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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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By employing 3,5-bis(trifluoromethyl) pyrazole (TFMP) as an electrolyte additive in both aqueous and non-aqueous mediums, a versatile interphase strategy is achieved. This facilitates stable Zn anodes with improved efficiency and longer cycling life.
The effects of rotating cavitation and cavitation surges on the Fastrac Engine Turbopump are described in a viewgraph presentation format. The bent inducer blade dilemma and observations of unsteady data and oscillation components are discussed. The pump-feed system stability modeling assessment is outlined. Recommendations are made urging further investigation.
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This handbook provides engineers and safety personnel with guidelines for the safe design or selection and use of primary batteries in spaceflight programs. Types of primary batteries described are silver oxide zinc alkaline, carbon-zinc, zinc-air alkaline, manganese dioxide-zionc alkaline, mercuric oxide-zinc alkaline, and lithium anode cells. Along with typical applications, the discussions of the individual battery types include electrochemistry, construction, capacities and configurations, and appropriate safety measures. A chapter on general battery safety covers hazard sources and controls applicable to all battery types. Guidelines are given for qualification and acceptance testing that should precede space applications. Permissible failure levels for NASA applications are discussed.
Assisted FAST facility personal with various upgrades and system installation activities during the summer 2026 FAST-IOTA shutdown as a part of the FORGE internship program. Herein is a summary of my involvement in and the results of that experience.
This report considers a novel process to acquire performance data for supersonic mixed compression inlets that is faster, and therefore less costly, than the previous one. In the previous process, measurements were recorded in discrete increments. The backpressuring actuator was advanced, there was a pause to allow for airflow fluctuations to diminish, and then the measurements were recorded. While this process was methodical, reliable and accurate, it consumed significant wind-on time. In general, high-speed wind tunnels are expensive to operate considering maintenance, energy and human resource requirements. Furthermore, many facilities, such as blowdown wind tunnels, are limited in the duration that they can maintain the desired test condition. Consequently, a quick method to collect the measurements is desired. A favored approach has the actuator moving in a continuous fashion with measurements recorded as the actuator continuously progresses through the increment points. This approach, identified as the dynamic inlet characteristic data acquisition procedure, uses in situ dynamic high-speed pressure sensors to measure pressure signals. While faster, continuous movement adds dynamic effects to the data. To better understand these dynamic effects and other potential influences, a study was undertaken to compare wind tunnel measurements taken at discrete actuator position points with data gathered during continuous actuator movement. Specially, plots of inlet pressure recovery versus mass capture ratio, or total pressure characteristic curves, were examined. The data were measured during experiments in the NASA Glenn Research Center Abe Silverstein 10- by 10-Foot Supersonic Wind Tunnel (SWT) with an inlet propulsion test article. In this report, the wind tunnel experiment and the study objectives are described. The processes to reduce the data and for analysis are explained. A discussion of the results along with features noted in the data is given. Finally, conclusions from this study that may be used to guide future wind tunnel experiment planning are presented.
This report considers a novel process to acquire performance data for supersonic mixed compression inlets that is faster, and therefore less costly, than the previous one. In the previous process, measurements were recorded in discrete increments. The backpressuring actuator was advanced, there was a pause to allow for airflow fluctuations to diminish, and then the measurements were recorded. While this process was methodical, reliable and accurate, it consumed significant wind-on time. In general, high-speed wind tunnels are expensive to operate considering maintenance, energy and human resource requirements. Furthermore, many facilities, such as blowdown wind tunnels, are limited in the duration that they can maintain the desired test condition. Consequently, a quick method to collect the measurements is desired. A favored approach has the actuator moving in a continuous fashion with measurements recorded as the actuator continuously progresses through the increment points. This approach, identified as the dynamic inlet characteristic data acquisition procedure, uses in situ dynamic high-speed pressure sensors to measure pressure signals. While faster, continuous movement adds dynamic effects to the data. To better understand these dynamic effects and other potential influences, a study was undertaken to compare wind tunnel measurements taken at discrete actuator position points with data gathered during continuous actuator movement. Specially, plots of inlet pressure recovery versus mass capture ratio, or total pressure characteristic curves, were examined. The data were measured during experiments in the NASA Glenn Research Center Abe Silverstein 10- by 10-Foot Supersonic Wind Tunnel (SWT) with an inlet propulsion test article. In this report, the wind tunnel experiment and the study objectives are described. The processes to reduce the data and for analysis are explained. A discussion of the results along with features noted in the data is given. Finally, conclusions from this study that may be used to guide future wind tunnel experiment planning are presented.
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The landscape of complex engineered systems is rapidly evolving, from smart manufacturing facilities to next-generation transportation vehicles. As these systems become increasingly sophisticated and interconnected, the need for advanced health management systems grows ever more critical. These systems must go beyond simple monitoring, actively predicting potential failures before they occur. This paradigm shift from fixed maintenance schedules to condition-based predictions is key to optimizing system performance, enhancing safety, and paving the way for autonomous decision-making across various industries. Whether in industrial processes, energy systems, or advanced transportation, the ability to anticipate and prevent failures is becoming a cornerstone of operational excellence. To accurately predict the future health of any complex system, knowledge of its current health state and future operational conditions is essential. Recent advancements in data-driven algorithms have generated growing interest in artificial intelligence for industrial applications. However, the limitations of pure data-driven methods, particularly in industries where data acquisition is costly and limited, have become apparent. This has led to a focus on blending physics with data-driven algorithms, mitigating the drawbacks of both approaches while emphasizing their respective advantages. This research proposes a novel framework for integrating physics-based performance models with deep learning algorithms for the prognostics of complex safety-critical systems. In this approach, physics-based models serve as a blueprint, capturing fundamental system behaviors, while deep learning algorithms, leveraging real-world sensor data, fill in gaps and identify subtle patterns indicative of potential problems. This hybrid methodology, utilizing techniques such as Physics-Informed Neural Networks (PINNs), offers a powerful solution for predicting system health. By fusing domain knowledge with data-driven insights, this approach promises more accurate, adaptable, and reliable models for health prediction. The resulting framework is versatile, applicable across various sectors including aerospace, manufacturing, and energy systems, ultimately contributing to safer, more efficient operations in our increasingly complex technological landscape.
The MARVEL reactor project has served to introduce a new generation of engineers to the processes required to transform a reactor design from simply an idea on paper into what will be an approved, constructed, and operational nuclear power system. Much as there have been advances in materials, analysis, and evaluation methodologies over the 50 years since the last reactor was built at INL, so too has the technology for managing the engineering process itself advanced. Digital Engineering tools and methods provide improved coordination between previously siloed engineering disciplines, reduced burdens of non-value-added data transcription processes and bring forward insights and improvements that might otherwise fall later in the design stage, where changes are much more costly. While the tools and techniques to support the full digital engineering vision are not yet complete, the MARVEL design processes provide valuable demonstrations and validations of key aspects and illuminate further areas for implementation by subsequent projects.
This presentation is designed to provide a high-level overview of the Microgravity Science Glovebox (MSG) and the Life Sciences Glovebox (LSG) facilities onboard the International Space Station. In addition, it provides metrics and lessons-learned information intended for the Commercial Low-Earth Orbit Development Program (CLDP) Partners.
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Supercapacitors are widely recognized as a favorable option for energy storage due to their higher power density compared to batteries, despite their lower energy density.
A gaseous fuel engine system includes a hydrogen fuel supply, an engine housing having an intake port extending to a cylinder, and an intake runner. The intake runner includes a valve mount attached to a conduit and having a valve mounting face, and a gaseous fuel admission valve is mounted upon the valve mounting face. A hydrogen fuel passage extends from the valve mount through the conduit and is oriented angularly to at least one of a clamping face of the intake runner or the valve mounting face. Related apparatus and methodology is also disclosed.
Engineering development of high capacity nonaqueous secondary battery
The objective of the NERVA engine program is the development of a nuclear rocket engine for use in space missions. The letters N E R V A mean Nuclear Engine for Rocket Vehicle Application. NERVA is a long-range program that had its beginning in about 1955 when the Los Alamos Scientific Laboratory began preliminary studies on the feasibility of thermal reactors for rocket application. At about the same time, the Livermore Laboratory began parallel studies, but this dual effort was discontinued about a year later. In 1961 an industrial contractor team, the Aerojet-General Corporation and the Westinghouse Electric Corporation, was selected to carry out the development of the NERVA engine, and their activity began in mid-1961. Aerojet was made the prime contractor with responsibility for the complete engine development program, and Westinghouse was made a principal subcontractor with responsibility for the development of the reactor. A government field office, the Cleveland Extension of the Space Nuclear Propulsion Office, was set up to manage this development program. This office is located in Cleveland because of the availability of technical backup at the Lewis Research Center.