Algorithm for automated generating pitting surfaces on steel structures in offshore and atmosphere environments

Abstract

The occurrence of pitting damage in steel structures has been identified as a significant threat to their mechanical properties and overall safety in atmosphere and offshore environments. The utilization of generative algorithms to generate pitting surfaces on steel structures in large quantities has the potential to facilitate further research on pitting in finite element analysis and deep learning. This study employed the fractal interpolation algorithm and the W-M surface, a fractal characteristic surface, to simulate the initial roughness of the steel structure. The ideal pitting surface, generated based on a statistical distribution model, was then subjected to geometric complexity, resulting in the fractal pitting surface for steel structures with pronounced fractal characteristics. A real pitted component was scanned using a 3D laser scanner to obtain the real pitting surface. By comparing the statistical and geometric characteristics of the real pitting surface with the generated pitting surface, it was proved that the pitting surface generated by the algorithm proposed in this study could well match the real pitting surface in terms of statistical and geometric characteristics, and it was confirmed that the algorithm could be used to automatically generate pitting surfaces with highly complex geometry and obvious pitting characteristics. The findings of this study can provide a basis for further applications of Synthetic data in the study of corrosion in steel structures in different environments.