Intelligent Technologies and Processes for Advanced Nuclear Power and Energy Engineering
A special issue of Processes (ISSN 2227-9717). This special issue belongs to the section "Energy Systems".
Deadline for manuscript submissions: closed (31 March 2023) | Viewed by 34999
Special Issue Editors
Interests: supply chain management; healthcare systems; sustainable logistics and production management; optimization algorithms; heuristics; metaheuristics
Special Issues, Collections and Topics in MDPI journals
Interests: design, kinematics and dynamics of mechanical systems; robot hands and the mechanics of manipulation; industrial robotic innovation; (4) mechatronic approaches to the design of robot manipulators; dynamic balancing and synthesis of high-speed machines; rehabilitation engineering, prosthetics and orthotics; numerical simulation and optimization of mechanisms using ADAMS software
Special Issues, Collections and Topics in MDPI journals
Interests: petri net theory and application; supervisory control of discrete event systems; workflow analysis; system reconfiguration; game theory; production scheduling and planning; data and process mining
Special Issues, Collections and Topics in MDPI journals
Interests: reconstruction of CAD models from triangular surface mesh; product optimal design; advanced manufacturing technology;networked manufacturing.
Special Issues, Collections and Topics in MDPI journals
Interests: remanufacturing and green manufacturing; green logistics and transportation; intelligent inspection and automotive repair
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Nuclear power equipment is a national name card which plays an important role in the nuclear power supply of the new generation of onshore nuclear power plants, submarine aircraft carriers, marine development, deep space exploration and other major national projects. From the designation to decommissioning of nuclear power equipment, lifecycle digital and intelligent technologies implement a visual and flexible analysis mode and integrate information on the whole process to supply systematic engineering service in design, manufacturing, operation and management. Because of the numerous subsystems, complex working conditions and lengthy service period of advanced nuclear power equipment, how to realize its lifecycle digital and intelligent technologies is a daunting task. This has recently motivated researchers to explore new lifecycle digital and intelligent technologies of advanced nuclear power equipment.
The objective of this Special Issue is to present the latest advances and developments dedicated to the lifecycle digital and intelligent technologies for advanced nuclear power equipment, such as digital collaborative design, multidisciplinary design optimization and autonomous decision making, intelligent and sustainable nuclear manufacturing, predictive maintenance and autonomous diagnostics.
Topics of interest for this Special Issue include, but are not limited to, the following:
- Digital collaborative design and manufacturing in the nuclear power industry;
- Multidisciplinary design optimization and autonomous decision making for nuclear power equipment;
- Modular technologies for nuclear engineering;
- The whole lifecycle model system of nuclear power equipment;
- Intelligent nuclear manufacturing with digital twin;
- Four-dimensional digital construction schedule management in the nuclear power industry;
- Visual simulation technologies in start-up commissioning of nuclear systems;
- Sustainable nuclear manufacturing using data-driven approaches;
- Predictive maintenance for long-term operation of nuclear power equipment;
- Autonomous diagnostics and prognostics for nuclear power equipment;
- Information integration and cognitive system in nuclear power scenarios;
- Quality control and traceability of state co-evolution for nuclear power equipment;
Domain knowledge coupling association and deep mining based on data space in the nuclear power industry.
Dr. Amir M. Fathollahi-Fard
Prof. Dr. Vigen H. Arakelian
Dr. Zhiwu Li
Dr. Zixian Zhang
Prof. Dr. Guangdong Tian
Guest Editors
Manuscript Submission Information
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Keywords
- lifecycle management
- sustainability
- quality control
- intellgent systems
- nuclear manufacturing
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