• International Journal of Naval Architecture and Ocean Engineering
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• v.13 no.1
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• pp.306-320
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• 2021

To ensure safe port operations around the world, it is important to solve mooring problems. In particular, the many ports that face open seas have difficulties with long-period waves. As a countermeasure, the installation of a breakwater is proposed for mooring safety. However, this often cannot be put into practice because of financial issues. Instead, port terminals control berthing schedules with weather forecasting. However, mooring problems remain unsolved, because of inaccurate wave forecasting. To quantify the current situation, numerical simulations are presented with ship motions, fender deflections, and rope tensions. In addition, novel simulations for mooring ropes are proposed considering tension, friction, bending fatigue, and temperature. With this novel simulation, the optimal mooring method in terms of safety and economic efficiency was confirmed. In terms of safety, the optimal mooring method is verified to minimize dangerous mooring situations. Moreover, the optimal mooring method shows economic benefits and efficiency. It can help to reinforce the safety of port terminals and improve the efficiency of port operations.

• Journal of the Korean Society of Industry Convergence
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• v.25 no.1
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• pp.55-60
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• 2022

This study conducted the measurements of air flow rate for blower systems with experiment and numerical. A new airflow rate test method is suggested, with which it is possible to accurate measurements and calculate the air flow rate for blower systems. The blower(axial fan) is an industrial fluid machine device that supplies a large amount of air by driving an impeller with an electric motor, and it is widely used throughout the industry such as steel, power plant, chemical, semiconductor, LC D, food, and cement. The airflow from the blower is for exchanging the heat in the cooling unit or heat exchanger. The temperature of coolants and hydraulic oil primarily depends on the amount of airflow rate through the cooling package so its accurate estimation is very important. Moreover, it required a larger investment in time and cost since it could not be executed until the system is actually made. Therefore, this research is intended to examine the phenomenon of air flow pattern when testing air flow rate, suggested new test method, and show the result of the validation test.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.4
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• pp.1209-1223
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• 2022

Blood pressure is one of the key physiological parameters for determining human health, and can prove whether human cardiovascular function is healthy or not. In general, what we call blood pressure refers to arterial blood pressure. Blood pressure fluctuates greatly and, due to the influence of various factors, even varies with each heartbeat. Therefore, achievement of continuous blood pressure measurement is particularly important for more accurate diagnosis. It is difficult to achieve long-term continuous blood pressure monitoring with traditional measurement methods due to the continuous wear of measuring instruments. On the other hand, radar technology is not easily affected by environmental factors and is capable of strong penetration. In this study, by using machine learning, tried to develop a linear blood pressure prediction model using data from a public database. The radar sensor evaluates the measured object, obtains the pulse waveform data, calculates the pulse transmission time, and obtains the blood pressure data through linear model regression analysis. Confirm its availability to facilitate follow-up research, such as integrating other sensors, collecting temperature, heartbeat, respiratory pulse and other data, and seeking medical treatment in time in case of abnormalities.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.275-275
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• 2023

기후변화는 우리의 현실로 다가와 있지만 기후변화로 인해 어떠한 일이 벌어질 것인지는 정확하게 알 수 없는 문제가 있다. 특히 호우의 강도와 지속시간 등은 수문설계에 영향을 미치는 주요한 인자 임에도 불구하고 과학적이고 합리적인 추론이 쉽지 않다. 본 논문에서는 일본에서 대규모 기후 앙상블 모의실험 기반으로 생성된 d4PDF(Data for Policy Decision Making for Future Change)자료 중 시간 단위의 강수앙상블 모의 자료를 이용하여 기상청 서울지점의 강우강도-지속시간-생기빈도 곡선(Intensity-Duration-Frequency Curve; IDF 곡선)의 변화를 추정해 보았다. 이를 위하여 대용량의 자료를 확보하고 서울지점에서의 과거 50년간의 실측자료와 동일기간의 모의자료에 대한 연최대치 계열에 분위사상법을 적용하여 모의자료의 계통적 오차를 소거할 수 있는 함수를 추정하고 이를 이용하여 미래 시나리오에 적용함으로써 지구평균기온 상승에 대응하는 서울관측지점의 IDF 곡선을 추정하여 제시하였다. 추정 결과의 내용은 다양한 요소에 의해 영향을 받는 미래 기후에 대한 내용이라 신뢰성의 평가가 어렵지만 기존의 강우강도에 일률적으로 위험률을 곱하는 방식보다는 좀 더 합리적인 방법이라 생각되며 향후 수문설계 등에 고려될 수도 있을 것이다.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.167-167
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• 2023

Soil organic carbon (SOC) is a critical component of soil health and is crucial in mitigating climate change by sequestering carbon from the atmosphere. Accurate estimation of SOC storage is essential for understanding SOC dynamics and developing effective soil management strategies. This study aimed to investigate the factors influencing the spatial distribution of SOC storage in South Korea, using bulk density (BD) prediction to estimate SOC stock. The study utilized data from 393 soil series collected from various land uses across South Korea established by Korea Rural Development Administration from 1968-1999. The samples were analyzed for soil properties such as soil texture, pH, and BD, and SOC stock was estimated using a predictive model based on BD. The average SOC stock in South Korea at 30 cm topsoil was 49.1 Mg/ha. The study results revealed that soil texture and land use were the most significant factors influencing the spatial distribution of SOC storage in South Korea. Forested areas had significantly higher SOC storage than other land use types. Climate variables such as temperature and precipitation had a relative influence on SOC storage. The findings of this study provide valuable insights into the factors influencing the spatial distribution of SOC storage in South Korea.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.8
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• pp.2259-2277
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• 2023

We propose a probabilistic fish growth model for smart aquaculture systems equipped with IoT sensors that monitor the ecological environment. As IoT sensors permeate into smart aquaculture systems, environmental data such as oxygen level and temperature are collected frequently and automatically. However, there still exists data on fish weight, tank allocation, and other factors that are collected less frequently and manually by human workers due to technological limitations. Unlike sensor data, human-collected data are hard to obtain and are prone to poor quality due to missing data and reading errors. In a situation where different types of data are mixed, it becomes challenging to develop an effective fish growth model. This study explores the unique characteristics of such a combined environmental and weight dataset. To address these characteristics, we develop a preprocessing method and a probabilistic fish growth model using mixed data sampling (MIDAS) and overlapping mixtures of Gaussian processes (OMGP). We modify the OMGP to be applicable to prediction by setting a proper prior distribution that utilizes the characteristic that the ratio of fish groups does not significantly change as they grow. We conduct a numerical study using the eel dataset collected from a real smart aquaculture system, which reveals the promising performance of our model.

• International Journal of Korean Welding Society
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• v.4 no.1
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• pp.38-45
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• 2004

A practical method for evaluating the possibility of the occurrence of cracking in actual thick-plate T-joint weldments is presented in this study. Systematic experitrients based on the method of the design of experiment are conducted in order to investigate the crack tendency in relation to typical welding parameters such as diffusible hydrogen, restraint intensity, preheating temperature and so on. The elastic analysis using the fmite element techniques is employed to quantify the restraint intensities of the specimens. The defined restraint intensities are treated in numerical way for the sake of considering the most uncertain factor among some major factors that govern the cracking phenomena due to welding. The critical plane for judgment of the crack occurrence or crack density is presented as a function of typical welding parameters including determined restraint intensities. The results of numerical estimation by the proposed method for the experimental specimens show the usefulness as a practical tool in welding induced crack problem having extensive uncertainties.

• Geomechanics and Engineering
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• v.34 no.5
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• pp.507-527
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• 2023

Accurately estimation of the geo-mechanical parameters in Artificial Ground Freezing (AGF) is a most important scientific topic in soil improvement and geotechnical engineering. In order for this, one way is using classical and conventional constitutive models based on different theories like critical state theory, Hooke's law, and so on, which are time-consuming, costly, and troublous. The others are the application of artificial intelligence (AI) techniques to predict considered parameters and behaviors accurately. This study presents a comprehensive data-mining-based model for predicting the Young's Modulus of frozen sand under the triaxial test. For this aim, several single and hybrid models were considered including additive regression, bagging, M5-Rules, M5P, random forests (RF), support vector regression (SVR), locally weighted linear (LWL), gaussian process regression (GPR), and multi-layered perceptron neural network (MLP). In the present study, cell pressure, strain rate, temperature, time, and strain were considered as the input variables, where the Young's Modulus was recognized as target. The results showed that all selected single and hybrid predicting models have acceptable agreement with measured experimental results. Especially, hybrid Additive Regression-Gaussian Process Regression and Bagging-Gaussian Process Regression have the best accuracy based on Model performance assessment criteria.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.6B
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• pp.675-681
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• 2008

In this study, the daily-based reference evapotranspiration was evaluated with Hargreaves equation at the 23 meteorological stations for the time period of 1997-2006. The Hargreaves coefficient was self-calibrated to give the best fit with Penman-Monteith evapotranspiration, being regarded as a reference. On the basis of the estimated parameter set, a generalized regression was conducted to estimate the Hargreaves evapotranspiration by just using temperature data. This study will contribute to water resources planning, irrigation schedule, and environmental management.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.6D
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• pp.1033-1041
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• 2006

In this study, we calculated a space-time variation of GPS precipitable water vapor using GPS meteorology technique during a progress of the typhoon EWINIAR had made an effect on Korean peninsular at 10 July, 2006. We estimated tropospheric dry delay and wet delay for one hourly using 22 GPS permanent stations and precipitable water vapor was conversed by using surface meteorological data. The Korean weighted mean temperature and air-pressure of versa-reduction to the mean sea level have been used for an accuracy improvement of GPS precipitable water vapor estimation. Finally, we compared MTSAT water vapor image, radar image and precipitable water vapor map during a passage of the typhoon EWINIAR.