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Study of historical evacuation drill data combining regression analysis and dimensionless numbers

The time needed to evacuate a building depends on many factors. Some are related to people’s behavior, while others are related to the physical characteristics of the building. This paper analyzes the historical data of 47 evacuation drills in 15 different university buildings, both academic and res...

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Detalles Bibliográficos
Autores principales: Miñambres, Maria D., Llanos, Diego R., Gento, Angel M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7194357/
https://www.ncbi.nlm.nih.gov/pubmed/32357168
http://dx.doi.org/10.1371/journal.pone.0232203
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author Miñambres, Maria D.
Llanos, Diego R.
Gento, Angel M.
author_facet Miñambres, Maria D.
Llanos, Diego R.
Gento, Angel M.
author_sort Miñambres, Maria D.
collection PubMed
description The time needed to evacuate a building depends on many factors. Some are related to people’s behavior, while others are related to the physical characteristics of the building. This paper analyzes the historical data of 47 evacuation drills in 15 different university buildings, both academic and residential, involving more than 19 000 persons. We propose the study of the data presented using a dimensionless analysis and statistical regression in order to give a prediction of the ratio between exit time and the number of people evacuated. The results obtained show that this approach could be a useful tool for comparing buildings of this type, and that it represents a promising research topic which can also be extended to other types of buildings.
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spelling pubmed-71943572020-05-11 Study of historical evacuation drill data combining regression analysis and dimensionless numbers Miñambres, Maria D. Llanos, Diego R. Gento, Angel M. PLoS One Research Article The time needed to evacuate a building depends on many factors. Some are related to people’s behavior, while others are related to the physical characteristics of the building. This paper analyzes the historical data of 47 evacuation drills in 15 different university buildings, both academic and residential, involving more than 19 000 persons. We propose the study of the data presented using a dimensionless analysis and statistical regression in order to give a prediction of the ratio between exit time and the number of people evacuated. The results obtained show that this approach could be a useful tool for comparing buildings of this type, and that it represents a promising research topic which can also be extended to other types of buildings. Public Library of Science 2020-05-01 /pmc/articles/PMC7194357/ /pubmed/32357168 http://dx.doi.org/10.1371/journal.pone.0232203 Text en © 2020 Miñambres et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Miñambres, Maria D.
Llanos, Diego R.
Gento, Angel M.
Study of historical evacuation drill data combining regression analysis and dimensionless numbers
title Study of historical evacuation drill data combining regression analysis and dimensionless numbers
title_full Study of historical evacuation drill data combining regression analysis and dimensionless numbers
title_fullStr Study of historical evacuation drill data combining regression analysis and dimensionless numbers
title_full_unstemmed Study of historical evacuation drill data combining regression analysis and dimensionless numbers
title_short Study of historical evacuation drill data combining regression analysis and dimensionless numbers
title_sort study of historical evacuation drill data combining regression analysis and dimensionless numbers
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7194357/
https://www.ncbi.nlm.nih.gov/pubmed/32357168
http://dx.doi.org/10.1371/journal.pone.0232203
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