• 한국자동차공학회논문집
• /
• 제23권5호
• /
• pp.486-493
• /
• 2015

In this paper, a battery model for electric vehicle virtual platform was developed. A battery model consisted of a battery cell model and battery thermal management system. A battery cell model was developed based on Randles equivalent circuit model. Circuit parameters in the form of 3D map data was obtained by charge-discharge experiment of Li-Polymer battery in various temperature condition. The developed battery cell model was experimentally verified by comparing voltages. Thermal management system model was also developed using heat generator, heat transfer and convection model, and cooling fan. For verification of the developed battery model in vehicle level, the integrated battery model was applied in to EV(electric vehicle) virtual platform, and virtual driving simulation using UDDS velocity profile was conducted. The accuracy of the developed battery model has been verified by comparing the simulation results from EV platform with the experimental data.

• 열처리공학회지
• /
• 제28권4호
• /
• pp.171-180
• /
• 2015

The variation in microstructure and texture during continuous annealing was examined in a series of 1.6% Mn-0.1% Cr-0.3% Mo-0.005% B steels with carbon contents in the range of 0.010 to 0.030%. It was found that microstructure of hot band consisted of ferrite and pearlite as a consequence of high coiling temperature, and eutectoid carbon content was between 0.011% and 0.016%. Martensite ranged in volume fraction from 1.5% to 4.0% when annealed at $820{\circ}C$ according to the typical continuous annealing cycle. The critical martensite content for the continuous yielding was about 4% from stress-strain curves. The continuous yielding was obtained in the 0.030% carbon steel and 0.010% to 0.020% carbon steels revealed some yield point elongation ranging from 0.8% to 2.2% in as-annealed conditions. Higher tensile strength in the higher carbon steel is due to both increase in the martensite volume fraction and ferrite grain refinement. Decreasing the carbon content to 0.01% strengthened the intensities of ${\gamma}$-fiber textures, resulting in the increase in the $r_m$ value, which was caused by the lower volume fraction of martensite. The higher carbon steels showed the lower $r_m$ value of about 1.0.

• 대한기계학회논문집B
• /
• 제32권10호
• /
• pp.800-809
• /
• 2008

Scanning Thermal Microscope (SThM) is the tool that can map out temperature or the thermal property distribution with the highest spatial resolution. Since the local temperature or the thermal property of samples is measured from the extremely small heat transferred through the nanoscale tip-sample contact, improving the sensitivity of SThM probe has always been the key issue. In this study, we develop a new design and fabrication process of SThM probe to improve the sensitivity. The fabrication process is optimized so that cantilevers and tips are made of thermally grown silicon dioxide, which has the lowest thermal conductivity among the materials used in MEMS. The new design allows much higher tip so that heat transfer through the air gap between the sample-probe is reduced further. The position of a reflector is located as far away as possible to minimize the thermal perturbation due to the laser. These full $SiO_2$ SThM probes have much higher sensitivity than that of previous ones.

• Nuclear Engineering and Technology
• /
• 제29권1호
• /
• pp.45-57
• /
• 1997

The direct contact condensation phenomenon, which occurs when steam is injected into the subcooled water, has been experimentally investigated. Two plume shapes in the stable condensation regime are found to be conical and ellipsoidal shapes depending on the steam mass flux and the liquid subcooling. Divergent plumes, however, are found when the subcooling is relatively small. The measured expansion ratio of the maximum plume diameter to the injector inner diameter ranges from 1.0 to 2.3. By means of fitting a large amount of measured data, an empirical correlation is obtained to predict the steam plume length as a function of a dimensionless steam mass flux and a driving potential for the condensation process. The average heat transfer coefficient of direct contact condensation has been found to be in the range 1.0~3.5 ㎿/$m^2$.$^{\circ}C$. Present results show that the magnitude of the average condensation heat transfer coefficient depends mainly on the steam mass fin By using dynamic pressure measurements and visual observations, six regimes of direct contact condensation have been identified on a condensation regime map, which are chugging, transition region from chugging to condensation oscillation, condensation oscillation, bubbling condensation oscillation, stable condensation, and interfacial oscillation condensation. The regime boundaries are quite clearly distinguishable except the boundaries of bubbling condensation oscillation and interfacial oscillation condensation.

• 한국멀티미디어학회논문지
• /
• 제19권8호
• /
• pp.1310-1319
• /
• 2016

Face detection is the first step in a wide range of face applications. However, detecting faces in the wild is still a challenging task due to the wide range of variations in pose, scale, and occlusions. Recently, many deep learning methods have been proposed for face detection. However, further improvements are required in the wild. Another important issue to be considered in the face detection is the computational complexity. Current state-of-the-art deep learning methods require a large number of patches to deal with varying scales and the arbitrary image sizes, which result in an increased computational complexity. To reduce the complexity while achieving better detection accuracy, we propose a fully convolutional network-based face detection that can take arbitrarily-sized input and produce feature maps (heat maps) corresponding to the input image size. To deal with the various face scales, a multi-scale network architecture that utilizes the facial components when learning the feature maps is proposed. On top of it, we design multi-task learning technique to improve detection performance. Extensive experiments have been conducted on the FDDB dataset. The experimental results show that the proposed method outperforms state-of-the-art methods with the accuracy of 82.33% at 517 false alarms, while improving computational efficiency significantly.

• 대한기계학회논문집B
• /
• 제35권3호
• /
• pp.309-319
• /
• 2011

질소 희석된 프로판 부상화염에서 열손실에 의한 자기진동을 기초로 화염안정화선도를 도출하기 위하여 노즐직경 0.3 mm, 1.0 mm에서 실험적 연구를 수행하였다. 예혼합화염에서 확산화염으로의 전도 열손실에 의한 자기진동 및 매연 복사에 의한 자기진동을 관찰하였다. 0.1 Hz보다 낮은 주파수 성향을 띄는 열손실에 의한 자기진동은 제안된 메커니즘에 의해 잘 묘사되었고 반면 매연복사에 의한 자기진동은 O(0.1 Hz)의 주파수 범위를 나타내었으며 제안된 메커니즘은 항온항습실 실험을 통해 입증하였다. 질소 희석된 프로판 부상화염에서 관찰된 열손실에 의한 자기진동의 특성화는 관련된 변수 및 스트라훌 수에 의해 잘 묘사되었다.

• 한국농림기상학회지
• /
• 제25권4호
• /
• pp.446-454
• /
• 2023

기후변화는 농업에 막대한 영향을 미치며, 특히 지구 온난화로 인해 미래로 갈수록 기온과 습도가 현재와는 다른 양상으로 변화될 것으로 예측된다. 현재와 다른 기후 환경하에서는 농작물과 더불어 가축들은 환경변화에 따른 스트레스에 노출될 위험성이 높아질 수 있다. 특히 미래 기후는 평균기온 상승으로 설명할 수 있는데, 고온 스트레스에 대한 위험도는 기온과 상대습도를 통해 계산되는 온습도지수를 통해 평가할 수 있다. 본 연구에서는 기상청 종관 관측 10개 지점에서 1961년부터 2020년까지 60년간 수집된 기온과 상대습도 자료를 활용하여 지점별 온습도지수를 기간에 따라 비교하고, 1981년부터 2020년까지 고해상도 분포도로 제작된 기온과 상대습도 분포도 자료를 통해 온습도지수를 분포도 형태로 제작하여 시간의 흐름에 따른 공간적인 변화량을 분석하였다. 또한, 온습도지수를 활용해 산출할 수 있는 고온 스트레스 발생 일수를 기간에 따라 비교하였다. 온습도지수는 과거에서 현재로 이어지는 동안 평균적으로 상승하는 양상을 나타냈으나 지점별로 상승 패턴은 차이가 있었다. 또한 온습도지수가 상승함에 따라 고온 스트레스 일수 또한 증가하는 양상을 나타냈으며, 이는 향후 열로 인한 축산업 분야의 비용증가를 예상할 수 있다. 본 연구의 결과는 온습도지수를 통해 가축의 고온 스트레스 위험성을 평가할 수 있음을 시사하며 향후 기후 변화 시나리오 자료를 통한 미래 기간에 대한 온습도지수 분석에 대한 연구가 필요할 것이다.

• 한국농림기상학회지
• /
• 제4권4호
• /
• pp.203-212
• /
• 2002

주로 도시에 소재하는 표준기상관측소 자료의 공간 내삽에 의해 일 최저기온의 평년값을 추정할 때, 도시 열섬효과의 전이에 의해 전원지역에서 과다추정 되는 오류를 수정하기 위해 본 연구를 수행하였다. 도시열섬효과의 공간적인 확산을 모의하기 위해 먼저 불연속적인 변량인 시군 행정구역단위 인구를 지표피복도 상의 시가지 픽셀에만 할당하여 규칙적인 격자점 단위의 평균인구로 변환함으로써 연속적인 변량인 수치인구모형(DPM)으로 표현하였다. 다섯 가지 평활화 DPM 가운데 최적으로 판명된 사방 2.5 km DPM과 기온추정 오차간 회귀식을 기존의 거리-고도 보정 내삽과정에 결합하였다. 이 방법을 적용하여 추정된 평년(1971-2000) 월별 일 최저기온의 추정오차는 기존방법에 비해 최소 50%가 개선되었다.

• Journal of Microbiology
• /
• 제44권4호
• /
• pp.375-382
• /
• 2006

From its initial colonization to causation of disease, Streptococcus pneumoniae has evolved strategies to cope with a number of stressful in vivo environmental conditions. In order to analyze a global view of this organism's response to heat shock, we established a 2-D electrophoresis proteome map of the S. pneumoniae D39 soluble proteins under in vitro culture conditions and performed the comparative proteome analysis to a 37 to $42^{\circ}C$ temperature up-shift in S. pneumoniae. When the temperature of an exponentially growing S. pneumoniae D39 culture was raised to $42^{\circ}C$, the expression level of 25 proteins showed changes when compared to the control. Among these 25 proteins, 12 were identified by MALDI-TOF and LC-coupled ESI MS/MS. The identified proteins were shown to be involved in the general stress response, energy metabolism, nucleotide biosynthesis pathways, and purine metabolism. These results provide clues for understanding the mechanism of adaptation to heat shock by S. pneumoniae and may facilitate the assessment of a possible role for these proteins in the physiology and pathogenesis of this pathogen.

• Nuclear Engineering and Technology
• /
• 제54권5호
• /
• pp.1825-1834
• /
• 2022

Performing high-fidelity computational fluid dynamics (HF-CFD) to predict the flow and heat transfer state of the coolant in the reactor core is expensive, especially in scenarios that require extensive parameter search, such as uncertainty analysis and design optimization. This work investigated the performance of utilizing a multi-fidelity reduced-order model (MF-ROM) in PWR rod bundles simulation. Firstly, basis vectors and basis vector coefficients of high-fidelity and low-fidelity CFD results are extracted separately by the proper orthogonal decomposition (POD) approach. Secondly, a surrogate model is trained to map the relationship between the extracted coefficients from different fidelity results. In the prediction stage, the coefficients of the low-fidelity data under the new operating conditions are extracted by using the obtained POD basis vectors. Then, the trained surrogate model uses the low-fidelity coefficients to regress the high-fidelity coefficients. The predicted high-fidelity data is reconstructed from the product of extracted basis vectors and the regression coefficients. The effectiveness of the MF-ROM is evaluated on a flow and heat transfer problem in PWR fuel rod bundles. Two data-driven algorithms, the Kriging and artificial neural network (ANN), are trained as surrogate models for the MF-ROM to reconstruct the complex flow and heat transfer field downstream of the mixing vanes. The results show good agreements between the data reconstructed with the trained MF-ROM and the high-fidelity CFD simulation result, while the former only requires to taken the computational burden of low-fidelity simulation. The results also show that the performance of the ANN model is slightly better than the Kriging model when using a high number of POD basis vectors for regression. Moreover, the result presented in this paper demonstrates the suitability of the proposed MF-ROM for high-fidelity fixed value initialization to accelerate complex simulation.