Transactions of Nanjing University of Aeronautics & Astronautics
Analysis of Ice-Shaped Surface Roughness Based on Fractal Theory
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Abstract:
The shape of ice accretion on aircraft surfaces is crucial to icing wind tunnel tests. Currently， geometrical parameters of ice， such as height， angle， and location， are used to characterise the ice shape from a 2-D perspective. However， the surface roughness of ice-shape， which is crucial to aerodynamic analysis， is always ignored. In this paper， the fractal theory is used to characterise the ice roughness， and the corresponding characterisation method is explained. An aerofoil-icing test is conducted in a large icing wind tunnel to verify the feasibility and validity of the proposed method. In the test， the icing growth information of the aerofoil surface is collected using laser line scan technology. Then， the 3-D ice shape is reconstructed using the collected data. Subsequently， the 3-D ice shape is analyzed using fractal theory， where the profile curves at different positions of the ice shape are extracted. Additionally， the corresponding fractal dimension and joint roughness characterisation are calculated to summarise the linear regression equations of the fractal dimension. Then， the data points from profile curves are extracted to simulate the fractal interpolation functions of the ice. Correlation analyses show that ice accretion on the aircraft surface exhibits fractal features， and the fractal dimension is proportional to the joint roughness characterisation， which can be used as the assessment parameter of surface roughness of ice. Consequently， the fractal interpolation simulation of the ice-shape curves represent an excellent approximation of the ice accretion on aircraft surfaces. The fractal characterisation of rough surfaces provides a new approach for scientifically quantifying 3-D ice features.
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Project Supported:
This work was supported by the National Natural Science Foundation of China （No.12132019）， and the National Science and Technology Major Project （No.J2019-III-0010-0054）.
Clc Number:
V321.2
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