The physical machinery in factory plants is becoming essentially an internet-of-things (IoT), connected among each other, and cooperating both with each other and with a human-in-the-loop. Intelligent data-driven produced design, manufacturing, and monitoring applications along with the distributed decision-making capability to such manufacturing systems enables what is now called Industry 4.0. This seamless integration of information via Industry 4.0 generates voluminous amounts of data that can be used to ensure greater transparency and management of quality across various tiers of the supply chain.
The development of long-lasting aerospace systems depends heavily on the advancement of high-performance materials and structures, which can withstand extreme environments and conditions. With the recent advances in additive manufacturing, the technology has several benefits compared to traditional manufacturing processes and thus, has become attractive for many complex mechanical-assemblies in aircraft systems.
The focus of this trust area is on the innovation of next generation materials and structures capable of operating efficiently under these conditions, which will help overcome many of the aerospace challenges ranging from improving durability of the aircraft and premature failure of the components to developing novel gas turbine engines. This includes systematic studies of novel manufacturing methods, as well as advanced materials that are lighter, stronger, resilient to corrosion, and that can operate at higher temperatures in gas turbine engine applications. The key themes of this thrust area include additive manufacturing, nanomaterials, particularly nano-composites for physical and mechanical property enhancement, smart structures as well as innovative coatings and surface engineering procedures that meet the ecological and environmental demands.
Design and Optimization of Aircraft Systems and Propulsion
With the increasing demands on sustainable and environmentally friendly solutions, design of more electric, hybrid aircraft and all-electric aircraft will be areas of significant growth in the near future and is, therefore, one of the main topics of this thrust area.
Furthermore, research in alternative fuels, advanced flight management systems, advanced flight control systems, air-frame and engine control systems, autonomy and artificial intelligence, hydrogen alternative power generation, propulsion alternatives such as electric motor technologies, electric power systems, battery development and integration, fuel cells and photovoltaic systems will also contribute to more optimal and efficient aircraft.
Design of innovative and unconventional aircraft configurations requires development of novel design methodologies, particularly for conceptual design and multi-disciplinary design analysis and optimization. In addition, model-based systems engineering is a promising area to enable the concurrent optimization of several subsystems so that their interconnection is symbiotic in the final aircraft design and development are of fundamental importance.
The use of AI and machine learning for analyzing data collected during flight operation is a focal point of this thrust area.
The expected sheer number of autonomous unmanned assets, inclusion of urban air taxis and drones in future that are all to be controlled and managed seamlessly, along with human-autonomy interactions, social dynamics, and team trust and cybersecurity requirements introduce significant challenges to flight management and air traffic management systems.
The transition to distributed air traffic control with vehicle-to-vehicle communication and, therefore, new distributed control algorithms for air traffic management is a major area of research to meet future challenges of airspace, including new airspace regulations that allow the operation of autonomous unmanned assets and drones.
The design of new drones with different shapes and control of swarms of drones for data collection (for example environmental data or traffic information) is also a promising direction of research.