embossing was considered. In terms of the proposed surface deflection measure, the maximum variation of curvature difference, the prediction with a planar anisotropic model shows better correspondence with experiment than the one using a normal anisotropic model.

• 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.

• International Journal of Advanced Culture Technology
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• 제11권4호
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• pp.310-316
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• 2023

This study aims to predict uncertain future scenarios that may unfold in South Korea in the near future, utilizing the theory of extreme events(X-events). A group of 32 experts, consisting of government emergency planning officers, was selected as the focus group to achieve this objective. Using the Focus Group Interview (FGI) technique, opinions were gathered from this focus group regarding potential X-events that may occur within the advanced science and technology domains over the next 10 years. The analysis of these opinions revealed that government emergency planning officers regarded the "Obsolescence of current technology and systems," particularly in the context of cyber network paralysis as the most plausible X-event within science and technology. They also put forth challenging and intricate opinions, including the emergence of new weapon systems and ethical concerns associated with artificial intelligence (AI). Given that X-events are more likely to emerge in unanticipated areas rather than those that are widely predicted, the results obtained from this study carry significant importance. However, it's important to note that this study is grounded in a limited group of experts, highlighting the necessity for subsequent research involving a more extensive group of experts. This research seeks to stimulate studies on extreme events at a national level and contribute to the preparation for future X-event predictions and strategies for addressing them.

• 한국산업융합학회 논문집
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• 제24권3호
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• pp.343-350
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• 2021

Unmanned aerial vehicles(UAV) photogrammetry provides a cost-effective option for collecting high-resolution 3D point clouds compared with UAV LiDAR and aerial photogrammetry. The main objectives of this study were to (1) validate the accuracy of 3D site model generated, and (2) determine the differences between Digital Elevation Model(DEM) and Digital Surface Model(DSM). In this study, DEM and DSM were shown to have varying degree of accuracy from observed data. The results indicated that the model predictions were considered tend to over- and under-estimated. The range of RMSE of DSM predicted was from 8.2 and 21.3 when compared with the observation. In addition, RMSE values were ranged from 10.2 and 25.8 to compare between DEM predicted and field data. The predict values resulting from the DSM were in agreement with the observed data compared to DEM calculation. In other words, it was determined that the DSM was a better suitable model than DEM. There is potential for enabling automated topography evaluation of the prior-harvest areas by using UAV technology.

• Nuclear Engineering and Technology
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• 제55권6호
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• pp.2172-2194
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• 2023

A variational nodal method (VNM) with unstructured-mesh is presented for solving steady-state and dynamic neutron diffusion equations. Orthogonal polynomials are employed for spatial discretization, and the stiffness confinement method (SCM) is implemented for temporal discretization. Coordinate transformation relations are derived to map unstructured triangular nodes to a standard node. Methods for constructing triangular prism space trial functions and identifying unique nodes are elaborated. Additionally, the partitioned matrix (PM) and generalized partitioned matrix (GPM) methods are proposed to accelerate the within-group and power iterations. Neutron diffusion problems with different fuel assembly geometries validate the method. With less than 5 pcm eigenvalue (k_eff) error and 1% relative power error, the accuracy is comparable to reference methods. In addition, a test case based on the kilowatt heat pipe reactor, KRUSTY, is created, simulated, and evaluated to illustrate the method's precision and geometrical flexibility. The Dodds problem with a step transient perturbation proves that the SCM allows for sufficiently accurate power predictions even with a large time-step of approximately 0.1 s. In addition, combining the PM and GPM results in a speedup ratio of 2-3.

• Steel and Composite Structures
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• 제44권5호
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• pp.691-705
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• 2022

Shear failure in reinforced concrete (RC) structures is very hazardous. This failure is rarely predicted and may occur without any prior signs. Accurate shear strength prediction of the RC members is challenging, and traditional methods have difficulty solving it. This study develops a JAYA-GBRT model based on the JAYA algorithm and the gradient boosting regression tree (GBRT) to predict the shear strength of RC slender beams without stirrups. Firstly, 484 tests are carefully collected and divided into training and test sets. Then, the hyperparameters of the GBRT model are determined using the JAYA algorithm and 10-fold cross-validation. The performance of the JAYA-GBRT model is compared with five well-known empirical models. The comparative results show that the JAYA-GBRT model (R² = 0.982, RMSE = 9.466 kN, MAE = 6.299 kN, µ = 1.018, and Cov = 0.116) outperforms the other models. Moreover, the predictions of the JAYA-GBRT model are globally and locally explained using the Shapley Additive exPlanation (SHAP) method. The effective depth is determined as the most crucial parameter influencing the shear strength through the SHAP method. Finally, a Graphic User Interface (GUI) tool and a web application (WA) are developed to apply the JAYA-GBRT model for rapidly predicting the shear strength of RC slender beams without stirrups.

• 대기
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• 제26권4호
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• pp.711-716
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• 2016

The dynamical model forecasts using state-of-art general circulation models (GCMs) have some limitations to simulate the real climate system since they do not depend on the past history. One of the alternative methods to correct model errors is to use the canonical correlation analysis (CCA) correction method. CCA forecasts at the present time show better skill than dynamical model forecasts especially over the midlatitudes. Model outputs are adjusted based on the CCA modes between the model forecasts and the observations. This study builds a canonical correlation prediction model for subseasonal (June) precipitation. The predictors are circulation fields over western North Pacific from the Global Seasonal Forecasting System version 5 (GloSea5) and observed snow cover extent over Eurasia continent from Climate Data Record (CDR). The former is based on simultaneous teleconnection between the western North Pacific and the East Asia, and the latter on lagged teleconnection between the Eurasia continent and the East Asia. In addition, we suggest a technique for improving forecast skill by applying the ensemble canonical correlation (ECC) to individual canonical correlation predictions.

• 한국자동차공학회논문집
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• 제21권3호
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• pp.1-14
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• 2013

In this paper, a finite element analysis technique of rolling stock models for collision-induced derailments was suggested using rolling contacts for wheel-rail interaction. The collision-induced derailments of rolling stock can be categorized into two patterns of wheel-climb and wheel-lift according to the friction direction between wheel flange and rail. The wheel-climb derailment types are classified as Climb-up, Climb/roll-over and Roll-over-C types, and the wheel-lift derailment types as Slip-up, Slip/roll-over and Roll-over-L types. To verify the rolling contact simulations for wheel-rail interaction, dynamic simulations of a single wheelset using Recurdyn of Functionbay and Ls-Dyna of LSTC were performed and compared for the 6-typical derailments. The collision-induced derailment simulation of the finite element model of KHST (Korean High Speed Train) was conducted and verified using the theoretical predictions of a simplified wheel-set model proposed for each derailment type.

• Structural Engineering and Mechanics
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• 제76권1호
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• pp.67-81
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• 2020

Pretensioned concrete (PC) is widely used in contemporary construction. Bond of prestressing strand is significant for composite-action between the strand and concrete in the transfer and flexural-bond zones of PC members. This study develops a new methodology for quantifying the bond of 18-mm prestressing strand in PC members based on results of a pullout test, the Standard Test for Strand Bond (STSB). The experimental program includes: (a) twenty-four pretensioned concrete beams, using a wide range of concrete compressive strength; and (b) twelve untensioned pullout specimens. By testing beams, the transfer length, flexural-bond length, and development length were all measured. In the STSB, the pullout forces for the strands were measured. Experimental results indicate a significant relationship between the bond of prestressing strand to the code-established design parameters, such as transfer length and development length. However, the code-predictions can be unconservative for the prestressing strands having a low STSB pullout force. Three simplified bond equations are proposed for the design applications of PC members.

• International Journal of Aeronautical and Space Sciences
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• 제18권1호
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• pp.144-153
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• 2017

In recent years, unmanned aerial vehicles (UAVs) have been developed and studied for various applications, including drone deliveries, broadcasting, scouting, crop dusting, and firefighting. To enable the wide use of UAVs, their exact aeroacoustic characteristics must be assessed. In this study, a noise prediction method for a ducted fan UAV with complicated geometry was developed. In general, calculation efficiency is increased by simulating a ducted fan UAV without the struts that fix the fuselage to the ducts. However, numerical predictions of noise and aerodynamics differ according to whether struts are present. In terms of aerodynamic performance, the total thrust with and without struts is similar owing to the tendency of the thrust of a blade to offset the drag of the struts. However, in aeroacoustic simulations, the strut effect should be considered in order to predict the UAV's noise because noise from the blades can be changed by the strut effect. Modelling of the strut effect revealed that the dominant tonal noises were closely correlated with the blade passage frequency of the experimental results. Based on the successful detection of noise sources from a ducted fan UAV system, using the proposed noise contribution contour, methods for noise reduction can be suggested by comparing numerical results with measured noise profiles.