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.

Modelling road traffic accidents using macroscopic second-order models of traffic flow

In this paper, we introduce a macroscopic model for road traffic accidents along highway sections. We discuss the motivation and the derivation of such a model, and we present its mathematical properties. The results are presented by means of examples where a section of a crowded one-way highway contains in the middle a cluster of drivers whose dynamics are prone to road traffic accidents. We discuss the coupling conditions and present some existence results of weak solutions to the associated Riemann Problems. Furthermore, we illustrate some features of the proposed model through some numerical simulations. © The authors 2012.

Dioxins released from chemical accidents

Discrepancies in environmental budgets of dioxin-like compounds may be explained by emissions from accidents involving chlorinated organic chemicals. This source may have important implications for regulation inventories. © 1995 Nature Publishing Group.

Risk factors for falls and injuries in a long-term care facility in Ontario

Objective: To identify risk factors for falls and injuries among seniors living in a long-term care facility. Method: Case-control study of 335 residents living at St. Joseph's Villa, Dundas, Ontario. Cases were defined as residents who fell between July 1, 1996 and June 30, 1997; controls were those who did not fall. To identify risk factors for injury, cases were defined as those with completed incident injury forms and controls as those without. Results: The most important risk factors for falls included: having fallen in the past three months; residing in a secured unit; living in the facility for two or more years; having the potential to cause injury to others; and having an illness, disease or behaviour that may cause a fall. The most important risk factor for injury among those who fell was altered mental state. Conclusion: The risk factors identified may be helpful to those planning falls prevention initiatives within long-term care settings.