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Model of Arrival Time for Gas Clouds in Urban Canopy
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SYSNO ASEP 0535220 Document Type C - Proceedings Paper (int. conf.) R&D Document Type Conference Paper Title Model of Arrival Time for Gas Clouds in Urban Canopy Author(s) Chaloupecká, Hana (UT-L) RID, ORCID, SAI
Jaňour, Zbyněk (UT-L) RID, ORCID
Jurčáková, Klára (UT-L) RID, ORCID
Kellnerová, Radka (UT-L) RID, ORCIDSource Title Air Pollution Modeling and its Application XXVI, Model of Arrival Time for Gas Clouds in Urban Canopy, 58. - Cham : Springer, 2020 / Mensink C. ; Gong W. ; Hakami A. - ISBN 978-3-030-22054-9 Pages s. 363-368 Number of pages 6 s. Number of pages 490 Publication form Print - P Action International Technical Meeting on Air Pollution Modeling and its Application /18./ Event date 14.05.2018 - 18.05.2018 VEvent location Ottawa Country CA - Canada Event type WRD Language eng - English Country CH - Switzerland Keywords wind tunnel ; gas cloud ; arrival time ; probability density function ; model Subject RIV DG - Athmosphere Sciences, Meteorology OECD category Meteorology and atmospheric sciences R&D Projects TJ01000383 GA TA ČR - Technology Agency of the Czech Republic (TA ČR) Institutional support UT-L - RVO:61388998 EID SCOPUS 85076779823 DOI 10.1007/978-3-030-22055-6_58 Annotation The aim of this paper is to present a new model of arrival time for gas clouds. To create such a model, simulations of short-term gas leakages were conducted in a wind tunnel with a neutrally stratified boundary layer. Into the tunnel, a model of an idealized urban canopy in scale 1:400 was placed. For simulations of the short-term gas discharges, ethane was utilized. Concentration time series were measured by a fast flame ionisation detector. The experiments were repeated about 400 times to get statistically representative datasets. The ensembles of concentration time series were measured at about 50 individual positions. From these data, puff arrival times were computed. The results showed that a suitable probability distribution to describe the variability in values at individual positions for arrival time is lognormal. Moreover, the parameters of this distribution do not change randomly with the change in the measurement position but their change can be described by functions. Utilizing them, probability density functions of arrival time can be constructed and whatever quantile of arrival time at a chosen position can be computed. Such a model could help emergency services to estimate how the situation could look like during the accident not only in the most frequently occurred but also in the extreme cases. Workplace Institute of Thermomechanics Contact Marie Kajprová, kajprova@it.cas.cz, Tel.: 266 053 154 ; Jana Lahovská, jaja@it.cas.cz, Tel.: 266 053 823 Year of Publishing 2021 Electronic address https://link.springer.com/chapter/10.1007%2F978-3-030-22055-6_58
Number of the records: 1