View source for Modelling of icing

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.


'''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.


<ref>Farzaneh, M. (2008) Atmospheric Icing of Power Networks. 1st ed. 2008. [Online]. Dordrecht: Springer Netherlands.</ref> <ref>Stenroos, C. (2015) Properties of icephobic surfaces in different icing conditions</ref> <ref>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.</ref> <ref>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.</ref> <ref>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.</ref> <ref>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).</ref> <ref>Makkonen, L. (2001). Modelling and prevention of ice accretion on wind turbines. Wind Engineering, 25(1), 3–21.</ref> <ref>Ansys FENSAP-ICE: Ice Accretion Simulation Software, Ansys, webpage, available (accessed 4.3.2021): <nowiki>https://www.ansys.com/products/fluids/ansysfensap-ice/fensap-ice-capabilities</nowiki></ref>