• Proceedings of the Korea Water Resources Association Conference
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• 2017.05a
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• pp.480-480
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• 2017

급격한 도시화 및 산업화는 주차장, 건물 및 도로 등 유역의 불투수 면적을 증가시켜 강우에 의한 침수피해 및 비점오염원에 따른 하천의 수질오염을 유발하고 있다. 최근 국내에서는 이러한 문제점을 개선하기 위해 유출저감 시설인 저영향개발 (Low Impact Development, LID)을 도입하여 연구를 진행하고 있다. LID 기술은 우수의 침투 및 저류를 통해 도시화에 따른 영향을 최소화하여 개발 이전의 토지 상태에 최대한 가깝게 만들기 위한 도시개발 기법이다. 대표적인 LID 요소기술로는 옥상녹화, 투수성포장 및 생태저류장치 등이 있으며 도로변, 건물주변, 건물옥상 등에 설치되어 강우유출량과 비점오염물질의 오염부하량을 저감시키는 역할을 한다. 본 연구에서는 안양천에 위치한 가산 1 빗물펌프장 유역에 LID 기법을 적용하였으며, LID 요소기술은 옥상녹화 및 투수성포장으로 선정하였다. LID의 설치위치를 변경하여 적용시키면서 유출지점에서의 우수유출량 및 오염부하량을 산정하고 이를 최대로 저감시킬 수 있는 최적위치를 결정하였다. 최적위치에 LID를 설치하였을 때 우수유출량은 옥상녹화의 경우 약 2.20 %, 투수성포장의 경우 약 2.28 %의 저감효과를 나타내었다. 또한, 오염부하량은 두 가지 경우에서 약 4.74 %의 저감효과를 나타내었다. 최적위치를 결정하는 과정에서 우수유출량과 오염부하량의 저감효과가 서로 독립적으로 거동한다는 것을 확인할 수 있었다. 추후 연구에서는 LID 요소기술을 복합적으로 설치한 경우의 저감효과에 대한 분석이 필요할 것으로 판단된다.

• Journal of IKEEE
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• v.23 no.2
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• pp.675-680
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• 2019

The coal-fired power plant is operated by a combined operation method, which is operated by sliding pressure operation under low load and by fixed pressure operation under high load for improved efficiency. The combined operation is divided into two and three valve open modes. Each plant is operated by selecting the turbine control valve mode in accordance with the manufacturer's recommendation, but is not really operating at the optimal sliding pressure operation according to load range, also Load range of each plant is configured differently. The internal efficiency of the high-pressure turbines is reduced due to loss of the turbine valves and the plant efficiency is reduced. To solve these problems, In this paper, the optimum load range is selected through the analysis method of thermal performance by each load in order to improve the optimum variable pressure operation load range by turbine control valve mode.

• Journal of the Korea institute for structural maintenance and inspection
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• v.15 no.4
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• pp.165-174
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• 2011

This research aims at the optimal constitution of sensors required to identify the structural shortcoming of roller-coaster. In this research we analyzed the dynamic characteristics of roller-coaster by three dimensional FE modelling, decided on the appropriate location and number of sensors through optimal transducer theory, abstracted the mathematical value of modal features before and after damage on the basis of optimally placed and numbered sensors. and then presented it as a primary information about the basic structure which would be applied to damage estimation. As a target structure, the roller-coater at Seoul Children's Grand Park was chosen and built as a model reduced by one twentieth in size. In order to consider the Kinetics features particular to the roller-coaster structure, we made an exact three-dimensional FE modelling for the model structure by means of Spline function. As for the proper location and number of sensors, it was done by applying EIM and EOT. We also estimated the damage from the combination of strength, flexibility, and model corelation after abstracting the value of modal features. Finally the optimal transducer theory presented here in this research was proved to be valid, and the structural damage was well identified through changes in strength and flexibility. As a result, we were able to present the optimal constitution of sensors needed for the analysis of dynamic characteristics and the development of techniques in dynamic characteristics, which would ultimately contribute to the development of health monitoring for roller-coaster.

• Journal of Korea Water Resources Association
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• v.44 no.7
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• pp.565-576
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• 2011

Within a basin, there are potentially multiple locations that can be used as a washland, given their relatively small size when compared with other hydraulic facilities such a dam. However, it is unreasonable to install washlands in all these potential locations due to economic and environmental considerations. In this study, a new methodology for determination of installation priority of washlands is presented. How to integrate the decision variables in this decision making problem has been a key issue in previous studies because a washland can provide many benefits such as flood reduction, agricultural benefit and recreational benefit. In particular, a methodology is needed to integrate all decision variables realistically, properly and reasonably, in situations where there is not sufficient data for direct integration of all these decision variables such as construction cost or benefits a washland can provide. This new methodology aims to suggest how to integrate methodologies used in previous studies. The suggested methodology uses four different rankings which are determined based on a flood reduction effect, a relative significance index, an economic analysis, and a space planning suitability index. These rankings are integrated to determine a final installation priority ranking of washlands by a multi-dimensional scaling method. The new methodology has been applied to the Anseong river basin, to show its applicability, and the application result compared with those of previous studies.

• Korean Journal of Construction Engineering and Management
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• v.17 no.5
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• pp.22-34
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• 2016

The Project Delivery System (PDS) is used in mixed way without clear classification from tendering system and the standard itself that can be selected is set with project budget or estimated cost only. Essentially, the PDS should consider and reflect project characteristics and types, internal and external factors for the purpose of improving the lives of citizens and their welfare. However, the current status is not operated flexibly due to the given budget, period and uniform laws and regulations. In order to solve this problem, this study suggests a Decision Support Model to select the optimal PDS for public construction projects. The current problem of the PDS for public construction projects were identified and the application of a decision support model was proposed. Subsequently a decision-making model was suggested for each PDS using the identified factors and linear discriminant function of discriminant analysis. An additional questionnaire survey and actual practical case analysis were carried out to verify the effectiveness and applicability of the model to actual work. It can be used by adjusting the decision support model and detailed factors according to the specific characteristics of public organization, ability of person in charge and project type.

• Economic and Environmental Geology
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• v.50 no.3
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• pp.225-238
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• 2017

In this study, two viable measures of mean length and cumulative thickness of sand layers as important spatial statistics responsible for optimal SAGD (Steam Assisted Gravity Drainage) location for oil sand development were compared. For the comparisons, various deposits composed of sand and clay media were realized using a geostatistical simulator and the extent of steam chamber is simulated using multiphysics numerical simulator (dualphase flow and heat transfer). Based on the spatial statistics of each realization and the corresponding size of simulated steam chamber, the representativeness of two candidate measures (cumulative thickness and mean length of permeable media) were compared. The results of the geostatistical and SAGD simulations suggest that the mean length of permeable media is better correlated to the size of steam chamber than the cumulative thickness. Given those two-dimensional results, it is concluded that the cumulative thickness of the permeable media alone may not be a sufficient criterion for determining an optimal SAGD location and the mean length needs to be complementarily considered for the sound selections.

• Journal of the Korean Society of Marine Environment & Safety
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• v.27 no.5
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• pp.574-583
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• 2021

Predicting shipping markets is an important issue. Such predictions form the basis for decisions on investment methods, fleet formation methods, freight rates, etc., which greatly affect the profits and survival of a company. To this end, in this study, we propose a shipping freight rate prediction model for container ships using gated recurrent units (GRUs) and long short-term memory structure. The target of our freight rate prediction is the China Container Freight Index (CCFI), and CCFI data from March 2003 to May 2020 were used for training. The CCFI after June 2020 was first predicted according to each model and then compared and analyzed with the actual CCFI. For the experimental model, a total of six models were designed according to the hyperparameter settings. Additionally, the ARIMA model was included in the experiment for performance comparison with the traditional analysis method. The optimal model was selected based on two evaluation methods. The first evaluation method selects the model with the smallest average value of the root mean square error (RMSE) obtained by repeating each model 10 times. The second method selects the model with the lowest RMSE in all experiments. The experimental results revealed not only the improved accuracy of the deep learning model compared to the traditional time series prediction model, ARIMA, but also the contribution in enhancing the risk management ability of freight fluctuations through deep learning models. On the contrary, in the event of sudden changes in freight owing to the effects of external factors such as the Covid-19 pandemic, the accuracy of the forecasting model reduced. The GRU1 model recorded the lowest RMSE (69.55, 49.35) in both evaluation methods, and it was selected as the optimal model.

• The Journal of the Korea Contents Association
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• v.18 no.5
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• pp.191-214
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• 2018

This research empirically analyzed the selection factors and the locational selection factors of the medical service facilities according to the gradual increase of the importance of the selection factors and the locational selection factors regarding the establishments of the small- and medium-sized hospitals according to the rapid changes of the socio-economic conditions. By analyzing the priority order according to the levels of the importance of each evaluation item factor through a research related to the selection factors and the locational selection factors of the small- and medium-sized hospitals and by drawing what the important factors that have the influences on the competitiveness of the pre-existent small- and medium-sized hospitals are through the classification of the real estate locational factors and the non-locational factors, the purpose lies in utilizing them as the basic data and materials for the opening strategies of the small- and medium-sized hospitals considering the special, locational characteristics according to the important factors of the selection factors of the small- and medium-sized hospitals, regarding the medical suppliers that have been preparing, for opening the new, small- and medium-sized hospitals. Based on the results of the preceding researches and the researches on the case examples, 28 evaluation factors were arrived at in terms of the level of the medical treatment, the medical services, the accessibilities of the hospitals, the conveniences of the hospitals, and the physical environment. And, regarding the 28 detailed evaluation factors that had been collected, through the interviews with the related experts, the 5 factors of the medical level, the medical service, the expertise of the hospital, the convenience of the hospital, and the physical environment were selected as the upper class evaluation factors. And, according to each upper class, a total of 28 low-part evaluation factors were selected. Regarding the optimal evaluation factors that were selected, the optimal locational factors were selected by carrying out an AHP questionnaire survey investigation with 200 medical experts as the subjects. Regarding the AHP analysis results, similarly with the case examples of the precedent researches, the levels of the importance appeared in the order of the medical level, the medical services, the accessibility of the hospital, the physical environment, and the convenience. And the factors that were related to the facilities of a hospital appeared low. The results of this research can be applied in providing the basis for the decision-makings regarding the selections of the locations of the small- and medium-sized hospitals in the future.

• Korean Journal of Agricultural and Forest Meteorology
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• v.18 no.4
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• pp.208-220
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• 2016

Automatic Mountain Meteorology Observation System (AMOS) is an important ingredient for several climatological and forest disaster prediction studies. In this study, we select the optimal sites for AMOS in the mountain areas of Honam and Jeju in order to prevent forest disasters such as forest fires and landslides. So, this study used spatial dataset such as national forest map, forest roads, hiking trails and 30m DEM(Digital Elevation Model) as well as forest risk map(forest fire and landslide), national AWS information to extract optimal site selection of AMOS. Technical methods for optimal site selection of the AMOS was the firstly used multifractal model, IDW interpolation, spatial redundancy for 2.5km AWS buffering analysis, and 200m buffering analysis by using ArcGIS. Secondly, optimal sites selected by spatial analysis were estimated site accessibility, observatory environment of solar power and wireless communication through field survey. The threshold score for the final selection of the sites have to be higher than 70 points in the field assessment. In the result, a total of 159 polygons in national forest map were extracted by the spatial analysis and a total of 64 secondary candidate sites were selected for the ridge and the top of the area using Google Earth. Finally, a total of 26 optimal sites were selected by quantitative assessment based on field survey. Our selection criteria will serve for the establishment of the AMOS network for the best observations of weather conditions in the national forests. The effective observation network may enhance the mountain weather observations, which leads to accurate prediction of forest disasters.

• Korean Journal of Environmental Agriculture
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• v.22 no.1
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• pp.26-35
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• 2003

An investigation was carried out to evaluate the effects of pebble size on the small-scale sewage treatment apparatus by natural purification method that consisted of aerobic and anaerobic plot. pH and EC in both plots varied minimally regardless of pebble size. DO in aerobic plot increased as the pebble size decreased. That in the anaerobic plot was slightly less in comparison with that of the aerobic plot but varied minimally, $2.4{\sim}5.1\;mg/L$ regardless of pebble size. Under all experimental conditions, removals of BOD, COD and turbidity in anaerobic plot were more than 98, 91 and 98, 98% respectively. Removals of T-N and T-P increased as pebble size decreased. Under all experimental conditions, removals of T-N and T-P in anaerobic plot were about $45{\sim}59$ and $480{\sim}96%$, respectively. Judging from the above results, it should be considered that the optimum pebble size and pebble permeability in both plot was $2{\sim}4$ and $0.1{\sim}4\;mm$, respectively.