• Title, Summary, Keyword: Airfield

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Establishment of Standard Model for Training Flight Infrastructure (훈련용 비행인프라 표준 모델 구축)

  • Lim, Jae-Hwan;Kim, Young-Rok;Choi, Yun-Chul
    • The Journal of Advanced Navigation Technology
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    • v.22 no.3
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    • pp.189-197
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    • 2018
  • In Korea, most of the land area is composed of mountainous areas, making it difficult to develop airports because there is not enough open space to operate airports or airfields. However, the current development of the air transportation industry and the rapid increase of aviation demand, the construction of the training airfield infrastructure should be more actively reviewed for safe and smooth flight training. In this study, we analyze the actual condition of operation of domestic training airfield and the case study of overseas training site in order to establish appropriate level standard model of training infrastructures. In addition, this study suggests implications for the appropriate scale and operational efficiency of the training flight infrastructure.

Noise Analysis of Turbo Prop Aircraft(C90GT) (터보프롭 항공기(C90GT)의 소음 분석)

  • Ryu, Jong-Hyeon;Kim, Woo-Jin;Kim, Gyou-Beom
    • Journal of Convergence for Information Technology
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    • v.9 no.9
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    • pp.141-146
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    • 2019
  • The aircraft noise analysis area in this study is a training airfield where various kinds of aircraft are operated. It is difficult to identify the noise analysis as a real measurement in a training airfield. In order to overcome these practical limitations and to establish appropriate noise countermeasures, a noise map is prepared using the Integrated Noise Model Version 7.0 of the aircraft noise prediction program used by the FAA. The noise of C90GT aircraft was measured while flying the takeoff route, landing route, and long route. We want to identify areas where noise damage is more than 70 WECPNL. No area exceeding the legal standard of 70 WECPNL was found in all routes.

A Case Study on the Application of Echelon Paving Method Using a 12m-Wide Screed Finisher on Flexible Airfield Pavements (광폭 Echelon 공법의 연성 활주로 포장 적용에 관한 사례 연구)

  • Jeon, Kook-Il;Choi, Heung-Sup;Bin, Cheol-Ho
    • 한국방재학회:학술대회논문집
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    • pp.353-356
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    • 2007
  • Asphalt pavements of the airport in service were monitored to construct new runway and taxiway and longitudinal cracks were found on the pavements. The sources of the longitudinal cracks were the low density which was caused by the longitudinal cold joint with asphalt Pavement constructions and the excessive loads of aircraft. Therefore, the echelon paving method using a 12m-wide screed finisher was used to eliminate longitudinal cracks. When the echelon paving is used, construction of the longitudinal joint is changed so that the compaction of the unconfined edge of the first lane is delayed until the second lane is placed. In conclusion, the use of this construction method results in the density of the longitudinal joint being equal to that of the adjacent mat.

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A Study on the Algorithm for Adaptive Odd/Even Multi-shell Median Filter (가변 문턱조건을 이용한 odd/even median filter 알고리즘)

  • 조상복;이일권
    • Proceedings of the IEEK Conference
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    • pp.495-498
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    • 1999
  • In this paper, we propose the adaptive Odd/Even Multi-shell Median Filter(adaptive O/E MMF) to improve the defect that Modified Multi-shell Median Filter(MMMF) can not recover missing lines of vertical and cross direction. This filter uses odd/even multi-shells and new proposed threshold strategy The performance of the proposed filter is evaluated over image 'airfield 'by using MATLAB. As the proposed threshold strategy eliminate the number of redundant replacement, it suppresses impulse noise and recovers missing lines.

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The Study On Customization for Domestic Application of Micro PAVER (Micro PAVER의 국내 적용을 위한 적정화에 대한 연구)

  • An, Deok-Soon;Kwon, Soo-Ahn;Suh, Young-Chan
    • International Journal of Highway Engineering
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    • v.5 no.3
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    • pp.21-29
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    • 2003
  • The management of existing airfield pavement information has currently become difficult and the maintenance cost has increased over time due to the long-term performance. It is needed to develop the method for effective budget allocation and systematic airfield pavement management services. The objectives of this paper are to introduce Micro PAVER, one of the popular pavement management systems, into our management system and customize Micro PAVER based on our environment and pavement management level. This study focused on the analysis on logics and structures of Micro PAVER and customization of important parts in the program using the existing pavement evaluation data and survey method. Customized items selected in this study included the pavement deterioration prediction models, critical PCI, maintenance cost by PCI, maintenance or rehabilitation method and unit cost, and PCI rank.

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Constitutive Modeling for Resilient Behavior of Granular Materials under Repeated Loading (반복하중을 받는 입상재료의 회복탄성거동에 관한 구성모델)

  • Rhee, Suk Keun
    • Journal of The Korean Society of Civil Engineers
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    • v.14 no.4
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    • pp.827-838
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    • 1994
  • Numerous pavement response models rely on constitutive relationships to describe the response of granular materials. In this study, a nonlinear elastic constitutive model which is a function of bulk stress and octahedral shear stress is proposed to describe the resilient behavior of thick granular base courses under flexible airfield pavements. Special features of this model are its accuracy to predict the nonlinear resilient behavior, its simplicity to determine the material constants and its ability to model the secondary effect of decreasing the resilient modulus due to shear effects. In laboratory tests, the nonlinear resilient behavior of granular materials is investigated and values of resilient moduli are determined to provide data for verifying the proposed model. It is found that the resilient modulus is much more dependent on the states of stresses in terms of bulk stress and deviator stress than any other factors. Result of comparison shows that predicted values of resilient moduli are in good agreement with the measured values indicating that the proposed model is suitable to describe the nonlinear resilient behavior of the granular material with wide range of stress states which meet in airfield pavements.

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Development for Estimation Model of Runway Visual Range using Deep Neural Network (심층신경망을 활용한 활주로 가시거리 예측 모델 개발)

  • Ku, SungKwan;Hong, SeokMin
    • The 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.

Performance analysis for Ground Position Accuracy Test of MLAT (MLAT 지상 위치정확도 시험에 대한 성능 분석)

  • Koo, Bon-soo;Jang, Jae-won;Kim, Woo-riul;Kim, Tae-sik
    • The Journal of Advanced Navigation Technology
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    • v.21 no.4
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    • pp.325-331
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    • 2017
  • As a GPS stability problem arises, MLAT system is spotlighted as an alternative technology of ADS-B. MLAT system has a high position accuracy as much as ADS-B. Also, MLAT receives the mode A,C,S, and 1090ES(ADS-B) signals from the mounted aircraft transponder. MLAT receives signals from several receiver units and calculates aircraft positions. MLAT has ADS-B level positioning accurarcy using GPS and can calculate the position information with objects independently. According to global environment changes, Local area multiltilateration(LAM) surveillance system is under development for moving vehicles and aircraft detection in airport. These are still under testing in Tae-an Airfield. In the paper, we analyzed the performance by comparing the calculated position data from MLAT to RTK. In order to confirm the position accuracy of MLAT and the deviation of position data between fixed target and moving target on the ground during the field test in Tae-an Airfield.

A Study for Method of Curved Approach Using the GPS to Apply VFR Airport (GPS를 이용한 VFR 공항에서의 곡선접근 방법에 관한 연구)

  • Ju, Yo-Han;Jun, Hyang-Sig;Jeong, Myeong-Sook;Park, Soo-Bog;Hong, Seung-Beom;Hong, Gyo-Young
    • The Journal of Advanced Navigation Technology
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    • v.18 no.4
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    • pp.296-303
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    • 2014
  • Recently a system is being required to replace ILS due to increasing air traffic. In this paper, Curved approach is applied to an airport where ILS approach cannot be applied due to its geographical condition and restricted aerospace condition, and verified by flight test. After analysing conditions of Tae-an airfield of Hanseo University with virtual ILS approach, airfield applicability was evaluated by Curved approach using by GPS. Normally simulation is performed after establishing approach procedure using electric map, but recently verification is being performed by flight test without simulation because accuracy and reliability are increased. In this paper, established procedure is verified modified by flight test with Pilot Test and Auto Pilot test and controllability and passenger's stability were also checked.

Improved CNN Algorithm for Object Detection in Large Images

  • Yang, Seong Bong;Lee, Soo Jin
    • Journal of the Korea Society of Computer and Information
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    • v.25 no.1
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    • pp.45-53
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    • 2020
  • Conventional Convolutional Neural Network(CNN) algorithms have limitations in detecting small objects in large image. In this paper, we propose an improved model which is based on Region Of Interest(ROI) selection and image dividing technique. We prepared YOLOv3 / Faster R-CNN algorithms which are transfer-learned by airfield and aircraft datasets. Also we prepared large images for testing. In order to verify our model, we selected airfield area from large image as ROI first and divided it in two power n orders. Then we compared the aircraft detection rates by number of divisions. We could get the best size of divided image pieces for efficient small object detection derived from the comparison of aircraft detection rates. As a result, we could verify that the improved CNN algorithm can detect small object in large images.