Application of total focusing method in thin, strongly attenuating materials for aerospace applications

Germano, Elmergue and Deans, Matthew and Lam, Kwok Ho and Bailet, Gilles (2024) Application of total focusing method in thin, strongly attenuating materials for aerospace applications. In: The UKRI EPSRC Centre for Doctoral Training in Future Ultrasonic Engineering Annual Scientific Meeting 2024, 2024-06-25 - 2024-06-25, University of Strathclyde.

[thumbnail of Germano-etal-FUSE-ASM-2024-Application-of-total-focusing-method-in-thin-strongly-attenuating-materials]
Preview
Text. Filename: Germano-etal-FUSE-ASM-2024-Application-of-total-focusing-method-in-thin-strongly-attenuating-materials.pdf
Final Published Version
License: Strathprints license 1.0

Download (639kB)| Preview

Abstract

Additive manufacturing (AM) in aerospace transforms traditional manufacturing processes by depositing material in layers to construct parts from digital 3D designs. These processes offer crucial benefits like design flexibility and weight optimisation. Materials such as Titanium, Inconel, Nylon, and PEEK provide high strength and durability, but consistency and reliability remain challenges due to variance in part performance and internal defects. Insufficient layer adhesion and uneven cooling can lead to internal defects such as cavities, which may compromise the functionality of parts. Overcoming these barriers is essential for AM's adoption in high-performance aerospace applications. Through the employment of post-processing techniques and inspection procedures, defects can be identified and rectified, contributing to cost efficiency by minimising material waste and rework efforts. Moreover, in industries, like aerospace, where regulatory compliance is imperative, detecting, and documenting defects is essential to meet quality standards and ensure product conformity. Pairing nondestructive testing (NDT) with material testing methods enables the correlation of defect extent to mechanical performance, allowing for the accurate prediction of structural performance. This capability facilitates reliable qualification or rejection of 3D printing processes, addressing a significant challenge in the widespread adoption of additive manufacturing in the aerospace industry.

ORCID iDs

Germano, Elmergue ORCID logoORCID: https://orcid.org/0000-0003-2499-6458, Deans, Matthew, Lam, Kwok Ho and Bailet, Gilles;