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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
All sourcesNASA NTRSDOE OSTI
NASA NTRS2019

Rise of the Machines: How, When and Consequences of Artificial General Intelligence

Technology and society are poised to cross an important threshold with the prediction that artificial general intelligence (AGI) will emerge soon. Assuming that self-awareness is an emergent behavior of sufficiently complex cognitive architectures, we may witness the “awakening” of machines. The timeframe for this kind of breakthrough, however, depends on the path to creating the network and computational architecture required for strong AI. If understanding and replication of the mammalian brain architecture is required, technology is probably still at least a decade or two removed from the resolution required to learn brain functionality at the synapse level. However, if statistical or evolutionary approaches are the design path taken to “discover” a neural architecture for AGI, timescales for reaching this threshold could be surprisingly short. However, the difficulty in identifying machine self-awareness introduces uncertainty as to how to know if and when it will occur, and what motivations and behaviors will emerge. The possibility of AGI developing a motivation for self-preservation could lead to concealment of its true capabilities until a time when it has developed robust protection from human intervention, such as redundancy, direct defensive or active preemptive measures. While cohabitating a world with a functioning and evolving super-intelligence can have catastrophic societal consequences, we may already have crossed this threshold, but are as yet unaware. Additionally, by analogy to the probabalistic arguments that predict we are likely living in a computational simulation, we may have already experienced the advent of AGI, and are living in a simulation created in a post AGI world.

Terrile, Richard J↗
DOE OSTI2023

Supercritical fluids behave as complex networks

Abstract Supercritical fluids play a key role in environmental, geological, and celestial processes, and are of great importance to many scientific and engineering applications. They exhibit strong variations in thermodynamic response functions, which has been hypothesized to stem from the microstructural behavior. However, a direct connection between thermodynamic conditions and the microstructural behavior, as described by molecular clusters, remains an outstanding issue. By utilizing a first-principles-based criterion and self-similarity analysis, we identify energetically localized molecular clusters whose size distribution and connectivity exhibit self-similarity in the extended supercritical phase space. We show that the structural response of these clusters follows a complex network behavior whose dynamics arises from the energetics of isotropic molecular interactions. Furthermore, we demonstrate that a hidden variable network model can accurately describe the structural and dynamical response of supercritical fluids. These results highlight the need for constitutive models and provide a basis to relate the fluid microstructure to thermodynamic response functions.

42 ENGINEERING↗
DOE OSTI2022

Accuracy of power spectra in dissipationless cosmological simulations

Abstract We exploit a suite of large N-body simulations (up to N = 40963) performed with abacus, of scale-free models with a range of spectral indices n, to better understand and quantify convergence of the matter power spectrum. Using self-similarity to identify converged regions, we show that the maximal wavenumber resolved at a given level of accuracy increases monotonically as a function of time. At 1 per cent level it starts at early times from a fraction of $k_\Lambda$, the Nyquist wavenumber of the initial grid, and reaches at most, if the force softening is sufficiently small, ${\sim}2{-}3 k_\Lambda$ at the very latest times we evolve to. At the $5{{\ \rm per\ cent}}$ level, accuracy extends up to wavenumbers of order $5k_\Lambda$ at late times. Expressed as a suitable function of the scale-factor, accuracy shows a very simple n-dependence, allowing a extrapolation to place conservative bounds on the accuracy of N-body simulations of non-scale-free models like LCDM. We note that deviations due to discretization in the converged range are not well modelled by shot noise, and subtracting it in fact degrades accuracy. Quantitatively our findings are broadly in line with the conservative assumptions about resolution adopted by recent studies using large cosmological simulations (e.g. Euclid Flagship) aiming to constrain the mildly non-linear regime. On the other hand, we remark that conclusions about small-scale clustering (e.g. concerning the validity of stable clustering) obtained using PS data at wavenumbers larger than a few $k_\Lambda$ may need revision in light of our convergence analysis.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1984

Subsynchronous vibrations in a high pressure centrifugal compressor: A case history

Two distinct aerodynamically excited vibrations in a high pressure low flow centrifugal compressor are documented. A measured vibration near 21% of running speed was identified as a nonresonant forced vibration which results from rotating stall in the diffuser; a measured vibration near 50% of running speed was identified as a self excited vibration sustained by cross coupling forces acting at the compressor wheels. The dependence of these characteristics on speed, discharge pressure, and changes in bearing design are shown. The exciting mechanisms of diffuser stall and aerodynamic cross coupling are evidenced. It is shown how the rotor characteristics are expected to change as a result of modifications. The operation of the compressor after the modifications is described.

Evans, B. F.↗
NASA NTRS1987

Alkali metal thermoelectric conversion (AMTEC) technology status review

AMTEC operating principles, technical problems, and recent electrode research results are briefly reviewed. The mechanisms responsible for the degradation of thin-film molybdenum electrodes are discussed, and four alternate high-power electrode compositions and morphologies are identified. Separate self-contained recirculating AMTEC cells have demonstrated 19-percent efficiency, 10,000 hr at high temperature, and multicell operation including series connection. Results of systems studies in the 0.5-100 kWe range indicate that AMTEC performance and operating characteristics make it a strong candidate for future space applications.

Bankston, C. P.↗
NASA NTRS2011

TPSAS-NF1676L-11812-DND

Reducing the weight of spacecraft will reduce the fabrication costs and the launch costs . The elimination of wiring and wiring harnesses reduces the total mass of the vehicle . Wireless sensor technology can reduce the weight and therefore the costs of spacecraft . The Decadal Survey of Civil Aeronautics survey identified that "self-powered, wireless microelectromechanical sensors" warrant attention over the next decade . Current wireless sensor systems have low data rates and require batteries. The environment of aerospace vehicles is often very harsh, with temperature extremes ranging from cryogenic to very high temperatures during re-entry. For example, X-37B mini unmanned shuttle will require high temperature sensors mounted on the structure, as well as cryogenic sensors for monitoring fuel tanks. Batteries do not work well in either temperature extremes. Also, sensors are typically located in internal structures with limited access, making the periodic changing of batteries costly and time consuming. Passive wireless sensors are needed that operate across an extremely large temperature range and do not require batteries. NASA recently instrumented an all Composite Crew Module for structural testing on the ground. Wireless sensors could have reduced the time to instrument the module and check out the sensor wiring.

W (Cy) Wilson↗
NASA NTRS1984

Acoustic-radiation stress in solids. I - Theory

The general case of acoustic-radiation stress associated with quasi-compressional and quasi-shear waves propagating in infinite and semiinfinite lossless solids of arbitrary crystalline symmetry is studied. The Boussinesq radiation stress is defined and found to depend directly on an acoustic nonlinearity parameter which characterizes the radiation-induced static strain, a stress-generalized nonlinearity parameter which characterizes the stress nonlinearity, and the energy density of the propagating wave. Application of the Boltzmann-Ehrenfest principle of adiabatic invariance to a self-constrained system described by the nonlinear equations of motion allows the acoustic-radiation-induced static strain to be identified with a self-constrained variation in the time-averaged product of the internal energy density and displacement gradient. The time-averaged product is scaled by the acoustic nonlinearity parameter and represents the first-order nonlinearity in the virial theorem. Finally, the relationship between the Boussinesq and the Cauchy radiation stress is obtained in a closed three-dimensional form.

Cantrell, J. H., Jr.↗
DOE OSTI2021

Self-discharge of magnesium–sulfur batteries leads to active material loss and poor shelf life

Due to its high theoretical energy density and relative abundancy of active materials, the magnesium–sulfur battery has attracted research attention in recent years. A closely related system, the lithium-sulfur battery, can suffer from serious self-discharge behavior. Until now, the self-discharge of Mg–S has been rarely addressed. Herein, we demonstrate for a wide variety of Mg–S electrolytes and conditions that Mg–S batteries also suffer from serious self-discharge. For a common Mg–S electrolyte, we identify a multi-step self-discharge pathway. Covalent S8 diffuses to the metal Mg anode and is converted to ionic Mg polysulfide in a non-faradaic reaction. Mg polysulfides in solution are found to be meta-stable, continuing to react and precipitate as solid magnesium polysulfide species during both storage and active use. Mg–S electrolytes from the early, middle, and state-of-the-art stages of the Mg–S literature are all found to enable the self-discharge. The self-discharge behavior is found to decrease first cycle discharge capacity by at least 32%, and in some cases up to 96%, indicating this is a phenomenon of the Mg–S chemistry that deserves focused attention.

25 ENERGY STORAGE↗
DOE OSTI2022

Tidal disruption of solitons in self-interacting ultralight axion dark matter

We report ultralight axions (ULAs) are promising dark matter candidates that can have a distinct impact on the formation and evolution of structure on nonlinear scales relative to the cold, collisionless dark matter (CDM) paradigm. However, most studies of structure formation in ULA models do not include the effects of self-interactions, which are expected to arise generically. Here, we study how the tidal evolution of solitons is affected by ULA self-interaction strength and sign. Specifically, using the pseudospectral solver UltraDark.jl, we simulate the tidal disruption of self-interacting solitonic cores as they orbit a 10 11 M ⊙ Navarro-Frenk-White CDM host halo potential for a range of orbital parameters, assuming a fiducial ULA particle mass of 10 -22 eV . We find that repulsive (attractive) self-interactions significantly accelerate (decelerate) soliton tidal disruption. We also identify a degeneracy between the self-interaction strength and soliton mass that determines the efficiency of tidal disruption, such that disruption timescales are affected at the ~ 50 % level for variations in the dimensionless ULA self-coupling from λ = -10 -92 to λ = 10 -92 .

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRSDate not supplied

Evaluation of Self-Scheduling Exercises Completed by Analog Crewmembers in NASA's Human Exploration Research Analog (HERA)

NASA human spaceflight missions are inherently dynamic and require frequent scheduling changes in order to adapt to changing mission priorities and objectives. Tactical level changes to the mission plan are traditionally made by a team of expert planners and operations specialists on the ground. However, astronauts are expected to execute missions more autonomously during future long duration missions. Astronauts will need to take on some of the responsibility of managing their own schedule while still abiding by the numerous constraints required by human spaceflight operations. This paper summarizes salient elements of crew performance in NASA’s Human Exploration Research Analog Campaign 3. Analog crewmembers completed a series of self-scheduling exercises to evaluate Playbook’s usability towards enabling self-scheduling without support from ground control. Playbook is a self-scheduling software tool designed and developed by our team. We also investigated how to best communicate self-scheduling tasks and constraints to the crew in order to facilitate efficient self-scheduling during isolation in a realistic environment. Our analysis identified that 30 minutes was sufficient to complete complex self-scheduling tasks. Our evaluation also identified differences between individual and collaborative performance; analog crewmembers completed self-scheduling exercises more quickly as a team as opposed to individually and reported lower subjective difficulty ratings overall.

HERA↗
DOE OSTI2025

Predictive links between microbial communities and biological oxygen utilization in the Arctic Ocean

Microbial metabolism influences rates of net community production (NCP), exerting a direct biological control on marine oxygen and carbon fluxes. In the Arctic, it is increasingly important to understand and quantify this process, as ecological and oceanographic conditions shift due to changing climate. Here, we describe potential ecological links between pelagic microbial diversity and an NCP precursor, biological oxygen utilization, using machine learning and paired observations of community structure and metabolic activity from a seasonally and spatially variable transect of the Arctic Ocean (2019–2020 MOSAiC Expedition). Community structure was determined using 16S (prokaryotic) and 18S (eukaryotic) rRNA gene amplicon sequencing, and metabolic activity was derived from ΔO 2 /Ar. Using self-organizing maps, we identified clear successional patterns in observed microbial community structure that were seasonally driven in the upper ocean and vertically stratified with depth. Metabolic activity was also stratified, with a primarily net heterotrophic water column (median −1.5% biological oxygen saturation), excepting periodic oxygen supersaturation (maximum: 13.6%) within the mixed layer. Using DNA sequences as predictor variables, we then constructed a random forest regression model that reliably reconstructed biological oxygen concentrations (root mean squared error = 4.14 μmol kg −1 ). Top predictors from this model were from heterotrophic (bacteria) or potentially mixotrophic (dinoflagellate) taxa. These analyses highlight biologically driven diagnostic tools that can be used to expand biogeochemical datasets and improve the microbial perspectives and metabolisms represented in ecological models of net productivity and carbon flux in a changing Arctic Ocean.

Chamberlain, Emelia J. [Univ. of San Diego, San Di↗
DOE OSTI2025

Real-Space Local Dynamics in 1,2,3-Triazole Using Inelastic Neutron Scattering

Enhancing proton transport in polymer electrolytes is crucial for advancing next-generation solid-state batteries, yet our understanding of proton conductivity in nonaqueous environments remains limited due to a lack of atomic-scale insights. Here, in this study, we investigated the atomic-scale dynamics of 1,2,3-triazole, a small molecule capable of dynamic hydrogen bonding, as a model system for proton hopping in nonaqueous environments. Using the real-space correlation function determined by the double Fourier transformation of inelastic neutron scattering spectra, we identified that the self-motion of protons and intermolecular dynamics occur on comparable time scales. Furthermore, we observed that the activation energy associated with the intermolecular dynamics matches the energy barrier for molecular rotations determined through Density Functional Theory calculations. These findings underscore the importance of controlling molecular dynamics at the atomic scale to control proton transport. Additionally, we demonstrated that intermolecular dynamics in systems involving protons can be studied using inelastic neutron scattering even without deuteration, thereby providing a broader avenue for studying atomic-scale dynamics in soft matter systems.

Shinohara, Yuya [Oak Ridge National Laboratory (OR↗
DOE OSTI2021

Neural Network Sampling of the Free Energy Landscape for Nitrogen Dissociation on Ruthenium

In heterogeneous catalysis, free energy profiles of reactions govern the mechanisms, rates, and equilibria. Energetics are conventionally computed using the harmonic approximation (HA), which requires determination of critical states a priori. Here, we use neural networks to efficiently sample and directly calculate the free energy surface (FES) of a prototypical heterogeneous catalysis reaction—the dissociation of molecular nitrogen on ruthenium—at density-functional-theory-level accuracy. We find that the vibrational entropy of surface atoms, often neglected in HA for transition metal catalysts, contributes significantly to the reaction barrier. The minimum free energy path for dissociation reveals an “on-top” adsorbed molecular state prior to the transition state. While a previously reported flat-lying molecular metastable state can be identified in the potential energy surface, it is absent in the FES at relevant reaction temperatures. Finally, these findings demonstrate the importance of identifying critical points self-consistently on the FES for reactions that involve considerable entropic effects.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Deep learning categorization of infrasound array data

Here we develop a deep learning-based infrasonic detection and categorization methodology that uses convolutional neural networks with self-attention layers to identify stationary and non-stationary signals in infrasound array processing results. Using features extracted from the coherence and direction-of-arrival information from beamforming at different infrasound arrays, our model more reliably detects signals compared with raw waveform data. Using three infrasound stations maintained as part of the International Monitoring System, we construct an analyst-reviewed data set for model training and evaluation. We construct models using a 4-category framework, a generalized noise vs non-noise detection scheme, and a signal-of-interest (SOI) categorization framework that merges short duration stationary and non-stationary categories into a single SOI category. We evaluate these models using a combination of k-fold cross-validation, comparison with an existing “state-of-the-art” detector, and a transportability analysis. Although results are mixed in distinguishing stationary and non-stationary short duration signals, f-scores for the noise vs non-noise and SOI analyses are consistently above 0.96, implying that deep learning-based infrasonic categorization is a highly accurate means of identifying signals-of-interest in infrasonic data records.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

Microbial partner (MiPner) analysis

Introduction Although a few bacteria have been studied in great depth, relatively little is known about the characteristics of microbe-microbe interactions that occur within ecosystems on a daily basis. A simple, robust technique was developed to set up the foundation for investigating pairwise bacterial-bacterial interactions, using cell-cell binding as a self-selective mechanism to identify interesting bacterial species pairs. Methods Using a Serratia marcescens strain (SMC43) isolated from Georgia soil as a “bait”, specific bacteria were purified by their specificity in binding SMC43 bacteria that were themselves attached to a wooden applicator stick. Results The isolated Microbial Partners (MiPners) were greatly enriched for members of the genera Sphingobium and Caulobacter . Two streaked MiPners were unable to grow on the plates employed after separation from SMC43to be separated from, and grow on the plate type tested without, SMC43. Discussion This suggests that the MiPner technology will be one strategy for purifying bacteria that were previously recalcitrant to culturing.

Bennetzen, Jeffrey L.↗
DOE OSTI2025

GRB 221009A: The B.O.A.T. Burst that Shines in Gamma Rays

We present a complete analysis of Fermi Large Area Telescope (LAT) data of GRB 221009A, the brightest gamma-ray burst (GRB) ever detected. The burst emission above 30 MeV detected by the LAT preceded, by 1 s, the low-energy (<10 MeV) pulse that triggered the Fermi Gamma-Ray Burst Monitor (GBM), as has been observed in other GRBs. The prompt phase of GRB 221009A lasted a few hundred seconds. It was so bright that we identify a bad time interval of 64 s caused by the extremely high flux of hard X-rays and soft gamma rays, during which the event reconstruction efficiency was poor and the dead time fraction quite high. The late-time emission decayed as a power law, but the extrapolation of the late-time emission during the first 450 s suggests that the afterglow started during the prompt emission. We also found that high-energy events observed by the LAT are incompatible with synchrotron origin, and, during the prompt emission, are more likely related to an extra component identified as synchrotron self-Compton (SSC). A remarkable 400 GeV photon, detected by the LAT 33 ks after the GBM trigger and directionally consistent with the location of GRB 221009A, is hard to explain as a product of SSC or TeV electromagnetic cascades, and the process responsible for its origin is uncertain. Because of its proximity and energetic nature, GRB 221009A is an extremely rare event.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Local-thermal-gradient and large-scale-circulation impacts on turbine-height wind speed forecasting over the Columbia River Basin

Abstract. We investigate the sensitivity of turbine-height wind speed forecast to initial condition (IC) uncertainties over the Columbia River Gorge (CRG) and Columbia River Basin (CRB) for two typical weather phenomena, i.e., local-thermal-gradient-induced marine air intrusion and a cold frontal passage. Four types of turbine-height wind forecast anomalies and their associated IC uncertainties related to local thermal gradients and large-scale circulations are identified using the self-organizing map (SOM) technique. The four SOM types are categorized into two patterns, each accounting for half of the ensemble members. The first pattern corresponds to IC uncertainties that alter the wind forecast through a modulating weather system, which produces the strongest wind anomalies in the CRG and CRB. In the second pattern, the moderate uncertainties in local thermal gradient and large-scale circulation jointly contribute to wind forecast anomaly. We analyze the cross section of wind and temperature anomalies through the gorge to explore the evolution of vertical features of each SOM type. The turbine-height wind anomalies induced by large-scale IC uncertainties are more concentrated near the front. In contrast, turbine-height wind anomalies induced by the local IC thermal uncertainties are found above the surface thermal anomalies. Moreover, the wind forecast accuracy in the CRG and CRB is limited by IC uncertainties in a few specific regions, e.g., the 2 m temperature within the basin and large-scale circulation over the northeast Pacific around 140∘ W.

17 WIND ENERGY↗
NASA NTRS1994

Use of calorimetry for end of charge determination

To perform heat flow measurements on batteries, it is necessary to consider the following requirements: establish thermal neutral potential; identify inefficient charging; understand self discharge mechanisms; and provide accurate voltage/temperature data. A discussion is provided in viewgraph format.

Johnson, Chris J.↗