• Transactions of the Korean Society of Automotive Engineers
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• v.23 no.4
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• pp.428-435
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• 2015

This paper presents the experimental study of cabin thermal comfort using a cold storage heat exchanger in a vehicle air-conditioning system. Recent vehicle-applied ISG functions for fuel economy and emission, but when vehicles stop, compressors in the air-conditioning system stop, and the cabin temperature sharply increases, making passengers feel thermal discomfort. This study conducts thermal comfort evaluation in the vehicle, which is applied to a cold storage system for the climate control wind tunnel test and the vehicle fleet road test with various airflow volume rates and ambient temperatures blowing to the cold storage heat exchanger. The experimental results, in the cold storage system, air discharge temperature is $3.1-4.2^{\circ}C$ lower than current air-conditioning system when the compressor stops and provides cold air for at least 38 extra seconds. In addition, the blowing airflow volume to the cold storage heat exchanger with various ambient temperature was examined for the control logic of the cold storage system, and in the results, the airflow volume rate is dominant over the outside temperature. For this study, a cold storage system is economically useful to keep the cabin at a thermally comfortable level during the short period when the engine stops in ISG vehicles.

• KIEAE Journal
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• v.14 no.5
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• pp.97-102
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• 2014

The beauty of Korean architecture is in its natural beauty. Traditional residence of Korea is architecture that expresses modesty that is embraces the nature. Hanok is designed based on understanding of the nature and responding to it. For this reason, Hanok is a nature-friendly residential space. There are many unique traits of Hanok and one of them is that it is built based on scientific principles. Hanok, without using modern technology and machines, utilizes effectively the natural environment and the climate, e.g., the sun and the wind. Hanok, based on Korea's geographical condition and climate characteristics, have produced a variety of residential houses. The principle of Hanok is not to challenge the nature but embrace and accept it. Furthermore, in Hanok is embedded Korea's traditional philosophy and ideas and it is not simply a simple residential space but also a place for meditation and spiritual training. As the time passes, there are more researches are being done to enhance health in addition to traditional role of protection and convenience. Accordingly, more efforts are being made to bring the nature into human life. Hanok, the traditional residential form of Korea, has environment-friendly architecture and characteristics that could promote human health and enhance our life. Therefore, the nature-oriented philosophy and environmental elements of Hanok should be more systematically studied to take advantage of its architectural advantages and create healthier modern residential culture.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.26 no.8
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• pp.375-380
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• 2014

The purpose of this paper is to investigate the cooling and heating performance of a standalone-type thermoelectric system equipped with a thermoelectric module. The system consists of a blower and two thermoelectric modules with a fin, which is soldered onto both sides of the thermoelectric module and a courtesy light. The thermoelectric system experiment is conducted with the intake voltage to find the optimum cooling and heating performance of each. The results showed that the cooling capacity and coefficient of performance (COP) were 22 W and 0.31, and the heating capacity and COP were 147 W and 1.1, respectively. In the vehicle cooling and heating performance test in a climate wind tunnel, the results showed that the standalone thermoelectric system's cooling performance was slightly better than the base system; and the heating performance of the standalone thermoelectric system was $54.1^{\circ}C$ and the COP was 1.3, compared to the base system.

• Journal of Integrative Natural Science
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• v.7 no.1
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• pp.39-44
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• 2014

The results of the synoptic meteorological analysis showed that when the cold and dry continental high pressure was extended, heavy snow occurred at dawn when the upper atmosphere cooled. In particular, when the continental high pressure was extended and the upper pressure trough passed through, heavy snow occurred due to the convergence region formed in the west coast area, sometimes in the inland of the Honam area. In addition, it was verified that the changes in the humidity coefficients in the upper and lower layers are important data for the determination of the probability, start/end and intensity of heavy snow. However, when the area was influenced by the middle-latitude low pressure, the heavy snow was influenced by the wind in the lower layer (925 hPa and 850 hPa), the equivalent potential temperature, the convergence field, the moisture convergence and the topography. In Case 2010 (30 December 2010), OSTIA had the best numerical simulation with diverse atmospheric conditions, and the maximum difference in the numerically simulated snowfall between NCEP/NCAR SST and OSTIA was 20 cm. Although there was a regional difference in the snowfall according to the difference in the SST, OSTIA and RTG SST numerical tests, it was not as significant as in the previous results. A higher SST led to the numerical simulation of larger snowfall, and the difference was greatest near Buan in the west coast area.

• Current Photovoltaic Research
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• v.7 no.2
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• pp.46-50
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• 2019

The photovoltaic (PV) system consists of solar cells, solar modules, inverters and peripherals. The related evaluation and certification are proceeding as standards published by the IEC (International Electrotechnical Commission) TC (Technical Committee) 82. In particular, PV module is a component that requires stable durability over 20 years, and evaluation in various external environments is very important. Currently, IEC 61215-based standards are being tested, but temperature, humidity, wind and solar radiation conditions are not considered in all areas. For this reason, various types of defects may occur depending on the installation area of the same photovoltaic module. In particular, the domestic climate (South Korea) is moderate. The various test methods proposed by IEC 61215 are appropriate, excessive, or insufficient, depending on environmental condition. In this paper, we analyze the climate data collection for one year to understand the vulnerability of this test method of PV modules. Through this, we propose a test method for PV module suitable for domestic climatic conditions and also propose a technical consideration for installation and design of PV system.

• Journal of the Korean Society of Industry Convergence
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• v.26 no.4_2
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• pp.715-724
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• 2023

Solar energy forecasting is essential for (1) power system planning, management, and operation, requiring accurate predictions. It is crucial for (2) ensuring a continuous and sustainable power supply to customers and (3) optimizing the operation and control of renewable energy systems and the electricity market. Recently, research has been focusing on developing solar energy forecasting models that can provide daily plans for power usage and production and be verified in the electricity market. In these prediction models, various data, including solar energy generation and climate data, are chosen to be utilized in the forecasting process. The most commonly used climate data (such as temperature, relative humidity, precipitation, solar radiation, and wind speed) significantly influence the fluctuations in solar energy generation based on weather conditions. Therefore, this paper proposes a hybrid forecasting model by combining the strengths of the Prophet model and the GRU model, which exhibits excellent predictive performance. The forecasting periods for solar energy generation are tested in short-term (2 days, 7 days) and medium-term (15 days, 30 days) scenarios. The experimental results demonstrate that the proposed approach outperforms the conventional Prophet model by more than twice in terms of Root Mean Square Error (RMSE) and surpasses the modified GRU model by more than 1.5 times, showcasing superior performance.

• Atmosphere
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• v.34 no.3
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• pp.257-271
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• 2024

In 2023, the World Meteorological Organization released a report on climate conditions in Asia, highlighting the region's high vulnerability to floods and the increasing severity and frequency of extreme precipitation events. While previous studies have largely concentrated on broader-scale phenomena such as the Asian monsoon, it is crucial to investigate the substantial characteristics of extreme precipitation for a better understanding. In this study, we analyze the spatiotemporal characteristics of extreme precipitation during summer and their affecting factors by decomposing the moisture budgets within specific Asian regions over 44 years (1979~2022). Our findings indicate that dynamic convergence terms (DY CON), which reflect changes in wind patterns, primarily drive extreme rainfall across much of Asia. In southern Asian sub-regions, particularly coastal areas, extreme precipitation is primarily driven by low-pressure systems, with DY CON accounting for 70% of the variance. However, in eastern Asia, both thermodynamic advection and nonlinear convergence terms significantly contribute to extreme precipitation. Notably, on the Korean Peninsula, thermodynamic advection plays an important role, driven by substantial moisture carried by strong southerly mean flow. Understanding these distinct characteristics of extreme rainfall across sub-regions is expected to enhance both predictability and resilience.

• Korean Journal of Environment and Ecology
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• v.34 no.5
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• pp.425-435
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• 2020

This study aims to investigate the impact of the physical structure, such as altitude, slope gradient, slope direction, and topographical structure, and the vegetation pattern, such as existing vegetation, diameter of breast height (DBH), and crown density, on climate. The analysis results showed the significant difference in relative humidity, wind speed, and solar radiation at varying altitudes, the significant difference in all climate factors except for the wind speed at varying slope gradient, and significant difference in temperature and relative humanity at varying slope direction. The topographic structures were divided into valleys, slopes, and ridges. They were found to differ in relative humidity. However, the differences between constant trends and types were found to be insignificant concerning temperature, wind speed, and solar radiation. Significant differences in temperature, relative humidity, and wind speed were recorded with changing existing vegetation. The DBH showed a significant difference in temperature, wind speed, and solar radiation. The crown density showed a significant difference in temperature and solar radiation. The result of the relationship analysis for the analysis of the effect of vegetation pattern and physical structure on the meteorological environment showed that temperature was affected by slope gradient, slope direction, DBH, and crown density. The relative humidity was correlated with the altitude, slope gradient, slope direction, and topological structure in physical structure and the existing vegetation and crow density in vegetation pattern. The wind speed was correlated with the altitude, existing vegetation, and DHB, and the solar radiation was correlated with the slope gradient, DHG, and crown density. The crown density was the most overall significant factor in temperature, relative humidity, and solar radiation, followed by the slope gradient. DBH was also found to be highly correlated with temperature and solar radiation and significantly correlated with wind speed, but there was no statistically significant correlation with relative humidity.

• Journal of The Korean Society of Grassland and Forage Science
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• v.42 no.1
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• pp.1-9
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• 2022

This study was carried out to compare the DMY (dry matter yield) of IRG (Italian ryegrass) in the southern coastal regions of Korea due to seasonal climate scenarios such as the Kaul-Changma (late monsoon) in autumn, extreme winter cold, and drought in the next spring. The IRG data (n = 203) were collected from various Reports for Collaborative Research Program to Develop New Cultivars of Summer Crops in Jeju, 203 Namwon, and Yeungam from the Rural Development Administration - (en DASH). In order to define the seasonal climate scenarios, climate variables including temperature, humidity, wind, sunshine were used by collected from the Korean Meteorological Administration. The discriminant analysis based on 5% significance level was performed to distinguish normal and abnormal climate scenarios. Furthermore, the DMY comparison was simulated based on the information of sample distribution of IRG. As a result, in the southern coastal regions, only the impact of next spring drought on DMY of IRG was critical. Although the severe winter cold was clearly classified from the normal, there was no difference in DMY. Thus, the DMY comparison was simulated only for the next spring drought. Under the yield comparison simulation, DMY (kg/ha) in the normal and drought was 14,743.83 and 12,707.97 respectively. It implies that the expected damage caused by the spring drought was about 2,000 kg/ha. Furthermore, the predicted DMY of spring drought was wider and slower than that of normal, indicating on high variability. This study is meaningful in confirming the predictive DMY damage and its possibility by spring drought for IRG via statistical simulation considering seasonal climate scenarios.

• Korean Journal of Agricultural and Forest Meteorology
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• v.26 no.1
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• pp.53-62
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• 2024

In this study, we built a model to estimate frost occurrence in South Korea using single-input deep learning and multi-input deep learning. Meteorological factors used as learning data included minimum temperature, wind speed, relative humidity, cloud cover, and precipitation. As a result of statistical analysis for each factor on days when frost occurred and days when frost did not occur, significant differences were found. When evaluating the frost occurrence models based on single-input deep learning and multi-input deep learning model, the model using both GRU and MLP was highest accuracy at 0.8774 on average. As a result, it was found that frost occurrence model adopting multi-input deep learning improved performance more than using MLP, LSTM, GRU respectively.