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Bounding Defaults in Egress Models

Published

Author(s)

Steve M. Gwynne, Erica D. Kuligowski, Michael Spearpoint, Enrico Ronchi

Abstract

The developers of egress models are in a difficult position. It is in their interest to develop models that are quick and easy to employ and at the same time to reduce accidental model misuse. While default values enables out-of-the-box use of models without in-depth familiarization with input formats and data structures, defaults often represent optimistic and/or even unrealistic evacuation conditions or occupant behaviour. In this paper, the term ‘default' relates to a pre-set, fixed value (or distribution) for a parameter or the application of a specific behavioural algorithm. Most egress models provide default values for five core behavioural elements: pre-evacuation time, travel speeds, route usage and availability, and flow conditions. These five core behavioural elements typically need to be represented in order for the model to function at all. The authors suggest that bounding default settings, rather than optimistic values, should be provided for each of the five core behavioural elements. In the context of this article, a bounding default setting is a value derived from relevant empirical data that prolongs the overall evacuation time produced for a particular design. If the model user wishes to decrease the conservative nature of a particular estimate or set of estimates, he/she would then be required to explicitly justify the modification of the bounding default value. This approach then allows the immediate use of the model, but in effect forces the user to modify the settings in order to obtain a credible scenario for the purposes of design.
Citation
Fire and Materials

Keywords

evacuation modelling, emergency evacuation, model defaults, human behaviour in fire

Citation

Gwynne, S. , Kuligowski, E. , Spearpoint, M. and Ronchi, E. (2013), Bounding Defaults in Egress Models, Fire and Materials, [online], https://doi.org/10.1002/fam.2212, https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=913547 (Accessed April 25, 2024)
Created November 27, 2013, Updated October 12, 2021