White PaperManufacturing & Prototyping
Using Digital Twins to Accelerate Qualification of Fatigue Critical Components
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Fatigue is a major challenge in aerospace alloys, requiring costly and time-consuming testing of numerous components. QuesTek’s ICMD® modeling software significantly reduces the need for extensive testing by predicting material properties using physics-based simulations. Leveraging Integrated Computational Materials Engineering (ICME), QuesTek has developed fatigue models that incorporate both intrinsic (e.g., grain size, texture) and extrinsic (e.g., porosity, surface roughness) microstructural features that influence fatigue life.
QuesTek’s framework combines crystal plasticity finite element methods with small and long crack growth algorithms to predict fatigue life from initiation to failure. This approach uses microstructure-informed digital twins and limited calibration experiments to simulate real-world conditions. The result: faster, less expensive qualification and deeper understanding of fatigue behavior.
Recent advancements include reduced computational costs and new capabilities for modeling complex microstructures in additively manufactured alloys—making this toolkit ideal for aerospace applications requiring high-performance, fatigue-resistant materials.
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Overview
The white paper presented at the 31st ICAF Symposium by Gary F. Whelan, Jiadong Gong, and Gregory B. Olson discusses the critical processes of qualification and certification in the aerospace industry, particularly focusing on fatigue-critical components. Qualification involves demonstrating that materials or components meet specific performance standards through rigorous testing, while certification verifies compliance with regulatory requirements set by agencies like the FAA and EASA. Both processes are essential for ensuring the safety and reliability of aerospace materials.
The authors introduce an Accelerated Qualification Framework that utilizes digital twins and Integrated Computational Materials Engineering (ICME) to enhance the qualification process. By creating a digital twin of the alloy and calibrating its mechanical properties with experimental data, the framework allows for a more efficient prediction of minimum fatigue life. This approach reduces the number of physical tests required, thereby lowering costs and time associated with qualification.
The paper highlights the challenges posed by traditional qualification methods, which are often slow and expensive, particularly for additive manufacturing (AM) technologies. The authors argue that the current qualification processes act as barriers to the widespread adoption of AM in aerospace, as they require extensive material testing and compliance with stringent standards.
To address these challenges, the authors propose the use of predictive modeling and selective experimental data to accelerate the qualification process. By determining minimum properties with fewer experiments, manufacturers can optimize materials and components before committing to extensive testing. This methodology has been successfully demonstrated in the development of new materials, such as Ferrium M54, which was rapidly qualified for military applications.
In conclusion, the white paper emphasizes the need for innovative approaches to streamline the qualification and certification processes in aerospace, ultimately enhancing the adoption of advanced materials and technologies while ensuring safety and reliability.