A curated list of open technology projects to sustain a stable climate, energy supply, biodiversity and natural resources.

uDALES

Large-eddy-simulation software for urban flow, dispersion and microclimate modelling.
https://github.com/uDALES/u-dales

Category: Climate Change
Sub Category: Earth and Climate Modeling

Keywords

cfd computational-fluid-dynamics large-eddy-simulation urban-climate

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uDALES: large-eddy-simulation software for urban flow, dispersion and microclimate modelling

README.md

uDALES CI

This is the development repository for the uDALES (urban Dutch Atmospheric Large Eddy Simulation) model. It contains the uDALES software source-code, tests, documentation, and examples with tools to pre- and post-process inputs and outputs.


Overview

With continuing urbanization, challenges associated with the urban environment such as air quality, heat islands, pedestrian thermal comfort, and wind loads on tall buildings, are increasingly relevant. Our ability to realistically capture processes such as the transport of heat, moisture, momentum and pollutants, and those of radiative transfer in urban environments is key to understanding and facing these challenges (Oke et al., 2017).

The turbulent nature of the urban flow field and the inherent heterogeneity and wide range of scales associated with the urban environment result in a complex modelling problem. uDALES is a large-eddy simulation (LES) model for urban environments. LES is an approach to turbulence modelling used in computational fluid dynamics to simulate turbulent flows over a wide range of spatial and temporal scales. LES is one of the most promising tools to model the interactions typical of urban areas due to its ability to resolve the urban flow field at resolutions of O(1 m, 0.1 s), over spatial domains of O(100 m), and time periods of O(10 h). Although there are many scalable LES models for atmospheric flows, to our knowledge, only few are capable of explicitly representing buildings and of modelling the full range of urban processes (e.g. PALM-4U; Resler et al. 2017; Maronga et al. 2020; or OpenFoam; Weller et al. 1998).

uDALES is capable of modelling urban environments at the microclimate scale including wet thermodynamics, idealized and complex morphologies, three-dimensional urban surface energy balance and urban air quality (emission, dispersion and reaction).

Publications and validation

To-date, uDALES has been used to study a number of research questions:

Research application Reference
Urban boundary layers/ boundary-layer meteorology Grylls et al. (2019); Sützl et al. (2021); Sützl (2021)
Urban climate (radiation, green roofs and walls, trees etc.) Suter (2018); Suter et al. (2021); Grylls & van Reeuwijk (2021)
Pollution dispersion/ urban air quality Grylls et al. (2019); Grylls (2020)
Buoyancy/ convective and stable conditions Suter (2018); Grylls et al. (2020); Grylls (2020); Grylls & van Reeuwijk (2021)

uDALES has been validated against both field and experimental studies and evaluated against other numerical models. The dynamic core, DALES, has been used to study atmospheric processes for over 30 years, being validated extensively in the process and used in several atmospheric intercomparison studies (Heus et al. 2010). The immersed boundary method, which is used to model obstacles in the fluid domain, was implemented into DALES and validated by Pourquie et al. (2009) and Tomas et al. (2015). The wall functions and three-dimensional surface energy balance model was validated by Suter (2018). The ability to model pollutuon dispersion in both idealised and realistic morphologies was been validated by Grylls et al. (2019) and Grylls (2020).

See the corresponding Journal of Open Source Software paper here:

DOI

Documentation

If you are new to uDALES, please follow our getting started guide. For User's guides and general reference documentation, please see the uDALES website.

If you are a developer, please also refer to the development notes.

How to cite

When using the uDALES please cite as:

Grylls, T., Suter, I., Sützl, B., Owens, S., Meyer, D., & van Reeuwijk, M. (2021). uDALES: large-eddy-simulation software for urban flow, dispersion, and microclimate modelling. Journal of Open Source Software, 6(63), 3055, https://doi.org/10.21105/joss.03055

@article{Grylls2021,
  doi = {10.21105/joss.03055},
  url = {https://doi.org/10.21105/joss.03055},
  year = {2021},
  publisher = {The Open Journal},
  volume = {6},
  number = {63},
  pages = {3055},
  author = {Tom Grylls and Ivo Suter and Birgit S. Sützl and Sam Owens and David Meyer and Maarten van Reeuwijk},
  title = {uDALES: large-eddy-simulation software for urban flow, dispersion, and microclimate modelling},
  journal = {Journal of Open Source Software}
}

If you are looking to also cite a specific version of the software, you can find correposding version-specific DOIs on Zenodo.

Contributing

If you are looking to contribute, please read our Contributors' guide for details.

Copyright and license

General DALES copyright applies for any files part of the original DALES distribution and are marked as such at the beginning of each file.

Additional files provided in uDALES are copyrighted "the uDALES Team" and are marked as such at the beginning of each file.

All files are licensed under the GNU General Public License. See LICENSE.txt.

Acknowledgements

The dynamic core of uDALES derives from the Dutch Atmospheric Large-Eddy Simulation (DALES) model. We would like to acknowledge the work of the contributors to DALES over the years (Heus et al. 2010) and specifically the work of J. Tomas, M. Pourquie and H. Jonker in implementing the immersed boundary method into DALES.

References

Heus, T., van Heerwaarden, C. C., Jonker, H. J. J., Siebesma, A. P., Axelsen, S., van den Dries, K., Geoffroy, O., Moene, A. F., Pino, D., Roode, S. R. de, & de Arellano, J. V.-G. (2010). Formulation of the dutch atmospheric large-eddy simulation (DALES) and overview of its applications. Geoscientific Model Development, 3(2), 415–444. https://doi.org/10.5194/gmd-3-415-2010

Grylls, T., Cornec, C. M. A. L., Salizzoni, P., Soulhac, L., Stettler, M. E. J., & van Reeuwijk, M. (2019). Evaluation of an operational air quality model using large-eddy simulation. Atmospheric Environment: X, 3, 100041. https://doi.org/10.1016/j.aeaoa.2019.100041

Grylls, T. (2020). Simulating air pollution in the urban microclimate, Imperial College London, PhD thesis.

Grylls, T., Suter, I., & van Reeuwijk, M. (2020). Steady-state large-eddy simulations of convective and stable urban boundary layers. Boundary-Layer Meteorology, 175(3), 309-341. https://doi.org/10.1007/s10546-020-00508-x

Grylls, T., & van Reeuwijk, M. (2021). Tree model with drag, transpiration, shading and deposition: Identification of cooling regimes and large-eddy simulation. Agricultural and Forest Meteorology, 298-299, 108288. https://doi.org/https://doi.org/10.1016/j.agrformet.2020.108288

Maronga, B., Banzhaf, S., Burmeister, C., Esch, T., Forkel, R., Fröhlich, D., Fuka, V., Gehrke, K. F., Geletič, J., Giersch, S., Gronemeier, T., Groß, G., Heldens, W., Hellsten, A., Hoffmann, F., Inagaki, A., Kadasch, E., Kanani-Sühring, F., Ketelsen, K., Raasch, S. (2020). Overview of the PALM model system 6.0. Geoscientific Model Development, 13(3), 1335–1372. https://doi.org/10.5194/gmd-13-1335-2020

Oke, T. R., Mills, G., Christen, A., & Voogt, J. A. (2017). Urban climates. Cambridge University Press. https://doi.org/10.1017/9781139016476

Pourquie, M. B. J. M., Breugem, W. P., & Boersma, B. J. (2009). Some issues related to the use of immersed boundary methods to represent square obstacles. International Journal for Multiscale Computational Engineering, 7(6). https://doi.org/10.1615/IntJMultCompEng.v7.i6.30

Resler, J., Krč, P., Belda, M., Juruš, P., Benešová, N., Lopata, J., Vlček, O., Damašková, D., Eben, K., Derbek, P., Maronga, B., & Kanani-Sühring, F. (2017). PALM-USM v1.0: A new urban surface model integrated into the PALM large120 eddy simulation model. Geoscientific Model Development, 10(10), 3635–3659. https://doi.org/10.5194/gmd-10-3635-2017

Suter, I. (2018). Simulating the impact of blue-green infrastructure on the microclimate of urban areas. Imperial College London, PhD thesis. https://doi.org/10.25560/78715

Suter, I., Grylls, T., Sützl, B. S., & van Reeuwijk, M. (2021). uDALES 1.0.0: A large-eddy simulation model for urban environments. In Geoscientific Model Development. Copernicus GmbH.

Sützl, B. S. (2021). Rising from the ground: Distributed drag parameterization of urban environments for numerical weather prediction. Imperial College London, PhD thesis.

Sützl, B. S., Rooney, G. G., & van Reeuwijk, M. (2021). Drag distribution in idealized heterogeneous urban environments. Boundary-Layer Meteorology, 178, 225-248. https://doi.org/10.1007/s10546-020-00567-0

Tomas, J. M., Pourquie, M. J. B. M., & Jonker, H. J. J. (2015). The influence of an obstacle on flow and pollutant dispersion in neutral and stable boundary layers. Atmospheric Environment, 113, 236–246. https://doi.org/10.1016/j.atmosenv.2015.05.016

Weller, H. G., Tabor, G., Jasak, H., & Fureby, C. (1998). A tensorial approach to computational continuum mechanics using object-oriented techniques. Computers in Physics, 12(6), 620. https://doi.org/10.1063/1.168744


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Last synced: 8 days ago

Total Commits: 992
Total Committers: 22
Avg Commits per committer: 45.091
Development Distribution Score (DDS): 0.617

Commits in past year: 67
Committers in past year: 6
Avg Commits per committer in past year: 11.167
Development Distribution Score (DDS) in past year: 0.567

Name Email Commits
Chiel c****n@g****m 380
Birgit Sutzl b****6@i****k 83
Thijs Heus t****s@k****e 68
Steef s****g@g****m 66
Huug Ouwersloot h****o@p****l 56
thijs t****s@z****e 54
dmey d****y 52
Tom Grylls t****5@c****k 46
Tom Grylls t****5@i****k 38
Maarten van Reeuwijk 5****k 29
Dipanjan Majumdar d****0@g****m 29
Thijs Heus t****s@g****m 29
ils13 i****3@i****k 16
samoliverowens 5****s 11
Thijs Heus h****t@p****l 8
Thijs Heus m****3@b****) 7
Thijs Heus m****3@t****e 6
Thijs Heus m****3@t****e 4
Dan Cummins 4****7 4
Christopher Cave-Ayland c****d@i****k 3
Eduardo Wilde Barbaro e****o@p****l 2
cedwardwilson 4****n 1

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Total issues: 115
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Average comments per issue: 3.03
Average comments per pull request: 2.45
Merged pull request: 94
Bot issues: 0
Bot pull requests: 0

Past year issues: 64
Past year pull requests: 32
Past year average time to close issues: about 1 month
Past year average time to close pull requests: 10 days
Past year issue authors: 7
Past year pull request authors: 5
Past year average comments per issue: 0.25
Past year average comments per pull request: 0.25
Past year merged pull request: 20
Past year bot issues: 0
Past year bot pull requests: 0

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Dependencies

.github/workflows/ci.yml actions
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environment.yml pypi
  • ford *
  • mkdocs-bibtex *

Score: 7.601901959875166