• 한국전자통신학회논문지
• /
• 제16권6호
• /
• pp.1195-1204
• /
• 2021

본 논문에서는 반응 표면 분석을 이용하여 파력 발전기의 최적 설계 방법을 제안한다. 특히 제안한 방법에서는 파도의 수직 운동을 직접 전기 에너지로 변환하기 위한 선형 운동 가능한 선형발전기를 선택함으로써 기계적 손실을 줄인다. 따라서 에너지 변환 효율 향상을 위해 느린 파 상태에서도 구동 장치에 작용하는 여자력을 계산하고 슬롯과 극의 비율로 권선 과정을 결정한다. 또한 발전기의 성능에 중요한 영향을 미치는 고정자와 변환기의 형상 인자를 도출하기 위해 회귀분석을 사용한다. 반응 표면 분석을 통해 최적의 설계 변수를 선정하고, 분석 결과를 활용하여 효율적인 실험 설계를 위한 최적화 방법을 제시한다. 마지막으로, 모의 실험 결과를 통해 제안한 방법의 타당성을 검증한다.

• 소성∙가공
• /
• 제31권4호
• /
• pp.214-228
• /
• 2022

The yield criterion, or called yield function, plays an important role in the study of plastic working of a sheet because it governs the plastic deformation properties of the sheet during plastic forming process. In this paper, we propose a novel anisotropic yield function useful for describing the plastic behavior of various anisotropic sheets. The proposed yield function includes the anisotropic version of the second stress invariant J₂ and the third stress invariant J₃. The anisotropic yield function newly proposed in this study is as follows. F(J₂)+ αG(J₃)+ βH (J₂ × J₃) = k^m The proposed yield function well explains the anisotropic plastic behavior of various sheets by introducing the parameters α and β, and also exhibits both symmetrical and asymmetrical yield surfaces. The parameters included in the proposed model are determined through an optimization algorithm from uniaxial and biaxial experimental data under proportional loading path. In this study, the validity of the proposed anisotropic yield function was verified by comparing the yield surface shape, normalized uniaxial yield stress value, and Lankford's anisotropic coefficient R-value derived with the experimental results. Application for the proposed anisotropic yield function to aluminum sheet shows symmetrical yielding behavior and to pure titanium sheet shows asymmetric yielding behavior, it was shown that the yield curve and yield behavior of various types of sheet materials can be predicted reasonably by using the proposed new yield anisotropic function.

• Nuclear Engineering and Technology
• /
• 제52권12호
• /
• pp.2743-2759
• /
• 2020

A detailed computational fluid dynamics (CFD) simulation analysis model was developed using ANSYS CFX 16.1 and analyzed to simulate the basic design and internal flow characteristics of a 180 MW small modular reactor (SMR) with a natural circulation flow system. To analyze the natural circulation phenomena without a pump for the initial flow generation inside the reactor, the flow characteristics were evaluated for each output assuming various initial powers relative to the critical condition. The eddy phenomenon and the flow imbalance phenomenon at each output were confirmed, and a flow leveling structure under the core was proposed for an optimization of the internal natural circulation flow. In the steady-state analysis, the temperature distribution and heat transfer speed at each position considering an increase in the output power of the core were calculated, and the conceptual design of the SMR had a sufficient thermal margin (31.4 K). A transient model with the output ranging from 0% to 100% was analyzed, and the obtained values were close to the T_hot and T_cold temperature difference value estimated in the conceptual design of the SMR. The K-factor was calculated from the flow analysis data of the CFX model and applied to an analysis model in RELAP5/MOD3.3, the optimal analysis system code for nuclear power plants. The CFX analysis results and RELAP analysis results were evaluated in terms of the internal flow characteristics per core output. The two codes, which model the same nuclear power plant, have different flow analysis schemes but can be used complementarily. In particular, it will be useful to carry out detailed studies of the timing of the steam generator intervention when an SMR is activated. The thermal and hydraulic characteristics of the models that applied porous media to the core & steam generators and the models that embodied the entire detail shape were compared and analyzed. Although there were differences in the ability to analyze detailed flow characteristics at some low powers, it was confirmed that there was no significant difference in the thermal hydraulic characteristics' analysis of the SMR system's conceptual design.

• 산업경영시스템학회지
• /
• 제45권4호
• /
• pp.233-239
• /
• 2022

The injection molding process is a process in which thermoplastic resin is heated and made into a fluid state, injected under pressure into the cavity of a mold, and then cooled in the mold to produce a product identical to the shape of the cavity of the mold. It is a process that enables mass production and complex shapes, and various factors such as resin temperature, mold temperature, injection speed, and pressure affect product quality. In the data collected at the manufacturing site, there is a lot of data related to good products, but there is little data related to defective products, resulting in serious data imbalance. In order to efficiently solve this data imbalance, undersampling, oversampling, and composite sampling are usally applied. In this study, oversampling techniques such as random oversampling (ROS), minority class oversampling (SMOTE), ADASYN(Adaptive Synthetic Sampling), etc., which amplify data of the minority class by the majority class, and complex sampling using both undersampling and oversampling, are applied. For composite sampling, SMOTE+ENN and SMOTE+Tomek were used. Artificial neural network techniques is used to predict product quality. Especially, MLP and RNN are applied as artificial neural network techniques, and optimization of various parameters for MLP and RNN is required. In this study, we proposed an SA technique that optimizes the choice of the sampling method, the ratio of minority classes for sampling method, the batch size and the number of hidden layer units for parameters of MLP and RNN. The existing sampling methods and the proposed SA method were compared using accuracy, precision, recall, and F1 Score to prove the superiority of the proposed method.

• 한국분말재료학회지
• /
• 제29권6호
• /
• pp.459-467
• /
• 2022

Soft magnetic powder materials are used throughout industries such as motors and power converters. When manufacturing Fe-based soft magnetic composites, the size and shape of the soft magnetic powder and the microstructure in the powder are closely related to the magnetic properties. In this study, Fe-Si-Al-P alloy powders were manufactured using various manufacturing process parameter sets, and the process parameters of the vacuum induction melt gas atomization process were set as melt temperature, atomization gas pressure, and gas flow rate. Process variable data that records are converted into 6 types of data for each powder recovery section. Process variable data that recorded minute changes were converted into 6 types of data and used as input variables. As output variables, a total of 6 types were designated by measuring the particle size, flowability, apparent density, and sphericity of the manufactured powders according to the process variable conditions. The sensitivity of the input and output variables was analyzed through the Pearson correlation coefficient, and a total of 6 powder characteristics were analyzed by artificial neural network model. The prediction results were compared with the results through linear regression analysis and response surface methodology, respectively.

• Nuclear Engineering and Technology
• /
• 제55권7호
• /
• pp.2628-2641
• /
• 2023

Nuclear safety is the lifeline for the development and application of nuclear energy. In severe accidents of pressurized water reactor (PWR), aerosols, as the main carrier of fission products, are suspended in the containment vessel, posing a potential threat of radioactive contamination caused by leakage into the environment. The gas-phase aerosols suspended in the containment will settle onto the wall or sump water through the natural deposition mechanism, thereby reducing atmospheric radioactivity. Aiming at the low accuracy of the aerosol model in the ISAA code, this paper improves the natural deposition model of aerosol in the containment. The aerosol dynamic shape factor was introduced to correct the natural deposition rate of non-spherical aerosols. Moreover, the gravity, Brownian diffusion, thermophoresis and diffusiophoresis deposition models were improved. In addition, ABCOVE, AHMED and LACE experiments were selected to validate and evaluate the improved ISAA code. According to the calculation results, the improved model can more accurately simulate the peak aerosol mass and respond to the influence of the containment pressure and temperature on the natural deposition rate of aerosols. At the same time, it can significantly improve the calculation accuracy of the residual mass of aerosols in the containment. The performance of improved ISAA can meet the requirements for analyzing the natural deposition behavior of aerosol in containment of advanced PWRs in severe accident. In the future, further optimization will be made to address the problems found in the current aerosol model.

• Structural Engineering and Mechanics
• /
• 제87권3호
• /
• pp.255-272
• /
• 2023

Spatial cable systems can provide more transverse stiffness and torsional stiffness without sacrificing the vertical bearing capacity compared with conventional vertical cable systems, which is quite lucrative for long-span earth-anchored suspension bridges' development. Higher economy highlights the importance of refined form-finding analysis. Meanwhile, the internal connection between the lateral and vertical sags has not yet been specified. Given this, an analytic algorithm of form-finding for the earth-anchored suspension bridge with spatial cables is proposed in this paper. Through the geometric compatibility condition and mechanical equilibrium condition, the expressions for cable segment, the recurrence relationship between catenary parameters and control equations of spatial cable are established. Additionally, the nonlinear general reduced gradient method is introduced into fast and high-precision numerical analysis. Furthermore, the analytic expression of the lateral and vertical sags is deduced and discussed. This is very significant for the space design above the bridge deck and the optimization of the sag-to-span ratio in the preliminary design stage of the bridge. Finally, the proposed method is verified with the aid of two examples, one being an operational self-anchored suspension bridge (with spatial cables and a 260 m main span), and the other being an earth-anchored suspension bridge under design (with spatial cables and a 500 m main span). The necessity of an iterative calculation for hanger tensions on earth-anchored suspension bridges is confirmed. It is further concluded that the main cable and their connected hangers are in very close inclined planes.

• 항공우주시스템공학회지
• /
• 제18권3호
• /
• pp.27-33
• /
• 2024

누리호의 성공과 차세대 우주발사체의 개발 목표를 통하여 국내 정지궤도위성 발사능력은 1톤에서 3.7톤으로 향상될 것으로 기대되며 화성, 소행성 등의 우주탐사에도 1톤 이상의 실질적인 능력을 제공해 줄 수 있을 것으로 예측된다. 고흥 우주발사장은 태양 동기궤도 소형위성에 최적화되어 있으며 타국의 영공을 침범하지 않아야 된다는 필수적인 전제조건으로 인하여 정지궤도위성 발사장으로는 다소 부족한 면이 존재한다. 초기 궤도 투입상태로부터 궤도면 회전을 위한 에너지의 증가가 필수적이며 운용 측면에서의 복잡성과 함께 경제성의 감소요인이 된다. 그러므로 차세대 우주발사체의 개발과 병행하여 지구 적도부근의 해외 지상발사장 또는 해상발사지점의 획득과 최적화된 정지궤도위성 투입에 관한 궤도 구성에 관한 연구가 계속되어야 한다.

• 한국음향학회지
• /
• 제25권7호
• /
• pp.312-318
• /
• 2006

기존의 립싱크 시스템은 음소 분할 후, 각각의 음소를 인식하는 2단계의 과정을 거쳤다. 하지만, 정확한 음소 분할의 부재와 음성이 끊긴 분할 된 음소로 이루어진 훈련 데이터들은 시스템의 전체 성능을 크게 떨어뜨렸다. 이런 문제를 해결하기 위해 Head-Body-Tail (HBT) 모델을 이용한 단모음 연속어 인식 기술을 제안한다. 주로 소규모 어휘를 다루는데 적합한 HBT 모델은 Head 와 Tail 부분에 문맥 종속 정보를 포함하여 앞 뒤 문맥에 따른 조음효과를 최대한 반영한다. 또한, 7개의 단모음을 입모양이 비슷한 세 개의 클래스로 분류하여, 클래스에 종속적인 코드북 3개를 가진 반연속HMM (Hidden Markov Model)을 적용하여 시스템을 최적화하고, 변이 부분이 큰 단어의 처음과 끝은 연속HMM의 8 믹스쳐 가우시안 구조를 사용하여 모델링하였다. 제안한 방법은 HBT구조의 연속HW과 대등한 성능을 보이지만, 파라미터 수는 33.92% 감소하였다. 파라미터 감소는 계산 양을 줄여주므로, 시스템이 실시간으로 동작 가능하게 한다.

• 한국환경복원기술학회지
• /
• 제26권6호
• /
• pp.85-96
• /
• 2023

This study proposes a method for forest vegetation monitoring using high-resolution aerial imagery captured by unmanned aerial vehicles(UAV) and deep learning technology. The research site was selected in the forested area of Mountain Dogo, Asan City, Chungcheongnam-do, and the target species for monitoring included Pinus densiflora, Quercus mongolica, and Quercus acutissima. To classify vegetation species at the pixel level in UAV imagery based on characteristics such as leaf shape, size, and color, the study employed the semantic segmentation method using the prominent U-net deep learning model. The research results indicated that it was possible to visually distinguish Pinus densiflora Siebold & Zucc, Quercus mongolica Fisch. ex Ledeb, and Quercus acutissima Carruth in 135 aerial images captured by UAV. Out of these, 104 images were used as training data for the deep learning model, while 31 images were used for inference. The optimization of the deep learning model resulted in an overall average pixel accuracy of 92.60, with mIoU at 0.80 and FIoU at 0.82, demonstrating the successful construction of a reliable deep learning model. This study is significant as a pilot case for the application of UAV and deep learning to monitor and manage representative species among climate-vulnerable vegetation, including Pinus densiflora, Quercus mongolica, and Quercus acutissima. It is expected that in the future, UAV and deep learning models can be applied to a variety of vegetation species to better address forest management.