• International conference on construction engineering and project management
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• 2013.01a
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• pp.397-402
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• 2013

In super-tall building construction projects, schedule risk factors which vertically change and are not found in the low and middle-rise building construction influence duration of a project by vertical attribute; and it makes hard to estimate activity or overall duration of a construction project. However, the existing duration estimating methods, that are based on quantity and productivity assuming activities of the same work item have the same risk and duration regardless of operation space, are not able to consider the schedule risk factors which change by the altitude of operation space. Therefore, in order to advance accuracy of duration estimation of super-tall building projects, the degree of changes of these risk factors according to altitude should be analyzed and incorporated into a duration estimating method. This research proposes a simulation model using Monte Carlo method for estimating activity duration incorporating schedule risk factors by weather conditions in a super-tall building. The research process is as follows. Firstly, the schedule risk factors in super-tall building are identified through literature and expert reviews, and occurrence of non-working days at high altitude by weather condition is identified as one of the critical schedule risk factors. Secondly, a calculating method of the vertical distributions of the weather factors such as temperature and wind speed is analyzed through literature reviews. Then, a probability distribution of the weather factors is developed using the weather database of the past decade. Thirdly, a simulation model and algorithms for estimating non-working days and duration of each activity is developed using Monte-Carlo method. Finally, sensitivity analysis and a case study are carried out for the validation of the proposed model.

• 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.

• Journal of National Security and Military Science
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• s.7
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• pp.155-231
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• 2009

Xu-Jing(徐競) an official of the Song(宋), a medieval Kingdom of China, wrote a book titled $\ll$Koryo Tu Jing(高麗圖經)$\gg$ which explains his travel to the Koryo as a member of diplomatic mission in 1123. $\ll$Koryo Tu Jing$\gg$ is the record of his personal experience in Koryo with many explanatory illustrations and especially contains 5 months' voyage record of his diplomatic fleet. His fleet set sail at a port located in the Ding Hai Xian(定海縣), Ming Zhou(明州) via a few islands of Koryo [Hyup Kye San(俠界山) , the Kun San Do(群山島) , the Ja Yon Do(紫燕島) , the Keup Su Mun(急水門) in Kang Hwa Gun(江華郡) and the Hap Gul(蛤窟) ] and finally arrived the Port Ye Song Hang(禮成港) . According to the Xu-Jing's record his fleet sailed the sea with the help of the favorable seaward winds and tides as the usual way of ancient sailing. The Xu- Jing's Fleet sailed the sea between the Mei Cen(梅岑), Ming Zhou(明州) of China and the Hyup Kye San(俠界山) of Koryo from about 5:00 a.m., May 24th(of the lunar calendar) to about 5:00 p.m., June 2nd. At this section, the average speed of the seaward winds was 19.45km/h and the average speed of the fleet which sailed only by the power of the winds was 6.29km/h. This means that 32.3% of the favorable seaward winds' speed was equal to the speed of the ancient fleet which sailed only by the power of the favorable seaward winds. The fleet sailed the sea between the Ja Yon Do(紫燕島) and the Keup Su Mun(急水門) from about 9:00 a.m., June 10th to about 1:00 p.m., the same day. At this section the fleet sailed by the power of tides in addition to the favorable seaward winds without oaring. The average speed of the winds was not different from that of former section and the average speed of the tides was 1.937km/h. And at this section the average speed of the fleet increased by 0.41km/h than that of the former section. This means that 21.1% of the speed of the tides was equal to the increased speed of the ancient fleet by virtue of the tides. The fleet sailed the sea between Keup Su Mun(急水門) and the Hap Gul(蛤窟) from about 1:00 p.m., June 10th to about 3:00 p.m., the same day. At this section, there were no seaward winds and the fleet sailed only by the powers of tides and oaring. And at this section, the tide increased the average speed of the fleet by 0.3114km/h and the fleet could sail at the speed of 4.3km/h. So we can conclude that the average speed of ancient fleet without any influences of the seaward winds and tides was 3.98 km/h. We can make use of the various sailing speeds of ancient fleets when judging their maritime activities. If we make use of the various sailing speeds of the ancient fleets as calculated in this article, we will be able to get various important informations about the certain ancient fleet's maritime maneuver. For example, we can infer the sailing routs of a certain fleet and the time when the fleet passed a certain spot by making use of the various sailing speeds of the ancient fleet. In this article I did not take account of the shapes of ships that consist of the ancient fleets and the sizes of the various ships and fleets. It was because that such factors would not change the foresaid conclusions seriously.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.26 no.6
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• pp.447-454
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• 2013

A model-based method is proposed to diagnose the gear crack in the gearbox under variable loading condition with the objective to apply it to the wind turbine CMS(Condition Monitoring System). A simple test bed is installed to illustrate the approach, which consists of motors and a pair of spur gears. A crack is imbedded at the tooth root of a gear. Tachometer-based order analysis, being independent on the shaft speed, is employed as a signal processing technique to identify the crack through the impulsive change and the kurtosis. Lumped parameter dynamic model is used to simulate the operation of the test bed. In the model, the parameter related with the crack is inversely estimated by minimizing the difference between the simulated and measured features. In order to illustrate the validation of the method, a simulated signal with a specified parameter is virtually generated from the model, assuming it as the measured signal. Then the parameter is inversely estimated based on the proposed method. The result agrees with the previously specified parameter value, which verifies that the algorithm works successfully. Application to the real crack in the test bed will be addressed in the next study.

• Journal of the Korea Society for Simulation
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• v.22 no.2
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• pp.101-107
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• 2013

Because forest fires are predicted to increase in severity and frequency under global climate change with important environmental implications, an understanding of fire dynamics is critical for mitigation of these negative effects. For the reason, researchers with different background, such as ecologists, physicists, and mathematical biologists, have developed the simulation models to mimic the forest fire spread patterns. In this study, we suggested a novel model considering the wind effect. Our theoretical forest was comprised of two different tree species with varying probabilities of transferring fire that were randomly distributed in space at densities ranging from 0.0 (low) to 1.0 (high). We then studied the distributional patterns of burnt trees using a two-dimensional stochastic cellular automata model with minimized local rules. We investigated the time, T, that the number of burnt trees reaches 25% of the whole trees for different values of the initial tree density, fire transition probability, and the degree of wind strength. Simulation results showed that the values of T decreased with the increase of tree density, and the wind effect decreased in the case of too high or low tree density. We believe that our model can be a useful tool to explore forest fire spreading patterns.

• Journal of the Korean Institute of Landscape Architecture
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• v.50 no.1
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• pp.68-77
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• 2022

The human thermal environment in an apartment complex located in Seoul was quantitatively analyzed to devise methods to modify human heat-related stresses in landscape and urban planning. Microclimatic data (air temperature, relative humidity, wind speed, and short- and long-wave radiation) were collected at 6 locations [Apt-center, roof (cement), roof (grass), ground, playground, and a tree-lined road] in the late spring and summer, and the data were used to estimate the human thermal sensation, physiological equivalent temperature (PET) and universal thermal climate index (UTCI). As a result, the playground location had the highest thermal environment, and the roof (grass) location had the lowest. The mean difference between the two locations was 0.8-1.1℃ in air temperature, 1.8-4.0% in relative humidity, and 7.5-8.0℃ in mean radiant temperature. In open space locations, the wind speed was 0.4-0.5 ms-1 higher than others. Also, a wind tunnel effect happened at the Apt-center location during the afternoon. For the human thermal sensation, PET and UTCI, the mean differences between the playground and roof (grass) locations were: 5.2℃ (Max. 11.7℃) in late spring and 5.4℃ (Max. 18.1℃) in summer in PET; and 3.0℃ (Max. 6.1℃) in late spring and 2.6℃ (Max. 9.8℃) in summer in UTCI. The mean differences indicated a level change in PET and 1/2 level in UTCI, and the maximum differences showed greater changes, 2-3 levels in PET, and 1-1.5 levels in UTCI. Moreover, the roof (grass) location gave 4.6℃ PET reduction and a 2.5℃ UTCI reduction in late spring, and a 4.4℃ PET reduction and a 2.0℃ UTCI reduction in the summer when compared with the roof (cement) location, which results in a 2/3 level change in PET and a 1/3 level in UTCI. Green infrastructure locations [roof (grass), ground, and a tree-lined road] were not statistically significant in the reduction of PET and UTCI in thermal environment modifying effects. The implementation of green infrastructure, such as rooftop gardens, grass pavement, and street tree planting, should be adopted in landscape planning and be employed for human thermal environment modification.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.34 no.6
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• pp.643-651
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• 2001

Paddlewheel-driven circulation in a culture pond has been simulated based on the depth integrated 2 dimensional hydrodynamic model. Acceleration by paddlewheel is expressed as shaft force divided by water mass discharged by paddlewheel blades. The model has been calibrated and applied to culture ponds as following steps:- i) The model predicted velocities at every 10 m along longitudinal direction from the paddlewheel. The model was calibrated comparing the results with the measured values at mass correction factor $\alpha$ and dimensionless eddy viscosity constant $\gamma$, respectively, in a range $15\~20$ and 6. ii) Wind shear stress was simulated under conditions of direction $0^{\circ}C,\;90^{\circ}C\;and\;180^{\circ}C$ and speed 0.0, 2.5, 5.0 and 7.5 m/s. Change rate of current speed was <$1\%$ at wind in parallel or opposite direction to the paddlewheel-driven jet flow, while $4\%$ at orthogonal angle. iii) The model was then applied to 2 culture ponds located at the Western coast of Korea. The measured and predicted currents for the ponds were compared using the regression analysis. Analysis of flow direction and speed showed correlation coefficients 0.8928 and 0.6782 in pond A, 0.8539 and 0.7071 in pond B, respectively. Hence, the model is concluded to accurately predict circulation driven by paddlewheel such that it can be a useful tool to provide pond management strategy relating to paddlewheel operation and water quality.

• KIPS Transactions on Software and Data Engineering
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• v.6 no.10
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• pp.473-478
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• 2017

Drones require altitude holding in order to achieve flight objectives. The altitude holding of the drone is to repeat the operation of raising or lowering the drone according to the altitude information being measured in real-time. When the drones are maintained altitude, the drone's altitude will continue to change due to external factors such as imbalance in thrust due to difference in motor speed or wind. Therefore, in order to maintain the altitude of drone, we have to exactly measure the continuously changing altitude of the drone. Generally, the acceleration sensor is used for measuring the height of the drones. In this method, there is a problem that the measured value due to the integration error accumulates, and the drone's vibration is recognized by the altitude change. To solve the difficulty of the altitude measurement, commercial drones and existing studies are used for altitude measurement together with acceleration sensors by adding other sensors. However, most of the additional sensors have a limitation on the measurement distance and when the sensors are used together, the calculation processing of the sensor values increases and the altitude measurement speed is delayed. Therefore, it is necessary to accurately measure the altitude of the drone without considering additional sensors or devices. In this paper, we propose a measurement algorithm that improves general altitude measurement method using acceleration sensor and show that accuracy of altitude holding and altitude measurement is improved as a result of applying this algorithm.

• Journal of Korean Society on Water Environment
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• v.29 no.1
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• pp.88-96
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• 2013

Much attention has been needed in water resource management at the watershed due to drought and flooding issues caused by climate change in recent years. Increase in air temperature and changes in precipitation patterns due to climate change are affecting hydrologic cycles, such as evaporation and soil moisture. Thus, these phenomena result in increased runoff at the watershed. The Soil and Water Assessment Tool (SWAT) model has been used to evaluate rainfall-runoff at the watershed reflecting effects on hydrology of various weather data such as rainfall, temperature, humidity, solar radiation, wind speed. For bias-correction of RCP data, at least 30 year data are needed. However, for most gaging stations, only precipitation data have been recorded and very little stations have recorded other weather data. In addition, the RCP scenario does not provide all weather data for the SWAT model. In this study, two scenarios were made to evaluate whether it would be possible to estimate streamflow using measured precipitation and long-term average values of other weather data required for running the SWAT. With measured long-term weather data (scenario 1) and with long-term average values of weather data except precipitation (scenario 2), the estimate streamflow values were almost the same with NSE value of 0.99. Increase/decrease by ${\pm}2%$, ${\pm}4%$ in temperature and humidity data did not affect streamflow. Thus, the RCP precipitation data for Hongcheon watershed were bias-corrected with measured long-term precipitation data to evaluate effects of climate change on streamflow. The results revealed that estimated streamflow for 2055s was the greatest among data for 2025s, 2055s, and 2085s. However, estimated streamflow for 2085s decreased by 9%. In addition, streamflow for Spring would be expected to increase compared with current data and streamflow for Summer will be decreased with RCP data. The results obtained in this study indicate that the streamflow could be estimated with long-term precipitation data only and effects of climate change could be evaluated using precipitation data as shown in this study.

• Korean Journal of Agricultural and Forest Meteorology
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• v.26 no.1
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• pp.1-30
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• 2024

The international community adopts the SSP (Shared Socioeconomic Pathways) scenario as a new greenhouse gas emission pathway. As part of efforts to reflect these international trends and support for climate change adaptation measure in the agricultural sector, the National Institute of Agricultural Sciences (NAS) produced high-resolution (1 km) climate change scenarios for the Korean Peninsula based on SSP scenarios, certified as a "National Climate Change Standard Scenario" in 2022. This paper introduces SSP climate change scenario of the NAS and shows the results of the climate change projections. In order to produce future climate change scenarios, global climate data produced from 18 GCM models participating in CMIP6 were collected for the past (1985-2014) and future (2015-2100) periods, and were statistically downscaled for the Korean Peninsula using the digital climate maps with 1km resolution and the SQM method. In the end of the 21^st century (2071-2100), the average annual maximum/minimum temperature of the Korean Peninsula is projected to increase by 2.6~6.1℃/2.5~6.3℃ and annual precipitation by 21.5~38.7% depending on scenarios. The increases in temperature and precipitation under the low-carbon scenario were smaller than those under high-carbon scenario. It is projected that the average wind speed and solar radiation over the analysis region will not change significantly in the end of the 21st century compared to the present. This data is expected to contribute to understanding future uncertainties due to climate change and contributing to rational decision-making for climate change adaptation.