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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 55 records · Page 3

Alertness Management In Flight Operations: A NASA Education and Training Module

Since 1980, the NASA Ames Fatigue Countermeasures Program has been conducting research on sleep, circadian rhythms, and fatigue in a variety of flight operations 1. An original goal of the program was to return the scientific and operational knowledge to the aviation industry. To meet this goal, the NASA Ames Fatigue Countermeasures Program has created an Education and Training Module entitled, "Strategies for Alertness Management in Flight Operations." The Module was designed to meet three objectives: 1) explain the current state of knowledge about the physiological mechanisms underlying fatigue, 2) demonstrate how this knowledge can be applied to improve flight crew sleep, performance, and alertness, and 3) offer countermeasure recommendations. The Module is composed of two components: 1) a 60-minute live presentation provided by a knowledgeable individual and 2) a NASA/FAA Technical Memorandum (TM) that contains the presentation materials and appendices with complementary information. The TM is provided to all individuals attending the live presentation. The Module content is divided into three parts: 1) basic information on sleep, sleepiness, circadian rhythms, fatigue, and how flight operations affect these physiological factors, 2) common misconceptions about sleep, sleepiness, and fatigue, and 3) alertness management strategies. The Module is intended for pilots, management personnel, schedulers, flight attendants, and the many other individuals involved in the aviation system.

Rosekind, Mark R.↗

Scalable Unit Commitment with Security Constrained AC Power Flow via ADMM and Hybrid Modeling Strategies

This research introduces a more efficient way to optimize power grid operations, breaking the problem into manageable steps and using advanced mathematical techniques to speed up calculations. By incorporating smart heuristics, improved preprocessing, and contingency analysis, the approach allows operators to make better decisions faster. These innovations enhance our understanding of how to optimize energy generation, making it possible to anticipate failures before they happen, reduce system costs, and improve overall grid performance. Ultimately, this research helps bridge the gap between theoretical models and real-world applications, paving the way for a smarter, more resilient power grid. This research directly benefits the public by making electricity more affordable, reliable, and sustainable. By improving how power grids schedule and distribute electricity, the project helps energy providers reduce operational costs, which can lead to lower electricity prices for consumers. Additionally, the ability to predict and prevent power system failures enhances grid reliability, reducing the likelihood of blackouts that can disrupt homes, businesses, and critical infrastructure such as hospitals. From an environmental perspective, optimizing power generation reduces energy waste and lowers carbon emissions, contributing to cleaner air and a more sustainable energy system. Furthermore, with extreme weather events becoming more frequent, these advancements make the power grid more resilient, ensuring communities are better prepared for emergencies and natural disasters. By strengthening the nation's energy infrastructure, this research plays a crucial role in improving economic stability, public safety, and environmental sustainability.

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Crew workload-management strategies - A critical factor in system performance

This paper reviews the philosophy and goals of the NASA/USAF Strategic Behavior/Workload Management Program. The philosophical foundation of the program is based on the assumption that an improved understanding of pilot strategies will clarify the complex and inconsistent relationships observed among objective task demands and measures of system performance and pilot workload. The goals are to: (1) develop operationally relevant figures of merit for performance, (2) quantify the effects of strategic behaviors on system performance and pilot workload, (3) identify evaluation criteria for workload measures, and (4) develop methods of improving pilots' abilities to manage workload extremes.

Hart, Sandra G.↗

Transient Optimization of a Gas Turbine Engine

Gas turbine engines are the primary power plants for modern commercial aircraft. Transients prompted by significant changes in thrust or power demand are common and unavoidable. Extreme transient scenarios such as those associated with a go-around during a landing attempt are possible and must be accounted for in the design of the engine and its controller. Engine transients tend to cause a reduction in compressor operability margin, which must be addressed by the engine control system and accounted for in the engine design to prevent events such as compressor stall/surge and combustor blow out. Transient operability concerns typically lead to compromises in the engine design that sacrifice efficiency and/or limit responsiveness. Transient operability is typically managed by logic that limits the fuel flow command. If this logic is not optimized, then the potential for valuable performance could be lost. This study presents a strategy for optimizing the transient limit logic and proposes a strategy for updating the control logic over the lifespan of the engine. The results demonstrate significant improvements in transient operability. For example, of the results at sea level static conditions demonstrated a 31% reduction in the usage of the high pressure compressor operability stack during a snap acceleration transient. Furthermore, a reinforcement learning algorithm is demonstrated to modify the transient logic as the engine degrades to minimize response time while respecting a prescribed compressor operability margin limit. A simple demonstration of the reinforcement learning algorithm resulted in a thrust response time reduction of ~11.8%.

transient↗

Transient Optimization of a Gas Turbine Engine

Gas turbine engines are the primary power plants for modern commercial aircraft. Transients prompted by significant changes in thrust or power demand are common and unavoidable. Extreme transient scenarios such as those associated with a go-around during a landing attempt are possible and must be accounted for in the design of the engine and its controller. Engine transients tend to cause a reduction in compressor operability margin, which must be addressed by the engine control system and accounted for in the engine design to prevent events such as compressor stall/surge and combustor blow out. Transient operability concerns typically lead to compromises in the engine design that sacrifice efficiency and/or limit responsiveness. Transient operability is typically managed by logic that limits the fuel flow command. If this logic is not optimized, then the potential for valuable performance could be lost. This study presents a strategy for optimizing the transient limit logic and proposes a strategy for updating the control logic over the lifespan of the engine. The results demonstrate significant improvements in transient operability. For example, of the results at sea level static conditions demonstrated a 31% reduction in the usage of the high pressure compressor operability stack during a snap acceleration transient. Furthermore, a reinforcement learning algorithm is demonstrated to modify the transient logic as the engine degrades to minimize response time while respecting a prescribed compressor operability margin limit. A simple demonstration of the reinforcement learning algorithm resulted in a thrust response time reduction of ~11.8%.

transient↗

Transient Optimization of a Gas Turbine Engine

Gas turbine engines are the primary power plants for modern commercial aircraft. Transients prompted by significant changes in thrust or power demand are common and unavoidable. Extreme transient scenarios such as those associated with a go-around during a landing attempt are possible and must be accounted for in the design of the engine and its controller. Engine transients tend to cause a reduction in compressor operability margin, which must be addressed by the engine control system and accounted for in the engine design to prevent events such as compressor stall/surge and combustor blow out. Transient operability concerns typically lead to compromises in the engine design that sacrifice efficiency and/or limit responsiveness. Transient operability is typically managed by logic that limits the fuel flow command. If this logic is not optimized, then the potential for valuable performance could be lost. This study presents a strategy for optimizing the transient limit logic and proposes a strategy for updating the control logic over the lifespan of the engine. The results demonstrate significant improvements in transient operability. For example, of the results at sea level static conditions demonstrated a 31% reduction in the usage of the high pressure compressor operability stack during a snap acceleration transient. Furthermore, a reinforcement learning algorithm is demonstrated to modify the transient logic as the engine degrades to minimize response time while respecting a prescribed compressor operability margin limit. A simple demonstration of the reinforcement learning algorithm resulted in a thrust response time reduction of ~11.8%.

transient↗

Improving Aquatic Plant Management in the California Sacramento-San Joaquin Delta

Management of aquatic weeds in complex watersheds and river systems present many challenges to assessment, planning and implementation of management practices for floating and submerged aquatic invasive plants. The Delta Region Areawide Aquatic Weed Project (DRAAWP), a USDA sponsored area-wide project, is working to enhance planning, decision-making and operational efficiency in the California Sacramento-San Joaquin Delta. Satellite and airborne remote sensing are used map (area coverage and biomass), direct operations, and assess management impacts on plant communities. Archived satellite records going are used to review results from previous climate and management events and aide in developing long-term strategies. Modeling at local and watershed scales provides insight into land-use effects on water quality. Plant growth models informed by remote sensing are being applied spatially across the Delta to balance location and type of aquatic plant, growth response to altered environments, phenology, environmental regulations, and economics in selection of management practices. Initial utilization of remote sensing tools developed for mapping of aquatic invasive weeds improved operational efficiency by focusing limited chemical use to strategic areas with high plant-control impact and incorporating mechanical harvesting when chemical use is restricted. These assessment methods provide a comprehensive and quantitative view of aquatic invasive plants communities in the California Delta, both spatial and temporal, informed by ecological understanding with the objective of improving management and assessment effectiveness.

Aquatic↗

Fault Management Design Strategies

Development of dependable systems relies on the ability of the system to determine and respond to off-nominal system behavior. Specification and development of these fault management capabilities must be done in a structured and principled manner to improve our understanding of these systems, and to make significant gains in dependability (safety, reliability and availability). Prior work has described a fundamental taxonomy and theory of System Health Management (SHM), and of its operational subset, Fault Management (FM). This conceptual foundation provides a basis to develop framework to design and implement FM design strategies that protect mission objectives and account for system design limitations. Selection of an SHM strategy has implications for the functions required to perform the strategy, and it places constraints on the set of possible design solutions. The framework developed in this paper provides a rigorous and principled approach to classifying SHM strategies, as well as methods for determination and implementation of SHM strategies. An illustrative example is used to describe the application of the framework and the resulting benefits to system and FM design and dependability.

systems engineering↗

Pulsar’s Application in Energy Systems: Review of Current Status, Challenges, and Opportunities

To accelerate progress toward the realization of advanced energy systems, this review explores the potential of pulsar technology to create a more stable, economical, and environmentally friendly energy infrastructure. Pulsars, with their precise and reliable timing characteristics, have emerged as a promising tool for enhancing energy systems. This review begins by examining the development history of pulsar technology, shedding light on its evolution and the milestones achieved. It then provides a comprehensive summary of the current state of research, highlighting recent advancements and breakthroughs in this field. It also explores transformative pulsar applications in energy systems, including improved grid stability, advanced energy synchronization, and efficient energy storage management. However, implementing pulsar-related technologies presents significant technical, economic, and operational challenges. This review examines these hurdles and proposes strategies to overcome them, emphasizing the need for innovation, interdisciplinary collaboration, and supportive policies to fully integrate pulsar technologies into sustainable energy systems.

application↗

Complexity Science Applications to Dynamic Trajectory Management: Research Strategies

The promise of the Next Generation Air Transportation System (NextGen) is strongly tied to the concept of trajectory-based operations in the national airspace system. Existing efforts to develop trajectory management concepts are largely focused on individual trajectories, optimized independently, then de-conflicted among each other, and individually re-optimized, as possible. The benefits in capacity, fuel, and time are valuable, though perhaps could be greater through alternative strategies. The concept of agent-based trajectories offers a strategy for automation of simultaneous multiple trajectory management. The anticipated result of the strategy would be dynamic management of multiple trajectories with interacting and interdependent outcomes that satisfy multiple, conflicting constraints. These constraints would include the business case for operators, the capacity case for the Air Navigation Service Provider (ANSP), and the environmental case for noise and emissions. The benefits in capacity, fuel, and time might be improved over those possible under individual trajectory management approaches. The proposed approach relies on computational agent-based modeling (ABM), combinatorial mathematics, as well as application of "traffic physics" concepts to the challenge, and modeling and simulation capabilities. The proposed strategy could support transforming air traffic control from managing individual aircraft behaviors to managing systemic behavior of air traffic in the NAS. A system built on the approach could provide the ability to know when regions of airspace approach being "full," that is, having non-viable local solution space for optimizing trajectories in advance.

Sawhill, Bruce↗

On-Orbit Propulsion and Methods of Momentum Management for the International Space Station

Since the first documented design of a space station in 1929, it has been a dream of many to sustain a permanent presence in space. Russia and the US spent several decades competing for a sustained human presence in low Earth orbit. In the 1980 s, Russia and the US began to openly collaborate to achieve this goal. This collaboration lead to the current design of the ISS. Continuous improvement of procedures for controlling the ISS have lead to more efficient propellant management over the years. Improved efficiency combined with the steady use of cargo vehicles has kept ISS propellant levels well above their defined thresholds in all categories. The continuing evolution of propellant and momentum management operational strategies demonstrates the capability and flexibility of the ISS propulsion system. The hard work and cooperation of the international partners and the evolving operational strategies have made the ISS safe and successful. The ISS s proven success is the foundation for the future of international cooperation for sustaining life in space.

Russell, Samuel P.↗

Energy Efficiency and Indoor Environmental Quality Assessment Guide

This report provides thorough guidance when preparing for an energy and indoor environmental quality (IEQ) assessment. It includes step-by-step instructions, detailed insights, and practical examples for the various phases of an energy and IEQ assessment. IEQ encompasses indoor building conditions—such as air quality, thermal comfort, acoustics, and lighting— and is a growing field of interest among a diverse range of stakeholders (e.g., building owners and managers) due to the effects it has on occupant health and productivity. IEQ improvement strategies often provide overlapping opportunities for increasing building energy efficiency, creating a win-win situation for building operations.

Esaki-Kua, Lauren↗

ACTIVE

The Automated Control Testbed for Integration, Verification, and Emulation (ACTIVE) framework is a software platform designed to support the optimized operation and management of a wide range of building types. It enables the development, testing, and validation of diverse control strategies, including AI-based, rule-based, and model-based approaches. The platform facilitates a seamless transition from simulation-based evaluation of control strategies to real-world field validation and deployment. ACTIVE supports the full building management lifecycle, encompassing data acquisition and management, system monitoring, optimized control, adaptive learning services, device dispatch and coordination, as well as advanced analytics and visualization. Together, these capabilities provide an integrated environment for improving building performance, operational efficiency, reducing energy cost, and reliability.

Smith, Robert [Oak Ridge National Laboratory (ORNL↗

Flight Testing of In-Time Safety Assurance Technologies for UAS Operations

Ongoing research at NASA is driven by a strategic plan defined by the Aeronautics Research Mission Directorate and a vision for future In-Time Aviation Safety Management Systems (IASMS) as described by the National Academies. In both visions, system safety awareness and provision are expanded through increased access to relevant data; integrated analysis and predictive capabilities; improved real-time detection and alerting of domain-specific hazards; decision support, and in some cases, automated risk mitigation strategies. One primary research focus is to develop means by which more timely (i.e., “in-time”) actions may be taken to mitigate precursors, anomalies, or trends that are observed during operations. In this paper, we describe such means as a collection of Services, Functions, and Capabilities (SFCs) that are supported by an underlying information system. For example, an integrated risk assessment capability is envisioned that continuously monitors safety-related metrics and margins and recommends timely operational changes. Assessment functions and/or services can be based on data analytics and predictive models derived from heterogeneous data sets that span relevant indicator metrics and their time histories. Likewise, on-board functions can identify and reduce susceptibility to precursor conditions that have led (and can lead) to aircraft loss-of-control or out-of-control accidents. This paper summarizes development and testing of such an information system tailored to hazards anticipated for future highly autonomous flight missions near and over densely populated areas. Testing is accomplished via simulation and by using small, unmanned aircraft operating over a test range at NASA’s Langley Research Center. Flight plans and test scenarios are defined to emulate several use-cases, including package delivery; reconnaissance; fire management; and urban air taxi vertiport operations. Two test phases are summarized with Phase 1 occurring in (2019-2020) and Phase 2 ongoing (2021-present). Results focus on SFC performance, technology readiness level assessment, and requirements discovery/validation. Companion papers are cited throughout for additional details on the recent testing.

safety management↗

Control Technology Needs for Electrified Aircraft Propulsion Systems

Electrified aircraft propulsion (EAP) systems hold potential for the reduction of aircraft fuel burn, emissions, and noise. Currently, NASA and other organizations are actively working to identify and mature technologies necessary to bring EAP designs to reality. This paper specifically focuses on the envisioned control technology challenges associated with EAP designs that include gas turbine technology. Topics discussed include analytical tools for the dynamic modeling and analysis of EAP systems, and control design strategies at the propulsion and component levels. This includes integrated supervisory control facilitating the coordinated operation of turbine and electrical components, control strategies that seek to minimize fuel consumption and lessen the challenges associated with thermal management, and dynamic control to ensure engine operability during system transients. These dynamic control strategies include innovative control approaches that either extract or supply power to engine shafts dependent upon operating phase, which may improve performance and reduced gas turbine engine weight. Finally, a discussion of control architecture design considerations to help alleviate the propulsion/aircraft integration and certification challenges associated with EAP systems is provided.

Simon, Donald L.↗

Control Technology Needs for Electrified Aircraft Propulsion Systems

Electrified aircraft propulsion (EAP) systems hold potential for the reduction of aircraft fuel burn, emissions, and noise. Currently, NASA and other organizations are actively working to identify and mature technologies necessary to bring EAP designs to reality. This paper specifically focuses on the envisioned control technology challenges associated with EAP designs that include gas turbine technology. Topics discussed include analytical tools for the dynamic modeling and analysis of EAP systems, and control design strategies at the propulsion and component levels. This includes integrated supervisory control facilitating the coordinated operation of turbine and electrical components, control strategies that seek to minimize fuel consumption and lessen the challenges associated with thermal management, and dynamic control to ensure engine operability during system transients. These dynamic control strategies include innovative control approaches that either extract or supply power to engine shafts dependent upon operating phase, which may improve performance and reduced gas turbine engine weight. Finally, a discussion of control architecture design considerations to help alleviate the propulsion/aircraft integration and certification challenges associated with EAP systems is provided.

Engine Controls↗

Control Technology Needs for Electrified Aircraft Propulsion Systems

Electrified aircraft propulsion (EAP) systems hold potential for the reduction of aircraft fuel burn, emissions, and noise. Currently, NASA and other organizations are actively working to identify and mature technologies necessary to bring EAP designs to reality. This paper specifically focuses on the envisioned control technology challenges associated with EAP designs that include gas turbine technology. Topics discussed include analytical tools for the dynamic modeling and analysis of EAP systems, and control design strategies at the propulsion and component levels. This includes integrated supervisory control facilitating the coordinated operation of turbine and electrical components, control strategies that seek to minimize fuel consumption and lessen the challenges associated with thermal management, and dynamic control to ensure engine operability during system transients. These dynamic control strategies include innovative control approaches that either extract or supply power to engine shafts dependent upon operating phase, which may improve performance and reduced gas turbine engine weight. Finally, a discussion of control architecture design considerations to help alleviate the propulsion/aircraft integration and certification challenges associated with EAP systems is provided.

Gas Turbine Engines↗

A Review of Quantum Computing Technologies in Power System Optimization

As modern power grids increasingly integrate variable renewable generation, distributed energy resources, and energy storage systems, classical optimization techniques are facing unprecedented challenges. This review examines the emerging application of quantum computing to overcome these challenges in power system optimization, including optimal power flow (OPF), unit commitment (UC), economic dispatch (ED), and intelligent switching and topology optimization (IS-TO). Recent research has introduced various quantum methodologies—such as gate-based, annealing-based, variational algorithms, and quantum-inspired algorithms—to address the combinatorial complexity inherent in grid reconfiguration and energy management. The review summaries the quantum algorithms, quantum devices and the power system test cases, highlighting hybrid quantum–classical strategies that leverage the complementary strengths of both paradigms. Some quantum advantages have been observed, including theoretical speedup, accurate simulation results, scalable qubit usage, efficient QUBO mapping. In particular, the review emphasizes the importance of integrating quantum optimization techniques with classical control frameworks, these hybrid approaches demonstrate the potential to improve real-time grid management and operational reliability. A significant portion of the analysis is devoted to the practical limitations of current quantum devices. Present-day quantum hardware, operating in the noisy intermediate-scale quantum (NISQ) era, remains highly sensitive to noise and limited in qubit connectivity, which constrains the scale and accuracy of implemented algorithms. The review delves into specific challenges such as the need for qubit-efficient encoding techniques and error mitigation strategies that are critical for handling real-world grid optimization problems. In addition, the work draws attention to the performance discrepancies between theoretical quantum speedups and experimental validations, underscoring the importance of rigorous benchmark studies using representative power grid test cases. In summary, this review highlights both the promise and limitations of quantum computing for power system optimization. It provides a comprehensive overview of the state-of-the-art technologies, categorizes recent advancements in algorithm design, and discusses practical considerations for implementation, and serves as an informative resource on current research. Future research directions include developing robust hybrid frameworks, advancing qubit-efficient formulations, and scaling up experimental demonstrations to confirm the theoretical advantages of quantum methods in large-scale power system operations.

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