SPARES combines physics-based modeling with machine learning-driven surrogate models to dramatically reduce the time and computational effort required to evaluate structural integrity, without ...

[This article was first published in Army Sustainment Professional Bulletin, which was then called Army Logistician, volume 1, number 2 (November–December 1969), pages 8–11, 24–25.] “… in the process ...

This article explores the potential of large language models (LLMs) in reliability systems engineering, highlighting their ...

Machine learning (ML) is rapidly emerging as a powerful tool to improve the safety, reliability, and long-term performance of marine structures exposed to harsh ocean environments. This study presents ...