ABSTRACT

The widespread adoption of composite materials in aerospace and civil engineering is often limited by their complex, long-term degradation. Unlike traditional materials, composites are highly susceptible to the combined effects of harsh environmental aging, such as temperature extremes and moisture absorption, and inevitable manufacturing defects. To ensure structural safety, the industry currently relies on the expensive and time-consuming physical "building block approach," applying highly conservative "knock-down factors" to account for these unknown variables.

This seminar presents a comprehensive methodology to move the industry from exhaustive physical testing toward cost-effective Virtual Certification. We will first explore the fundamental mechanics of environmental degradation, highlighting the dangerous synergy between hygrothermal aging and manufacturing flaws (such as gaps and voids) which actively accelerate structural deterioration. By extracting the exact degraded material properties and applying Uncertainty Quantification (UQ), we will demonstrate how high-fidelity Finite Element Models (FEM) can propagate these variables to virtually calculate reliable safety margins. Finally, the presentation will outline ongoing research into the integration of Artificial Intelligence (AI), showcasing how machine learning surrogate models will soon bypass computationally heavy simulations to enable the rapid, near-instantaneous optimization of next-generation composite structures.