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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 469 records · Page 26
All sourcesNASA NTRSDOE OSTI
NASA NTRS1993

Pigs in cyberspace

Exploration and colonization of the universe awaits, but Earth-adapted biological humans are ill-equipped to respond to the challenge. Machines have gone farther and seen more, limited though they presently are by insect-like behavior inflexibility. As they become smarter over the coming decades, space will be theirs. Organizations of robots of ever increasing intelligence and sensory and motor ability will expand and transform what they occupy, working with matter, space and time. As they grow, a smaller and smaller fraction of their territory will be undeveloped frontier. Competitive success will depend more and more on using already available matter and space in ever more refined and useful forms. The process, analogous to the miniaturization that makes today's computers a trillion times more powerful than the mechanical calculators of the past, will gradually transform all activity from grossly physical homesteading of raw nature, to minimum-energy quantum transactions of computation. The final frontier will be urbanized, ultimately into an arena where every bit of activity is a meaningful computation: the inhabited portion of the universe will be transformed into a cyberspace. Because it will use resources more efficiently, a mature cyberspace of the distant future will be effectively much bigger than the present physical universe. While only an infinitesimal fraction of existing matter and space is doing interesting work, in a well developed cyberspace every bit will be part of a relevant computation or storing a useful datum. Over time, more compact and faster ways of using space and matter will be invented, and used to restructure the cyberspace, effectively increasing the amount of computational spacetime per unit of physical spacetime. Computational speed-ups will affect the subjective experience of entities in the cyberspace in a paradoxical way. At first glimpse, there is no subjective effect, because everything, inside and outside the individual, speeds up equally. But, more subtly, speed-up produces an expansion of the cyber universe, because, as thought accelerates, more subjective time passes during the fixed (probably lightspeed) physical transit time of a message between a given pair of locations - so those fixed locations seem to grow farther apart. Also, as information storage is made continually more efficient through both denser utilization of matter and more efficient encodings, there will be increasingly more cyber-stuff between any two points. The effect may somewhat resemble the continuous-creation process in the old steady-state theory of the physical universe of Hoyle, Bondi and Gold, where hydrogen atoms appear just fast enough throughout the expanding cosmos to maintain a constant density.

Moravec, Hans↗
NASA NTRS1999

Climatic Implications of the Observed Temperature Dependence of the Liquid Water Path of Low Clouds

The uncertainty in the global climate sensitivity to an equilibrium doubling of carbon dioxide is often stated to be 1.5-4.5 K, largely due to uncertainties in cloud feedbacks. The lower end of this range is based on the assumption or prediction in some GCMs that cloud liquid water behaves adiabatically, thus implying that cloud optical thickness will increase in a warming climate if the physical thickness of clouds is invariant. Satellite observations of low-level cloud optical thickness and liquid water path have challenged this assumption, however, at low and middle latitudes. We attempt to explain the satellite results using four years of surface remote sensing data from the Atmospheric Radiation Measurements (ARM) Cloud And Radiation Testbed (CART) site in the Southern Great Plains. We find that low cloud liquid water path is insensitive to temperature in winter but strongly decreases with temperature in summer. The latter occurs because surface relative humidity decreases with warming, causing cloud base to rise and clouds to geometrically thin. Meanwhile, inferred liquid water contents hardly vary with temperature, suggesting entrainment depletion. Physically, the temperature dependence appears to represent a transition from higher probabilities of stratified boundary layers at cold temperatures to a higher incidence of convective boundary layers at warm temperatures. The combination of our results and the earlier satellite findings imply that the minimum climate sensitivity should be revised upward from 1.5 K.

DelGenio, Anthony↗
NASA NTRS1999

Metrics for Labeled Markov Systems

Partial Labeled Markov Chains are simultaneously generalizations of process algebra and of traditional Markov chains. They provide a foundation for interacting discrete probabilistic systems, the interaction being synchronization on labels as in process algebra. Existing notions of process equivalence are too sensitive to the exact probabilities of various transitions. This paper addresses contextual reasoning principles for reasoning about more robust notions of "approximate" equivalence between concurrent interacting probabilistic systems. The present results indicate that:We develop a family of metrics between partial labeled Markov chains to formalize the notion of distance between processes. We show that processes at distance zero are bisimilar. We describe a decision procedure to compute the distance between two processes. We show that reasoning about approximate equivalence can be done compositionally by showing that process combinators do not increase distance. We introduce an asymptotic metric to capture asymptotic properties of Markov chains; and show that parallel composition does not increase asymptotic distance.

Desharnais, Josee↗
DOE OSTI2021

On the Stochastic Stability of Deep Markov Models

Deep Markov models (DMM) are generative models which are scalable and expressive generalization of Markov models for representation, learning, and inference problems. DMMs using deep neural networks to parametrize the transition of Markov probability distributions have recently been shown to provide more expressiveness in modeling sequential data and dynamical system responses. However, the fundamental stochastic stability guarantees of such models have not been thoroughly investigated. In this paper, we present a rigorous analytical method to prove the necessary and sufficient conditions of DMM's stochastic stability. This task is achieved by spectral analysis of the efficiently computed Jacobians of probabilistic maps modeled by deep neural networks. We make theoretical connections between the eigenvalues of neural network's weights and the different activation function types used on the stability and overall dynamic behavior of DMMs with Gaussian distributions. We empirically substantiate our theoretical results on stochastic stability and eigenvalue spectra via several numerical experiments. Formal stability guarantees of DMMs can substantially improve their robustness and trustworthiness, necessary for reliable use in safety-critical real-world applications.

Drgona, Jan↗
NASA NTRS1971

Pyrotechnic hazards classification and evaluation program. Phase 2, segment 3: Test plan for determining hazards associated with pyrotechnic manufacturing processes

A comprehensive test plan for determining the hazards associated with pyrotechnic manufacturing processes is presented. The rationale for each test is based on a systematic analysis of historical accounts of accidents and a detailed study of the characteristics of each manufacturing process. The most hazardous manufacturing operations have been determined to be pressing, mixing, reaming, and filling. The hazard potential of a given situation is evaluated in terms of the probabilities of initiation, communication, and transition to detonation (ICT). The characteristics which affect the ICT probabilities include the ignition mechanisms which are present either in normal or abnormal operation, the condition and properties of the pyrotechnic material, and the configuration of the processing equipment. Analytic expressions are derived which describe the physical conditions of the system, thus permitting a variety of processes to be evaluated in terms of a small number of experiments.

Source record↗
NASA NTRS2017

Characterizing K2 Candidate Planetary Systems Orbiting Low-Mass Stars. II. Planetary Systems Observed During Campaigns 1-7

We recently used near-infrared spectroscopy to improve the characterization of 76 low-mass stars around which K2 had detected 79 candidate transiting planets. 29 of these worlds were new discoveries that had not previously been published. We calculate the false positive probabilities that the transit-like signals are actually caused by non-planetary astrophysical phenomena and reject five new transit-like events and three previously reported events as false positives. We also statistically validate 17 planets (7 of which were previously unpublished), confirm the earlier validation of 22 planets, and announce 17 newly discovered planet candidates. Revising the properties of the associated planet candidates based on the updated host star characteristics and refitting the transit photometry, we find that our sample contains 21 planets or planet candidates with radii smaller than 1.25 solar radii, 18 super-Earths (1.25-2 solar radii), 21 small Neptunes (2-4 solar radii), three large Neptunes (4-6 solar radii), and eight giant planets (greater than 6 solar radii). Most of these planets are highly irradiated, but EPIC 206209135.04 (K2-72e, 1.29 from plus 0.19 to minus 0.18 solar radii), EPIC 211988320.01 (perihelion radius equals 2.86 from plus 0.16 to minus 0.15 solar radii), and EPIC 212690867.01 (2.20 from plus 0.19 to minus 0.18 solar radii) orbit within optimistic habitable zone boundaries set by the "recent Venus" inner limit and the "early Mars" outer limit. In total, our planet sample includes eight moderately irradiated 1.5-3 solar radii planet candidates (planetary flux greater than or approximately 20 times Earth's flux) orbiting brighter stars (Ks less than 11) that are well-suited for atmospheric investigations with the Hubble, Spitzer, and/or James Webb Space Telescopes. Five validated planets orbit relatively bright stars (Kp less than 12.5) and are expected to yield radial velocity semi-amplitudes of at least 2 meters per second. Accordingly, they are possible targets for radial velocity mass measurement with current facilities or the upcoming generation of red optical and near-infrared high-precision RV (Radial Velocity) spectrographs.

Dressing, Courtney D.↗
DOE OSTI2022

Dissipative Floquet Dynamics: from Steady State to Measurement Induced Criticality in Trapped-ion Chains

Quantum systems evolving unitarily and subject to quantum measurements exhibit various types of non-equilibrium phase transitions, arising from the competition between unitary evolution and measurements. Dissipative phase transitions in steady states of time-independent Liouvillians and measurement induced phase transitions at the level of quantum trajectories are two primary examples of such transitions. Investigating a many-body spin system subject to periodic resetting measurements, we argue that many-body dissipative Floquet dynamics provides a natural framework to analyze both types of transitions. We show that a dissipative phase transition between a ferromagnetic ordered phase and a paramagnetic disordered phase emerges for long-range systems as a function of measurement probabilities. A measurement induced transition of the entanglement entropy between volume law scaling and sub-volume law scaling is also present, and is distinct from the ordering transition. The two phases correspond to an error-correcting and a quantum-Zeno regimes, respectively. The ferromagnetic phase is lost for short range interactions, while the volume law phase of the entanglement is enhanced. An analysis of multifractal properties of wave function in Hilbert space provides a common perspective on both types of transitions in the system. Our findings are immediately relevant to trapped ion experiments, for which we detail a blueprint proposal based on currently available platforms.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRSDate not supplied

Detectability of Transiting Terrestrial Planets in the Habitable Zone with TESS

In the Revised TESS Habitable Zone Catalog, Kaltenegger et al. (2021) identified the 2-min TESS target stars that were observed for sufficient duration over consecutive primary mission sectors to unambiguously capture a transit signature of planets orbiting in the Habitable Zone (HZ). The Catalog did not, however, identify the host stars for which transiting planets with HZ orbits and specified radii would be detectable based on the photometric precision of the retrieved light curves. We employ the Combined Differential Photometric Precision (CDPP) computed at 15 pulse durations in the Science Processing Operations Center (SPOC) transit searches of the primary mission light curves to estimate the signal-to-noise ratio (S/N) associated with transiting terrestrial planets (1.0 Re <= Rp<= 2.0 Re) in the HZ of the Catalog stars. We consider orbital periods under three HZ scenarios: Recent Venus, Earth Analog, and Early Mars. Given S/N, we further estimate the probability of detection of transiting terrestrial planets for each Catalog star and HZ scenario in the primary mission SPOC transit searches. We also present the expected yield by HZ scenario and planet radius under the assumption that all Catalog stars host such planets.

TESS↗
DOE OSTI2025

Unavoidable multilevel biaxial symmetry breaking in chiral hybrid liquid crystals

Chiral nematic or cholesteric liquid crystals (LCs) are fluid mesophases with long-ranged orientational order featuring a quasilayered periodicity imparted by a helical director configuration but lacking long-range positional order. Doping molecular cholesteric LCs with strongly anisotropic uniaxial colloidal particles adds another level of complexity because of the interplay between weak surface-anchoring boundary conditions and bulk-based elastic distortions near the particle-LC interface. Using cylindrical colloidal disks and rods with different geometric shapes and surface conditions, we demonstrate that these colloidal inclusions generically exhibit biaxial orientational probability distributions which may impart anomalously strong local biaxiality onto the hybrid cholesteric LC structure. Unlike nonchiral hybrid molecular-colloidal LCs, where biaxial order emerges only at critical colloid volume fractions exceeding some uniaxial-biaxial transition value, the orientational probability of the colloidal inclusions immersed in chiral nematic hosts is unambiguously biaxial even at infinite dilution. We demonstrate that the colloids induce local biaxial perturbations within the molecular orientational order of the LC host medium which strongly enhances the weak but native biaxial order of chiral nematic LC induced by the chiral symmetry breaking of the director field. With the help of analytical modeling and computer simulations based on the Landau–de Gennes free energy of the host LC around the colloids, we rationalize the observed multilevel biaxial order and conclude that it is not only unavoidable but also strongly enhanced compared to both achiral hybrid LCs and purely molecular cholesteric LCs.

biaxial liquid crystals↗
NASA NTRS1975

A method for the evaluation of damage on the surface of carbon-carbon ablation samples

The effect of weave geometry on the onset of transition from laminar to turbulent flow around a sample of an orthogonally woven fine weave carbon-carbon material tested in an arc-jet is investigated. Seventeen post-test models which had undergone only partial transition around the circumference were examined as to location of turbulent regions relative to the weave axes. It was statistically shown that the weave axes had the lowest probability of being a position of initial transition onset. The probability generally increased with distance from a major axis, with some rays, notably the 45 deg rays, showing better transition resistance than the adjacent rays. The incidence of initial transition onset correlated well with the number of X or Y fibers that the flow passes over from stagnation point to the shoulder.

Heinonen, E. W.↗
NASA NTRS1991

Survival of discrete structures in the solar wind

Survival time scales are estimated for structures ejected from the sun into the solar wind, which are subject to decay processes during their transit from the sun to the earth. With the assumption that the structures are magnetic, MHD estimates are made to determine the time scales for reconnection into the ambient magnetic field. It is found that for structures smaller than a few tens of Mm at the sun, the probability of surviving the transit to the earth is low. The transition in size between structures that survive the sun-earth transit and those that do not (20-30 Mm at the sun) corresponds to scales of (4-6) x 10 to the 11th cm at the earth orbit (assuming radial expansion).

Mullan, D. J.↗
DOE OSTI2021

State predictive information bottleneck

We report the ability to make sense of the massive amounts of high-dimensional data generated from molecular dynamics simulations is heavily dependent on the knowledge of a low-dimensional manifold (parameterized by a reaction coordinate or RC) that typically distinguishes between relevant metastable states, and which captures the relevant slow dynamics of interest. Methods based on machine learning and artificial intelligence have been proposed over the years to deal with learning such low-dimensional manifolds, but they are often criticized for a disconnect from more traditional and physically interpretable approaches. To deal with such concerns, in this work we propose a deep learning based state predictive information bottleneck approach to learn the RC from high-dimensional molecular simulation trajectories. We demonstrate analytically and numerically how the RC learnt in this approach is connected to the committor in chemical physics and can be used to accurately identify transition states. A crucial hyperparameter in this approach is the time delay or how far into the future the algorithm should make predictions about. Through careful comparisons for benchmark systems, we demonstrate that this hyperparameter choice gives useful control over how coarse-grained we want the metastable state classification of the system to be. We thus believe that this work represents a step forward in systematic application of deep learning based ideas to molecular simulations.

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

Supervised learning and the finite-temperature string method for computing committor functions and reaction rates

A central object in the computational studies of rare events is the committor function. Though costly to compute, the committor function encodes complete mechanistic information of the processes involving rare events, including reaction rates and transition-state ensembles. Under the framework of transition path theory, Rotskoff et al. [Proceedings of the 2nd Mathematical and Scientific Machine Learning Conference, Proceedings of Machine Learning Research (PLMR, 2022), Vol. 145, pp. 757–780] proposes an algorithm where a feedback loop couples a neural network that models the committor function with importance sampling, mainly umbrella sampling, which collects data needed for adaptive training. Here, in this work, we show additional modifications are needed to improve the accuracy of the algorithm. The first modification adds elements of supervised learning, which allows the neural network to improve its prediction by fitting to sample-mean estimates of committor values obtained from short molecular dynamics trajectories. The second modification replaces the committor-based umbrella sampling with the finite-temperature string (FTS) method, which enables homogeneous sampling in regions where transition pathways are located. We test our modifications on low-dimensional systems with non-convex potential energy where reference solutions can be found via analytical or finite element methods, and show how combining supervised learning and the FTS method yields accurate computation of committor functions and reaction rates. We also provide an error analysis for algorithms that use the FTS method, using which reaction rates can be accurately estimated during training with a small number of samples. The methods are then applied to a molecular system in which no reference solution is known, where accurate computations of committor functions and reaction rates can still be obtained.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Hydrogen Bonding Enhances the Electrochemical Hydrogenation of Benzaldehyde in the Aqueous Phase

Abstract The hydrogenation of benzaldehyde to benzyl alcohol on carbon‐supported metals in water, enabled by an external potential, is markedly promoted by polarization of the functional groups. The presence of polar co‐adsorbates, such as substituted phenols, enhances the hydrogenation rate of the aldehyde by two effects, that is, polarizing the carbonyl group and increasing the probability of forming a transition state for H addition. These two effects enable a hydrogenation route, in which phenol acts as a conduit for proton addition, with a higher rate than the direct proton transfer from hydronium ions. The fast hydrogenation enabled by the presence of phenol and applied potential overcompensates for the decrease in coverage of benzaldehyde caused by competitive adsorption. A higher acid strength of the co‐adsorbate increases the intensity of interactions and the rates of selective carbonyl reduction.

Sanyal, Udishnu↗
DOE OSTI2022

Reinforcement learning for adaptive maintenance policy optimization under imperfect knowledge of the system degradation model and partial observability of system states

Maintenance policy optimization usually is faced with challenges that arise from an imperfect knowledge of system degradation models and from the partial observability of system degradation states. Here, this paper proposes a reinforcement learning method to address these two challenges for a class of maintenance problems with Markov degradation processes. The reinforcement learning approach consists of a learning component and a planning component. Using sequentially collected observations, at each step of decision-making the learning component improves the knowledge of system degradation in terms of the probability distributions of the transition rates based on sequential Bayesian inference. Using the updated transition rates, at each step of decision-making the maintenance policy optimization problem is then formulated as a partially observable Markov decision problem, and the planning component computes the optimal maintenance policy that maximizes the expected cumulative reward. The proposed method is illustrated using a numerical example with repair and inspection maintenance actions. The result shows that as more observations are collected, the learning component progressively learns the true system degradation process, and the planning component adjusts the optimal maintenance policy accordingly as well, which leads to increased reward.

42 ENGINEERING↗
DOE OSTI2021

No ordinary proteins: Adsorption and molecular orientation of monoclonal antibodies

The interaction of monoclonal antibodies (mAbs) with air/water interfaces plays a crucial role in their overall stability in solution. We aim to understand this behavior using pendant bubble measurements to track the dynamic tension reduction and x-ray reflectivity to obtain the electron density profiles (EDPs) at the surface. Native immunoglobulin G mAb is a rigid molecule with a flat, “Y” shape, and simulated EDPs are obtained by rotating a homology construct at the surface. Comparing simulations with experimental EDPs, we obtain surface orientation probability maps showing mAbs transition from flat-on Y-shape configurations to side-on or end-on configurations with increasing concentration. The modeling also shows the presence of β sheets at the surface. Overall, the experiments and the homology modeling elucidate the orientational phase space during different stages of adsorption of mAbs at the air/water interface. These finding will help define new strategies for the manufacture and storage of antibody-based therapeutics.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1976

Skylab ultraviolet stellar spectra - Emission lines from the Beta Lyrae system

Observations of Beta Lyr with the Skylab S-019 ultraviolet objective-prism spectrograph show numerous emission lines in the region from 1400 to 2300 A. Some variations in line strength between phases 0.25 and 0.50 are seen, which probably explain the shallowness of the OAO-2 light curve at 1910 A. Many of the emission lines are probably due to intercombination transitions, thus confirming the concept that the emission is produced by collisional excitation in low-density clouds of hot gas.

Kondo, Y.↗
NASA NTRS1986

Aerothermal tests of spherical dome protuberances on a flat plate at a Mach number of 6.5

Aerothermal tests were conducted in the Langley 8-Foot High-Temperature Tunnel at a Mach number of 6.5 on a series of spherical dome protuberances mounted on a flat-plate test apparatus. Detailed surface pressure and heating-rate distributions were obtained for various dome heights and diameters submerged in both laminar and turbulent boundary layers including a baseline geometric condition representing a thermally bowed metallic thermal protection system (TPS) tile. The present results indicated that the surface pressures on the domes were increased on the windward surface and reduced on the leeward surface as predicted by linearized small-perturbation theory, and the distributions were only moderately affected by boundary-layer variations. Surface heating rates for turbulent flow increased on the windward surface and decreased on the leeward surface similar to the pressure; but for laminar boundary layers, the heating rates remained high on the leeward surface, probably due to local transition. Transitional flow effects cause heat load augmentation to increase by 30 percent for the maximum dome height in a laminar boundary layer. However, the corresponding augmentation for a dome with a height of 0.1 in. and a diameter of 14 in. representative of a bowed TPS tile was 14 percent or less for either a laminar or turbulent boundary layer.

Glass, C. E.↗