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.

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.

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.

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.

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.

Safer by design: using computer simulation to predict the evacuation performance of passenger ships

When designing a new passenger ship or modifiying an existing design, how do we ensure that the proposed design is safe from an evacuation point of view? In the building and aviation industries, computer based evacuation models are being used to tackle similar issues. In these industries, the traditonal restrictive prescriptive approach to design is making way for performance based design methodologies using risk assessment and computer simulation. In the maritime industry, ship evacuation models off the promise to quickly and efficiently bring these considerations into the design phase, while the ship is "on the drawing board". This paper describes the development of evacuation models with applications to passenger ships and further discusses issues concerning data requirements and validation.

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 airEXODUS evacuation model and its application to aircraft safety

Computer based mathematical models describing the aircraft evacuation process have a vital role to play in the design and development of safer aircraft, the implementation of safer and more rigorous certification criteria, in cabin crew training and post-mortem accident investigation. As the risk of personal injury and the costs involved in performing full-scale certification trials are high, the development and use of these evacuation modelling tools are essential. Furthermore, evacuation models provide insight into the evacuation process that is impossible to derive from a single certification trial. The airEXODUS evacuation model has been under development since 1989 with support from the UK CAA and the aviation industry. In addition to describing the capabilities of the airEXODUS evacuation model, this paper describes the findings of a recent CAA project aimed at investigating model accuracy in predicting past certification trials. Furthermore, airEXODUS is used to examine issues related to the Blended Wing Body (BWB) and Very Large Transport Aircraft (VLTA). These radical new aircraft concepts pose considerable challenges to designers, operators and certification authorities. BWB concepts involving one or two decks with possibly four or more aisles offer even greater challenges. Can the largest exits currently available cope with passenger flow arising from four or five aisles? Do we need to consider new concepts in exit design? Should the main aisle be made wider to accommodate more passengers? In this paper we discuss various issues evacuation related issues associated VLTA and BWB aircraft and demonstrate how computer based evacuation models can be used to investigage these issues through examination of aisle/exit configurations for BWB cabin layouts.

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.

Self-adaptability and man-in-the-loop: a dilemma in autonomic computing systems

This paper addresses some controversial issues relating to two main questions. Firstly, we discuss 'man-in-the loop' issues in SAACS. Some people advocate this must always be so that man's decisions can override autonomic components. In this case, the system has two subsystems - man and machine. Can we, however, have a fully autonomic machine - with no man in sight; even for short periods of time? What kinds of systems require man to always be in the loop? What is the optimum balance in self-to-human control? How do we determine the optimum? How far can we go in describing self-behaviour? How does a SAACS system handle unexpected behaviour? Secondly, what are the challenges/obstacles in testing SAACS in the context of self/human dilemma? Are there any lesson to be learned from other programmes e.g. Star-wars, aviation and space explorations? What role human factors and behavioural models play whilst in interacting with SAACS?.

Computational fire engineering - do we have what we need?

This presentation will attempt to address the issue of whether the engineering design community has the knowledge, data and tool sets required to undertake advanced evacuation analysis. In discussing this issue I want to draw on examples not only from the building industry but more widely from where ever people come into contact with an environment fashioned by man. Prescriptive design regulations the world over suggest that if we follow a particular set of essentially configurational regulations concerning travel distances, number of exits, exit widths, etc it should be possible to evacuate a structure within a pre-defined acceptable amount of time. In the U.K. for public buildings this turns out to be 2.5 minutes, internationally in the aviation industry this is 90 seconds, in the UK rail industry this is 90 seconds and the international standard adopted by the maritime industry is 60 minutes. The difficulties and short comings of this approach are well known and so I will not repeat them here, save to say that this approach is usually littered with “magic numbers” that do not stand up to scrutiny. As we are focusing on human behaviour issues, it is also worth noting that more generally, the approach fails to take into account how people actually behave, preferring to adopt an engineer’s view of what people should do in order to make their design work. Examples of the failure of this approach are legion and include the; Manchester Boeing 737 fire, Kings Cross underground station fire, Piper Alpha oil platform explosion, Ladbroke Grove Rail crash and fire, Mont Blanc tunnel fire, Scandinavian Star ferry fire and the Station Nightclub fire.

Report on the Testing and Systematic Evaluation of the airEXODUS Aircraft Evacuation Model

This report covers the testing and evaluation of the airEXODUS evacuation model. airEXODUS has been developed for evacuation certification testing, crew training and aircraft design. The report demonstrates the effectiveness of the model.

The use of computer simulation for aircraft evacuation certification: a report from the VERRES project

In this paper a methodology for the application of computer simulation to the evacuation certification of aircraft is suggested. The methodology suggested here involves the use of computer simulation, historic certification data, component testing and full-scale certification trials. The proposed methodology sets out a protocol for how computer simulation should be undertaken in a certification environment and draws on experience from both the marine and building industries. Along with the suggested protocol, a phased introduction of computer models to certification is suggested. Given the sceptical nature of the aviation community regarding any certification methodology change in general, this would involve as a first step the use of computer simulation in conjunction with full-scale testing. The computer model would be used to reproduce a probability distribution of likely aircraft performance under current certification conditions and in addition, several other more challenging scenarios could be developed. The combination of full-scale trial, computer simulation (and if necessary component testing) would provide better insight into the actual performance capabilities of the aircraft by generating a performance probability distribution or performance envelope rather than a single datum. Once further confidence in the technique is established, the second step would only involve computer simulation and component testing. This would only be contemplated after sufficient experience and confidence in the use of computer models have been developed. The third step in the adoption of computer simulation for certification would involve the introduction of several scenarios based on for example exit availability instructed by accident analysis. The final step would be the introduction of more realistic accident scenarios into the certification process. This would require the continued development of aircraft evacuation modelling technology to include additional behavioural features common in real accident scenarios.

A computational study of the characteristics of aircraft post-crash fires

Full-scale furnished cabin fires have been studied experimentally for the purpose of characterising the post-crash cabin fire environment by the US Federal Aviation Administration for many years. In this paper the Computational Fluid Dynamics fire field model SMARTFIRE is used to simulate one of these fires conducted in the C-133 test facility in order to provide further validation of the computational approach and the SMARTFIRE software. The experiment involves exposing the interior cabin materials to an external fuel fire, opening only one exit at the far end of the cabin (the same side as the rupture) for ventilation, and noting the subsequent spread of the external fire to the cabin interior and the onset of flashover at approximately 210 seconds. Through this analysis, the software is shown to be in good agreement with the experimental data, producing reasonable agreement with the fire dynamics prior to flashover and producing a reasonable prediction of the flashover time i.e. 225 seconds. The paper then proceeds to utilize the model to examine the impact on flashover time of the extent of cabin furnishings and cabin ventilation provided by available exits