A Critique on the Role of Object-Oriented Finite Element Analysis (OOF2) in Predicting Thermal and Mechanical Properties in Thermal Sprayed Coatings

Microstructural modeling at progressive length scales can enable the prediction of thermal and mechanical properties of thermal sprayed coatings with hierarchical features. Object-oriented finite (OOF2) element modeling conducted using microstructural images, although a powerful technique, has been employed to a limited extent in thermally sprayed materials. Consequently, there is little scientific understanding of the efficiency of the OOF2 technique for estimating bulk properties. For the first time, this study provides a comprehensive analysis of these factors’ role in the OOF2 technique’s capability to predict thermal and mechanical properties in ceramic and metallic coatings manufactured by plasma spray, high-velocity oxyfuel (HVOF) spray, wire_arc spray, and cold spray. The prediction efficiency generally increases for larger grain sizes as overall microstructural features are captured even at lower magnifications. The same effect is obtained in microstructures having lower and uniformly shaped pores. The data on the porosity suggest that OOF2 predictions are most accurate when conducted on coatings manufactured using sintered feedstock because of the dense powder. In contrast, OOF2 predictions are the least accurate when hollow spherical (HOSP) feedstock having empty cores is used. These multiscale facets of microstructure, porosity, etc., thus, highlight the importance of the selection of the representative volume element for accurate analysis in OOF2, which, depending upon the process, is captured at 300× − 500× for HVOF and wire-arc spray, and 1000× − 15,000× magnifications for plasma and cold spray. This overall assessment charts the relative importance of variables such as grain size, porosity, and feedstock as compared to that of the process and anisotropy in the prediction of properties in thermally sprayed coatings. While these conclusions are based on the limited literature of 37 articles, this study makes a bold attempt towards a guidebook for future thermal spray researchers in conducting more accurate OOF2 analysis.