• Tunnel and Underground Space
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• v.9 no.4
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• pp.306-314
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• 1999

In underground spaces including nuclear waste repository, prediction of air quantity, temperature/humidity and pollutant concentration is utmost important for space construction and management during the normal state as well as for determining the measures in emergency cases such as underground fires. This study aims at developing a model for underground space environment which has capabilities to take into account the effects of autocompression for the natural ventilation head calculation, to find the optimal location and size of fans and regulators, to predict the temperature and humidity by calculating the convective heat transfer coefficient and the sensible and latent heat transfer rates, and to estimate the pollutant levels throughout the network. The temperature/humidity prediction model was applied to a military storage underground space and the relative differences of dry and wet temperatures were 1.5 ~ 2.9% and 0.6 ~ 6.1%, respectively. The convection-based pollutant transport model was applied to two different vehicle tunnels. Coefficients of turbulent diffusion due to the atmospheric turbulence were found to be 9.78 and 17.35$m^2$/s, but measurements of smoke and CO concentrations in a tunnel with high traffic density and under operation of ventilation equipment showed relative differences of 5.88 and 6.62% compared with estimates from the convection-based model. These findings indicate convection is the governing mechanism for pollutant diffusion in most of the tunnel-type spaces.

• International Journal of Advanced Culture Technology
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• v.6 no.4
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• pp.190-194
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• 2018

The runway visual range is one of the important factors that decide the possibility of taking offs and landings of the airplane at local airports. The runway visual range is affected by weather conditions like fog, wind, etc. The pilots and aviation related workers check a local weather forecast such as runway visual range for safe flight. However there are several local airfields at which no other forecasting functions are provided due to realistic problems like the deterioration, breakdown, expensive purchasing cost of the measurement equipment. To this end, this study proposes a prediction model of runway visual range for a local airport by applying convolutional neural network that has been most commonly used for image/video recognition, image classification, natural language processing and so on to the prediction of runway visual range. For constituting the prediction model, we use the previous time series data of wind speed, humidity, temperature and runway visibility. This paper shows the usefulness of the proposed prediction model of runway visual range by comparing with the measured data.

• Advances in concrete construction
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• v.5 no.2
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• pp.155-171
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• 2017

The phenomenon of concrete column shortening has been widely acknowledged since it first became apparent in the 1960s. Axial column shortening is due to the combined effect of elastic and inelastic deformations, shrinkage and creep. This study aims to investigate the effects of ambient temperature, relative humidity, cement hardening speed and aggregate type on concrete column shortening. The investigation was conducted using a column shortening prediction model which is underpinned by the Eurocode 2. Critical analysis and evaluation of the results showed that the concrete aggregate types used in the concrete have significant impact on column shortening. Generally, aggregates with higher moduli of elasticity hold the best results in terms of shortening. Cement type used is another significant factor, as using slow hardening cement gives better results compared to rapid hardening cement. This study also showed that environmental factors, namely, ambient temperature and relative humidity have less impact on column shortening.

• Journal of the Korean Society of Tobacco Science
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• v.12 no.2
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• pp.59-65
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• 1990

In order to predict the shelf-life of cigarettes packaged in typical flexible film under conditions of various temperature, relative humidity and sealing degree, a computer iterative technique was used. Although there were some significant differences at initial equilibrium relative humidity(55%), the experimental results agree fairly well with predictions following the student's t test($\alpha$=0.01) in most cases. Essentially, the higher the storage temperature, the shorter the shelf-life of the cigarette product. The bigger the differences from the initial equilibrium relative humidity, the shorter the storage period of the cigarette. Moisture transfer through the film at relatively high temperature gave higher confidence. The sealing degree, one of the storage parameters, appeared to be a major influencing factor to shelf-life. Slopes($\beta$) of the temp., sealing degree and %rh of the dependent variable to shelf life were 0.49, -0.39 and -0, 28 respectively, when analysed by multiple regression of SPSS software. Below 600m1/min sealing decree of the packed cigarette through the sealing Position at 30mmH20 differential pressure, the shelf-life could be increased by more than six months.

• Journal of Conservation Science
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• v.32 no.4
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• pp.491-500
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• 2016

Fog is atmospheric in which tiny drops of water vapor are suspended in the air near the ground. Its form, occurrence, etc., change according to the temperature, relative humidity, wind and geographical features of the space around it. In particular, fog tends to occur near a source of water because of temperature and relative humidity difference. These days, climate change is increasingly affecting the occurrence of fog. Therefore the purpose of this study was to investigate how fog affects materials that are part of our cultural properties through outdoor exposure tests and artificial degradation. The degradation evaluation of materials as a function of fog occurrence frequency, showed that the color of metals changed noticeably, whereas dyed silk and Dancheong showed degradation on the surface and color differences but no particular tendencies. Therefore, damage prediction by color differences as a function of fog occurrence frequency was based on metal samples, which showed constant color differences. Through a comparison of the predictive value and color difference by outdoor exposure, the accuracy and applicability of the damage prediction formula was confirmed. If a more complex damage prediction formula is created, it is expected that prediction of the degree of material damage in the field would be possible.

• Journal of Korean Society of Forest Science
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• v.99 no.2
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• pp.163-171
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• 2010

Forest fires have potentials to change the structure and function of forest ecosystems and significantly influence on atmosphere and biogeochemical cycles. Forest fire also affects the quality of public benefits such as carbon sequestration, soil fertility, grazing value, biodiversity, or tourism. The prediction of fire occurrence and its spread is critical to the forest managers for allocating resources and developing the forest fire danger rating system. Most of fires were human-caused fires in Korea, but meteorological factors are also big contributors to fire behaviors and its spread. Thus, meteorological factors as well as social factors were considered in the fire danger rating systems. A total of 298 forest fires occurred during the fall season from 2002 to 2006 in South Korea were considered for developing a logistic model of forest fire occurrence. The results of statistical analysis show that only effective humidity and temperature significantly affected the logistic models (p<0.05). The results of ROC curve analysis showed that the probability of randomly selected fires ranges from 0.739 to 0.876, which represent a relatively high accuracy of the developed model. These findings would be necessary for the policy makers in South Korea for the prevention of forest fires.

• Journal of the Korean Solar Energy Society
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• v.36 no.1
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• pp.1-9
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• 2016

To well design the solar energy system, the correlation to calculate and predict solar irradiation is basically needed. So, this study was performed to reveal the relationships between the solar irradiation and four meteorological observation data(dry-bulb temperature, relative humidity, duration of sunshine, and amount of cloud) that didn't show from previous any other researches. And then, we finally proposed the various order non-linear correlation from the measured solar irradiation and four meteorological measurement data using MINITAB. To show the deviation and accuracy of the solar irradiation between measured and calculated, this study compared for the daily total solar insolation. From those results, the calculation error could well predicted about maximum 97% for the daily total solar insolation. But, the coefficients of the proposed correlations didn't show any relationships. So, needs more studies to make the proper one correlation for the country.

• Proceedings of the Korean Environmental Sciences Society Conference
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• 2003.11a
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• pp.89-94
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• 2003

The formation of a severe snow storm occurred in the mountainous coastal region near Mt. Taegualyang and Kangnung city in the eastern part of Korea was investigate from 0900LST, December 7 through 9, 2002, using MM5 model. As synoptic scale easterly wind induced a great amount of moisture from the East Sea into the inland coastal region and sea-breeze further induced more moisture from the basin toward the top of the mountain side. The lifted moisture toward the mountain top was cooled down along the eastern slope of the mountain and near the mid of the mountain the moisture was much cooled down with relative humidity of 100％ under the air temperature below $O^{\circ}C$, resulting in the formation of snow. Relative humidity of 100％ generally occurred at the 5km away from the coast toward the inland mountain and the band of 100％ RH was parallel to the coastal line. The 100％ band coincided with minimum air temperature band and line.

• Journal of the Korean earth science society
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• v.24 no.5
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• pp.449-455
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• 2003

Climatic elements were investigated in order to understand the atmospheric environment around the Pohang area and for use as basic information in prediction. In this analysis, we could find that the annual mean temperature, relative humidity, and precipitation are 14.39$^{\circ}C$, 63.3%, and 1.178mm, respectively. The prevailing wind direction was southwestern, and the mean wind speed is 2.7m/s. The amount of cloud was abundant during the summer because of the Jang-ma phenomenon and convective clouds induced by terrain effect. The annual mean duration of sunshine represented about 2,221 hours.

• Journal of Information Technology Applications and Management
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• v.29 no.5
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• pp.27-37
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• 2022

This study intends to link agricultural machine history data with related organizations or collect them through IoT sensors, receive input from agricultural machine users and managers, and analyze them through AI algorithms. Through this, the goal is to track and manage the history data throughout all stages of production, purchase, operation, and disposal of agricultural machinery. First, LSTM (Long Short-Term Memory) is used to estimate oil consumption and recommend maintenance from historical data of agricultural machines such as tractors and combines, and C-LSTM (Convolution Long Short-Term Memory) is used to diagnose and determine failures. Memory) to build a deep learning algorithm. Second, in order to collect historical data of agricultural machinery, IoT sensors including GPS module, gyro sensor, acceleration sensor, and temperature and humidity sensor are attached to agricultural machinery to automatically collect data. Third, event-type data such as agricultural machine production, purchase, and disposal are automatically collected from related organizations to design an interface that can integrate the entire life cycle history data and collect data through this.