Structural Health Monitoring, Damage Diagnosis, and Damage Prognosis: New Technologies and Applications

Dear Colleagues,

In recent years, the integration of machine learning algorithms within structural mechanics frameworks has revolutionized several aspects, from making numerical simulations faster to identifying patterns in diagnostic signals for damage diagnosis and prognosis.

This Special Issue aims to collate the most recent advances in the field of artificial intelligence techniques for structural health monitoring, focusing on damage diagnosis and prognosis. We invite submissions presenting theoretical contributions and applications based on experimental and/or numerical case studies.

Topics of interest include but are not limited to:

1. Innovative applications of deep learning techniques for damage diagnosis and prognosis;
2. Exploring the transition from traditional supervised methods to unsupervised machine learning approaches;
3. Advancements in generative artificial intelligence and its implications for structural health monitoring;
4. Delving into the interpretability of intelligent algorithms.

Dr. Luca Lomazzi
Dr. Francesco Cadini
Guest Editors

Manuscript Submission Information

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