AcknowledgmentsThe authors would like to recognize Rick Farmer, Roxanne Garland, and Jamie Holladay of the U.S. Department of Energy for funding this work. George Sverdrup of the National Renewable Energy Laboratory (NREL) and Vicki McCarl of Xcel Energy were both very helpful in scoping and defining the Wind2H2 project and have provided excellent feedback throughout the project. Brad Hollenbaugh and Curtis Perry of Xcel Energy were instrumental in helping design and configure the Wind2H2 system and in participating in the readiness verification review. The authors would like to acknowledge John Cornish of EPC and Marc Mann of Spectrum Automation for their work installing and programming the Wind2H2 system. The authors would like to thank Connie Komomua for her assistance in editing the work. Finally, the authors would like to thank Robert Remick, Dave Mooney, Ben Kroposki, Mike Stewart, and Genevieve Saur of NREL for their technical assistance throughout the project. and is enjoying success as a demonstration project, producing hydrogen directly from renewable energy sources. This unique research-oriented project uses solar and wind energy to produce and store hydrogen. The stored hydrogen can be used both as a transportation fuel and as an energy storage medium, effectively allowing renewable energy to be stored and converted back to electricity at a later time.The Wind2H2 project is helping researchers understand the hurdles and potential areas for improvement in emerging renewable electrolysis technologies. By allowing engineers to operate and configure an integrated electrolysis facility, this project has enabled the investigation and analysis of hydrogen production, compression, storage, and electricity generation that is providing valuable data that are being used to improve the designs of future renewable electrolysis systems. This first report on the Wind2H2 project provides important guidance to industry and key stakeholders for development of future renewable electrolysis systems.The Wind2H2 project is the only renewable hydrogen production facility in the world that can operate multiple electrolyzers in any of the following configurations: 1. Grid connected 2. Directly connected from the output of a photovoltaic array to the electrolyzer stack 3. Real-time electrolyzer stack current control based on a power signal from a wind turbine 4. Closely coupled photovoltaic (PV) and wind energy sources to the electrolyzer stack with custom designed and built power electronics.NREL and Xcel Energy have undertaken the Wind2H2 project with several key objectives in mind. First and foremost, the Wind2H2 project is being used to demonstrate operation of a renewable electrolysis system, allowing researchers to evaluate actual system performance and costs and to identify areas for cost and efficiency improvements. Additionally, the project provides operational experience with a renewable electrolysis hydrogen production facility, enabling project engineers to investigate operational challenges and to explore system-...

The future deployment of single pilot operations must be supported by new cockpit computer services. Such services require an adaptive context-aware integration of technical functionalities with the concurrent tasks that a pilot must deal with. Advanced artificial intelligence supporting services and improved communication capabilities are the key enabling technologies that will render future cockpits more integrated with the present digitalized air traffic management system. However, an issue in the integration of such technologies is the lack of socio-technical analysis in the design of these teaming mechanisms. A key factor in determining how and when a service support should be provided is the dynamic evolution of pilot workload. This paper investigates how the socio-technical model-based systems engineering approach paves the way for the design of a digital assistant framework by formalizing this workload. The model was validated in an Airbus A-320 cockpit simulator, and the results confirmed the degraded pilot behavioral model and the performance impact according to different contextual flight deck information. This study contributes to practical knowledge for designing human-machine task-sharing systems.