Open Access

REVIEW

Advances in Crack Formation Mechanisms, Evaluation Models, and Compositional Strategies for Additively Manufactured Nickel-Based Superalloys

Huabo Wu^1,2, Jialiao Zhou³, Lan Huang^1,2,*, Zi Wang^1,2,*, Liming Tan^1,2, Jin Lv⁴, Feng Liu^1,2

1 State Key Laboratory of Powder Metallurgy, Central South University, Changsha, 410083, China
2 Research Institute of Powder Metallurgy, Central South University, Changsha, 410083, China
3 Hunan Runfeng Innovation Tech Co., Ltd., Zhuzhou, 412007, China
4 Puli (Ningbo) Advanced Material Technology Co., Ltd., Ningbo, 315599, China

* Corresponding Authors: Lan Huang. Email: ; Zi Wang. Email:

Computer Modeling in Engineering & Sciences 2025, 143(3), 2675-2709. https://doi.org/10.32604/cmes.2025.064854

Received 25 February 2025; Accepted 04 June 2025; Issue published 30 June 2025

Abstract

Nickel-based superalloys are indispensable for high-temperature engineering applications, yet their additive manufacturing (AM) is plagued by significant cracking defects. This review investigates crack failure mechanisms in AM nickel-based superalloys, emphasizing methodologies to evaluate crack sensitivity and compositional design strategies to mitigate defects. Key crack types—solidification, liquation, solid-state, stress corrosion, fatigue, and creep-fatigue cracks—are analyzed, with focus on formation mechanisms driven by thermal gradients, solute segregation, and microstructural heterogeneities. Evaluation frameworks such as the Rappaz-Drezet-Gremaud (RDG) criterion, Solidification Cracking Index (SCI), and Strain Age Cracking (SAC) index are reviewed for predicting crack susceptibility through integration of thermodynamic parameters, solidification kinetics, and mechanical properties. Alloy compositional design strategies are presented, including optimization of strengthening elements (Al, Ti), grain boundary modifiers (B, Zr, Re), and impurity control (C, O), which suppress crack initiation and propagation via microstructure refinement and enhanced high-temperature resistance. Computational approaches, such as thermodynamically assisted design, high-throughput experimentation, and machine learning, are highlighted for decoding complex composition-structure-property relationships. Challenges in modeling multi-scale defect interactions and developing unified frameworks for manufacturing- and service-induced cracks are outlined. This review underscores the necessity of integrated computational-experimental strategies to advance reliable AM of nickel-based superalloys, providing insights for defect prediction, alloy optimization, and process control.

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Keywords

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