Artificial Intelligence in Slurry Erosion and Protection Techniques

Slurry erosion is a major problem for industrial components such as pipelines and turbines, where particle-laden fluid can wear away the material once it impacts the surface area. With the introduction of artificial intelligence (AI), predictive, analytical, and preventative slurry erosion abilities, have slowly begun to be made possible through data-driven insights and optimization techniques. The chapter discusses machine learning (ML) and deep learning (DL) techniques to model erosion rates, optimize protective coatings, as well as, predict material coatings in a compound operating system. The chapter will focus on AI-based genetic algorithms developed and used to design novel composite coatings, which feature layers of titanium matrix composite (TiNTiC) that are more erosion-resistant depending on a prediction of microstructure evolution under impact. AI can be applied or surfaced quickly into experimental and computational methods, and in combination we may be able to speed the high-performance protective material development. The chapter describes the use of “AI” and filler erosion, which provides experience to both predictive maintenance for the systems mentioned but also solves the current material design problem.