• Journal of Nutrition and Health
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• 제50권5호
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• pp.494-503
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• 2017

Purpose: The purpose of this study was to evaluate the effects of an eco-friendly foodservice program at a high school on dietary behaviors of students, awareness of importance of eco-friendly activities, and foodservice satisfaction. Methods: The survey was conducted with students at two schools in Gyeonggi, Korea. A total of 576 of 650 students were used for this study. Data were analyzed using Chi-square test, independent t-test, and factor analysis to test the two group's differences. Results: The practices of 'eat balanced meals' or 'finish all food on the plate' scored high (p < 0.001) in students that participated in the eco-friendly foodservice program than those who did not. Regarding awareness of the importance of eco-friendly activities, all attributes scored higher in students that participated in the eco-friendly foodservice program. All attributes for satisfaction except two scored higher (p < 0.05) in students that participated in the eco-friendly foodservice program. Principal Components Analysis (PCA) of the correlation showed that high subjective income status was positively associated with foodservice satisfaction. Conclusion: Students that participated in the eco-friendly foodservice program are highly aware of the importance of eco-friendly activities. They demonstrate more positive dietary behaviors and higher awareness of the importance of eco-friendly programs with greater foodservice satisfaction.

• 대한조선학회논문집
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• 제42권5호
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• pp.528-533
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• 2005

A mono-static high frequency acoustic target strength analysis scheme was developed for underwater targets, based on the far-field Kirchhoff approximation. Au adaptive triangular beam method and a concept of virtual surface were adopted for considering the effect of hidden surfaces and multiple reflections of an underwater target, respectively. A test of a simple target showed that the suggested hidden surface removal scheme is valid. Then some numerical analyses, for several underwater targets, were carried out; (1) for several simple underwater targets, like sphere, square plate, cylinder, trihedral corner reflector, and (2) for a generic submarine model, The former was exactly coincident with the theoretical results including beam patterns versus azimuth angles, and the latter suggested that multiple reflections have to be considered to estimate more accurate target strength of underwater targets.

• International Journal of Naval Architecture and Ocean Engineering
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• 제4권1호
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• pp.20-32
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• 2012

A software system for a complex object scattering analysis, named SYSCOS, has been developed for a systematic radar cross section (RCS) analysis and reduction design. The system is based on the high frequency analysis methods of physical optics, geometrical optics, and physical theory of diffraction, which are suitable for RCS analysis of electromagnetically large and complex targets as like naval ships. In addition, a direct scattering center analysis function has been included, which gives relatively simple and intuitive way to discriminate problem areas in design stage when comparing with conventional image-based approaches. In this paper, the theoretical background and the organization of the SYSCOS system are presented. To verify its accuracy and to demonstrate its applicability, numerical analyses for a square plate, a sphere and a cylinder, a weapon system and a virtual naval ship have been carried out, of which results have been compared with analytic solutions and those obtained by the other existing software.

• 설비공학논문집
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• 제18권4호
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• pp.304-311
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• 2006

Experiments on evaporative spray cooling on the square plate heaters with plain or micro-porous coated surfaces were performed in this study. Micro-porous coated surfaces were made by using DOM [Diamond particle, Omegabond 101, Methyl-Ethyl-Keton] method. In case of purely air-jet cooling, the micro-porous coating doesn't affect the cooling capacity. In spray cooling three different flow patterns (complete wetting, evaporative wetting, dryout) are observed on both plain and micro-porous coated surfaces. The effects of various operating conditions, such as water flow rate, particle size, and coating thickness were investigated on the micro-porous coated surfaces. It is found that the level of surface wetting is an important factor to determine the performance of spray cooling. It depends on the balance between absorbed liquid amount by capillary force over porosity and the evaporative amount. The micro-porous coated surface has largest cooling capacity, especially in the evaporative wetting zone. It is found that the effects of liquid flow rate and coating thickness are significant in evaporative wetting zone, but are not in complete wetting and dryout zones.

• 한국구조물진단유지관리공학회 논문집
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• 제23권3호
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• pp.96-102
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• 2019

강바닥판 교량의 교면 포장에 $240^{\circ}C$ 이상의 온도에서 포설 되는 구스 아스팔트 가 적용되는 경우, 구조물에 발생하는 열 영향의 검토를 수행하지만, 수치해석에 적용 가능한 열원 데이터에 대한 연구는 미흡하여 단순화된 온도 하중을 절점 하중으로 사용하고 있다. 이에 본 연구에서는 구스 아스팔트 포장 시 계측된 온도 데이터를 이용하여 비록 제한적이지만 평판요소에 직접 재하 가능한 열원 방정식을 구성하여 제시하였으며 간략한 수치해석을 통해 그 타당성을 확인하였다.

• Structural Engineering and Mechanics
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• 제70권5호
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• pp.535-549
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• 2019

This study aimed to develop a high-order shear deformation theory to predict the free vibration of hybrid cross-ply laminated plates under different boundary conditions. The equations of motion for laminated hybrid rectangular plates are derived and obtained by using Hamilton's principle. The closed-form solutions of anti-symmetric cross-ply and angle-ply laminates are obtained by using Navier's solution. To assess the validity of our method, we used the finite element method. Firstly, the analytical and the numerical implementations were validated for an antisymmetric cross-ply square laminated with available results in the literature. Then, the effects of side-to-thickness ratio, aspect ratio, lamination schemes, and material properties on the fundamental frequencies for different combinations of boundary conditions of hybrid composite plates are investigated. The comparison of the analytical solutions with the corresponding finite element simulations shows the good accuracy of the proposed analytical closed form solution in predicting the fundamental frequencies of hybrid cross-ply laminated plates under different boundary conditions.

• Geomechanics and Engineering
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• 제18권1호
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• pp.21-27
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• 2019

Rockburst disasters pose serious threat to mining safety and underground excavation, especially in China, resulting in massive life-wealth loss and even compulsive closed-down of some coal mines. To investigate the mechanism of rockbursts that occur under a state of static forces, a stress model with sidewall as prototype was developed and verified by a group of laboratory experiments and numerical simulations. In this model, roadway sidewall was simplified as a square plate with axial compression and end (horizontal) restraints. The stress field was solved via the Airy stress function. To track the "closeness degree" of the stress state approaching the yield limit, an unbalanced force F was defined based on the Mohr-Coulomb yield criterion. The distribution of the unbalanced force in the plane model indicated that only the friction angle above a critical value could cause the first failure on the coal in the deeper of the sidewall, inducing the occurrence of rockbursts. The laboratory tests reproduced the rockburst process, which was similar to the prediction from the theoretical model, numerical simulation and some disaster scenes.

• Nuclear Engineering and Technology
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• 제53권6호
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• pp.1796-1809
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• 2021

The subchannel of a research reactor used to generate high power density is designed to be narrow and rectangular and comprises plate-type fuels operating under downward flow conditions. Critical heat flux (CHF) is a crucial parameter for estimating the safety of a nuclear fuel; hence, this parameter should be accurately predicted. Here, machine learning is applied for the prediction of CHF in a narrow rectangular channel. Although machine learning can effectively analyze large amounts of complex data, its application to CHF, particularly for narrow rectangular channels, remains challenging because of the limited flow conditions available in existing experimental databases. To resolve this problem, we used four CHF correlations to generate pseudo-data for training an artificial neural network. We also propose a network architecture that includes pre-training and prediction stages to predict and analyze the CHF. The trained neural network predicted the CHF with an average error of 3.65% and a root-mean-square error of 17.17% for the test pseudo-data; the respective errors of 0.9% and 26.4% for the experimental data were not considered during training. Finally, machine learning was applied to quantitatively investigate the parametric effect on the CHF in narrow rectangular channels under downward flow conditions.

• Steel and Composite Structures
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• 제38권6호
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• pp.637-656
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• 2021

The component-based method is widely used to analyze the initial stiffness of joint in steel structures. In this study, an analytical component model for determining the column face stiffness of square or rectangular hollow section (SHS/RHS) subjected to tension was established, focusing on endplate connections. Equations for calculating the stiffness of the SHS/RHS column face in bending were derived through regression analysis using numerical results obtained from a finite element model database. Because the presence of bolt holes decreased the bending stiffness of the column face, this effect was calculated using a novel plate-spring-based model through numerical analysis. The developed component model was first applied to predict the bending stiffness of the SHS column face determined through tests. Furthermore, this model was incorporated into the component-based method with other effective components, e.g., bolts under tension, to determine the tensile stiffness of the T-stub connections, which connects the SHS column, and the initial rotational stiffness of the joints. A comparison between the model predictions, test data, and numerical results confirms that the proposed model shows satisfactory accuracy in evaluating the bending stiffness of SHS column faces.

• Smart Structures and Systems
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• 제32권2호
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• pp.83-99
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• 2023

The temperature prediction approaches of three important locations in an operational longitudinal slab track-bridge structure by using three typical neural network methods based on the field measuring platform of four meteorological factors and internal temperature. The measurement experiment of four meteorological factors (e.g., ambient temperature, solar radiation, wind speed, and humidity) temperature in the three locations of the longitudinal slab and base plate of three important locations (e.g., mid-span, beam end, and Wide-Narrow Joint) were conducted, and then their characteristics were analyzed, respectively. Furthermore, temperature prediction effects of three locations under five various meteorological conditions are tested by using three neural network methods, respectively, including the Artificial Neural Network (ANN), the Long Short-Term Memory (LSTM), and the Convolutional Neural Network (CNN). More importantly, the predicted effects of solar radiation in four meteorological factors could be identified with three indicators (e.g., Root Means Square Error, Mean Absolute Error, Correlation Coefficient of R2). In addition, the LSTM method shows the best performance, while the CNN method has the best prediction effect by only considering a single meteorological factor.