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Publication list

uDALES was used in the following publications :

2024

  • The drag length is key to quantifying tree canopy drag1.
  • A conservative immersed boundary method for the multi-physics urban large-eddy simulation model uDALES v2.02.

2022

  • How trees affect urban air quality: It depends on the source3.
  • uDALES 1.0: a large-eddy-simulation model for urban environments4.
  • Pollutant dispersion by tall buildings in rural-to-urban landscapes: Laboratory experiments and Large-Eddy Simulation5.

2021

  • Distributed urban drag parameterization for sub-kilometre scale numerical weather prediction6.
  • uDALES: large-eddy-simulation software for urban flow, dispersion and micro-climate7.
  • Tree model with drag, transpiration, shading and deposition: identification of cooling regimes and large-eddy simulation8.

2020

  • Drag distribution in idealized heterogeneous urban environments9.
  • Steady-state large-eddy simulations of convective and stable urban boundary layers10.

2019

  • Evaluation of an operational air quality model using large-eddy simulation11.

References

  1. D. Majumdar, G. Vita, R. Ramponi, N. Glover, and M. Van Reeuwijk. The drag length is key to quantifying tree canopy drag. J. Ind. Wind Eng. Ind. Aero., (under review). URL: https://arxiv.org/abs/2411.01570. ↩

  2. S. O. Owens, D. Majumdar, C. E. Wilson, P. Bartholomew, and M. van Reeuwijk. A conservative immersed boundary method for the multi-physics urban large-eddy simulation model uDALES v2.0. Geosc. Mod. Dev., 17(16):6277–6300, 2024. doi:10.5194/gmd-17-6277-2024. ↩

  3. Tom Grylls and Maarten van Reeuwijk. How trees affect urban air quality: it depends on the source. Atmos. Env., 290:119275, 2022. doi:https://doi.org/10.1016/j.atmosenv.2022.119275. ↩

  4. I. Suter, T. Grylls, B. S. Sützl, S. O. Owens, C. E. Wilson, and M. van Reeuwijk. uDALES 1.0: a large-eddy simulation model for urban environments. Geosc. Mod. Dev., 15(13):5309–5335, 2022. doi:10.5194/gmd-15-5309-2022. ↩

  5. H.D. Lim, D. Hertwig, T. Grylls, H. Gough, M. van Reeuwijk, C.S.E. Grimmond, and C. Vanderwel. Drag distribution in idealized heterogeneous urban environments. Exp. Fluids, 63:92, 2022. doi:10.1007/s00348-022-03439-0. ↩

  6. B.S. Suetzl, G.G. Rooney, A. Finnenkoeter, S. Bohnenstengel, C.S. Grimmond, and M. Van Reeuwijk. Distributed urban drag parameterization for sub-kilometre scale numerical weather prediction. Q. J. Roy. Met. Soc., 147:3940–3956, 2021. doi:10.1002/qj.4162. ↩

  7. T. Grylls, I. Suter, B.S. Suetzl, S. Owens, D. Meyer, and M. van Reeuwijk. Udales: large-eddy-simulation software for urban flow, dispersion, and microclimate modelling. J. Open Source Softw., 6(63):3055, 2021. doi:10.21105/joss.03055. ↩

  8. T. Grylls and M. Van Reeuwijk. Tree model with drag, transpiration, shading and deposition: identification of cooling regimes and large-eddy simulation. J. Agricul. Forestry Meteo., 298–299:108288, 2021. doi:10.1016/j.agrformet.2020.108288. ↩

  9. B.S. Suetzl, G.G. Rooney, and M. van Reeuwijk. Drag distribution in idealized heterogeneous urban environments. Bound.-Lay. Met., 178:225–248, 2020. doi:10.1007/s10546-020-00567-0. ↩

  10. T. Grylls, I. Suter, and M. van Reeuwijk. Steady-state large-eddy simulations of convective and stable urban boundary layers. Bound.-Lay. Met., 175(3):309–341, 2020. doi:10.1007/s10546-020-00508-x. ↩

  11. T. Grylls, C.M.A. Le Cornec, P. Salizzoni, L. Soulhac, M.E.J. Stettler, and M. van Reeuwijk. Evaluation of an operational air quality model using large-eddy simulation. Atmos. Env. X, 3:100041, 2019. doi:10.1016/j.aeaoa.2019.100041. ↩