Abstract
Icing is a common natural phenomenon that occurs widely in daily life and production, often resulting in adverse effects. For a long time, reducing the harm caused by icing has been a concern in many fields of research. Effective application of ice prediction technology can significantly reduce or even eliminate the potential hazards of icing across various industries. Ice prediction technology is a method that predicts future icing conditions based on existing data. It utilizes both hardware and software to acquire input parameters such as current meteorological data and uses these pieces of information to predict future parameters like ice thickness. By using ice prediction technology, management departments can make arrangements and plans in advance to mitigate ice disaster problems. The application scenarios of ice prediction technology can be divided into stationary surfaces and moving surfaces and can be classified into model-driven methods and data-driven methods based on principle differences. This chapter chooses the analysis of ice prediction technology for two types of stationary surfaces: roads and power transmission lines, and two types of moving surfaces: wind turbine blades and aircraft. The results indicate that for the aforementioned four typical cold surfaces, the average prediction accuracy of relevant parameters, such as ice thickness, using existing technology exceeds 80%. This chapter summarizes ice prediction technologies for simple cold surfaces in both stationary and moving states and further outlines the main research directions in this field. The aim is to provide guidance for the advancement and enhancement of antiicing technologies for low-temperature surfaces in various engineering scenarios.
Original language | English |
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Title of host publication | Frosting and Icing for Efficient Energy Use in Engineering Applications |
Publisher | Elsevier |
Pages | 327-350 |
Number of pages | 24 |
ISBN (Electronic) | 9780443154959 |
ISBN (Print) | 9780443154966 |
DOIs | |
Publication status | Published - 1 Jan 2025 |
Externally published | Yes |
Keywords
- data-driven method
- Ice prediction
- model-driven method
- moving surface
- stationary surface