Efficient multidisciplinary modeling of aircraft undercarriage landing gear using data-driven Naïve Bayes and finite element analysis

• Published in: Multiscale and Multidisciplinary Modeling, Experiments and Design Vol. 7; no. 4; pp. 3187 - 3199
• Main Authors: Al-Haddad, Luttfi A., Mahdi, Nibras M.
• Format: Journal Article
• Language: English
• Published: Cham Springer International Publishing 01.09.2024
• Subjects: Characterization and Evaluation of Materials; Engineering; Mathematical Applications in the Physical Sciences; Mechanical Engineering; Numerical and Computational Physics; Original Paper; Simulation; Solid Mechanics; Naïve Bayes; Finite element analysis; Artificial intelligence; Landing gear; Machine learning

Advancements in aircraft design and production necessitate exhaustive simulations of critical components, such as landing gear, to ensure optimal performance and safety. This paper presents a novel approach that combines finite element analysis (FEA) and machine learning (ML) for comprehensive simul...