Modelling of icing

From IcingWiki
Jump to navigation Jump to search
Image shows one possible type of ice accretion that can be produced in the NASA Icing Research Tunnel. [1]

Icing is hard to model, and many of the models are very situational.

Most important meteorological parameters for modelling atmospheric icing are air temperature, wind speed and direction, and relative humidity. For precipitation icing, also precipitation rate and air temperature at the surface level matter. In-cloud specific parameters are liquid water content of the cloud and droplet size distribution.


Ice accretion models

During the past decades there has been a great interest on modelling ice accretion on different manmade structures. These models have been used in the assessment of mechanical loads that accreted ice inflicts on the certain structure, which can be taken into account in the designing phase. Ice accretion models should describe how main parameters in the icing event have been taken into consideration. The main parameters in the icing event, that have influenced the accreted ice’s shape, density and rate of accretion, are LWC of rain, droplet size distribution, temperature, wind speed and direction and in addition relative humidity.


Lozowski & Makkonen (2005) state that proper ice accretion model should include the following six factors:

1. Consider how air flow goes around the icing obstacle.

2. Impingement of supercooled droplets.

3. Internal and external heat load which affect the sticking probability of the droplets.

4. Behavior of unfreezed liquid on the surface after an impact.

5. Ice properties; growth direction, shape, density, roughness and icicle formation.

6. Response of the iced structure i.e. growth, twisting.

Multiple ice accretion models have been presented in literature, which take a stand for accretion of different ice types rime, glaze, hoar frost, wet snow and sea spray icing or the impact on different engineered structures such as power network lines, wind turbines and tall structures etc.

Testing in an Icing Research Tunnel 1983. Cold water is sprayed into the tunnel and freezes on the test model. [2]


Prediction models

There have been models created to predict icing on different structures, and for different icing phenomena. For example, icing of power lines has been modelled by several studies, as they are vulnerable to ice, easily breaking under the added weight.

Another very common icing modelling field is wind turbines and especially their blades. Ice modelling for wind turbines has been focused on the shape of the accreted ice because the ice changes the aerodynamics of the blade.


Turbice model One commonly used model for wind turbine blades is the TURBICE model developed by Makkonen et al.

There is also a model for in-cloud icing by Makkonen, known simply as Makkonen’s model.

Another icing model is the axial-growth model for horizontal unheated cylinder, developed by Lozowski et al.

Another model for icing is Weather Research and Forecasting, often abbreviated as the WRF model. It is a Numerical Weather Prediction model (NWP).

Using an Icing Wind Tunnel (IWiT), is ice accreted in a wind tunnel in a cold room. This method can be used to copy natural icing.

Icing modelling programs can also be used for simulating icing.

Some empirical studies also use specific object to accrete ice on.


[3] [4] [5] [6] [7] [8] [9] [10] [11] [12] [13] [14] [15] [16]

References

  1. NASA. wikimedia commons. 2008. Public domain. Icing on a rotor.jpg.
  2. Nasa. Wikimedia commons. 1983. Public domain. Icing Research Tunnel - GPN-2000-001836.jpg
  3. Farzaneh, M. (2008) Atmospheric Icing of Power Networks. 1st ed. 2008. [Online]. Dordrecht: Springer Netherlands.
  4. Stenroos, C. (2015) Properties of icephobic surfaces in different icing conditions
  5. Thorsson, P. et al. (2015) Modelling atmospheric icing: A comparison between icing calculated with measured meteorological data and NWP data. Cold regions science and technology. [Online] 119124–131.
  6. Makkonen, L. (2000). Models for the growth of rime, glaze, icicles and wet snow on structures. Philosophical Transactions of the Royal Society of London. Series A: Mathematical, Physical, and Engineering Sciences, 358(1776), 2913–2939.
  7. Molinder, J. et al. (2018) Probabilistic forecasting of wind power production losses in cold climates: a case study. Wind energy science. [Online] 3 (2), 667– 680.
  8. Tabatabaei, G. (2019). Wind Turbine Aerodynamic Modeling in Icing Condition: Three-Dimensional RANS-CFD Versus Blade Element Momentum Method. Journal of Energy Resources Technology, 141(7).
  9. Makkonen, L. (2001). Modelling and prevention of ice accretion on wind turbines. Wind Engineering, 25(1), 3–21.
  10. Ansys FENSAP-ICE: Ice Accretion Simulation Software, Ansys, webpage, available (accessed 4.3.2021): https://www.ansys.com/products/fluids/ansysfensap-ice/fensap-ice-capabilities
  11. S. M. Fikke, J. E. Kristjánsson, B. E. Kringlebotn Nygaard, Modern meteorology and atmospheric icing, Atmospheric Icing of Power Networks, IWAIS XI, Montreal, Canada, 2005, pp. 1–29.
  12. E. P. Lozowski & L. Makkonen, Fifty Years of Progress in Modelling the Accumulation of Atmospheric Ice on Power Network Equipment, IWAIS XI, Montréal, Canda, 2005.
  13. ISO-12494, Atmospheric icing of structures, 2001, 56 p.
  14. R. Blackmore & E. Lozowski, A theoretical spongy spray icing model with surficial structure, Atmospheric Research, vol. 49, no. 4, 1998, pp. 267–288.
  15. L. Makkonen, P. Lehtonen, M. Hirviniemi, Determining ice loads for tower structure design, Engineering Structures, vol. 74, 2014 pp. 229–232,.
  16. L. Makkonen & M. M. Oleskiw, Small-scale experiments on rime icing, Cold Regions Science and Technology, vol. 25, no. 3, 1997, pp. 173–182.