Owen, M., Galea, E.R. ORCID: https://orcid.org/0000-0002-0001-6665, Lawrence, P.J. ORCID: https://orcid.org/0000-0002-0269-0231 and Filippidis, L. ORCID: https://orcid.org/0000-0002-1852-0042 (1998) AASK - Aircraft accident statistics and knowledge: A database of human experience in evacuation, derived from aviation accident reports. The Aeronautical Journal, 102 (1017). pp. 353-363. ISSN 0001-9240

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Abstract

Computer based mathematical models describing the aircraft evacuation process have a vital role to play in aviation safety. However such models have a heavy dependency on real evacuation data in order to (a) identify the key processes and factors associated with evacuation, (b) quantify variables and parameters associated with the identified factors/processes and finally (c) validate the models. The Fire Safety Engineering Group of the University of Greenwich is undertaking a large data extraction exercise from three major data sources in order to address these issues. This paper describes the extraction and application of data from one of these sources - aviation accident reports. To aid in the storage and analysis of the raw data, a computer database known as AASK (aircraft accident statistics and knowledge) is under development. AASK is being developed to store human observational and anecdotal data contained in accident reports and interview transcripts. AASK comprises four component sub-databases. These consist of the ACCIDENT (crash details), FLIGHT ATTENDANT (observations and actions of the flight attendants), FATALS (details concerning passenger fatalities) and PAX (observations and accounts from individual passengers) databases. AASK currently contains information from 25 survivable aviation accidents covering the period 4 April 1977 to 6 August 1995, involving some 2415 passengers, 2210 survivors, 205 fatalities and accounts from 669 people. In addition to aiding the development of aircraft evacuation models, AASK is also being used to challenge some of the myths which proliferate in the aviation safety industry such as, passenger exit selection during evacuation, nature and frequency of seat jumping, speed of passenger response and group dynamics. AASK can also be used to aid in the development of a more comprehensive approach to conducting post accident interviews, and will eventually be used to store the data directly.

Item Type:	Article
Uncontrolled Keywords:	aircraft evacuation, AASK (aircraft accident statistics and knowledge)
Subjects:	Q Science > QA Mathematics T Technology > TL Motor vehicles. Aeronautics. Astronautics
Pre-2014 Departments:	School of Computing & Mathematical Sciences School of Computing & Mathematical Sciences > Centre for Numerical Modelling & Process Analysis School of Computing & Mathematical Sciences > Centre for Numerical Modelling & Process Analysis > Fire Safety Engineering Group School of Computing & Mathematical Sciences > Department of Mathematical Sciences
Related URLs:	Publisher Organisation Organisation
Last Modified:	18 Feb 2020 16:20
URI:	http://gala.gre.ac.uk/id/eprint/138

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