Internal defect database of mechanically deformed ferritic steel via X-ray computed tomography

Abstract

Steel is widely utilized as a structural material due to its favorable mechanical properties, cost-effectiveness, and reliability, and it is expected to remain critical in engineering applications. The properties and durability of steel are significantly influenced by internal defects formed during mechanical deformation. Quantitative analysis of the formation and evolution of these defects is essential for developing materials that are both sustainable and tailored to specific applications. However, acquiring statistically meaningful datasets of internal defects is complex, time-consuming, and costly, resulting in a scarcity of comprehensive studies. In this study, we present two comprehensive datasets obtained from mechanically deformed ferritic steel samples using X-ray computed tomography (X-CT): (1) tensile deformation and (2) fatigue deformation. The database includes detailed quantitative descriptions of 938 defect features from 134 tensile-tested samples and 2,305 defect features from 142 fatigue-tested samples. Each dataset comprises high-resolution X-CT images and quantified internal defect metrics, facilitating detailed statistical analysis.