Nodular cast iron has been commonly applied in industry and many engineering applications due to its low production cost and the similarity of its mechanical properties to carbon steel. The mechanical properties of nodular cast iron are very dependent on its microstructure and also on the characteristics of the graphite nodules. In this sense, the main objective of this paper was to evaluate and characterize the nodular cast iron grades GGG40, GGG60 and GGG70 in the absence of heat treatment. In addition, specimens were obtained from casted bars and blocks without the Y-block casting process. The microstructure was analyzed by optical microscopy with the support of computational image analysis for determination of the attributes of the graphite nodules and the quantification of each phase present in the microstructure of the nodular cast iron. The results showed that the microstructure has a strong effect on the material’s strength, especially the density of graphite nodules in the material. This difference reinforces the idea that cast iron can undergo mechanical changes due to changes in the casting process, confirming the importance of checking the characteristics of the cast batch before engineering applications of the material.

This work aims for a novel thermoelastic analysis methodology based on experimental steady-state temperature data and numerical displacement evaluation. The temperature data was acquired using thermal imaging and used as the input for a boundary element method (BEM) routine to evaluate its consequent thermoelastic displacement. The thermoelastic contribution to the resultant displacement arises in the BEM formulation as a domain integral, which compromises the main benefits of the BEM. To avoid the necessity of domain discretization, the radial integration method (RIM) was applied to convert the thermoelastic domain integral into an equivalent boundary integral. Due to its mathematical development, the resultant formulation from RIM requires the temperature difference to be input as a function. The efficacy of the proposed methodology was verified based on experimental displacement fields obtained via digital image correlation (DIC) analysis. For this purpose, a CNC (computer numerical control) marker was developed to print the speckle pattern instead of preparing the specimen by using manual spray paint or using commercially available pre-painted adhesives. The good agreement observed in the comparison between the numerical and experimental displacements indicates the viability of the proposed methodology.