Model of Arrival Time for Gas Clouds in Urban Canopy

0535220 - ÚT 2021 RIV CH eng C - Conference Paper (international conference)
Chaloupecká, Hana - Jaňour, Zbyněk - Jurčáková, Klára - Kellnerová, Radka
Model of Arrival Time for Gas Clouds in Urban Canopy.
Air Pollution Modeling and its Application XXVI. Vol. 58. Cham: Springer, 2020 - (Mensink, C.; Gong, W.; Hakami, A.), s. 363-368. ISBN 978-3-030-22054-9.
[International Technical Meeting on Air Pollution Modeling and its Application /18./. Ottawa (CA), 14.05.2018-18.05.2018]
R&D Projects: GA TA ČR(CZ) TJ01000383
Institutional support: RVO:61388998
Keywords : wind tunnel * gas cloud * arrival time * probability density function * model
OECD category: Meteorology and atmospheric sciences
https://link.springer.com/chapter/10.1007%2F978-3-030-22055-6_58

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.
Permanent Link: http://hdl.handle.net/11104/0315818