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.

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.

Uncertainty analysis to minimise risk in designing micro-electronics manufacturing processes

A design methodology based on numerical modelling, integrated with optimisation techniques and statistical methods, to aid the process control of micro and nano-electronics based manufacturing processes is presented in this paper. The design methodology is demonstrated for a micro-machining process called Focused Ion Beam (FIB). This process has been modelled to help understand how a pre-defined geometry of micro- and nano- structures can be achieved using this technology. The process performance is characterised on the basis of developed Reduced Order Models (ROM) and are generated using results from a mathematical model of the Focused Ion Beam and Design of Experiment (DoE) methods. Two ion beam sources, Argon and Gallium ions, have been used to compare and quantify the process variable uncertainties that can be observed during the milling process. The evaluations of the process performance takes into account the uncertainties and variations of the process variables and are used to identify their impact on the reliability and quality of the fabricated structure. An optimisation based design task is to identify the optimal process conditions, by varying the process variables, so that certain quality objectives and requirements are achieved and imposed constraints are satisfied. The software tools used and developed to demonstrate the design methodology are also presented.

Optimisation methodology for risk mitigation in advanced micro-system electronics manufacturing

This paper presents a design methodology based on numerical modelling, integrated with optimisation techniques and statistical methods, to aid the development of new advanced technologies in the area of micro and nano systems. The design methodology is demonstrated for a micro-machining process called Focused Ion Beam (FIB). This process has been modelled to provide knowledge of how a pre-defined geometry can be achieved through this direct milling. The geometry characterisation is obtained using a Reduced Order Models (ROM), generated from the results of a mathematical model of the Focused Ion Beam, and Design of Experiment (DoE) methods. In this work, the focus is on the design flow methodology which includes an approach on how to include process parameter uncertainties into the process optimisation modelling framework. A discussion on the impact of the process parameters, and their variations, on the quality and performance of the fabricated structure is also presented. The design task is to identify the optimal process conditions, by altering the process parameters, so that certain reliability and confidence of the application is achieved and the imposed constraints are satisfied. The software tools used and developed to demonstrate the design methodology are also presented.

Hazard and risk assessment from Hurricane Ivan (2004) in Grenada using Geographical Information Systems and remote sensing

Hurricanes are destructive storms with strong winds, intense storm surges, and heavy rainfall. The resulting impact from a hurricane can include structural damage to buildings and infrastructure, flooding, and ultimately loss of human life. This paper seeks to identify the impact of Hurricane Ivan on the aected population of Grenada, one of the Caribbean islands. Hurricane Ivan made landfall on 7th September 2004 and resulted in 80% of the population being adversely aected. The methods that were used to model these impacts involved performing hazard and risk assessments using GIS and remote sensing techniques. Spatial analyses were used to create a hazard and a risk map. Hazards were identied initially as those caused by storm surges, severe winds speeds, and flooding events related to Hurricane Ivan. These estimated hazards were then used to create a risk map. An innovative approach was adopted, including the use of hillshading to assess the damage caused by high wind speeds. This paper explains in detail the methodology used and the results produced.