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The AASK database V4.0: aircraft accident statistics and knowledge. A database to record human experience of evacuation in aviation accidents

The AASK database V4.0: aircraft accident statistics and knowledge. A database to record human experience of evacuation in aviation accidents

Galea, E.R., Finney, K.M., Dixon, A.J.P, Siddiqui, A. and Cooney, D.P. (2004) The AASK database V4.0: aircraft accident statistics and knowledge. A database to record human experience of evacuation in aviation accidents. In: Fourth Triennial International Fire and Cabin Safety Research Conference, 15–19 Nov 2004, Lisbon, Portugal.

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Abstract

This paper describes the AASK database. The AASK database is unique as it is a record of human behaviour during survivable aviation accidents. The AASK database is compiled from interview data compiled by agencies such as the NTSB and the AAIB. The database can be found on the website http://fseg.gre.ac.uk

Item Type: Conference or Conference Paper (Paper)
Additional Information: [1] This paper was first presented at the Fourth Triennial International Fire and Cabin Safety Research Conference held from 15-19 November 2004 in Lisbon, Portugal. It was given within the Evacuation Section.
Uncontrolled Keywords: Aircraft Accident Statistics and Knowledge (AASK) database, aircraft accidents, survivor accounts
Subjects: Q Science > QA Mathematics > QA76 Computer software
T Technology > T Technology (General)
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 Computer Science
School of Computing & Mathematical Sciences > Department of Mathematical Sciences
Related URLs:
Last Modified: 14 Oct 2016 09:02
Selected for GREAT 2016: None
Selected for GREAT 2017: None
Selected for GREAT 2018: None
URI: http://gala.gre.ac.uk/id/eprint/897

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