• Transactions of the Korean hydrogen and new energy society
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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.

• Journal of Advanced Navigation Technology
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• v.27 no.4
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• pp.365-373
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• 2023

Unmanned aerial vehicles are widely used in various fields, and real-time path replanning is a critical factor in enhancing the safety and efficiency of these devices. In this paper, we propose a real-time path replanning technique based on RRT* and LOSPO. The proposed technique first generates an initial path using the RRT* algorithm and then optimizes the path using LOSPO. Additionally, the optimized path can be converted into a trajectory that considers actual time and the dynamic limits of the aircraft. In this process, environmental changes and collision risks are detected in real-time, and the path is replanned as needed to maintain safe operation. This method has been verified through simulation-based experiments. The results of this paper make a significant contribution to the research on real-time path replanning for UAVs, and by applying this technique to various situations, the safety and efficiency of UAVs can be improved.

• The Korean Journal of Air & Space Law and Policy
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• v.31 no.2
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• pp.37-72
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• 2016

In the aerospace field, besides special purpose airplanes, contracts for supply of various types of products such as prototypes, unmanned aerial vehicles and space launch vehicles are increasing. In the case of the contractor, it was planned to spend a large amount of money to supply the production, but if the purchase specification that presents the quality and performance standard of the product is poor or lacks the capacity to judge the performance, consuming enormous amounts of time and money. Even if the undertaker does not have the ability to supply the products with the required performance and quality to achieve the purpose of the contract, he/she must pay the cost of burial due to the incompleteness of the work and the compensation for the cancellation of the contract. In this case, the defendant ordered the plaintiff to supply the aircraft by the Happy Box method, which is capable of ILS Offset flight as specified in the Purchase Specification, but the plaintiff attempted to supply the aircraft by the RNAV method. Although the ILS ground signal can be inspected by the RNAV method, the aircraft manufactured in the manner claimed by the plaintiff does not have the ILS Offset flight function required by the purchase specification, so the defendant can not achieve the purpose required by the purchase specification. It was a question of whether a defendant's cancellation of contract was legitimate. The aircraft, which is the object of this contract, is a subordinate substitute, so the case contract is of undertaking. Therefore, in order to complete the work in this contract, the major structural parts of the aircraft must be manufactured as agreed and have the performance generally required in the social sense. However, the aircraft delivered by the plaintiff has serious defects because the defendant can not achieve the purpose required by the purchase specification due to the lack of the ILS Offset flight function required by the purchase specification. This deficiency is impossible for the plaintiff to repair, so the defendant 's cancellation of the contract is legitimate.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.39 no.7
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• pp.652-659
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• 2011

A computational system to predict flowfield and infrared signature in aircraft exhaust system is developed. As the first step, a virtual mission profile is considered and an engine is selected through a performance analysis. Then a nozzle that meets the requirement of each mission is designed. The internal flow in the exhaustion nozzle at the maximum thrust is analyzed using a state-of-the-art CFD code. In addition, a system to combine information of the skin temperature distribution of the nozzle and after-body surface with an infrared prediction code is developed. Finally, qualitative results for the infrared signature reduction design are obtained by investigating the infrared signature level under various conditions.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.45 no.7
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• pp.531-538
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• 2017

A flush air data sensing system, which can predict flight speed, angle of attack, and angle of sideslip of the aircraft is designed and manufactured for a small UAV. Two kinds of flush pressure ports, four ports and five ports, are tapped at the same section of fuselage nose-cone. Calibration pressure data at flush ports are obtained through computations for the total aircraft by using Fluent code. Angle of attack, angle of sideslip, total pressure, and static pressure are represented with 4th-order polynomial function and calibration coefficient matrix is obtained using least square method with calibration pressure data. Flight test showed that flight speed, angle of attack, and sideslip angle predicted by four flush ports and five flush ports compared well with those by five-hole probe installed for data comparison. Especially four flush ports revealed nearly same results as those by five flush ports.

• Journal of Advanced Navigation Technology
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• v.21 no.5
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• pp.435-442
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• 2017

The runway visual range affected by fog and so on is one of the important indicators to determine whether aircraft can take off and land at the airport or not. In the case of airports where transportation airplanes are operated, major weather forecasts including the runway visual range for local area have been released and provided to aviation workers for recognizing that. This paper proposes a runway visual range estimation model with a deep neural network applied recently to various fields such as image processing, speech recognition, natural language processing, etc. It is developed and implemented for estimating a runway visual range of local airport with a deep neural network. It utilizes the past actual weather observation data of the applied airfield for constituting the learning of the neural network. It can show comparatively the accurate estimation result when it compares the results with the existing observation data. The proposed model can be used to generate weather information on the airfield for which no other forecasting function is available.

• Journal of Industrial Convergence
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• v.18 no.1
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• pp.79-85
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• 2020

Recently, the RPAS(Remote Piloted Aircraft System), by remote control and autonomous navigation, has been increasing in interest and utilization in various industries and public organizations along with delivery drones, fire drones, ambulances, agricultural drones, and others. The problems of the stability of unmanned drones, which can be self-controlled, are also the biggest challenge to be solved along the development of the drone industry. drones should be able to fly in the specified path the autonomous flight control system sets, and perform automatically an accurate landing at the destination. This study proposes a technique to check arrival by landing point images and control landing at the correct point, compensating for errors in location data of the drone sensors and GPS. Receiving from the Google Map API and learning from the destination video, taking images of the landing point with a drone equipped with a NAVIO2 and Raspberry Pi, camera, sending them to the server, adjusting the location of the drone in line with threshold, Drones can automatically land at the landing point.

• Transactions of the KSME C: Technology and Education
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• v.3 no.1
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• pp.71-78
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• 2015

Although there are differences in the classification of category adopted by each country, small UAS is usually classified as the one less than 25 kg. UAS has been mainly used for military and public purposes, but in recent years, it has spread to the private sector for hobby, media, and so on. Especially, considering the nature of the operating region and applications, it is necessary to improve operating time, noise and vibration in small UAS to ensure the same level of safety with a manned aircraft. This is because the drone can pose health and safety hazard through collision with manned aircraft or crashing into the ground. In this paper, we investigated operational regulations in the United States and European countries. Based on the investigation, a domestic system development plan for small UAS operation is under development.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1433-1435
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• 2003

Very decisive progress was made in advancing fundamental POL-IN-SAR theory and algorithm development during the past decade. This was accomplished with the aid of airborne & shuttle platforms supporting single -to-multi-band multi-modal POL-SAR and also some POL-IN-SAR sensor systems, which will be compared and assessed with the aim of establishing the hitherto not completed but required missions such as tomographic and holographic imaging. Because the operation of airborne test-beds is extremely expensive, aircraft platforms are not suited for routine monitoring missions which is better accomplished with the use drones or UAVs. Such unmanned aerial vehicles were developed for defense applications, however lacking the sophistic ation of implementing advanced forefront POL-IN-SAR technology. This shortcoming will be thoroughly scrutinized resulting in the finding that we do now need to develop most rapidly POL-IN-SAR drone-platform technology especially for environmental stress-change monitoring with a great variance of applications beginning with flood, bush/forest-fire to tectonic-stress (earth-quake to volcanic eruptions) for real-short-time hazard mitigation. However, for routine global monitoring purposes of the terrestrial covers neither airborne sensor implementation - aircraft and/or drones - are sufficient; and there -fore multi-modal and multi-band space-borne POL-IN-SAR space-shuttle and satellite sensor technology needs to be further advanced at a much more rapid phase. The existing ENVISAT with the forthcoming ALOSPALSAR, RADARSAT-2, and the TERRASAT will be compared, demonstrating that at this phase of development the fully polarimetric and polarimetric-interferometric modes of operation must be viewed and treated as preliminary algorithm verification support modes and at this phase of development are still not to be viewed as routine modes.

• Journal of Advanced Navigation Technology
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• v.22 no.6
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• pp.491-499
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• 2018

Runway visual range (RVR), one of the important indicators of aircraft takeoff and landing, is affected by meteorological conditions such as temperature, humidity, etc. It is important to estimate the RVR at the time of arrival in advance. This study estimated the RVR of the local airport after 1 hour by upgrading the RVR estimation model using the proposed deep learning network. To this end, the advancement of the estimation model was carried out by changing the time interval of the meteorological data (temperature, humidity, wind speed, RVR) as input value and the linear conversion of the results. The proposed method generates estimation model based on the past measured meteorological data and estimates the RVR after 1 hour and confirms its validity by comparing with measured RVR after 1 hour. The proposed estimation model could be used for the RVR after 1 hour as reference in small airports in regions which do not forecast the RVR.