SEARCH · Engineering Papers
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.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
A partial list of controllers; multiple means of generating forces and moments available; control power requirements; new aircraft design vs existing configuration; critical technology areas; parameter identification; and types of failure or emergency for reconfiguration are considered.
At the request of NASA and under the aegis of the National Research Council, representatives from industry, academic institutions and government have participated in a workshop to consider opportunities for the exploitation of aircraft technology in such fields as aerodynamics, materials, structures, guidance, navigation and control, human factors, propulsion, computers and data processing, and systems integration. Attention is given to the advanced vehicle concepts that have emerged for possible year-2000 implementation, which encompass such diverse aircraft types as supersonic transports, hypersonic airliners, missiles, and interceptors, transatmospheric vehicles, next-generation space shuttles, subsonic transports and attack aircraft, advanced helicopter, tilt-rotor VTOL configurations, and solar- and microwave beam-powered extremely high altitude aircraft.
The next generation of Earth observing satellites and sensor networks will face challenges in supporting robust high rate communications links from the increasingly sophisticated onboard instruments. Emerging applications will need data rates forecast to be in the 100's to 1000's of Mbps. As mission designers seek smaller spacecraft, challenges exist in reducing the size and power requirements while increasing the capacity of the spacecraft's communications technologies. To meet these challenges, this work looks at three areas of selected space communications and data services technologies, specifically in the development of reflectarray antennas, demonstration of space Internet concepts, and measurement of atmospheric propagation effects on Ka-band signal transmitted from LEO.
An engineering discipline denoted as hybrid power management (HPM) has emerged from continuing efforts to increase energy efficiency and reliability of hybrid power systems. HPM is oriented toward integration of diverse electric energy-generating, energy-storing, and energy-consuming devices in optimal configurations for both terrestrial and outer-space applications. The basic concepts of HPM are potentially applicable at power levels ranging from nanowatts to megawatts. Potential applications include terrestrial power-generation, terrestrial transportation, biotechnology, and outer-space power systems. Instances of this discipline at prior stages of development were reported (though not explicitly labeled as HPM) in three prior NASA Tech Briefs articles: "Ultracapacitors Store Energy in a Hybrid Electric Vehicle"(LEW-16876), Vol. 24, No. 4 (April 2000), page 63; "Photovoltaic Power Station With Ultracapacitors for Storage" (LEW-17177), Vol. 27, No. 8 (August 2003), page 38; and "Flasher Powered by Photovoltaic Cells and Ultracapacitors" (LEW-17246), Vol. 24, No. 10 (October 2003), page 37. As the titles of the cited articles indicate, the use of ultracapacitors as energy-storage devices lies at the heart of HPM. An ultracapacitor is an electrochemical energy-storage device, but unlike in a conventional rechargeable electrochemical cell or battery, chemical reactions do not take place during operation. Instead, energy is stored electrostatically at an electrode/electrolyte interface. The capacitance per unit volume of an ultracapacitor is much greater than that of a conventional capacitor because its electrodes have much greater surface area per unit volume and the separation between the electrodes is much smaller. Power-control circuits for ultracapacitors can be simpler than those for batteries, for two reasons: (1) Because of the absence of chemical reactions, charge and discharge currents can be greater than those in batteries, limited only by the electrical resistances of conductors; and (2) whereas the charge level of a battery depends on voltage, temperature, age, and load condition, the charge level of an ultracapacitor, like that of a conventional capacitor, depends only on voltage.
This work investigates two machine learning techniques: Support Vector Machine (SVM) and Autoencoders (AE)with SVM layer for classification of radar trajectories as General Aviation (GA), fixed-wing small Unmanned Aerial System (sUAS), or not-an-aircraft using radar data recorded from sUAS. Onboard identification of intruder aircraft type is useful for planning avoidance maneuvers and is necessary to provide autonomous systems to meet or exceed the avoidance capability of a human pilot. Aircraft classification can identify intruder aircraft that are not part of the team and may be violating a Temporary Flight Restriction. Aircraft classification is needed in monitoring an airspace where multiple aircraft are teaming on a shared task. Scalable Traffic Management for Emergency Response Operations (STEReO) is a NASA project aimed at improving disaster response by enabling large scale aircraft operations through the teaming of manned aircraft with sUAS to maximize emergency response resources. To this end, this work uses trajectories and radar derived features to classify aircraft from a multirotor sUAS. The AE + SVM generated the strongest classification overall accuracy of 93.5% using the first 4 seconds of radar track data for tracks that activated the avoidance system. Subsampling the available track data increased the available training data with the maximum aircraft recall of 0.94 achieved using the SVM with 1 second track data.
World Nuclear Association (WNA) believes that the waste hierarchy is best implemented when a good compromise exists between disposal and reuse/recycling methods of valuable materials and waste generated by the nuclear industry. The rapid normalization of recycling in both domestic and industrial worlds strengthens WNA's position, as new facilities worldwide emerge providing treatment for clearance. As a foundation for reuse and recycling, the International Atomic Energy Agency (IAEA) provided international guidance on clearance (Safety Guide RSG 1.7) [1], defining associated threshold values approved by all member states. Nevertheless, despite this consensus, a lack of alignment of national regulations has occurred as countries have departed for this international guidance, leading to confusion, even between neighborhood countries. As a consequence, this discrepancy between national rules, despite industrial and technical international consensus based on radiological and environmental considerations appeared as a brake, weakening public acceptance as well as nuclear industry credibility. As a matter of fact, what is allowed in one side of a border may be forbidden on the other side. Conversely, an international consensus on clearance would promote: - Sustainability improvements, including preservation of natural and rare resources resulting from optimized recycling and reuse practices; - A broader acceptance of free released materials; - taking advantage of the available technologies worldwide in materials treatment aiming for clearance; - Increased sharing and use of methods, know-how and operators, leading to better efficiency, innovation, improvement as well as technical and financial mastery. (authors)
The Flood Disaster Mitigation Decision Support System (DSS) is a computerized information system that allows regional emergency-operations government officials to make decisions regarding the dispatch of resources in response to flooding. The DSS implements a real-time model of inundation utilizing recently acquired lidar elevation data as well as real-time data from flood gauges, and other instruments within and upstream of an area that is or could become flooded. The DSS information is updated as new data become available. The model generates realtime maps of flooded areas and predicts flood crests at specified locations. The inundation maps are overlaid with information on population densities, property values, hazardous materials, evacuation routes, official contact information, and other information needed for emergency response. The program maintains a database and a Web portal through which real-time data from instrumentation are gathered into the database. Also included in the database is a geographic information system, from which the program obtains the overlay data for areas of interest as needed. The portal makes some portions of the database accessible to the public. Access to other portions of the database is restricted to government officials according to various levels of authorization. The Flood Disaster Mitigation DSS has been integrated into a larger DSS named REACT (Real-time Emergency Action Coordination Tool), which also provides emergency operations managers with data for any type of impact area such as floods, fires, bomb
As humanity gears up for its return to the moon after more than half a century, collaborative efforts between NASA, Artemis Accords Partners, and private industry are underway to establish the necessary infrastructure and technologies for lunar habitation and eventual Mars exploration. However, the traditional ISS resupply and waste management model is impractical and economically infeasible for prolonged missions to the Moon and Mars. Advanced chemical conversion technologies are needed to generate vital consumable products from local planetary resources (ISRU) and recycled gasses and waste within semi-closed loop life-support systems. Low-temperature plasma reactors are emerging power-to-gas technologies with the potential to facilitate various chemical synthesis processes with hardware commonality and redundancy. In plasma-based systems, electrical power is used to ionize a feedstock gas, creating a highly reactive environment that leverages electron excitation chemistry to break stable molecular bonds and form value added products. Unlike thermal chemical processes, plasma reactors operate at non-equilibrium conditions, allowing for lower-temperature operation and instantaneous start-up, making them adaptable to intermittent power availability. Moreover, their scalability permits deployment in both portable astronaut systems and large-scale industrial setups for colonies. One promising application of plasmas is for CO 2 conversion. Carbon dioxide comprises 96% of the Martian atmosphere and is a byproduct of human respiration, which typically must be scrubbed and vented from space habitats. A plasma source integrated with membrane separation technology could generate a stream of oxygen for life support and rocket propellant. CO 2 splitting may also be beneficial as a precursor to manufacture carbon-based products and fuels in situ, like methane, methanol, and polyethylene. Plasma-assisted CO 2 conversion is a simpler case to study without the concern of selectivity and is the first step toward complex chemical synthesis. This work presents preliminary experimental case study from a plasma reactor for CO 2 conversion and casts a vision for the potential of plasma technologies in a sub-architecture for resource production to enable the next generation of human spaceflight activities.
Effective and safe control of an aircraft may be difficult or nearly impossible for a pilot following an unexpected system failure. Without prior training, the pilot must ascertain on the fly those changes in both manual control technique and procedures that will lead to a safe landing of the aircraft. Sophisticated techniques for determining the required control techniques are now available. Likewise, a body of literature on pilot decision making provides formalisms for examining how pilots approach discrete decisions framed as the selection between options. However, other aspects of behavior, such as the task of route planning and guidance, are not as well studied. Not only is the pilot faced with possible performance changes to the aircraft dynamics, but he or she is also tasked to create a plan of actions that will effectively take the aircraft down to a safe landing. In this plan, the many actions that the pilot can perform are closely intertwined with the trajectory of the aircraft, making it difficult to accurately predict the final outcome. Coupled with the vast number of potential actions to be taken, this problem may seem intractable. This is reflected in the lack of a pre-specified procedure capable of giving pilots the ability to find a resolution for this task. This report summarizes a multi-year effort to examine methods to aid pilots in planning an approach and arrival to an airport following an aircraft systems failure. Ultimately, we hypothesize that automatic assistance to pilots can be provided in real-time in the form of improving pilot control of a damaged aircraft and providing pilots with procedural directives suitable for critical flight conditions; such systems may also benefit pilot training and procedure design. To achieve this result, a systematic, comprehensive research program was followed, building on prior research. This approach included a pencil-and-paper study with airline pilots examining methods of representing a flight route in an immediately understandable manner, and in a manner that would allow the pilot to modify an automatically-generated route and/or detect any inappropriate elements in an automatically-generated route. Likewise, a flight simulator study examined different cockpit systems for the relative merits of providing pilots with any of a variety of automated functions for emergency flight planning. The results provide specific guidance for the design of such systems.
Aqueous organic redox flow batteries (AORFBs) have gained popularity in renewable energy storage due to their low cost, environmental friendliness and scalability. The rapid discovery of aqueous soluble organic (ASO) redox-active materials necessitates efficient machine learning surrogates for predicting battery performance. The physics-guided continual learning (PGCL) method proposed in this study can incrementally learn data from new ASO electrolytes while addressing catastrophic forgetting issues in conventional machine learning. Using a AORFB database with a thousand potential materials generated by a 780 $\text{cm}^2$ interdigitated cell model, PGCL incorporates AORFB physics to optimize the continual learning task formation and training strategies to retain previously learned battery material knowledge. Finally, the trained PGCL demonstrates its capability in assessing emerging ASO materials within the established parameter space when evaluated with the dihydroxyphenazine isomers.
Metasurfaces have emerged as powerful tools for controlling spontaneous emission, offering unprecedented control over light-matter interactions at sub-wavelength scales. While metasurfaces are traditionally utilized for shaping coherent electromagnetic waves, they have recently extended their capabilities to control incoherent or spontaneous emission. This examines review how metasurfaces can enhance and precisely control properties of thermal, luminescent, and quantum emission. In thermal emission, metasurfaces enable control over spatial, temporal, and spin coherence, offering new possibilities for applications such as energy harvesting, radiative cooling and heat assisted ranging and detection. For luminescent emission, metasurfaces significantly improve emission rates, quantum efficiency, and directionality, driving innovations in lighting and display technologies. For controlling quantized spontaneous emission, metasurfaces are instrumental in enhancing single-photon sources and enabling novel functionalities in quantum states through photon-pair generation, which is vital for quantum communication, meteorology, and computing. Here, despite these advancements several challenges to increase the operational bandwidths, accelerate and develop simulation strategies, and fabrication complexities persist. Emerging trends are also discussed, such as dynamic metasurfaces and their integration with nanophotonic platforms, which could further expand the capabilities of light-emitting metasurfaces.
Silicon carbide (SiC) fibers are responsible for the ultimate strength and toughness of SiC-fiber reinforced composites in harsh environments. The development of a new generation of continuous SiC fibers continues to advance the mechanical properties of composite materials. Tyranno™ SA4 fiber was recently released as a successor of Tyranno™ SA3 fiber. Laser-driven chemical vapor deposition (LCVD) has been adopted as an alternative fiber processing route to synthesizing high-strength SiC fiber with tailorable small diameters and chemical compositions. Both Tyranno™ SA4 and laser-driven CVD fibers show very high tensile strength, about 4 GPa in the as-fabricated condition. The degradation of thermal stability and strength due to annealing in an inert environment were similar for Tyranno™ SA3 and SA4 fibers because of their similar carbon-rich, crystalline microstructure. Silicon-rich fibers produced by LCVD possessed heterogeneous crystallinity, which was attributed to laser power distribution and showed microstructural instability at 1500 °C and above. Finally, the new SiC fibers demonstrated an increase in as-fabricated strength but faced the same challenges in environmental resistance as the traditional SiC fibers do.
Electric fields can transform materials with respect to their structure and properties, enabling various applications ranging from batteries to spintronics. Recently electrolytic gating, which can generate large electric fields and voltage-driven ion transfer, has been identified as a powerful means to achieve electric-field-controlled phase transformations. The class of transition metal oxides provide many potential candidates that present a strong response under electrolytic gating. However, very few show a reversible structural transformation at room-temperature. Here, we report the realization of a digitally synthesized transition metal oxide that shows a reversible, electric-field-controlled transformation between distinct crystalline phases at room-temperature. In superlattices comprised of alternating one-unit-cell of SrIrO 3 and La 0.2 Sr 0.8 MnO 3 , we find a reversible phase transformation with a 7% lattice change and dramatic modulation in chemical, electronic, magnetic and optical properties, mediated by the reversible transfer of oxygen and hydrogen ions. Strikingly, this phase transformation is absent in the constituent oxides, solid solutions and larger period superlattices. Our findings open up this class of materials for voltage-controlled functionality.
Combinatorial synthesis combined with high throughput electrochemistry enabled discovery of 29 ternary oxide photoanodes, 15 with visible light response for oxygen evolution. Y 3 Fe 5 O 12 and trigonal V 2 CoO 6 emerge as particularly promising candidates due to their photorepsonse at sub-2.4 eV illumination.
The test results of measurements performed on two different sizes of ferroelectric random access memory (FeRAM) suggest the degradation is due to the low radiation tolerance of sense amplifiers and reference voltage generators which are based on commercial complementary metal oxide semiconductor (CMOS) technology. This paper presents total ionizing dose (TID) testing of 64Kb Ramtron FM1608 and 256Kb Ramtron FM1808.
Deep generative models such as diffusion and flow matching are powerful machine learning tools capable of learning and sampling from high-dimensional distributions. They are particularly useful when the training data appears to be concentrated on a submanifold of the data embedding space. For high-energy physics data, consisting of collections of relativistic energy-momentum 4-vectors, this submanifold can enforce extremely strong physically-motivated priors, such as energy and momentum conservation. If these constraints are learned only approximately, rather than exactly, this can inhibit the interpretability and reliability of such generative models. To remedy this deficiency, we introduce generative models which are, by construction, confined at every step of their sampling trajectory to the manifold of massless N-particle Lorentz-invariant phase space in the center-of-momentum frame. In the case of diffusion models, the "pure noise" forward process endpoint corresponds to the uniform distribution on phase space, which provides a clear starting point from which to identify how correlations among the particles emerge during the reverse (de-noising) process. We demonstrate that our models are able to learn both few-particle and many-particle distributions with various singularity structures, paving the way for future interpretability studies using generative models trained on simulated jet data.
Brown dwarf and giant planet atmospheric structure and composition has been studied both by forward models and, increasingly so, by retrieval methods. While indisputably informative, retrieval methods are of greatest value when judged in the context of grid model predictions. Meanwhile retrieval models can test the assumptions inherent in the forward modeling procedure. In order to provide a new, systematic survey of brown dwarf atmospheric structure, emergent spectra, and evolution, we have constructed a new grid of brown dwarf model atmospheres. We ultimately aim for our grid to span substantial ranges of atmospheric metallilcity, C/O ratios, cloud properties, atmospheric mixing, and other parameters. Spectra predicted by our modeling grid can be compared to both observations and retrieval results to aid in the interpretation and planning of future telescopic observations. We thus present Sonora, a new generation of substellar atmosphere models, appropriate for application to studies of L, T, and Y-type brown dwarfs and young extrasolar giant planets. The models describe the expected temperature-pressure profile and emergent spectra of an atmosphere in radiative-convective equilibrium for ranges of effective temperatures and gravities encompassing 200 less than or equal to T(sub eff) less than or equal to 2400 K and 2.5 less than or equal to log g less than or equal to 5.5. In our poster we briefly describe our modeling methodology, enumerate various updates since our group's previous models, and present our initial tranche of models for cloudless, solar metallicity, and solar carbon-to-oxygen ratio, chemical equilibrium atmospheres. These models will be available online and will be updated as opacities and cloud modeling methods continue to improve.
The next-generation silicon photovoltaics will be based on passivating electron- and hole-selective contacts with both very low interface recombination and contact resistivities. While the emerging mainstream TOPCon technology has developed excellent electron-selective poly-Si/tunneling SiOx contacts, hole-selective contacts, especially on textured surfaces, have remained a significant challenge. This contribution introduces novel high-performance hole selective poly-Si contacts on pyramid-textured Si, enabled by electrochemically produced hole transport nanopinholes in a 10 nm oxynitride passivating dielectric stack capped by p+ poly-Si. The highly passivating oxynitride layer is produced via atomic intermixing of O and N atoms in the initial SiOx/SiNy layer stack upon thermal annealing. Carrier transport is governed by nanopinhole density and size are tuned by Ag nanoparticle electrodeposition and surface attachment chemistries. This results in passivating hole contact resistivities in the m..omega..-cm2 range, while preserving interface recombination current prefactor around 5 fA/cm2.