LEGEND is a Marie Skłodowska-Curie Doctoral Network dedicated to understanding and mitigating the effects of defects in composite structures. Bringing together a wide European network of academic and industrial partners, the project delivers a coordinated research and training programme for 14 Doctoral Candidates, combining experimental research, non-destructive inspection, computational modelling and machine learning to support the safer,   more sustainable, and more efficient use of advanced composites in aerospace applications. 

Defects in composite structures can arise across multiple length scales and from different manufacturing and service conditions, and their effects are still difficult to quantify reliably in industrial settings. This creates barriers across the full value chain, from material qualification and structural design certification, to inspection and maintenance decisions, and long-term safety assessment. 

LEGEND responds to these challenges by improving the way defects are inspected, characterised, and represented in predictive tools, with the aim of reducing unnecessary conservatism while supporting robust engineering judgement and safer certification pathways. 

LEGEND’s overarching research objective is to overcome current limitations in characterising and predicting the effects of defects in composite structures. Its research programme is organised around four connected research objectives (ROs):

RO1. Develop fast, automated methods for defect inspection, classification, and quantification, using advanced non-destructive inspection and machine-learning-enabled tools.

RO2. Develop improved experimental methods to characterise how defects affect structural behaviour under different loading conditions, including interactive defect scenarios.

RO3. Develop efficient numerical frameworks for qualification-by-analysis and certification-by-analysis that account for defect effects across multiple scales.

RO4. Develop improved methods for generating statistically informed defect acceptance criteria for industrial applications.

In practical terms, LEGEND aims to help engineers answer four key questions: what defects are present, how important they are, how they influence structural performance, and how they should be handled in qualification, certification, and inspection practices.

LEGEND is structured as an integrated research programme divided into 4 Work Packages that connect inspection data, experimental test evidence, modelling tools and machine learning techniques, so that each scientific advance can feed into the next stage of analysis and validation.

The doctoral projects are distributed across the network and linked to the common research objectives, allowing the consortium to address defect effects from the micro-scale to the structural scale, while maintaining a clear route toward industrial relevance. The programme combines universities, research training organisations (RTOs), and industrial partners across Portugal, Spain, Italy, Germany, Sweden, and the United Kingdom.

As a MSCA Doctoral Network, LEGEND is not only a research project but also a structured training environment for early-stage researchers. The 14 Doctoral Candidates will work on connected research topics while benefiting from local supervision, network-wide training, secondments, and exposure to both academic and industrial methods and expectations. 

This approach is designed to develop a new generation of researchers and engineers who can work confidently across inspection, testing, modelling, and certification-related challenges in advanced composite structures.