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

IF 3.2 3区 材料科学 Q2 MATERIALS SCIENCE, COATINGS & FILMS
Riddhi Joshi, Tanaji Paul, Cheng Zhang, Benjamin Boesl, Arvind Agarwal
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Abstract

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.

Abstract Image

关于面向对象有限元分析 (OOF2) 在预测热喷涂涂层的热性能和机械性能中的作用的评论
渐进长度尺度的微观结构建模可以预测具有层次特征的热喷涂涂层的热性能和机械性能。使用微观结构图像进行的面向对象有限元(OOF2)建模虽然是一种强大的技术,但在热喷涂材料中的应用还很有限。因此,人们对 OOF2 技术估算体积特性的效率还缺乏科学认识。本研究首次全面分析了这些因素在 OOF2 技术预测等离子喷涂、高速富氧喷涂、线弧喷涂和冷喷涂制造的陶瓷和金属涂层的热性能和机械性能方面所起的作用。晶粒尺寸越大,预测效率越高,因为即使在较低的放大倍率下也能捕捉到整体微观结构特征。在具有较小且形状均匀的孔隙的微结构中也能获得同样的效果。孔隙率数据表明,由于粉末致密,在使用烧结原料制造的涂层上进行 OOF2 预测最为准确。相反,在使用空心球形(HOSP)原料时,OOF2 预测的准确性最低。因此,微观结构、孔隙率等这些多尺度方面突出了选择具有代表性的体积元素对 OOF2 精确分析的重要性,根据工艺的不同,HVOF 和线弧喷射的捕捉倍数为 300× - 500×,等离子和冷喷射的捕捉倍数为 1000× - 15,000×。这一总体评估显示了晶粒大小、孔隙率和原料等变量与工艺和各向异性变量相比在预测热喷涂涂层性能方面的相对重要性。虽然这些结论是基于有限的 37 篇文献得出的,但本研究大胆尝试为未来的热喷涂研究人员提供指导手册,以进行更准确的 OOF2 分析。
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来源期刊
Journal of Thermal Spray Technology
Journal of Thermal Spray Technology 工程技术-材料科学:膜
CiteScore
5.20
自引率
25.80%
发文量
198
审稿时长
2.6 months
期刊介绍: From the scientific to the practical, stay on top of advances in this fast-growing coating technology with ASM International''s Journal of Thermal Spray Technology. Critically reviewed scientific papers and engineering articles combine the best of new research with the latest applications and problem solving. A service of the ASM Thermal Spray Society (TSS), the Journal of Thermal Spray Technology covers all fundamental and practical aspects of thermal spray science, including processes, feedstock manufacture, and testing and characterization. The journal contains worldwide coverage of the latest research, products, equipment and process developments, and includes technical note case studies from real-time applications and in-depth topical reviews.
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