• Journal of Aerospace System Engineering
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• v.18 no.4
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• pp.96-101
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• 2024

The Synthetic Aperture Radar (SAR) is equipped with a Transmitter/Receiver (TR) module, which serves as the signal transmission and reception unit for acquiring image data. The TR module generates significant heat during signal generation and amplification, potentially degrading performance or causing mission failure. Furthermore, launch and operational environments may result in structural damage to the components. Thus, assessing the thermal and structural safety of the TR module through thermal and vibration tests is essential to guarantee its safety. Safety assessments can be verified through environmental tests prescribed in MIL-STD-883. This paper explores the thermal and structural safety characteristics of the TR module by simulating test environments using finite element analysis prior to conducting environmental tests.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1035-1046
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• 2022

This study evaluated the applicability of multi-resolution data fusion for land-cover classification. In the applicability evaluation, a spatial time-series geostatistical deconvolution/fusion model (STGDFM) was applied as a multi-resolution data fusion model. The study area was selected as some agricultural lands in Iowa State, United States. As input data for multi-resolution data fusion, Moderate Resolution Imaging Spectroradiometer (MODIS) and Landsat satellite images were used considering the landscape of study area. Based on this, synthetic Landsat images were generated at the missing date of Landsat images by applying STGDFM. Then, land-cover classification was performed using both the acquired Landsat images and the STGDFM fusion results as input data. In particular, to evaluate the applicability of multi-resolution data fusion, two classification results using only Landsat images and using both Landsat images and fusion results were compared and evaluated. As a result, in the classification result using only Landsat images, the mixed patterns were prominent in the corn and soybean cultivation areas, which are the main land-cover type in study area. In addition, the mixed patterns between land-cover types of vegetation such as hay and grain areas and grass areas were presented to be large. On the other hand, in the classification result using both Landsat images and fusion results, these mixed patterns between land-cover types of vegetation as well as corn and soybean were greatly alleviated. Due to this, the classification accuracy was improved by about 20%p in the classification result using both Landsat images and fusion results. It was considered that the missing of the Landsat images could be compensated for by reflecting the time-series spectral information of the MODIS images in the fusion results through STGDFM. This study confirmed that multi-resolution data fusion can be effectively applied to land-cover classification.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.7
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• pp.2632-2637
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• 2010

Information in UbiComp Environment are transformed to knowledge by relationship in a spatio-temporal location, and then became intelligent contents with task procedures or application models. The entities in U-City has lots of relationships. It is important in U-City contents to provide intelligent and personalized response to meet the intention of users. We extend the spatial ontology model of SPIRIT to other domain. Domain ontologies are consist of type, relation, and instance ontologies. When the relationship model by shared concepts are not defined, we used the spatio-temporal events to find relationships. So we proposed the methods to recommend semantically related terms, not syntactically.

• Composites Research
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• v.20 no.4
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• pp.42-50
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• 2007

This paper describes the results of experiments and numerical simulation studies on the low-velocity impact damage of two different sandwich composite panels for application to bodyshell and floor structure of the BIMODAL tram vehicle. Square test samples of 100mm sides were subjected to low-velocity impact loading using an instrumented testing machine at four impact energy levels. Part of this work presented is focused on the finite element analysis of low-velocity impact response onto a sandwich composite panels. It is based on the application of explicit finite element (FE) analysis codes LS-DYNA 3D to study the impact response of sandwich structures under low-velocity impact conditions. Material testing was conducted to determine the input parameters for the metallic and composite material model, and the effective equivalent damage model for the orthotropic honeycomb materials. Numerical and experimental results showed a good agreement for damage area and the depth of indentation of sandwich composite panels created by the impact loading.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.48 no.1
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• pp.23-33
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• 2020

In this study, the effect of surface roughness distribution and its influence on the inflight icing code was investigated. Previous numerical studies focused on the magnitude of surface roughness, and the effects were only addressed in terms of changes in thermal boundary layers with fully turbulent assumption. In addition, the empirical formula was used to take account the turbulent transition due to surface roughness, which was regarded as reducing the accuracy of ice shape prediction. Therefore, in this study, the turbulent transition model based on the two-equation turbulence model was applied to consider the effects of surface roughness. In order to consider the effect of surface roughness, the transport equation for roughness amplification parameter was applied, and the surface roughness distribution model was implemented to consider the physical properties. For validation, the surface roughness, convective heat transfer coefficient, and ice shape were compared with experimental results and other numerical methodology. As a result, it was confirmed that the excessive prediction of the heat transfer coefficient at the leading edge and the ice horn shape at the bottom of the airfoil were improved accordingly.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.19 no.3
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• pp.169-179
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• 2014

Monthly mean surface heat fluxes in the southeastern Yellow Sea are calculated using directly observed airsea variables from an ocean buoy station including short- and longwave radiations, and COARE 3.0 bulk flux algorithm. The calculated monthly mean heat fluxes are then compared with previous estimates of climatological monthly mean surface heat fluxes near the buoy location. Sea surface receives heat through net shortwave radiation ($Q_i$) and loses heat as net longwave radiation ($Q_b$), sensible heat flux ($Q_h$), and latent heat flux ($Q_e$). $Q_e$ is the largest contribution to the total heat loss of about 51 %, and $Q_b$ and $Q_h$ account for 34% and 15% of the total heat loss, respectively. Net heat flux ($Q_n$) shows maximum in May ($191.4W/m^2$) when $Q_i$ shows its annual maximum, and minimum in December ($-264.9W/m^2$) when the heat loss terms show their annual minimum values. Annual mean $Q_n$ is estimated to be $1.9W/m^2$, which is negligibly small considering instrument errors (maximum of ${\pm}19.7W/m^2$). In the previous estimates, summertime incoming radiations ($Q_i$) are underestimated by about $10{\sim}40W/m^2$, and wintertime heat losses due to $Q_e$ and $Q_h$ are overestimated by about $50W/m^2$ and $30{\sim}70W/m^2$, respectively. Consequently, as compared to $Q_n$ from the present study, the amount of net heat gain during the period of net oceanic heat gain between April and August is underestimated, while the ocean's net heat loss in winter is overestimated in other studies. The difference in $Q_n$ is as large as $70{\sim}130W/m^2$ in December and January. Analysis of long-term reanalysis product (MERRA) indicates that the difference in the monthly mean heat fluxes between the present and previous studies is not due to the temporal variability of fluxes but due to inaccurate data used for the calculation of the heat fluxes. This study suggests that caution should be exercised in using the climatological monthly mean surface heat fluxes documented previously for various research and numerical modeling purposes.

• Spatial Information Research
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• v.13 no.4 s.35
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• pp.345-354
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• 2005

Super resolution image reconstruction method refers to image processing algorithms that produce a high resolution(HR) image from observed several low resolution(LR) images of the same scene. This method has proven to be useful in many practical cases where multiple frames of the same scene can be obtained, such as satellite imaging, video surveillance, video enhancement and restoration, digital mosaicking, and medical imaging. In this paper, we applied the super resolution reconstruction method in spatial domain to video sequences. Test images are adjacently sampled images from continuous video sequences and are overlapped at high rate. We constructed the observation model between the HR images and LR images applied with the Maximum A Posteriori(MAP) reconstruction method which is one of the major methods in the super resolution grid construction. Based on the MAP method, we reconstructed high resolution images from low resolution images and compared the results with those from other known interpolation methods.

• The KIPS Transactions:PartD
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• v.18D no.6
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• pp.493-500
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• 2011

The trends of technical terms express the changes of particular subjects in a specific research field over time. However, the amount of academic literature and patent data is too large to be analyzed by human resources. In this paper, we propose a method that can detect and analyze the trends of terms by modeling the life cycle of the terms. The proposed method is composed of the following steps. First, the technical terms are extracted from academic literature data, and the TDVs(Term Dominance Values) of terms are computed on a periodic basis. Based on the TDVs, the life cycles of terms are modeled, and technical terms with similar temporal patterns of the life cycles are classified into the same trends class. The experiments shown in this paper is performed by exploiting the NDSL academic literature data maintained by KISTI.

• Solar Energy
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• v.10 no.2
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• pp.10-17
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• 1990

Short-term tests were conducted on a house at KIER, Daejon for its thermal performance evaluation. The test procedure and data analysis were made according to the PSTAR method. Each test period was 3 days during which the building was unoccupied. The data measured with 8 channels were used to renormalize an audit based simulation model of the house. The following are the key parameters obtained in the present analysis: 1) the building loss coefficient(skin conductance plus infiltration conductance during coheating period); 2) the effective building heat capacity; and 3) the effective solar gain. An estimation of total heat required to maintain a standard level of comfort during a typical winter season is also calculated on the basis of the renormalized simulation model and typical long term weather data.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.6
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• pp.121-132
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• 2005

In the formation of images in a camera, the exposure time is appropriately adjusted to obtain a good image. Hence for a successful alignment of a sequence of images to the same scene, it is required to compensate the different exposure times. If we have no knowledge regarding the exposure time, then we should develop an algorithm that can compensate an image with respect to a reference image without using any camera formation models. In this paper, an exposure compensation is performed by designing predictors based on the conditional expectation between the reference and input images. Further, an adaptive predictor design is conducted to manage the irregular exposure or histogram problem. In order to alleviate the blocking artifact and the overfitting problems in the adaptive scheme, a smoothing technique, which uses the pixels of the adjacent blocks, is proposed. We successfully conducted the exposure compensation using real images obtained from digital cameras and the transmission electron microscopy.