Deadline Date: 15 February 2026
The increasing complexity of modern industrial systems demands advanced tools for ensuring structural integrity, safety, and operational efficiency. This special issue focuses on the integration of high-fidelity Finite Element Modeling (FEM) with real-time condition monitoring and intelligent systems for predictive maintenance and structural health management. By merging numerical simulation precision with sensor-based monitoring and emerging digital twin technologies, this interdisciplinary approach facilitates dynamic, condition-aware decision-making in industries such as aerospace, energy, transportation, and civil infrastructure.
We invite research contributions that explore the development and application of intelligent technologies such as AI, machine learning, IoT, robotics, and real-time data analytics for enhancing FEM frameworks. Emphasis is placed on adaptive simulations, anomaly detection, reduced-order modeling, and physics-informed neural networks (PINNs) for scalable, real-time asset monitoring. Contributions highlighting applications in digital twins, fatigue life prediction, and smart maintenance of critical systems like pipelines, turbines, and offshore structures are especially encouraged. This issue aims to provide a comprehensive overview of cutting-edge solutions that bridge the gap between physical systems and their virtual counterparts to optimize performance, reduce operational costs, and promote sustainable asset management.
Suggested Topics of Interest include (but are not limited to):
- Robotics-Aided Inspection and Model-Referenced Monitoring of Infrastructure Assets
- Thermal-Structural Digital Twins for Early Failure Detection in Energy Equipment
- AI-Powered Condition Monitoring Framework for Smart Industrial Pipelines
- Machine Learning Enhanced Structural Models for Critical Asset Management
- Neural Network-Assisted Real-Time FEM Updates for Dynamic Load Environments
- Mechatronic Integration for Fault Prediction Using Advanced Numerical Simulations
- Big Data-Driven Optimization of FEM Workflows for Industrial Equipment Monitoring
- Integrated Sensing and Real-Time FEM for Predicting Fatigue in High-Stress Components
- Condition-Aware Numerical Modeling Frameworks for Sustainable Industrial Operations
- Surrogate Modeling for High-Speed Predictive Maintenance in Industrial Digital Twins
- Cloud-Based Condition Assessment Using Adaptive FEM and Intelligent Sensing
- Vibration Analytics and Model-Driven Insights for Rotating Equipment Maintenance
- Robotics-Aided Inspection and Model-Referenced Monitoring of Infrastructure Assets
The increasing complexity of modern industrial systems demands advanced tools for ensuring structural integrity, safety, and operational efficiency. This special issue focuses on the integration of high-fidelity Finite Element Modeling (FEM) with real-time condition monitoring and intelligent systems for predictive maintenance and structural health management. By merging numerical simulation precision with sensor-based monitoring and ... show more
Editorial board
