Deadline Date: 31 December 2026
This Special Issue focuses on the integration of artificial intelligence, digital workflows, and computational modelling in mechanical engineering, with emphasis on structural integrity, materials behaviour, and system performance. The objective is to examine how data-driven methods and physics-based approaches can be combined to improve analysis, design, and lifecycle management of mechanical components and systems.The collection particularly targets contributions that bridge classical mechanics with modern computational techniques such as machine learning, physics-informed models, and surrogate-based optimisation. Applications may include stress analysis, fatigue, dynamics, and reliability of engineering systems under complex loading and environmental conditions.Studies addressing sustainable and efficient engineering solutions are encouraged, including lightweight design, durability assessment, and reuse of materials and components. Both fundamental and applied works are welcome, provided they demonstrate clear relevance to mechanical engineering practice and offer measurable advancements in modelling accuracy, computational efficiency, or system performance.
Deadline Date: 31 December 2026
This Special Issue focuses on the integration of artificial intelligence, digital workflows, and computational modelling in mechanical engineering, with emphasis on structural integrity, materials behaviour, and system performance. The objective is to examine how data-driven methods and physics-based approaches can be combined to improve analysis, design, and lifecycle management of mechanical components ... show more
Editorial board
