• Journal of Navigation and Port Research
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• v.47 no.4
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• pp.182-190
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• 2023

This study proposes a predictive model using XGBoost and SHapley Additive exPlanation (SHAP) to estimate fuel consumption in bulk carriers. Previous studies have also utilized ship engine data and weather data. However, they lacked reliability in predicted results and explanations of variables used in the fuel consumption prediction model implementation. To address these limitations, this study developed a predictive model using XGBoost and SHAP. It provides research background, scope, relevant regulations, previous studies, and research methodology. Additionally, it explains the data cleaning method for bulk carriers and verifies results of the predictive model.

• Journal of Navigation and Port Research
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• v.43 no.6
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• pp.335-343
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• 2019

As the regulations of ship exhaust gas have been strengthened recently, many measures are under consideration to reduce fuel consumption. Among them, research has been performed actively to develop a machine-learning model that predicts fuel consumption by using data collected from ships. However, many studies have not considered the methodology of the main parameter selection for the model or the processing of the collected data sufficiently, and the reckless use of data may cause problems such as multicollinearity between variables. In this study, we propose a method to predict the fuel consumption of the ship by using the principal component analysis to solve these problems. The principal component analysis was performed on the operational data of the 13K TEU container ship and the fuel consumption prediction model was implemented by regression analysis with extracted components. As the R-squared value of the model for the test data was 82.99%, this model would be expected to support the decision-making of operators in the voyage planning and contribute to the monitoring of energy-efficient operation of ships during voyages.

• Fire Science and Engineering
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• v.33 no.5
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• pp.1-6
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• 2019

The recent development of biofuel production technology facilitates the widespread use of bioethanol and biodiesel by mixing them with fossil fuels. However, the use of these new blended fuels in combustion could result in severe safety problems, such as fire and explosion. In this study, numerical simulation was performed on the well-stirred reactor (WSR) to simulate the autoignition temperature (AIT) in homogeneous combustion and clarify the effect of ethanol addition on the AIT, the most important property for assessing the potential for fire and explosion. Response surface methodology (RSM) was introduced as a design of experiment (DOE), enabling the AIT to be predicted and optimized systematically with respect to three independent variables: ethanol mole fraction, equivalence ratio, and pressure. The results show that the autoignition temperature primarily depends on the ethanol mole fraction and pressure, while the effects of the equivalence ratio are independent of the AIT. RSM accurately predicted the experimental AIT, indicating that this method can be used to effectively predict the key properties involved in fires and explosions.

• The Korean Journal of Applied Statistics
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• v.30 no.5
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• pp.633-645
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• 2017

This study proposes a statistical procedure for analyzing container ship operation data that can help determine fuel consumption patterns. We first investigate the features that affect fuel consumption and develop the prediction model to find current fuel consumption. The ship data can be divided into two-type data. One set of operation data includes sea route, voyage information, longitudinal water speed, longitudinal ground speed, and wind, the other includes machinery data such as engine power, rpm, fuel consumption, temperature, and pressure. In this study, we separate the effects of external force on ships according to Beaufort Scale and apply a partial least squares regression to develop a prediction model.

• Journal of Korea Port Economic Association
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• v.33 no.1
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• pp.75-87
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• 2017

The purpose of this study is to utilize the system dynamics to carry out a medium and long-term forecasting analysis of the bunker price. In order to secure accurate bunker price forecast, a quantitative analysis was established based on the casual loop diagram between various variables that affects bunker price. Based on various configuration variables such as crude oil price which affects crude oil consumption & production, GDP and exchange rate which influences economic changes and freight rate which is decided by supply and demand in shipping and logistic market were used in accordance with System Dynamics to forecast bunker price and then objectivity was verified through MAPEs. Based on the result of this study, bunker price is expected to rise until 2029 compared to 2016 but it will not be near the surge sighted in 2012. This study holds value in two ways. First, it supports shipping companies to efficiently manage its fleet, offering comprehensive bunker price risk management by presenting structural relationship between various variables affecting bunker price. Second, rational result derived from bunker price forecast by utilizing dynamic casual loop between various variables.

• Proceedings of the KIEE Conference
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• 2009.07a
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• pp.2259_2260
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• 2009

현재 전력수급 상황은 제4차 전력수급 기본계획을 통하여 안정적인 전력공급을 도모하고 있다. 미래의 전력수요를 예측하는 수요예측(Load Forecast)과 소비자의 합리적인 전기소비를 가능하게 하는 수요관리(Demand Management) 및 소비자가 능동적으로 전기소비를 선택하여 사용할 수 있는 수요반응(Demand response)이 있다. 이와 더불어 제 3차 신재생에너지 기본계획을 바탕으로 신재생에너지원을 고려해 수요예측 및 수요관리를 한다면 환경문제와 연료고갈 문제의 개선과 기타 에너지원의 절약이 가능하다. 또한 탄소량 배출 감소 효과와 현재의 수요관리 목표량보다 효과적인 수요관리가 가능하다.

• Journal of Advanced Marine Engineering and Technology
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• v.37 no.4
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• pp.332-337
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• 2013

National investment was performed in the research and development of renewable energy because of climate change by air pollution, exhaustion of energy sources, energy security, and so on. Biodiesel fuel of the renewable energy is highlighted as friendly environment energy, it is possible to operate in regular diesel engines when it is blended with invariable ratios without making any changes. Emission factors have been estimated for commercial ship from various research institutes; however, it is difficult to develop emission factors for military vessels. In this work, biodiesel blended fuel emission factors for sulfur dioxide and carbon dioxide were quantitatively estimated from propulsive diesel engine installed on naval vessel using fuel property analysis. In addition, exhaust emissions were quantitatively calculated on the basis of fuel consumption rate with biodiesel content by percentage.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.33 no.5
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• pp.99-105
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• 2005

Development of an engine with good fuel economy is very important for successful implementation of long endurance miniature UAVs (unmanned aerial vehicles). In the study, a 4-stroke glow-plug engine was modified to a gasoline-fueled spark-ignition engine. Engine tests measuring performance and friction losses were conducted to tune a simulation program for performance prediction. It has been found that excessive friction losses are caused by insufficient lubrication at high speeds. The simulation program predicts that engine power and fuel economy get worse with high altitude due to increasing portion of friction losses. The simulation results suggest quantitative guidelines for further development of a practical engine.

• Journal of the Korean Professional Engineers Association
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• v.26 no.3
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• pp.19-25
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• 1993

산업활동에 의해서 대기중에 배출되어지는 $CO_2$의 예측수법으로써 1983연도 미환경보호국의 보고서 $\ulcorner$지구기후안정화의 정책선정$\lrcorner$ 및 세계적으로 폭넓게 쓰여지고 있는 J. Edmonds & J. Reilly 양씨가 발표한 보문 $\ulcorner$장기 지구 Energy $CO_2$모델$\lrcorner$등을 사용해서 각종 화석연료의 궁극가채매장양으로부터 $CO_2$의 방출양을 예측 검토해 본 것이다. 대기중의 $CO_2$농도는 산업혁명 이후의 약 280ppm에서 최근 약 350ppm으로까지 증대되어가고 있다는 보고다. 그 원인은 지구삼림 개발과 석탄등의 화석연료 연소에 의해 대기중에 방출되어 지는 $CO_2$ 때문인 것이다. 현재 인류는 연간 탄소환산으로써 약 52억톤의 화석연료를 소비하여 발생시킨 $CO_2$를 대기중에 방출하고 있다. 세계기상기구(WMO)와 유엔환경계획(UNEP)이 주최하는 기후변동의 정부간판넬(IPCC)의 보고에서는 만약 아무런 대책도 공시하지 않고 있다면(시나리오 Bau: Bussiness as Usual), 전지구적 평균기온은 내세기의 10년안에 0.3$^{\circ}C$씩 상승이 예상된다고 한다. 이와같은 변화는 과거 1 만년간에 비유할수 없을만큼 급격한 변화도 있다고 하는 것이다. 이것은 2025년에는 내세기말 까지에는 3$^{\circ}C$의 기온상승이 예상되고, 이에 따른 해면상승은 2030년에는 20cm, 내세기말까지에는 65cm로 예상하고 있다.

• Plant Journal
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• v.11 no.3
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• pp.46-52
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• 2015

200MWe 순환유동층보일러인 A화력발전소는 정부정책에 의해 국내 무연탄만을 연료로 배정받아 운영되었다. 하지만 무연탄에 대한 민간수요 증가에 따른 정부의 정책변경에 따라 유 무연탄 혼탄을 2000년대 후반부터 시행하고 있다. 하지만 기동시 석탄 투입온도는 여전히 무연탄 전소시의 기준온도인 $600^{\circ}C$에 석탄을 투입하고 있는 실정이라 기동시간 지연의 한 원인으로 작용하고 있고 기동 중 소요되는 경유의 과다소비라는 고질적인 문제점을 안고 있다. 이에 본 연구에서는 A화력에서 사용되는 석탄에 대한 공업분석과 원소분석을 통하여 비교적 휘발분이 많고 반응성이 좋은 러시아산 유연탄(Suek) 연소에 따른 경유에서 석탄으로의 연료교체시 경제적인 시점을 예측하였다. 실험결과 러시아산 유연탄 (Suek) 연소시 투입가능온도는 연소전환율이 90%이상이 되는 연소최대온도($426^{\circ}C$)가 기술적, 경제적으로 가장 적합한 것으로 예상하였다.