Modelling occupant interaction with fire conditions using the buildingEXODUS evacuation model

When evacuating through fire environments, the presence of smoke may not only have a physiological impact on the evacuees but may also lead occupants to adapt their evacuation strategy through the adoption of another exit. This paper attempts to introduce this type of adaptive behaviour within the buildingEXODUS evacuation model through enabling occupants to make decisions concerning the selection of the most viable available exit during an evacuation involving fire. The development of this adaptive behaviour requires the introduction of several new capabilities namely, the representation of the occupants’ familiarity with the structure, the behaviour of an occupant that is engulfed in smoke and the behaviour of an occupant that is faced with a smoke barrier. The appropriateness of the redirection decision is dependent upon behavioural data gathered from real fire incidents (in the UK and USA) that is used to construct the redirection probabilities. The implementation is shown to provide a more complex and arguably more realistic representation of this behaviour than that provided previously.

Numerical experiments of some Krylov subspace methods for black oil model

This paper discusses preconditioned Krylov subspace methods for solving large scale linear systems that originate from oil reservoir numerical simulations. Two types of preconditioners, one being based on an incomplete LU decomposition and the other being based on iterative algorithms, are used together in a combination strategy in order to achieve an adaptive and efficient preconditioner. Numerical tests show that different Krylov subspace methods combining with appropriate preconditioners are able to achieve optimal performance.