AASK - Aircraft accident statistics and knowledge: A database of human experience in evacuation, derived from aviation accident reports

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.

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

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

Aircraft accident statistics and knowledge database: analyzing passenger behavior in aviation accidents

The Aircraft Accident Statistics and Knowledge (AASK) database is a repository of passenger accounts from survivable aviation accidents/incidents compiled from interview data collected by agencies such as the US NTSB. Its main purpose is to store observational and anecdotal data from the actual interviews of the occupants involved in aircraft accidents. The database has wide application to aviation safety analysis, being a source of factual data regarding the evacuation process. It also plays a significant role in the development of the airEXODUS aircraft evacuation model, where insight into how people actually behave during evacuation from survivable aircraft crashes is required. This paper describes the latest version of the database (Version 4.0) and includes some analysis of passenger behavior during actual accidents/incidents.

CAA paper 2006/01: a database to record human experience of evacuation in aviation accidents: the aircraft accident statistics and knowledge database (AASK)

This report concerns the development of the AASK V4.0 database (CAA Project 560/SRG/R+AD). AASK is the Aircraft Accident Statistics and Knowledge database, which is a repository of survivor accounts from aviation accidents. Its main purpose is to store observational and anecdotal data from interviews of the occupants involved in aircraft accidents. The AASK database has wide application to aviation safety analysis, being a source of factual data regarding the evacuation process. It is also key to the development of aircraft evacuation models such as airEXODUS, where insight into how people actually behave during evacuation from survivable aircraft crashes is required. With support from the UK CAA (Project 277/SRG/R&AD), AASK V3.0 was developed. This was an on-line prototype system available over the internet to selected users and included a significantly increased number of passenger accounts compared with earlier versions, the introduction of cabin crew accounts, the introduction of fatality information and improved functionality through the seat plan viewer utility. The most recently completed AASK project (Project 560/SRG/R+AD) involved four main components: a) analysis of the data collected in V3.0; b) continued collection and entry of data into AASK; c) maintenance and functional development of the AASK database; and d) user feedback survey. All four components have been pursued and completed in this two-year project. The current version developed in the last year of the project is referred to as AASK V4.0. This report provides summaries of the work done and the results obtained in relation to the project deliverables.

The airEXODUS evacuation model and its application to evacuation certification, crew training and accident investigation.

Computer based mathematical models describing the aircraft evacuation process have a vital role to play in the design and development of safer aircraft, in the implementation of safer and more rigorous certification criteria, cabin crew training and in post mortuum accident investigation. As the risk of personal injury and costs involved in performing large-scale evacuation experiments for the next generation 'Ultra High Capacity Aircraft' (UHCA) are expected to be high, the development and use of these evacuation modelling tools may become essential if these aircraft are to prove a viable reality. In this paper the capabilities and limitations of the airEXODUS evacuation model are described. Its successful application to the prediction of a recent certification trial, prior to the actual trial taking place, is described. Also described is a newly defined parameter known as OPS which can be used as a measure of evacuation trial optimality. In addition, sample evacuation simulations in the presence of fire atmospheres are described. Finally, the data requiremnets of the airEXODUS evacuation model is discussed along with several projects currently underway at the the Univesity of Greenwich designed to obtain this data. Included in this discussion is a description of the AASK - Aircraft Accident Statistics and Knowledge - data base which contains detailed information from aircraft accident survivors.

An analysis of the passenger to cabin crew ratio and exit reliability based on past survivable aviation accidents

A hotly debated issue in the area of aviation safety is the number of cabin crew members required to evacuate an aircraft in the event of an emergency. Most countries regulate the minimum number required for the safe operation of an aircraft, but these rulings are based on little if any scientific evidence. Another issue of concern is the failure rate of exits and slides. This paper examines these issues using the latest version of Aircraft Accident Statistics and Knowledge database AASK V4.0, which contains information from 105 survivable crashes and more than 2,000 survivors, including accounts from 155 cabin crew members.

Individual crisis episodes and cultural transition: finding the macrocosm in the microcosm

According to dialogical self theory (Hermans, 2001), individual identities reflect cultural and subcultural values, and appropriate voices and discourses from the social environment. Bronfenbrenner’s (1979) systemic theory of human development similarly postulates that individual and social development occur in a symbiotic and interdependent fashion. It would therefore be predicted that individual changes in identity reflect macrocosmic changes in cultural values and social structures. The current study investigated narratives of crisis transitions within adults aged 25-40, by way of interviews with 22 participants. An intensive qualitative analysis showed that the narratives of crisis could indeed be viewed as individual manifestations of contemporary cultural changes. National statistics and academic research have documented in the UK substantial cultural shifts over the last twenty years including the lessening popularity of marriage, the rise of freelance and portfolio careers and the growth of accepted alternative gender roles. In individual crises, changes made over the course of the episode were invariably in the same direction as these social changes; towards flexible work patterns, non-marital relationships and redefined gender identities. Before the crisis, participants described their identity as bound into an established discourse of conventionality, a traditional sense of masculinity or feminitity and a singular career role, while after the crisis alternative and fluid identities are explored, and identity is less defined by role and institution. These findings show that changes in the social macrocosm can be found in the individual microcosm, and therefore support dialogical self theory.

The role of evacuation modelling in the development of safer air travel

Computer based mathematical models describing the aircraft evacuation process have a vital role to play in the design and development of safer aircraft, in the implementation of safer and more rigorous certification criteria and in post mortuuum accident investigation. As the risk of personal injury and costs involved in performing large-scale evacuation experiments for the next generation 'Ultra High Capacity Aircraft' (UHCA) are expected to be high, the development and use of these evacuation modelling tools may become essential if these aircraft are to prove a viable reality. In this paper the capabilities and limitation of the air-EXODUS evacuation model are described. Its successful application to the prediction of a recent certificaiton trial, prior to the actual trial taking place, is described. Also described is a newly defined parameter known as OPS which can be used as a measure of evacuation trial optimality. Finally, the data requirements of aircraft evacuation models is discussed along with several projects currently underway at the University of Greenwich designed to obtain this data. Included in this discussion is a description of the AASK - Aircraft Accident Statistics and Knowledge - data base which contains detailed information from aircraft accident survivors.

An aircraft accident database of human experience in evacuation derived from aviation accident reports

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. The Fire Safety Engineering Group of the University of Greenwich is undertaking a large data extraction exercise in order to address this issue. This paper describes the extraction and application of data from 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 currently contains information from 25 survivable aviation accidents covering the period 04/04/77 to 06/08/95, involving some 2415 passengers, 2210 survivors, 205 fatalities and accounts from 669 people. Copyright © 1999 John Wiley & Sons, Ltd.

Research in statistical education — planning of an international survey

As announced in the November 2000 issue of MathStats&OR [1], one of the projects supported by the Maths, Stats & OR Network funds is an international survey of research into pedagogic issues in statistics and OR. I am taking the lead on this and report here on the progress that has been made during the first year. A paper giving some background to the project and describing initial thinking on how it might be implemented was presented at the 53rd session of the International Statistical Institute in Seoul, Korea, in August 2001 in a session on The future of statistics education research [2]. It sounded easy. I considered that I was something of an expert on surveys having lectured on the topic for many years and having helped students and others who were doing surveys, particularly with the design of their questionnaires. Surely all I had to do was to draft a few questions, send them electronically to colleagues in statistical education who would be only to happy to respond, and summarise their responses? I should have learnt from my experience of advising all those students who thought that doing a survey was easy and to whom I had to explain that their ideas were too ambitious. There are several inter-related stages in survey research and it is important to think about these before rushing into the collection of data. In the case of the survey in question, this planning stage revealed several challenges. Surveys are usually done for a purpose so even before planning how to do them, it is advisable to think about the final product and the dissemination of results. This is the route I followed.

An analysis of human behaviour during aircraft evacuation situations using the AASK v3.0 database

The Aircraft Accident Statistics and Knowledge (AASK) database is a repository of survivor accounts from aviation accidents. Its main purpose is to store observational and anecdotal data from the actual interviews of the occupants involved in aircraft accidents. The database has wide application to aviation safety analysis, being a source of factual data regarding the evacuation process. It is also key to the development of aircraft evacuation models such as airEXODUS, where insight into how people actually behave during evacuation from survivable aircraft crashes is required. This paper describes recent developments with the database leading to the development of AASK v3.0. These include significantly increasing the number of passenger accounts in the database, the introduction of cabin crew accounts, the introduction of fatality information, improved functionality through the seat plan viewer utility and improved ease of access to the database via the internet. In addition, the paper demonstrates the use of the database by investigating a number of important issues associated with aircraft evacuation. These include issues associated with social bonding and evacuation, the relationship between the number of crew and evacuation efficiency, frequency of exit/slide failures in accidents and exploring possible relationships between seating location and chances of survival. Finally, the passenger behavioural trends described in analysis undertaken with the earlier database are confirmed with the wider data set.

The AASK Database V3.0: a database of human experience during aircraft evacuation incidents

This paper describes recent developments with the Aircraft Accident Statistics and Knowledge (AASK) database. The AASK database is a repository of survivor accounts from aviation accidents developed by the Fire Safety Engineering Group of the University of Greenwich with support from the UK CAA. Its main purpose is to store observational and anecdotal data from the actual interviews of the occupants involved in aircraft accidents. Access to the latest version of the database (AASK V3.0) is available over the Internet. AASK consists of information derived from both passenger and cabin crew interviews, information concerning fatalities and basic accident details. Also provided with AASK is the Seat Plan Viewer that graphically displays the starting locations of all the passengers - both survivors and fatalities - as well as the exits used by the survivors. Data entered into the AASK database is extracted from the transcripts supplied by the National Transportation Safety Board in the US and the Air Accident Investigation Branch in the UK. The quality and quantity of the data was very variable ranging from short summary reports of the accidents to boxes of individual accounts from passengers, crew and investigators. Data imported into AASK V3.0 includes information from 55 accidents and individual accounts from 1295 passengers and 110 crew.

A modelling approach for coupling numerical analytical techniques applied in microsystems

In this paper, a method for the integration of several numerical analytical techniques that are used in microsystems design and failure analysis is presented. The analytical techniques are categorized into four groups in the discussion, namely the high-fidelity analytical tools, i.e. finite element (FE) method, the fast analytical tools referring to reduced order modeling (ROM); the optimization tools, and probability based analytical tools. The characteristics of these four tools are investigated. The interactions between the four tools are discussed and a methodology for the coupling of these four tools is offered. This methodology consists of three stages, namely reduced order modeling, deterministic optimization and probabilistic optimization. Using this methodology, a case study for optimization of a solder joint is conducted. It is shown that these analysis techniques have mutual relationship of interaction and complementation. Synthetic application of these techniques can fully utilize the advantages of these techniques and satisfy various design requirements. The case study shows that the coupling method of different tools provided by this paper is effective and efficient and it is highly relevant in the design and reliability analysis of microsystems