This paper is a study to improve the energy harvesting output of a TENG(Triboelectric nanogenerator) driven by wind power using fine PTFE(Polytetrafluoroethylene) flakes. The structure of the nanogenerator was manufactured in the cylindrical structure, Al(Aluminium) was attached to the inner wall of the cylinder and the PTFE flakes were rotated by the wind inside the cylinder. The number of contact and separation motions was increased as there are multiple PTFE flakes, resulting in improvement of the harvesting output. Through this, it was evaluated to the energy harvesting output characteristics according to the change in the number of PTFE flakes. Up to the optimum, the energy collection efficiency shows the linear correlation with the increase in PTFE flakes and decreases after that. As the PTFE flakes are more than the optimum, the lowering in the harvesting output is induced by obstructing the flow of wind inside the cylinder.

공간 샘플링은 공간모델링 연구에 활용되어 샘플링 비용을 줄이면서 모델링의 효율성을 높이는 역할을 한다. 농업분야에서는 기후변화 영향을 예측하고 평가하기 위한 고해상도 공간자료 기반 모델링에 대한 연구 수요가 빠르게 증가하고 있으며, 이에 따라 공간 샘플링의 필요성과 중요성이 증가하고 있다. 본 연구는 국내 농지 공간샘플링 연구를 통해 농업분야 기후변화연구의 공간자료 활용의 효율성을 제고하고자 하였다. 본 연구는 층화랜덤샘플링 을 기반으로 하였으며, 1 km 해상도의 농지 공간격자자료 모집단 (11,386개 격자)에 대해서 RCP 시나리오별 (RCP 4.5/8.5) 연대별 (2030/2050/2080년대) 공간샘플링을 설 계하였다. 국내 농지는 기상 및 토양 특성에 따라 계층화 되었으며, 샘플링 효율 극대화를 위해 최적 층화 및 샘플 배정 최적화를 수행하였다. 최적화는 작물수량, 온실가스 배출량, 해충 분포 확률을 포함하는 16개 목표 변수에 대해 주어진 정밀도 제한 내에서 샘플 수를 최소화하는 방향으로 진행되었다. 샘플링의 정밀도와 정확도 평가는 각각 변동계수 (CV)와 상대적 편향을 기반으로 하였다. 국내 농지 공간격자 모집단 계층화 및 샘플 배정 및 샘플 수 최적화 결과, 전체 농지는 5~21개 계층, 46~69개 샘플 수 수준에서 최적화되었다. 본 연구결과물들은 국내 농업시스템 대표 공간격자로써 널리 활용될 수 있을 것으로 기대된다. 또한, 기후변화 영향예측 공간모델링 연구들에 활용되어 샘플링 비용 및 계산 시간을 줄이면서도 모델의 효율성을 높이는 데에 기여할 수 있다.

Molds are actively used for mass production of products such as mobile phones. Molds are required to be durable and have a high level of surface roughness. Therefore, the optimization of mold processing is essential. In this study, the cutting processing of SDP20 steel used in molds was analyzed and optimized. This study is expected to contribute to the improvement of product productivity to which plastics are applied.

The multi-layered heat source model is a model that can cover most of existing studies and can be defined with a simple formula. Based on the methodology performed in previous studies, the welding heat source was found through experiments and FEM under the welding power conditions of three cases and the parameters of the welding heat source were analyzed according to the welding power. In this study, parameters of fiber laser welding heat source according to welding power were searched through optimization algorithm and finite element analysis, and the correlation was analyzed. It was confirmed that the concentration of the welding heat source in the 1st layer was high regardless of the welding power, and it was confirmed that the concentration of the welding heat source in the 5th layer (last layer) increased as the welding power increased. This reflects the shape of the weld bead that appears during actual fiber laser welding, and it was confirmed that this study represents the actual phenomenon.

본 연구의 목적은 식품 중 안나토색소를 검출하기 위하여 주성분인 cis-bixin과 cis-norbixin의 동시분석법을 개발 하는 것이다. 최적 시험법 확립을 위해 국내외 기관 중 유럽식품안전청, 일본 후생노동성, 우리나라 식품의약품안전 평가원의 HPLC분석법들을 비교 및 검토하였다. 그리고 직선성, 검출한계, 정량한계 및 분석시간을 고려하여 최적 HPLC 동시분석조건을 선택 후 여러 식품에 적용가능한 최적 전처리법을 개발하였다. 식품의약품안전평가원 HPLC 분석법이 가장 우수한 직선성(R2≥0.999)을 보였으며, cisnorbixin 및 cis-bixin에 대한 검출한계와 정령한계가 각각 0.03과 0.05 μg/mL 그리고 0.097과 0.16 μg/mL로 낮게 나타났다. 모든 보고된 전처리방법은 여러 식품적용에 한계가 있었으며, 어육 및 육가공품, 가공치즈, 음료의 주요 세 식품군 모두에 대해서 높은 회수율을 보이는 최적 전처리법이 새롭게 확립되었다. 이 전처리 방법은 cis-norbixin과 cis-bixin에 대해서 98% 이상의 우수한 동시 회수율을 나 타냈었다. 새로운 전처리방법이 적용된 분석법은 두 성분에 대해 모두 결정계수(R2) 1로서 높은 직선성을 나타냈으며, 정확도(회수율)와 정밀도(%RSD)가 각각 평균 98% 및 0.4-7.9 이었다. 이러한 결과로부터 최적화된 분석시험법은 식품 중 안나토색소의 cis-norbixin과 cis-bixin 두 성분 동시분석에 매우 적합한 것으로 판단되었다.

The most important factor in the processing of composite materials is the creation of burrs. In order to minimize the generation of burrs, the preceding researchers changed the shape and processing conditions of the tool. The developed composite material using carbon and aramid fibers has limitations in reducing the formation of burrs. In this study, in order to solve this problem, by applying a jig under the test piece during drilling, it was possible to perform high-quality hole processing with minimal burr generation.

In this study, a welding heat source model was presented and verified during fiber laser welding. The multi-layered heat source model is a model that can cover most of existing studies and can be defined with a simple formula. It consists of a total of 12 parameters, and an optimization algorithm was used to find them. As optimization algorithms, adaptive simulated annealing, multi island genetic algorithm, and Hooke-Jeeves technique were applied for comparative analysis. The parameters were found by comparing the temperature distribution when the STS304L was bead on plate welding and the temperature distribution derived through finite element analysis, and all three models were able to derive a model with similar trends. However, there was a deviation between parameters, which was attributed to the many variables. It is expected that a more clear welding heat source model can be derived in subsequent studies by giving a guide to the relational expression and range between variables and increasing the temperature measurement point, which is the target value.

Welding is the most widely used technology for manufacturing in the automobile, and shipbuilding industries. Fiber laser welding is rapidly introduced into the field to minimize welding distortion and fast welding speed. Although it is advantageous to use finite element analysis to predict welding distortion and find optimized welding conditions, there are various heat source model for fiber laser welding. In this study, a welding heat source was proposed using a multi-layered heat source model that encompasses most of the existing various welding heat source models: conical shape, curved model, exponential model, conical-cylindrical model, and conical-conical model. A case study was performed through finite element analysis using the radius of each layer and the ratio of heat energy of the layer as variables, and the variables were found by comparing them with the actual experimental results. For case study, by applying Adaptive simulated annealing, one of the global optimization algorithms, we were able to find the heat source model more efficiently.

PURPOSES : The purpose of this study is to build an optimization model using the capacity and initial travel speed of the volume delay functions for network calibration performed in the traffic demand analysis process. METHODS : The optimization model contains an error term between the observed traffic volume and estimated traffic volume, based on the user equilibrium principle, and was constructed as a bi-level model by applying range constraints on capacity and travel time. In addition, we searched the split section to apply the method of adjusting the section instead of adjusting the single link. The optimization model is constructed by applying the warm-start method using the bush of the origin-based model so that parameter adjustment and traffic assignment are repeatedly executed within the model and the convergence of the model configured %RSSE. RESULTS : As a result of analysis using the toy network, the optimization model is that the observed traffic volume is estimated when there are no restrictions and, when the constraint conditions were set, the error with the observed traffic volume and error rate was significantly reduced. As a result of the comparative analysis of the trial-and-error methods, KTDB optimum values, and optimization models in empirical analysis using a large-scale network, the evaluation indexes (e.g., RMSE and %RMSE) were significantly improved by applying the optimization model. CONCLUSIONS : Based on the empirical analysis, the optimization model of this study can be applied to large-scale networks and it is expected that the efficiency and reliability of road network calibration will be improved by repeatedly performing parameter adjustment and traffic assignment within the model.

Hydro-electric power is a method of generating electricity from the rotational force of turbine blades by using the potential energy of a river or reservoir water. Recently, the necessity of small hydropower development is expanding due to the development and support of renewable energy, and because of the difficulty and environmental problems of huge dams. The purpose of this paper is to deal with a method of increasing the efficiency of small water turbine that can be adopt in low head condition. In order to improve the turbine efficiency, channel shape is optimized in order to minimize head loss using computational fluid dynamics. The angle values for the contraction and enlargement part of the channel where the turbine is located are found from the analyses. Additionally, three-dimensional analysis is applied to the optimized channel shape in order to confirm the optimized pipe.

The estimation of heat source model is very important for heat transfer analysis with finite element method. Part I of this study used adaptive simulated annealing which is one of the global optimization algorithm for anticipating the parameters of the Goldak model. Although the analysis with 3D model which depicted the real situation produced the correct answer, that took too much time with moving heat source model based on Fortran and Abaqus. This research suggests the procedure which can reduce time with maintaining quality of analysis. The lead time with 2D model is reduced by 90% comparing that of 3D model, the temperature distribution is similar to each other. That is based on the saturation of heat transfer among the direction of heat source movement. Adaptive simulated annealing with 2D model can be used to estimate more proper heat source model and which could enhance to reduce the resources and time for experiments.

The purpose of this study was to establish the optimum experimental conditions by investigating the relationship between the nine experimental conditions using Taguchi technique. Through experiments, we found that the weight, thickness, and length of the sample were most affected by the angle at which the sample was installed, while the width had the largest influence on the sample's x-axis and the inner diameter. It was confirmed. Therefore, through this experiment, it was confirmed that the installation angle of the product had the greatest influence on the error occurrence of the product during 3D printer processing.