Numerical Simulation and Accuracy Verification of Surface Morphology of Metal Materials Based on Fractal Theory

Abstract

This paper presents a numerical simulation method to determine the surface morphology characteristics of metallic materials. First, a surface profiler (NV5000 5022s) was used to measure the surface, and the morphology data thereof were characterized. Second, fractal theory was used to simulate the surface profile for different fractal dimensions D and scale coefficients G, and statistical analyses of different surface morphologies were carried out. Finally, the fractal dimension D of the simulated morphology and the actual morphology were compared. The analysis showed that the error of fractal dimension D between the two morphologies was less than 10%; meanwhile, the comparison values of the characterization parameters of the simulated morphology and the actual morphology were approximately equal, and the errors were below 6%. Therefore, the current method used to evaluate the surface morphologies of parts processed by the grinding/milling method can be replaced by the simulated method using the corresponding parameters. This method makes it possible to theorize about the surface morphologies of machined parts, and provides a theoretical basis and reference value for the surface morphology design of materials, with the potential to improve the assembly quality of products.

A High Precision Modeling Technology of Material Surface Microtopography and Its Influence on Interface Mechanical Properties

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Simulation and analysis of micro-textured rough curved surface based on fractal characterization method

“…Zhang Xinbao (Shen et al , 2023) used the fractal function to reconstruct the lubrication surface profile of the bearing and integrated the surface profile parameters into the numerical calculation of the lubricating oil film of the tilting pad thrust bearing to explore the influence of surface morphology changes on the lubrication characteristics. Mu et al (2020) proposed a surface classification characterization method based on real process parameters. The measured fractal dimension was consistent with the simulated fractal dimension, and the error was within 6%.…”