Computer modelling of human behaviour in aircraft fire accidents

The mathematical simulation of the evacuation process has a wide and largely untapped scope of application within the aircraft industry. The function of the mathematical model is to provide insight into complex behaviour by allowing designers, legislators, and investigators to ask ‘what if’ questions. Such a model, EXODUS, is currently under development, and this paper describes its evolution and potential applications. EXODUS is an egress model designed to simulate the evacuation of large numbers of individuals from an enclosure, such as an aircraft. The model tracks the trajectory of each individual as they make their way out of the enclosure or are overcome by fire hazards, such as heat and toxic gases. The software is expert system-based, the progressive motion and behaviour of each individual being determined by a set of heuristics or rules. EXODUS comprises five core interacting components: (i) the Movement Submodel — controls the physical movement of individual passengers from their current position to the most suitable neighbouring location; (ii) the Behaviour Submodel — determines an individual's response to the current prevailing situation; (iii) the Passenger Submodel — describes an individual as a collection of 22 defining attributes and variables; (iv) the Hazard Submodel — controls the atmospheric and physical environment; and (v) the Toxicity Submodel — determines the effects on an individual exposed to the fire products, heat, and narcotic gases through the Fractional Effective Dose calculations. These components are briefly described and their capabilities and limitations are demonstrated through comparison with experimental data and several hypothetical evacuation scenarios.

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.

Hydrochemical and isotopic tracing of mixing dynamics and water quality evolution under pumping conditions in the mine shaft of the abandoned Frances Colliery, Scotland.

Since 1995, when pumps were withdrawn from deep mines in East Fife (Scotland), mine waters have been rebounding throughout the coalfield. Recently, it has become necessary to pump and treat these waters to prevent their uncontrolled emergence at the surface. However, even relatively shallow pumping to surface treatment lagoons of the initially chemically-stratified mine water from a shaft in the coastal Frances Colliery during two dynamic step-drawdown tests to establish the hydraulic characteristics of the system resulted in rapid breakdown of the stratification within 24 h and a poor pumped water quality with high dissolved Fe loading. Further, data are presented here of hydrochemical and isotopic sampling of the extended pump testing lasting up to several weeks. The use in particular of the environmental isotopes d18O, d2H, d34S, 3H, 13C and 14C alongside hydrochemical and hydraulic pump test data allowed characterisation of the Frances system dynamics, mixing patterns and water quality sources feeding into this mineshaft under continuously pumped conditions. The pumped water quality reflects three significant components of mixing: shallow freshwater, seawater, and leakage from the surface treatment lagoons. In spite of the early impact of recirculating lagoon waters on the hydrochemistries, the highest Fe loadings in the longer-term pumped waters are identified with a mixed freshwater–seawater component affected by pyrite oxidation/melanterite dissolution in the subsurface system.

Towards Extracting Absolute Roughness From Underground Mine Drift Profile Data

The purpose of this paper is to demonstrate a technique to utilize underground mine drift profile data for estimating absolute roughness of an underground mine drift in order to implement the Darcy-Weisbach equation for mine ventilation calculations. This technique could provide mine ventilation engineers with more accurate information upon which they might base their ventilation systems designs. This paper presents preliminary work suggesting that it is possible to estimate the absolute roughness of drift-like tunnels by analyzing profile data (e.g., collected using a scanning laser rangefinder). The absolute roughness is then used to estimate the friction factor employed in the Darcy-Weisbach equation. The presented technique is based on an analysis of the spectral characteristics of profile ranges. Simulations based on real mine data are provided to illustrate the potential viability of this method. It is shown that mining drift roughness profiles appear similar to Gaussian profiles