Submission Deadline: 30 June 2026 View: 302 Submit to Special Issue
Assoc. Prof. Zhuyun Chen
Email: mezychen@gdut.edu.cn
Affiliation: School of Electromechanical Engineering, Guangdong University of Technology, Guangzhou, 510006, China
Research Interests: intelligent predictive maintenance and health management, digital twin, dynamic signal processing
Dr. Junyu Qi
Email: junyu.qi@reutlingen-university.de
Affiliation: Reutlingen Research Institute, Reutlingen University, Reutlingen, 72762, Germany
Research Interests: condition monitoring, industry 4.0, prognostics and health management, intelligent manufacturing
Dr. Bin Zhang
Email: jog_back@foxmail.com
Affiliation: Department of Electromechanical Engineering and Centre of Artificial Intelligence and Robotics, University of Macau Taipa 999078, Macau, China
Research Interests: deep learning methods for guided wave detection and nondestructive evaluation
Prof. Wu Qin
Email: qw@ecjtu.edu.cn
Affiliation: School of Mechatronics & Vehicle Engineering, East China Jiaotong University, Nanchang, 330013, China
Research Interests: vehicle dynamics, physical data model, electro-hydraulic servo system
Assist. Prof. Deepam Goyal
Email: bkdeepamgoyal@outlook.com
Affiliation: Department of Mechanical Engineering, Chitkara University, Rajpura, 140401, India
Research Interests: vibration, condition monitoring, machine fault diagnostics, sensors, optimization, manufacturing technology
The field of computational engineering is being transformed by the integration of physics-based modeling and data-driven AI. This synergy offers new ways to model, predict, and optimize complex dynamical systems - such as advanced manufacturing, robotics, and energy infrastructure, which often involve multi-physics interactions and span multiple scales. Faced with system complexity and abundant IoT data, this Special Issue seeks cutting-edge research that bridge first-principles dynamics with AI/ML to advance predictive operations, health monitoring, and autonomous control optimization.
This special issue invites original research contributions, technical advances, and application-driven studies in intelligent dynamics modeling, predictive operations and maintenance, and control optimization for complex systems. Both theory-focused, computational frameworks, and real-world applications are welcome. We particularly encourage submissions with strong technical depth or emerging applications in fields such as aerospace, energy, robotics, and intelligent infrastructure. Potential topics include, but are not limited to the following:
· Physics-informed neural networks and hybrid modeling
· Digital twin technology for dynamic systems
· Reinforcement learning and AI-based control
· Prognostic and health management (PHM)
· Multi-physics and multi-scale simulation
· Model predictive and adaptive control
· Intelligent fault diagnosis and self-healing control
· Evolutionary and swarm intelligence-based optimization
· Real-time sensing and decision support systems
· AI-Powered Autonomous Maintenance Systems
· Case Studies in PHM
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