• Journal of Astronomy and Space Sciences
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• v.28 no.3
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• pp.203-216
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• 2011

To prepare for a future Korean lunar orbiter mission, semi-optimal lunar capture orbits using finite thrust are designed and analyzed. Finite burn delta-V losses during lunar capture sequence are also analyzed by comparing those with values derived with impulsive thrusts in previous research. To design a hypothetical lunar capture sequence, two different intermediate capture orbits having orbital periods of about 12 hours and 3.5 hours are assumed, and final mission operation orbit around the Moon is assumed to be 100 km altitude with 90 degree of inclination. For the performance of the on-board thruster, three different performances (150 N with $I_{sp}$ of 200 seconds, 300 N with $I_{sp}$ of 250 seconds, 450 N with $I_{sp}$ of 300 seconds) are assumed, to provide a broad range of estimates of delta-V losses. As expected, it is found that the finite burn-arc sweeps almost symmetric orbital portions with respect to the perilune vector to minimize the delta-Vs required to achieve the final orbit. In addition, a difference of up to about 2% delta-V can occur during the lunar capture sequences with the use of assumed engine configurations, compared to scenarios with impulsive thrust. However, these delta-V losses will differ for every assumed lunar explorer's on-board thrust capability. Therefore, at the early stage of mission planning, careful consideration must be made while estimating mission budgets, particularly if the preliminary mission studies were assumed using impulsive thrust. The results provided in this paper are expected to lead to further progress in the design field of Korea's lunar orbiter mission, particularly the lunar capture sequences using finite thrust.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.6
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• pp.4002-4006
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• 2014

The automotive exhaust gases generated by the vehicles containing carbon monoxide, hydrocarbons and lead, is a large concern because of their harm to human health or the living environment. To reduce exhaust gas, it is important to develop a variety of techniques that are currently being used by elemental analysis to determine the optimal conditions. In this study, the anti-freeze coolant contained in the exhaust gas was examined, which can affect the emissions. The effects of the commercially available coolant from five domestic companies on the HC, NOx and $CO_2$ emissions were analyzed to determine the optimal amount of antifreeze. In addition, antifreeze products from the five companies were analyzed with respect to driving time of the cooling fan and the correlation of the NOx emission analysis. The temperature of the engine oil was matched using a manual gear of small passenger inspection standard speed $40{\pm}2Km/h$ so the vehicle could meet the specifications for inspection $90{\sim}93^{\circ}C$. The Company D fan operation time resulted in the shortest antifreeze, $CO_2$ and NOx emissions.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.35 no.2
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• pp.121-127
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• 2011

NOx (Nitrogen Oxide) reduction system periodically needs a rich or stoichiometric operating condition to reduce NOx. A new method that optimizes the control of external HC injection into a diesel exhaust pipe for HC-type LNT (Lean NOx Trap) catalyst system has been developed. In this paper, these catalysts are called HC-LNT catalysts. The concentration and amount of HC can be controlled by controlling the external injection. In this study, we investigated the relationship between the spray behavior of hydrocarbons injected into the transparent exhaust pipe and NOx reduction characteristics. From the results of this experiment, we obtained useful information about the optimum injection and position of HC injector to the exhaust pipe. Further, we obtained useful information about the optimal injection condition for an HC-LNT catalyst system with a gasoline PFI (port fuel injection) typeinjector.

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.10
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• pp.51-57
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• 2016

In this paper, we propose an optimal energy management system using the data inference scheme and the cloud hosting technique in order to improve the efficiency of the energy management. We have been interested in the issue that the energy-saving and efficient management techniques are very useful for reducing the production and supply of energy. The energy management system refers to the control and management system in order to enable the efficient use of energy and also to maintain a comfortable and functional working environment effectively with the help of a computer. The proposed system controls a variety of equipment for energy management, and also gets the data for the inference from the changes in energy consumption environment, which is implemented to enable efficient energy management by adapting and controlling the changes optimally in the working environment. In order to evaluate the performance of the implemented system, some experiments have been performed under consideration of the monthly electric power consumption on the server that the inference engine is operating for the target facilities. Finally, the results show that the proposed system has a good performance.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.40 no.4
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• pp.112-119
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• 2017

Selecting suppliers in the global supply chain is the very difficult and complicated decision making problem particularly due to the various types of supply risk in addition to the uncertain performance of the potential suppliers. This paper proposes a multi-phase decision making model for supplier selection under supply risks in global supply chains. In the first phase, the model suggests supplier selection solutions suitable to a given condition of decision making using a rule-based expert system. The expert system consists of a knowledge base of supplier selection solutions and an "if-then" rule-based inference engine. The knowledge base contains information about options and their consistency for seven characteristics of 20 supplier selection solutions chosen from articles published in SCIE journals since 2010. In the second phase, the model computes the potential suppliers' general performance indices using a technique for order preference by similarity to ideal solution (TOPSIS) based on their scores obtained by applying the suggested solutions. In the third phase, the model computes their risk indices using a TOPSIS based on their historical and predicted scores obtained by applying a risk evaluation algorithm. The evaluation algorithm deals with seven types of supply risk that significantly affect supplier's performance and eventually influence buyer's production plan. In the fourth phase, the model selects Pareto optimal suppliers based on their general performance and risk indices. An example demonstrates the implementation of the proposed model. The proposed model provides supply chain managers with a practical tool to effectively select best suppliers while considering supply risks as well as the general performance.

• Journal of the Korean Society of Propulsion Engineers
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• v.17 no.5
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• pp.1-9
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• 2013

Variable area nozzle, where both throat and exit area vary, is required for optimal expansion and optimal nozzle shape upon operation of after-burner. Steady-state and transient analyses are carried out for each condition with and without afterburner operation and as a function of the location of the nozzle flap. Effects of that nozzle displacement on flow and thrust characteristics are analyzed from numerical results. With variable area nozzle adopted, the combustion field is variable in time, leading to periodically variable thrust. For off-design conditions, flow separation shows up due to over expansion at the flap tips and shock wave does in the nozzle due to under expansion. The undesirable phenomena can be solved by control of variable area nozzle.

• Journal of Hydrogen and New Energy
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• v.25 no.4
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• pp.405-418
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• 2014

Fuel cells are suitable for a power plant of a unmanned aerial vehicle (UAV) as it is not only environmentally friendly and quiet but also more efficient than an internal combustion engine. A fuel cell hybrid UAV has better performance in endurance than a fuel cell only or battery only UAV. One of the key purposes of making fuel cell hybrid UAVs is having long endurance and now maximum 26 hours of flight is possible. Because optimal design and control methods for fuel cell hybrid UAVs are absolutely needed for their long endurance we have to check the methods. The aircraft made by using application-integrated design method has less BOP mass and better performances. The optimal design and control methods are generally based on computer simulations or Hardware-In-The-Loop simulations by using dynamic models for their design and control. The Hardware-In-The-Loop simulation (HILS) is to use a hardware device like a fuel cell stack as well as a simulation program and it allows for making optimally designed applications. This paper introduce efficient methods of design, control and evaluation for the fuel cell hybrid UAVs.

• KIPS Transactions on Software and Data Engineering
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• v.5 no.10
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• pp.477-482
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• 2016

As being the advanced analytics indispensable on big data for agile decision-making and tactical planning in enterprises, distributed processing platforms, such as Hadoop and Spark which distribute and handle the large volume of data on multiple nodes, receive great attention in the field. In Spark platform stack, Spark SQL unveiled recently to make Spark able to support distributed processing framework based on SQL. However, Spark SQL cannot effectively handle advanced analytics that involves machine learning and graph processing in terms of iterative tasks and task allocations. Motivated by these issues, this paper proposes the design of SQL-based big data optimal processing engine and processing framework to support advanced analytics in Spark environments. Big data optimal processing engines copes with complex SQL queries that involves multiple parameters and join, aggregation and sorting operations in distributed/parallel manner and the proposing framework optimizes machine learning process in terms of relational operations.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.10
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• pp.33-39
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• 2019

The improvement of emissions, fuel economy, and combustion noise is a primary target in the development of heavy-duty diesel engines. Multiple injection has been introduced as one of the most promising strategies for this goal. In this research, various multiple injection methods were applied to achieve the optimal strategy in terms of emissions, fuel economy, and combustion noise. In the case of one pilot injection, the smoke emission deteriorated, while the NOx emission was reduced. In the case of 2 pilot injections, the NOx and smoke emissions were reduced by 73% and 84%, respectively. In this case, the combustion noise was analyzed with the maximum pressure-rise rate, and the fuel economy was evaluated with the help of the indicated specific fuel consumption. A 15%:15% 2-pilot injection strategy accomplished improvements of 32.9% for NOx, 60.4% for smoke, 1.95% for fuel consumption, and 19.4% for combustion noise compared to the case of single injection. Based on the data, an optimal injection strategy will be developed for a greater operating range in future work.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.47 no.7
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• pp.479-488
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• 2019

A cruise missile uses wings and a jet engine like an airplane to reach the target after cruising a considerable distance. An integrated design of a cruise missile based on radar cross section (RCS) reduction and enhanced aerodynamic performance is indispensable, since it must be able to fly long-distance at subsonic speed without being detected by enemy radar. In this study, we designed a Taurus-type cruise missile and analyzed its RCS and aerodynamic characteristics using the physical optics (PO) technique and the Navier-Stokes CFD code. As a result, we obtained the optimal shape of cruise missile with improved aerodynamic performance and reduced RCS.