Journal of the Korean Society for Aviation and Aeronautics (한국항공운항학회지)

The Korean Society for Aviation and Aeronautics (한국항공운항학회)
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A Study on the Precursors of Aviation Turbulence via QAR Data Analysis

QAR 데이터 분석을 통한 항공난류 조기 인지 가능성 연구

  • 김인규 (한국항공대학교 항공운항관리학과) ;
  • 장조원 (한국항공대학교 항공운항학과)
  • Received : 2018.11.25
  • Accepted : 2018.12.27
  • Published : 2018.12.31
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Abstract

Although continuous passenger injuries and physical damages are repeated due to the unexpected aviation turbulence encountered during operations, there is still exist the limitation for preventing recurrence of similar events because the lack of real-time information and delay in technological developments regarding various operating conditions and variable weather phenomena. The purpose of this study is to compare and analyze the meteorological data of the aviation turbulence occurred and actual flight data extracted from the Quick Access Recorder(QAR) to provide some precursors that the pilot can identify aviation turbulence early by referring thru the flight instrumentation indications. The case applied for this study was recent event, a scheduled flight from Incheon Airport, Korea to Narita Airport, Japan that suddenly encountered turbulence at an altitude of approximately 14,000 feet during approach. According to the Korea Meteorological Administration(KMA)'s Regional Data Assessment and Prediction System(RDAPS) data, it was observed that the strong amount of vorticity in the rear area of jet stream, which existed near Mount Fuji at that time. The QAR data analysis shows significant changes in the aircraft's parameters such as Pitch and Roll angle, Static Air Temperature(SAT), and wind speed and direction in tens of seconds to minutes before encounter the turbulence. If the accumulate reliability of the data in addition and verification of various parameters with continuous analysis of additional cases, it can be the precursors for the pilot's effective and pre-emptive action and conservative prevention measures against aviation turbulence to reduce subsequent passenger injuries in the aviation operations.

Keywords

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Fig 1. Company SIGWX Chart

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Fig 2. RDAPS_700hpa Chart at 10,000ft

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Fig 3. ALT vs Vertical G

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Fig 4. Pitch vs Vertical G

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Fig 5. Roll vs Vertical G

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Fig 6. SAT vs Vertical G

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Fig 7. Wind Speed vs Vertical G

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Fig 8. Wind Direction vs Vertical G

Table 2. QAR Data Analysis

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Table 1. QAR Data Parameter List

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References

  1. Jung-Hoon Kim and Hye-Yeong Chun, 2011, A Study on Aviation Turbulence over Korea and East Asia
  2. Jung-Hoon Kim and Hye-Yeong Chun, 2012, Development of the Korean Aviation Turbulence Guidance(KTG) System using the Operational Unified Model(UM) of the Korea Meteorological Administration(KMA) and Pilot Report(PIREPs), KSAA
  3. Jimmy Krozel and Robert Sharman, 2015, Remote Detection of Turbulence via ADS-B, AIAA Guidance, Navigation, and Control Conf.
  4. ICAO Annex 6, Operation of Aircraft, Part 1, 6.3 Flight recorders, 9th Edition July 2010
  5. ICAO Annex 13, Aircraft Accident and Incident Investigation, Attachment E, Legal Guidance for the Protection of Information from Safety Data Collection and Processing System, 10th Edition July 2010