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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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Research on force balance instrumentation to measure the skin friction of hypersonic vehicles at extreme temperatures, high altitudes and in a vibration field is discussed. A rough overall summary and operating instructions for the equipment are presented.
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Self-healing offers promise for addressing structural failures, increasing lifespan, and improving durability in polymeric materials. Implementing self-healing in thermoset polymers faces significant manufacturing challenges, especially due to the elevated temperature requirements of thermoset processing. To introduce self-healing into structural thermosets, the self-healing system must be thermally stable and compatible with the thermoset chemistry. This article demonstrates a self-healing microcapsule-based system stable to frontal polymerization (FP), a rapid and energy-efficient manufacturing process with a self-propagating exothermic reaction (≈200 °C). A thermally latent Grubbs-type complex bearing two N-heterocyclic carbene ligands addresses limitations in conventional G2-based self-healing approaches. Under FP's elevated temperatures, the catalyst remains dormant until activated by a Cu(I) co-reagent, ensuring efficient polymerization of the dicyclopentadiene (DCPD) upon damage to the polyDCPD matrix. The two-part microcapsule system consists of one capsule containing the thermally latent Grubbs-type catalyst dissolved in the solvent, and another capsule containing a Cu(I) coagent blended with liquid DCPD monomer. Using the same chemistry for both matrix fabrication and healing results in strong interfaces as demonstrated by lap-shear tests. In an optimized system, the self-healing system restores the mechanical properties of the tough polyDCPD thermoset. Self-healing efficiencies greater than 90% via tapered double cantilever beam tests are observed.
This study examines boundary layer turbulence derived from high temporal resolution meteorological measurements from 40 research flights over the western North Atlantic Ocean during the 2020 deployments of ACTIVATE. Frequency distributions of various turbulent quantities reveal stronger turbulence during the winter deployment than in summer and for cloud‐topped than in cloud‐free boundary layers during the summer deployment. Maximum turbulence kinetic energy (TKE) is most often within cloud from observations in winter and summer, whereas it is mostly below cloud in both seasons by a global model turbulence parameterization. Further, bivariate frequency distributions are consistent with the bivariate Gaussian probability distribution functions assumed for the closure of higher‐order turbulence/shallow convection parameterizations used by some global models. Turbulence simulated by the Community Atmosphere Model version 6 and the Energy Exascale Earth System Model Atmosphere Model version 2 using such parameterizations is not as strong as observed, with more TKE going into vertical wind perturbations rather than into zonal wind perturbations as observed, suggesting that the treatment of turbulence in Earth system models still needs to be further improved.
High-temperature molten chloride salts are a desirable heat transfer and energy storage media. The NaCl-KCl-MgCl 2 is of particular interest because of its low melting point and relatively inexpensive constituents. Moisture and hydroxides must be removed from the salt to control corrosion at high temperatures. Previous studies have developed and demonstrated various techniques for bench-scale salt purifications. This paper details the system, process, and insight gained in the purification of a 200 kg scale batch of NaCl-KCl-MgCl 2 salt at Oak Ridge National Laboratory.
A model is developed to assist in the planning, specification, development, and verification of space information systems involving distributed rule-based systems. The model is based on an analysis of possible uses of rule-based systems in control centers. This analysis is summarized as a data-flow model for a hypothetical intelligent control center. From this data-flow model, the logical model of cooperating rule-based systems is extracted. This model consists of four layers of increasing capability: (1) communicating agents, (2) belief-sharing knowledge sources, (3) goal-sharing interest areas, and (4) task-sharing job roles.
This paper evaluates the use of Markov chain process in probabilistic life cycle cost analysis and suggests further uses of the process as a design aid tool. A methodology is developed for estimating operations and support cost and expected life for reusable space transportation systems. Application of the methodology is demonstrated for the case of a hypothetical space transportation vehicle. A sensitivity analysis is carried out to explore the effects of uncertainty in key model inputs.
We describe the design of a high-throughput pushbroom imaging spectrometer and telescope system that is capable of Landsat swath and resolution while providing better than 10 nm per pixel spectral resolution. The design is based on a 3200 x 480 element x 18 μm pixel size focal plane array, two of which are utilized to cover the full swath. At an optical speed of F/1.8, the system is the fastest proposed to date to our knowledge. The utilization of only two spectrometer modules fed from the same telescope reduces system complexity while providing a solution within achievable detector technology. Predictions of complete system response are shown. Also, it is shown that detailed ghost analysis is a requirement for this type of spectrometer and forms an essential part of a complete design.
The OSS on the Origins Space Telescope is designed to decode the cosmic history of nucleosynthesis, star formation, and supermassive black hole growth with wide-area spatial-spectral 3-D surveys across the full 25 to 590 micron band. Six wideband grating modules combine to cover the full band at R=300, each couples a long slit with 60–190 beams on the sky. OSS will have a total of 120,000 background-limited detector pixels in the six 2-D arrays which provide spatial and spectral coverage. The suite of grating modules can be used for pointed observations of targets of interest, and are particularly powerful for 3-D spectral spectral surveys. To chart the transition from interstellar material, particularly water, to planetary systems, two high-spectral-resolution modes are included. The first incorporates a Fourier-transform spectrometer (FTS) in front of the gratings providing resolving power of 25,000 (δv = 12 km/s) at 179µm to resolve water emission in protoplanetary disk spectra. The second boosts the FTS capability with an additional etalon (Fabry-Perot interferometer) to provide 2 km/s resolution in this line to enable detailed structural studies of disks in the various water and HD lines. Optical, thermal, and mechanical designs are presented, and the system approach to the detector readout enabling the large formats is described.
Graph algorithms enable myriad large-scale applications including cybersecurity, social network analysis, resource allocation, and routing. The scalability of current graph algorithm implementations on conventional computing architectures are hampered by the demise of Moore’s law. We present a theoretical framework for designing and assessing the performance of graph algorithms executing in networks of spiking artificial neurons. Although spiking neural networks (SNNs) are capable of general-purpose computation, few algorithmic results with rigorous asymptotic performance analysis are known. SNNs are exceptionally well-motivated practically, as neuromorphic computing systems with 100 million spiking neurons are available, and systems with a billion neurons are anticipated in the next few years. Beyond massive parallelism and scalability, neuromorphic computing systems offer energy consumption orders of magnitude lower than conventional high-performance computing systems. We employ our framework to design and analyze new spiking algorithms for shortest path and dynamic programming problems. Our neuromorphic algorithms are message-passing algorithms relying critically on data movement for computation. For fair and rigorous comparison with conventional algorithms and architectures, which is challenging but paramount, we develop new models of data-movement in conventional computing architectures. This allows us to prove polynomial-factor advantages, even when we assume a SNN consisting of a simple grid-like network of neurons. To the best of our knowledge, this is one of the first examples of a rigorous asymptotic computational advantage for neuromorphic computing.
The increased levels of carbon dioxide (CO 2 ) emissions due to the combustion of fossil fuels and the consequential impact on global climate change have made CO 2 capture, storage, and utilization a significant area of focus for current research. In most electrochemical CO 2 applications, water is used as a proton donor due to its high availability and mobility and use as a polar solvent. Additionally, supercritical CO 2 is a promising avenue for electrochemical applications due to its unique chemical and physical properties. Consequently, understanding the interactions between water and supercritical CO 2 is of great importance for future electrochemical applications. Molecular dynamics (MD) simulation is a powerful tool that enables atomistic-resolution dynamics of molecular systems, which can complement and guide future experimental investigations. This study employed atomistic MD to study the cosolubilities, codiffusivities, and structure of supercritical CO 2 and water systems, with a polarizable water model (SWM4-NDP) and a nonpolarizable CO 2 model (TraPPE). Additionally, ab initio MD simulations were used to better understand how atomistic polarizable/nonpolarizable models compare to explicit modeling of electron densities. The polarizable water model exhibited substantial improvement in water-associated properties. In conclusion, we anticipate the development of a compatible polarizable CO 2 model to yield similar improvement, providing a pathway for realizing novel high-pressure electrochemical systems.
Recent developments in artificial intelligence (AI) and machine learning (ML), implemented through self-driving laboratories (SDLs), are rapidly creating unprecedented opportunities for the accelerated discovery and optimization of materials. This paper provides a joint analysis of SDLs from both academic and industry perspectives, highlighting the importance of integrating human intelligence in these systems. It discusses the necessity of careful planning in SDL design across physical, data, and workflow dimensions, including instrumental setup, experimental workflow, data management, and human–SDL interaction. The significance of integrating human input within SDLs, especially as the focus shifts from individual tools and tasks to the creation and management of complex workflows, is emphasized. The paper stresses on the crucial role of reward function design in developing forward-looking workflows and examines the interplay between hardware evolution, ML application across chemical processes, and the influence of reward systems in research. Ultimately, the article advocates for a future where SDLs blend human intuition in hypothesis formulation with AI's precision, speed, and data-handling capabilities.
Pyrite structure transition-metal disulfides exhibit diverse ground states vs d-band filling, spanning diamagnetic semiconducting, ferromagnetic metallic, antiferromagnetic Mott insulating, and superconducting in FeS 2 , CoS 2 , NiS 2 , and CuS 2 . NiS is particularly interesting and poorly understood as its Mott insulating behavior is accompanied by complex antiferromagnetic ordering below ~38 K and perplexing weak ferromagnetism below ~30 K. Temperature-, pressure-, and composition-dependent insulator-metal transitions also occur, particularly in bandwidth-controlled NiS 2–x Se x , hole-doped Ni 1–x Co x S 2 , etc. Here, we use high-quality chemical-vapor-transport-grown NiS 2 single crystals characterized by x-ray diffraction, energy-dispersive x-ray spectroscopy, magnetometry, and extensive transport and magnetotransport measurements, to generate new insight into this system. In particular, resistivity, magnetoresistance, and Hall effect analyses vs temperature, thickness, and surface preparation, provide unequivocal evidence of surface conduction, where the more conductive surface shunts essentially all current at low temperatures. The surface transport changes from two dimensional and insulating to three dimensional and metallic as the surface preparation is varied (also displaying intriguing sensitivity to magnetic ordering), significantly clarifying literature ambiguities with respect to the electronic ground state. These results have immediate implications. First, the temperature-, pressure-, and composition-dependent insulator-metal transitions deduced in the extensive prior work on NiS 2-x Se x , Ni 1–x Co x S 2 , etc., must clearly be reexamined in light of rife metallic surface conduction, not previously taken into account. Second, NiS 2 now joins FeS 2 and CoS 2 as systems in which bulk and surface electronic behaviors are strikingly different, suggesting that metallic surface states could be a universal feature of pyrite structure transition-metal disulfides.
Conformation-dependent dynamics play an important role in organic chemistry syntheses such as electrocyclic reactions, as well as in biological processes such as protein folding. However, current time-resolved experimental methods struggle to distinguish conformers from each other, and conformational isomerism is usually analyzed through reactant and product distributions. Using a combination of mega–electron volt ultrafast electron diffraction and quantum wave packet simulations, Champenois et al. directly followed the photochemical electrocyclic ring opening of the molecule α-phellandrene with femtosecond time resolution and confirmed that the transformation of a specific molecular conformer follows the famous Woodward-Hoffmann rules. The proposed method is potentially a powerful tool to follow conformer specificity in various organic and biological systems in real time.
The Ames-Dryden Flight Research Facility (DFRF) serves as the site for high-risk flight research on many one-of-a-kind test vehicles like the X-29A advanced technology demonstrator, F-16 advanced fighter technology integration (AFTI), AFTI F-111 mission adaptive wing, and F-18 high-alpha research vehicle (HARV). Ames-Dryden is on a section of the historic Muroc Range. The facility is oriented toward the testing of high-performance aircraft, as shown by its part in the development of the X-series aircraft. Given the cost of research flight tests and the complexity of today's systems-driven aircraft, an integrated set of ground support experimental facilities is a necessity. In support of the research flight test of highly advanced test beds, the DFRF is developing a network of facilities to expedite the acquisition and distribution of flight research data to the researcher. The network consists of an array of experimental ground-based facilities and systems as nodes and the necessary telecommunications paths to pass research data and information between these facilities. This paper presents the status of the current network, an overview of current developments, and a prospectus on future major enhancements.
The Ames-Dryden Flight Research Facility (DFRF) serves as the site for the conduct of high-risk flight research on many one-of-a-kind test vehicles like the X-29A advanced technology demonstrator, F-16 advanced fighter technology integration (AFTI), AFTI F-111 mission adaptive wing, and F-18 high-alpha research vehicle (HARV). Ames-Dryden is on a section of the historic Muroc Range. The facility is oriented toward the testing of high-performance aircraft, as shown by its part in the development of the X-series aircraft. Given the cost of research flight test and the complexity of today's systems-driven aircraft, an integrated set of ground support experimental facilities is a necessity. In support of the research flight test of highly advanced test beds, the DFRF is developing a network of facilities to expedite the acquisition and distribution of flight research data to the researcher. This network consists of an array of experimental ground-based facilities and systems as nodes and the necessary telecommunications paths to pass research data and information between these facilities. This paper presents a status of the current network, an overview of current developments, and a prospectus on future major enhancements.
We recently determined that a short exposure to artificial gravity (AG) improved the orthostatic tolerance limit (OTL) of cardiovascularly deconditioned subjects. We now seek to determine the mechanisms of that improvement in these hypovolemic men and women. Methods. We determined the orthostatic tolerance limit (OTL) of 9 men and 8 women following a 90 min exposure to AG compared to 90 min of head down bed rest (HDBR). In both cases (21 days apart), subjects were made hypovolemic (low salt diet plus 20 mg intravenous furosemide). Orthostatic tolerance was determined from a combination of head up tilt and increasing lower body negative pressure until presyncope. Mean values and correlations with OTL were determined for heart rate, blood pressure, stroke volume, cardiac output and peripheral resistance (Finometer), cerebral artery blood velocity (DWL), partial pressure of carbon dioxide (Novametrics) and body segmental impedance (UFI THRIM) were measured during supine baseline, during OTL to presyncope and during supine recovery Results. Orthostatic tolerance of these hypovolemic subjects was significantly greater on the day of AG exposure than on the HDBR day. Regression of OTL on these variables identified significant relationships on the HDBR day that were not evident on the AG day: resting TPR correlated positively while resting cerebral flow correlated negatively with OTL. On both days, women's resting stroke volume correlated positively with orthostatic tolerance. Higher group mean values of stroke volume and cerebral artery flow and lower values of blood pressure, peripheral vascular and cerebrovascular resistance both at control and during OTL testing were observed on the AG day. Even though regression of OTL on resting stroke volume was significant only in women, presyncopal stroke volume reached the same level on each day of study for both men and women while the OTL test lasted 30% longer in men and 22% longer in women. Cerebral artery flow appeared to follow stroke volume and absolute values of cerebral flow did not correlate with the development of presyncope. Women responded to AG exposure with elevated cerebral flow at resting control and throughout the OTL test, implying a loss of autoregulation in deconditioned (hypovolemic) women following AG exposure. Conclusions. Before countermeasures to space flight cardiovascular deconditioning are established, gender differences in cardiovascular responses to orthostatic stress, in general, and to orthostatic stress following exposure to artificial gravity, in particular, need to be determined. Since, in both men and women, a single, acute bout of AG exposure improved orthostatic tolerance, the feasibility of short exposures to AG during longer spaceflights or prior to entry into a gravity (Earth or Mars) environment, should be explored. Given the known beneficial effects of AG on other organ systems, the present study indicates that the positive effects of AG on cardiac stroke volume make AG a likely candidate for maintaining cardiovascular conditioning.
Recent work was reviewed in the field of remote sensing relative to soil moisture. The target parameters were recognized that are necessary if optimum data retrieval is to be realized, and proper sensor instrumentation was recommended to achieve this goal.