• International Journal of Quality Innovation
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• v.3 no.2
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• pp.13-28
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• 2002

Higher efficiency and effectiveness of Research & Development phases can be attained using advanced statistical methodologies. In this work statistical methodologies are combined with a deterministic approach to engineering design. In order to show the potentiality of such integration, a simple but effective example is presented. It concerns the problem of optimising the performances of a paper helicopter. The design of this simple device is not new in quality engineering literature and has been mainly used for educational purposes. Taking full advantage of fundamental engineering knowledge, an aerodynamic model is originally formulated in order to describe the flight of the helicopter. Screening experiments were necessary to get first estimates of model parameters. Subsequently, deterministic evaluations based on this model were necessary to set up further experimental phases needed to search (or a better design. Thanks to this integration of statistical and deterministic phases, a significant performance improvement is obtained. Moreover, the engineering knowledge かms out to be developed since an explanation of the “why” of better performances, although approximate, is achieved. The final design solution is robust in a broader sense, being both validated by experimental evidence and closely examined by engineering knowledge.

• International Journal of Advanced Culture Technology
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• v.6 no.4
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• pp.190-194
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• 2018

The runway visual range is one of the important factors that decide the possibility of taking offs and landings of the airplane at local airports. The runway visual range is affected by weather conditions like fog, wind, etc. The pilots and aviation related workers check a local weather forecast such as runway visual range for safe flight. However there are several local airfields at which no other forecasting functions are provided due to realistic problems like the deterioration, breakdown, expensive purchasing cost of the measurement equipment. To this end, this study proposes a prediction model of runway visual range for a local airport by applying convolutional neural network that has been most commonly used for image/video recognition, image classification, natural language processing and so on to the prediction of runway visual range. For constituting the prediction model, we use the previous time series data of wind speed, humidity, temperature and runway visibility. This paper shows the usefulness of the proposed prediction model of runway visual range by comparing with the measured data.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.29 no.4
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• pp.1-20
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• 2021

Due to the recent rapid increase in passenger and cargo air transport demand, the capacity of Jeju International Airport has been approaching its limit. Even though in COVID-19 crisis which has started from Nov 2019, Jeju International Airport still suffers from strong demand in terms of air passenger and cargo transportation. However, it is an undeniable fact that the delay has also increased in Jeju International Airport. In this study, we analyze the correlation between weather and delayed departure operation based on both datum collected from the historical airline operation information and aviation weather statistics of Jeju International Airport. Adopting machine learning techniques, we then analyze weather condition Jeju International Airport and construct a delay prediction model. The model presented in this study is expected to play a useful role to predict aircraft departure delay and contribute to enhance aircraft operation efficiency and punctuality in the Jeju International Airport.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.31 no.3
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• pp.30-41
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• 2023

Aviation turbulence, caused by atmospheric eddies, is a disruptive phenomenon that leads to abrupt aircraft movements during flight. To minimize the damages caused by such aviation turbulence, the Aviation Meteorological Office provides turbulence information through the Korea aviation Turbulence Guidance (KTG) and the Global-Korean aviation Turbulence Guidance (GKTG). In this study, we evaluated the performance of the KTG and GKTG models by comparing the in-situ EDR observation data and the generated aviation turbulence prediction data collected from the mid-level Korean Peninsula region from January 2019 to December 2021. Through objective validation, we confirmed the level of prediction performance and proposed improvement measures based on it. As a result of the improvements, the KTG model showed minimal difference in performance before and after the changes, while the GKTG model exhibited an increase of TSS after the improvements.

• International Journal of Aeronautical and Space Sciences
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• v.17 no.3
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• pp.432-441
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• 2016

Solar energy is the ideal power choice for long-endurance stratospheric airships. The output performance of solar array on stratospheric airship is affected by several major factors: flying latitude, flight date, airship's attitude and the temperature of solar cell, but the research on the effect of these factors on output performance is rare. This paper establishes a new simplified analytical model with thermal effects to analyze the output performance of the solar array. This model consisting of the geometric model of stratospheric airship, solar radiation model and incident solar radiation model is developed using MATLAB computer program. Based on this model, the effects of the major factors on the output performance of the solar array are investigated expediently and easily. In the course of the research, the output power of solar array is calculated for five airship's latitudes of $0^{\circ}$, $15^{\circ}$, $30^{\circ}$, $45^{\circ}$ and $60^{\circ}$, four special dates and different attitudes of five pitch angles and four yaw angles. The effect of these factors on output performance is discussed in detail. The results are helpful for solving the energy problem of the long endurance airship and planning the airline.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.49 no.9
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• pp.749-757
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• 2021

In transportation missions using quadrotor, the payload may change the model parameters, such as mass, moment of inertia, and center of gravity. Moreover, if position of the payload is constantly changing during flight, the effect can adversely affect the control performances. To handle this issue, we suggest Model Reference Adaptive Control based on Linear Quadratic Regulator(LQR+MRAC) to compensate the uncertainty caused by payload. Firstly, the mathematical modeling with the fixed payload is derived. Second, Linear Quadratic Regulator (LQR) is used to design the reference model and baseline controller. Also, through the Stability method, Adaptive law is derived to estimate the model parameters. To verify the performance of proposed control scheme, we compared LQR and LQR+MRAC in situations where uncertainties exist. And, when the disturbance exist, the classic MRAC and proposed controller is compared to analyze the transient response and robustness.

• Proceedings of the Korean Geotechical Society Conference
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• 2006.03a
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• pp.784-793
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• 2006

As the number of CFRD constructions increases, the necessity of an accurate assessment on its behavior also has been increasing accordingly. The performance of concrete faced rockfill dam (CFRD) under different water levels is greatly concerned by dam engineers and designers in the world. However, domestic research on CFRD design and construction has yet been insignificant. This study deals with three centrifuge model tests, mainly investigates the deformation of the concrete faced slabs with different face slab stiffness under different water levels. The prototype of a centrifugal model dam is half size of domestic CFRD dam. Detailed material preparation, model design, model set-up, model instrumentation and testing procedures are presented. In order to simulate the prototype concrete faced slab, three kinds of thin fiberglass plates with different thickness was adopted in the three model tests. The water level control facility was specially designed for this experiment to control the water level rise and drawdown during centrifuge flight. Although most of the results from the three model tests are satisfactory, it is also required that the centrifuge test results should be compared with those of numerical analysis and field measurements to analyze the centrifuge test results more in detail.

• Journal of Korean Society of Transportation
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• v.33 no.2
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• pp.214-222
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• 2015

Jeju International Airport has become the most delayed airport in Korea, due to increased demand in air passengers and unexpected local weather condition. Observing the demands continuously grow for a decade, the airport is expected to be saturated in the near future. As a part of effort to prepare effective and timely measure for this expected situation, airport planners seeks the annual runway capacity, i.e., the appropriate number of flight operations in a given year with tolerable delay. In practice, the FAA formula is frequently adopted for the capacity estimation. The method, however, has intrinsic issues: 1) the hourly capacity imbedded in the formula is not clearly defined and thus the estimated value is vulnerable to be subjective judgement, and 2) the formula doesn't consider aircraft delay resulted from runway congestion. In this paper, we explain a novel method for estimating the daily runway capacity and then converting to the annual capacity taking into account the aircraft delay. In this paper, average delay of aircraft was measured using microscopic air traffic simulation model. Daily capacity of the runways were analyzed based on the simulation outputs and the method to assess the yearly capacity is introduced. Using a microscopic simulation model named TAAM, we measure the average aircraft delay at various levels of flight demand, and then estimate the practical daily runway capacity. The estimated daily and annual runway capacities of Jeju airport are about 460 operations a day which is equal to 169,000 operations year. The paper discusses how to verify the simulation model, and also suggests potential enhancement of the method.

• Journal of the Korean Association of Geographic Information Studies
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• v.22 no.2
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• pp.1-14
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• 2019

In rural areas, composting is a source of non-point pollutants. However, as the quantitative distribution and loading have not been estimated, it is difficult to determine the effect of composting on stream water quality. In this study, composting datum acquired by unmanned aerial vehicle(UAV) was verified by using terrestrial LiDAR, and the management status and load change of the composting was investigated by UAV with manual control flight, thereby obtaining the basic data to determine the effect on the water system. As a result of the comparative accuracy assessment based on terrestrial LiDAR, the difference in the digital surface model(DSM) was within 0.21m and the accuracy of the volume was 93.24%. We expect that the accuracy is sufficient to calculate and utilize the composting load acquired by UAV. Thus, the management status of composting can be investigated by UAV. As the total load change of composting were determined to be $1,172.16m^3$, $1,461.66m^3$, and $1,350.53m^3$, respectively, the load change of composting could be confirmed. We expect that the results of this study can contribute to efficient management of non-point source pollution by UAV.

• Korean Journal of Remote Sensing
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• v.34 no.6_4
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• pp.1545-1553
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• 2018

Recent eruptive activity at Kīlauea Volcano started on at the end of April in 2018 showed rapid ground deflation between May and June in 2018. On summit area Halema'uma'u lava lake continued to drop at high speed and Kīlauea's summit continued to deflate. GPS receivers and electronic tiltmeters detected the surface deformation greater than 2 meters. We explored the time-series surface deformation at Kīlauea Volcano, focusing on the early stage of eruptive activity, using multi-temporal COSMO-SkyMed SAR imagery. The observed maximum deformation in line-of-sight (LOS) direction was about -1.5 meter, and it indicates approximately -1.9 meter in subsiding direction by applying incidence angle. The results showed that summit began to deflate just after the event started and most of deformation occurred between early May and the end of June. Moreover, we confirmed that summit's deflation rarely happened since July 2018, which means volcanic activity entered a stable stage. The best-fit magma source model based on time-series surface deformation demonstrated that magma chambers were lying at depths between 2-3 km, and it showed a deepening trend in time. Along with the change of source depth, the center of each magma model moved toward the southwest according to the time. These results have a potential risk of including bias coming from single track observation. Therefore, to complement the initial results, we need to generate precise magma source model based on three-dimensional measurements in further research.