• Journal of Advanced Navigation Technology
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• v.27 no.6
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• pp.888-896
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• 2023

When an aircraft is landing, it is expected that the aircraft will follow a specified approach procedure and then land at the airport. However, depending on the airport situation, neighbouring aircraft or the instructions of the air traffic controller, there can be a deviation from the specified approach. Detecting aircraft approach patterns is necessary for traffic flow and flight safety, and this paper suggests clustering techniques to identify aircraft patterns in the approach segment. The Gaussian Mixture Model (GMM), one of the machine learning techniques, is used to cluster the trajectories of aircraft, and ADS-B data from aircraft landing at the Gimhae airport in 2019 are used. The aircraft trajectories are clustered on the plane, and a total of 86 approach trajectory patterns are extracted using the centroid value of each cluster. Considering the correlation between the approach procedure pattern and overshoots, the distribution of overshoots is calculated.

• Journal of the Society of Naval Architects of Korea
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• v.61 no.5
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• pp.289-296
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• 2024

Recently, with the acceleration of global warming, the importance of carbon neutrality is being emphonasized. In response to this, various technologies are being developed to achieve carbon neutrality, with Carbon Capture, Utilization, and Storage (CCUS) being a prominent example. Research has been conducted on the injection technology to environmentally discharge carbon captured by using one of the carbon capture technologies, HAK-CRS. In this study, numerical simulations were performed using commercial software, ANSYS Fluent, to understand the dispersed multiphase flow between a water jet and CaCO₃ particles. The analysis focused on the differences in particle behavior when injecting CaCO₃ with different flow rates. It was observed that as the mass flow rate of CaCO₃ increased, there was a tendency for the particles to deviate from the flow of the jet and rapidly fall, influenced significantly by gravity. These results indicate that, for CaCO₃ particles to disperse widely, the flow rate should not be excessively high. Given the potential adverse impacts on marine ecosystems due to the high density of CaCO₃, research on injection technology should also be conducted.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.21 no.1
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• pp.1-10
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• 2016

Currently available surface seawater partial pressure carbon dioxide ($pCO_2$) data sets in the East Sea are not enough to quantify statistically the carbon dioxide flux through the air-sea interface. To complement the scarcity of the $pCO_2$ measurements, we construct a neural network (NN) model based on satellite data to map $pCO_2$ for the areas, which were not observed. The NN model is constructed for the Ulleung Basin, where $pCO_2$ data are best available, to map and estimate the variability of $pCO_2$ based on in situ $pCO_2$ for the years from 2003 to 2012, and the sea surface temperature (SST) and chlorophyll data from the MODIS (Moderate-resolution Imaging Spectroradiometer) sensor of the Aqua satellite along with geographic information. The NN model was trained to achieve higher than 95% of a correlation between in situ and predicted $pCO_2$ values. The RMSE (root mean square error) of the NN model output was $19.2{\mu}atm$ and much less than the variability of in situ $pCO_2$. The variability of $pCO_2$ with respect to SST and chlorophyll shows a strong negative correlation with SST than chlorophyll. As SST decreases the variability of $pCO_2$ increases. When SST is lower than $15^{\circ}C$, $pCO_2$ variability is clearly affected by both SST and chlorophyll. In contrast when SST is higher than $15^{\circ}C$, the variability of $pCO_2$ is less sensitive to changes in SST and chlorophyll. The mean rate of the annual $pCO_2$ increase estimated by the NN model output in the Ulleung Basin is $0.8{\mu}atm\;yr^{-1}$ from 2003 to 2014. As NN model can successfully map $pCO_2$ data for the whole study area with a higher resolution and less RMSE compared to the previous studies, the NN model can be a potentially useful tool for the understanding of the carbon cycle in the East Sea, where accessibility is limited by the international affairs.

• Korean Journal of Environment and Ecology
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• v.33 no.6
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• pp.624-635
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• 2019

Bird strike accidents, a collision between aircraft and birds, have been increasing annually due to an increasing number of aircraft operating each year to meet heavier demand for air traffic. As such, many airports have conducted studies to assess and manage bird strike risks effectively by identifying and ranking bird species that can damage aircraft based on the bird strike records. This study was intended to investigate the bird species that were likely to threaten aircraft and compare and discuss the risk of each species estimated by the single-matrix and multi-matrix risk assessment models based on the Integrated Flight Information Service (IFIS) data collected in Gimpo, Gimhae and Jeju Airports in South Korea from 2005 to 2013. We found that there was a difference in the assessment results between the two models. The single-matrix model estimated 2 species and 6 taxa in Gimpo and Gimhae Airports and 2 species and 5 taxa in Jeju Airport to have the risk score above "high," whereas the multi-matrix model estimated 3 species and 5 taxa in Gimpo Airport, 4 species and 5 taxa in Gimhae Airport, and 2 species and 3 taxa in Jeju Airport to have the risk score above "very high." Although both models estimated the similar high-risk species in Gimpo and Gimhae Airports, there was a significant difference in Jeju Airport. Gimpo and Gimhae Airports are near the estuary of a river, which is an excellent habitat for large and heavy waterbirds. On the other hand, Jeju Airport is near the coast and the city center, and small and light bird species are mostly observed. Since collisions with such species have little effect on aircraft fuselage, the impact of common variables between the two models was small, and the additional variables caused a significant difference between the estimation by the two models.

• Korean Journal of Agricultural and Forest Meteorology
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• v.21 no.1
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• pp.29-41
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• 2019

Terrestrial Gross Primary Production (GPP) is the largest global carbon flux, and forest ecosystems are important because of the ability to store much more significant amounts of carbon than other terrestrial ecosystems. There have been several attempts to estimate GPP using mechanism-based models. However, mechanism-based models including biological, chemical, and physical processes are limited due to a lack of flexibility in predicting non-stationary ecological processes, which are caused by a local and global change. Instead mechanism-free methods are strongly recommended to estimate nonlinear dynamics that occur in nature like GPP. Therefore, we used the mechanism-free machine learning techniques to estimate the daily GPP. In this study, support vector machine (SVM), random forest (RF) and artificial neural network (ANN) were used and compared with the traditional multiple linear regression model (LM). MODIS products and meteorological parameters from eddy covariance data were employed to train the machine learning and LM models from 2006 to 2013. GPP prediction models were compared with daily GPP from eddy covariance measurement in a deciduous forest in South Korea in 2014 and 2015. Statistical analysis including correlation coefficient (R), root mean square error (RMSE) and mean squared error (MSE) were used to evaluate the performance of models. In general, the models from machine-learning algorithms (R = 0.85 - 0.93, MSE = 1.00 - 2.05, p < 0.001) showed better performance than linear regression model (R = 0.82 - 0.92, MSE = 1.24 - 2.45, p < 0.001). These results provide insight into high predictability and the possibility of expansion through the use of the mechanism-free machine-learning models and remote sensing for predicting non-stationary ecological processes such as seasonal GPP.

• Korean Journal of Food Science and Technology
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• v.29 no.2
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• pp.292-301
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• 1997

In drying process, to minimize the quality degradation by improved drying process and pretreatment methods, carrots, cabbages and radishes were dried and rehydrated. Physico-chemical properties of product were analyzed to determine the optimum pretreatment method and drying models were applied to explain drying mechanisms. Microwave, steam and water were used prior to drying as blanching method. In consideration of physical properties, optimum treatment time was decided that microwave was 1 min, steam and water were each 10 min. Control, steam, water, microwave and osmotic dehydration were treated prior to drying as pretreatment individually, osmotic dehydration was lower than the other treatmemt in drying efficiency, but carotene content was higher than the others. The effect continued after rehydration. Ten panelists tested dried and rehydrated carrots. After rehydration, the quality of air dried product with osmotic dehydration was superior to freeze dried without treatment. The fittness of drying models were conducted in order to explain the mechanism of drying each process. Quadratic model was most fittable to explain during drying. However, in rehydration process, no fittable model was found.

• Journal of Advanced Marine Engineering and Technology
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• v.37 no.4
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• pp.316-323
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• 2013

The use of artificial roughness in various forms of shapes and sizes is the most common and effective way to improve the performance of a flat-plate solar collector. In the present study, numerical analysis on heat transfer and pressure drop was performed in a rectangular channel with various rib arrays. The uniform heat flux is applied to the channel from the upper side. The forms of ribs considered in this study were rib $90^{\circ}$, groove $90^{\circ}$, groove $60^{\circ}$, baffle $90^{\circ}$, baffle $60^{\circ}$, wave $90^{\circ}$ and wave $60^{\circ}$. Air is the working fluid, and the Reynolds number ranges from 3200 to 17800. Nusselt number and friction factor were investigated to predict the performance of the system with various type of ribs. The average Nusselt number and pressure drop were increased with the increase of velocity in all types of ribs. The highest heat transfer and pressure drop occurred for the baffle $90^{\circ}$, but highest performance factor considering heat transfer and pressure drop together occurred for the groove $60^{\circ}$. Therefore, heat transfer and pressure drop should be considered together when a flat plate solar collector is designed.

• Journal of the Korea Organic Resources Recycling Association
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• v.8 no.2
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• pp.154-160
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• 2000

Landfill gas (LFG) utilization in old landfill was estimated using LFG models. The results showed that Scholl Canyon model best described the LFG generation. LFG was extracted more than the amount of natural production which caused air inflow from outside that resulted in dilution of methane concentration and increase of oxygen concentration. It was negative for the LFG utilization. Therefore, to use LFG, the plan of stabilization by LFG extraction should be ineffective. The use of LFG will have no problem if LFG is extracted less than the amount of natural production which was estimated based on modeling. At 8 years elapsed from landfill, now, the amount of natural landfill gas production was decreased sharply. The plan for using LFG from old landfill is feasible if LFG is used for the less than the amount of natural production as a small scale even though for the aspect of efficiency, it was less economic than use of LFG just after closing landfilling and it was helpful for stabilization of landfill by LFG extraction.

• The Journal of the Korea Contents Association
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• v.17 no.2
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• pp.327-336
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• 2017

People spend most of their time in the indoor environment. Among the various indoor environmental factors, air and thermal environment directly affect human's health and efficiency of work. Therefore, efficient monitoring of indoor environment is highly important. For assisting the residents to understand the state of the indoor environment much easier and more intuitive, this paper analyze the visualization cases of the conventional indoor environment. Then explore the direction of improvement for the visualization method to propose a more effective visualization method. The approach of web and BIM(Building Information Model)-based visualization of indoor environment proposed in this study is composed of four major parts: 1) the generation of the model data of the building; 2) the generation of indoor environmental data; 3) the creation of visualization elements; 4) data mapping. Then it realized through the generating process of visualization results.

• Journal of Bio-Environment Control
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• v.9 no.4
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• pp.201-206
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• 2000

A certain system to overcome high temperature should be introduced for the stable year-round cultivation in greenhouses. There are efficient methods to overcome high temperature such as ventilation system with shading screen, fan and pad system with screen, and fog system with screen. This study was carried out to find a means to determine the capacity of such system. Heat balance equations for each system were established and verified by experimental results. The calculated ventilation rates from heat balance equations showed a good agreement with the measured ones. The evapotranspiration coefficient was the most important parameter affecting the ventilation requirement among input parameter affecting the ventilation requirement among input parameters except weather data. When the evaportanspiration coefficient increased 1%, the ventilation requirement decreased 1.3%. Therefore the data of evapotranspiration coefficient should be accumulated by various experiments, and then design standards and selection guidelines should be provided. The simulation results for same design conditions shown that air exchanges requirement and evaporating water of fan and pad system were 5.1∼7.7% and 6.8∼9.3% larger than those of fog system, respectively.