Advances in CFD Modeling of Urban Wind Applied to Aerial Mobility

[EN] The feasibility, safety, and efficiency of a drone mission in an urban environment are heavily influenced by atmospheric conditions. However, numerical meteorological models cannot cope with fine-grained grids capturing urban geometries; they are typically tuned for best resolutions ranging fro...

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Detalhes bibliográficos
Autores: García Gutiérrez, Adrián, Gonzalo de Grado, Jesús, López Rodríguez, Deibi, Delgado Marcos, Adrián
Formato: artículo
Estado:Versión publicada
Fecha de publicación:2022
País:España
Recursos:Universidad Rey Juan Carlos
Repositorio:BULERIA. Repositorio Institucional de la Universidad de León
OAI Identifier:oai:buleria.unileon.es:10612/17698
Acesso em linha:https://www.mdpi.com/2311-5521/7/7/246
https://hdl.handle.net/10612/17698
Access Level:acceso abierto
Palavra-chave:Aeronáutica
Urban CFD
Urban wind database
Now-casting
3301 Ingeniería y Tecnología Aeronáuticas
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spelling Advances in CFD Modeling of Urban Wind Applied to Aerial MobilityGarcía Gutiérrez, AdriánGonzalo de Grado, JesúsLópez Rodríguez, DeibiDelgado Marcos, AdriánAeronáuticaUrban CFDUrban wind databaseNow-casting3301 Ingeniería y Tecnología Aeronáuticas[EN] The feasibility, safety, and efficiency of a drone mission in an urban environment are heavily influenced by atmospheric conditions. However, numerical meteorological models cannot cope with fine-grained grids capturing urban geometries; they are typically tuned for best resolutions ranging from 1 to 10 km. To enable urban air mobility, new now-casting techniques are being developed based on different techniques, such as data assimilation, variational analysis, machine-learning algorithms, and time series analysis. Most of these methods require generating an urban wind field database using CFD codes coupled with the mesoscale models. The quality and accuracy of that database determines the accuracy of the now-casting techniques. This review describes the latest advances in CFD simulations applied to urban wind and the alternatives that exist for the coupling with the mesoscale model. First, the distinct turbulence models are introduced, analyzing their advantages and limitations. Secondly, a study of the meshing is introduced, exploring how it has to be adapted to the characteristics of the urban environment. Then, the several alternatives for the definition of the boundary conditions and the interpolation methods for the initial conditions are described. As a key step, the available order reduction methods applicable to the models are presented, so the size and operability of the wind database can be reduced as much as possible. Finally, the data assimilation techniques and the model validation are presented.SIMDPIIngenieria AeroespacialEscuela de Ingenierias Industrial, Informática y Aeroespacial2022info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttps://www.mdpi.com/2311-5521/7/7/246https://hdl.handle.net/10612/17698reponame:BULERIA. Repositorio Institucional de la Universidad de Leóninstname:Universidad Rey Juan CarlosIngléshttps://www.mdpi.com/2311-5521/7/7/246http://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccessoai:buleria.unileon.es:10612/176982026-06-24T12:43:27Z
dc.title.none.fl_str_mv Advances in CFD Modeling of Urban Wind Applied to Aerial Mobility
title Advances in CFD Modeling of Urban Wind Applied to Aerial Mobility
spellingShingle Advances in CFD Modeling of Urban Wind Applied to Aerial Mobility
García Gutiérrez, Adrián
Aeronáutica
Urban CFD
Urban wind database
Now-casting
3301 Ingeniería y Tecnología Aeronáuticas
title_short Advances in CFD Modeling of Urban Wind Applied to Aerial Mobility
title_full Advances in CFD Modeling of Urban Wind Applied to Aerial Mobility
title_fullStr Advances in CFD Modeling of Urban Wind Applied to Aerial Mobility
title_full_unstemmed Advances in CFD Modeling of Urban Wind Applied to Aerial Mobility
title_sort Advances in CFD Modeling of Urban Wind Applied to Aerial Mobility
dc.creator.none.fl_str_mv García Gutiérrez, Adrián
Gonzalo de Grado, Jesús
López Rodríguez, Deibi
Delgado Marcos, Adrián
author García Gutiérrez, Adrián
author_facet García Gutiérrez, Adrián
Gonzalo de Grado, Jesús
López Rodríguez, Deibi
Delgado Marcos, Adrián
author_role author
author2 Gonzalo de Grado, Jesús
López Rodríguez, Deibi
Delgado Marcos, Adrián
author2_role author
author
author
dc.contributor.none.fl_str_mv Ingenieria Aeroespacial
Escuela de Ingenierias Industrial, Informática y Aeroespacial
dc.subject.none.fl_str_mv Aeronáutica
Urban CFD
Urban wind database
Now-casting
3301 Ingeniería y Tecnología Aeronáuticas
topic Aeronáutica
Urban CFD
Urban wind database
Now-casting
3301 Ingeniería y Tecnología Aeronáuticas
description [EN] The feasibility, safety, and efficiency of a drone mission in an urban environment are heavily influenced by atmospheric conditions. However, numerical meteorological models cannot cope with fine-grained grids capturing urban geometries; they are typically tuned for best resolutions ranging from 1 to 10 km. To enable urban air mobility, new now-casting techniques are being developed based on different techniques, such as data assimilation, variational analysis, machine-learning algorithms, and time series analysis. Most of these methods require generating an urban wind field database using CFD codes coupled with the mesoscale models. The quality and accuracy of that database determines the accuracy of the now-casting techniques. This review describes the latest advances in CFD simulations applied to urban wind and the alternatives that exist for the coupling with the mesoscale model. First, the distinct turbulence models are introduced, analyzing their advantages and limitations. Secondly, a study of the meshing is introduced, exploring how it has to be adapted to the characteristics of the urban environment. Then, the several alternatives for the definition of the boundary conditions and the interpolation methods for the initial conditions are described. As a key step, the available order reduction methods applicable to the models are presented, so the size and operability of the wind database can be reduced as much as possible. Finally, the data assimilation techniques and the model validation are presented.
publishDate 2022
dc.date.none.fl_str_mv 2022
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv https://www.mdpi.com/2311-5521/7/7/246
https://hdl.handle.net/10612/17698
url https://www.mdpi.com/2311-5521/7/7/246
https://hdl.handle.net/10612/17698
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv https://www.mdpi.com/2311-5521/7/7/246
dc.rights.none.fl_str_mv http://creativecommons.org/licenses/by/4.0/
info:eu-repo/semantics/openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by/4.0/
eu_rights_str_mv openAccess
dc.publisher.none.fl_str_mv MDPI
publisher.none.fl_str_mv MDPI
dc.source.none.fl_str_mv reponame:BULERIA. Repositorio Institucional de la Universidad de León
instname:Universidad Rey Juan Carlos
instname_str Universidad Rey Juan Carlos
reponame_str BULERIA. Repositorio Institucional de la Universidad de León
collection BULERIA. Repositorio Institucional de la Universidad de León
repository.name.fl_str_mv
repository.mail.fl_str_mv
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