6 resultados para Board group dynamics

em Greenwich Academic Literature Archive - UK


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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.

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A commercial pyrometallurgical process for the extraction of platinum-group metals (PGM) from a feedstock slag was analysed with the use of a model based on computational fluid dynamics. The results of the modelling indicate that recovery depends on the behaviour of the collector phase. A possible method is proposed for estimation of the rate at which PGM particles in slag are absorbed into an iron collector droplet that falls through it. Nanoscale modelling techniques (for particle migration or capture) are combined with a diffusion-controlled mass-transfer model to determine the iron collector droplet size needed for >95% PGM recovery in a typical process bath (70 mm deep) in a realistic time-scale (<1 h). The results show that an iron droplet having a diameter in the range 0.1–0.3 mm gives good recovery (>90%) within a reasonable time. This finding is compatible with published experimental data. Pyrometallurgical processes similar to that investigated should be applicable to other types of waste that contain low levels of potentially valuable metals.

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SMARTFIRE, an open architecture integrated CFD code and knowledge based system attempts to make fire field modeling accessible to non-experts in Computational Fluid Dynamics (CFD) such as fire fighters, architects and fire safety engineers. This is achieved by embedding expert knowledge into CFD software. This enables the 'black-art' associated with the CFD analysis such as selection of solvers, relaxation parameters, convergence criteria, time steps, grid and boundary condition specification to be guided by expert advice from the software. The user is however given the option of overriding these decisions, thus retaining ultimate control. SMARTFIRE also makes use of recent developments in CFD technology such as unstructured meshes and group solvers in order to make the CFD analysis more efficient. This paper describes the incorporation within SMARTFIRE of the expert fire modeling knowledge required for automatic problem setup and mesh generation as well as the concept and use of group solvers for automatic and manual dynamic control of the CFD code.

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At 8.18pm on 2 September 1998, Swissair Flight 111 (SR 111), took off from New York’s JFK airport bound for Geneva, Switzerland. Tragically, the MD-11 aircraft never arrived. According to the crash investigation report, published on 27 March 2003, electrical arcing in the ceiling void cabling was the most likely cause of the fire that brought down the aircraft. No one on board was aware of the disaster unfolding in the ceiling of the aircraft and, when a strange odour entered the cockpit, the pilots thought it was a problem with the air-conditioning system. Twenty minutes later, Swissair Flight 111 plunged into the Atlantic Ocean five nautical miles southwest of Peggy’s Cove, Nova Scotia, with the loss of all 229 lives on board. In this paper, the Computational Fluid Dynamics (CFD) analysis of the in-flight fire that brought down SR 111 is described. Reconstruction of the wreckage disclosed that the fire pattern was extensive and complex in nature. The fire damage created significant challenges to identify the origin of the fire and to appropriately explain the heat damage observed. The SMARTFIRE CFD software was used to predict the “possible” behaviour of airflow as well as the spread of fire and smoke within SR 111. The main aims of the CFD analysis were to develop a better understanding of the possible effects, or lack thereof, of numerous variables relating to the in-flight fire. Possible fire and smoke spread scenarios were studied to see what the associated outcomes would be. This assisted investigators at Transportation Safety Board (TSB) of Canada, Fire & Explosion Group in assessing fire dynamics for cause and origin determination.

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In 1998, Swissair Flight I I I (SR111) developed an in-flight fire shortly after take-off which resulted in the loss of the aircraft, a McDonnell Douglas MD-I 1, and all passengers and crew. The Transportation Safety Board (TSB) of Canada, Fire and Explosion Group launched a four year investigation into the incident in an attempt to understand the cause and subsequent mechanisms which lead to the rapid spread of the in-flight fire. As part of this investigation, the SMARTFIRE Computational Fluid Dynamics (CFD) software was used to predict the 'possible' development of the fire and associated smoke movement. In this paper the CFD fire simulations are presented and model predictions compared with key findings from the investigation. The model predictions are shown to be consistent with a number of the investigation findings associated with the early stages of the fire development. The analysis makes use of simulated pre-fire airflow conditions within the MD-11 cockpit and above ceiling region presented in an earlier publication (Part 1) which was published in The Aeronautical Journal in January 2006(4).

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Purpose – This study aims to investigate the pattern among 17 heterodox economic journals over a prolonged period to provide evidence about the social dynamics among the group of researchers who publish in them and the extent to which they hold or develop a collective identity as heterodox economists. Design/methodology/approach – Traditional approaches to citation analysis are extended by the use of techniques from social network analysis. In addition to citation counts, measures of network position and clique membership are used to identify key journals and turning points in a longitudinal analysis. Findings – Important shifts in the nature of citation within the network of journals are identified in the 1998-2001 period and evidence is found of the emergence of a collective identity. Research limitations/implications – The methods prove a valuable extension of citation analysis and also focus greater consideration on the social relationships that citations represent. They are well suited to addressing the principal limitation of the study, its restriction to journals within the defined community rather than journals in general. Originality/value – This extends traditional approaches to citation analysis, provides an important new technique in identifying emergent collective identities and provides insight into the history and nature of the heterodox economic community.