Fiber metal laminates are advanced materials that comprise alternating metal and fiber-reinforced polymer layers, which are predominantly used in lightweight applications such as aerospace providing enhanced strength and fatigue performance due to their high specific strength. However, these aerospace structures made out of FMLs are susceptible to impact damage which can have catastrophic consequences [1] as witnessed in the past with the Columbia space shuttle disaster where the impact of foam insulation on the leading edge of the wing [2] led to structural failure during atmospheric re-entry. Therefore, early identification and mitigation of these impact damage is crucial for structural safety and operational integrity. These impact damages may persist within the structure while enduring mechanical loads, leading to damage evolution and progression that can eventually result in complete or ultimate failure. To effectively address the challenges associated with impact damage, a comprehensive understanding of impact damage evolution under mechanical loads is essential.

This study focuses on the influence of mechanical loads on post-impact fiber metal laminates (FMLs) and the differentiation between new and existing impact damage. Differentiating recent impact damage from older damage is crucial for optimizing maintenance strategies, reducing lead times, and prioritizing repairs based on severity, ultimately enhancing aircraft safety and operational efficiency. Older damage, which has endured significant mechanical loads, may exhibit characteristics distinct from newer damage, making it critical to assess the current condition of the structure with better precision. By applying mechanical loads, nuanced differences in damage characteristics, such as matrix cracking, delamination, and fiber breakage, can be observed, enabling the development of refined damage classification which can be utilized for a direct correlation with Guided Ultrasonic Waves methods for damage identification [3].

In this research, FML specimens will be subjected to mechanical loading to simulate near real-world operational stresses. Damage patterns will be analyzed using X-ray computed tomography (CT) in both pre and post-load applications to capture detailed structural changes. The study could potentially demonstrate that mechanical loading amplifies the differences between new and existing impact damage, facilitating more accurate differentiation. Furthermore, these findings are expected to contribute to the development of more advanced structural health monitoring (SHM) systems and repair strategies, enabling more targeted and efficient maintenance of critical aircraft components.

References

[1] C. Shah, S. Bosse, and A.v. Hehl. Taxonomy of Damage Patterns in Composite Materials, Measuring Signals, and Methods for Automated Damage Diagnostics. Materials, 2022, 15, 4645.

[2] J.D. Walker. From Columbia to Discovery: Understanding the impact threat to the space shuttle. International Journal of Impact Engineering, 2009, 36, 303-317.

[3] C. Shah, S. Bosse, C. Zinn, A. von Hehl. Optimization of Non-destructive Damage Detection of Hidden Damages in Fiber Metal Laminates Using X-ray Tomography and Machine Learning Algorithms. Advances in System-Integrated Intelligence. SYSINT 2022. Lecture Notes in Networks and Systems, 2022, 546. 387-402.