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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
NASA NTRS1992

Mentat/A: Medium grain parallel processing

The objective of this project is to support the Algorithm to Architecture Mapping Model (ATAMM) firing rules using the Mentat run-time system and the Mentat Programming Language (MPL). Specifically, this required changes to (1) modify the run-time system to control queue length and inhibit actor firing until required data tokens are available and space is available in the input queues of all of the direct descendent actors, (2) disallow the specification of persistent object classes in the MPL, and (3) permit only decision free graphs in the MPL. We have been successful in implementing the spirit of the plan, although some goals changed as we came to better understand the problem. Here, we report on what we accomplished and the lessons we learned. The Mentat/A runtime system, the compiler, results for three applications, and a summary and some observations are given. Appendix A contains a list of technical reports and published papers partially supported by the grant. Appendix B contains listings for the three applications.

Grimshaw, Andrew S.↗
NASA NTRS1992

Mentat/A: Medium grain parallel processing

The objective of this project is to test the Algorithm to Architecture Mapping Model (ATAMM) firing rules using the Mentat run-time system and the Mentat Programming Language (MPL). A special version of Mentat, Mentat/A (Mentat/ATAMM) was constructed. This required changes to: (1) modify the run-time system to control queue length and inhibit actor firing until required data tokens are available and space is available in the input queues of all of the direct descendent actors; (2) disallow the specification of persistent object classes in the MPL; and (3) permit only decision free graphs in the MPL. We were successful in implementing the spirit of the plan, although some goals changed as we came to better understand the problem. We report on what we accomplished and the lessons we learned. The Mentat/A run-time system is discussed, and we briefly present the compiler. We present results for three applications and conclude with a summary and some observations. Appendix A contains a list of technical reports and published papers partially supported by the grant. Appendix B contains listings for the three applications.

Grimshaw, Andrew S.↗
DOE OSTI2024

Robustness of topological persistence in knowledge distillation for wearable sensor data

Topological data analysis (TDA) has shown great success in various applications involving wearable sensor data. However, there are difficulties in leveraging topological features in machine learning and wearable sensors because of the large time consumption and computational resources required to extract the features. To address this problem, knowledge distillation (KD) is utilized to generate a small model and accommodate topological features with persistence image (PI) representations from the raw time series data. Deploying topological knowledge in KD enables the student to achieve better performance compared to the one trained solely on raw time series data. However, it is not yet known if there are coherent characteristics for topological features in PI, which can aid in improving the performance during KD. In this paper, we investigate the suitability and challenges of utilizing topological features in KD for wearable sensor data, thereby contributing to the advancement of the field. Our study explores the impact of transferred topological features by comparing the Teacher-to-Student framework with Multiple Teachers-to-Student where teachers utilize both time series data and persistence images obtained by TDA as inputs. Additionally, we conduct a rigorous examination of topological knowledge effects by testing under various corruptions, knowledge types, and learning strategies in the context of human activity recognition tasks. Our analysis of topological features in KD presents the optimal strategy for incorporating these features. This study includes datasets of varying scales, window lengths, and activity classes, providing a comprehensive evaluation. Our results demonstrate that leveraging topological features in KD to enhance performance across databases.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1998

An Experimental Investigation of Transition as Applied to Low Pressure Turbine Suction Surface Flows

Results of an experimental study of flow separation and transition in either attached boundary layers or separated shear layers over the suction surface of a simulation of a low-pressure turbine airfoil flow are presented. Detailed velocity profiles were measured with the hot-wire technique. Static pressure distributions are also presented. Flow transition is documented using measured intermittency distributions in the boundary layer and the separated shear layer. Cases for Reynolds numbers of 50,000, 100,000, 200,000 and 300,000 are reported. These Reynolds numbers are based on suction surface length and exit velocity. Three Free Stream Turbulence Intensity values, 0.5%, 2.5% and 10%, are represented. Flow separation is observed for all the low-FSTI cases. Of these, the lowest Reynolds number case was not able to complete transition of the shear layer and the separation bubble persisted over the entire blade surface. For the other low-FSTI cases, transition is observed in the shear layer over the separation bubble. This transition proceeded quickly, spreading rapidly toward the wall. Elevated FSTI drives an earlier transition than in the low-FSTI cases and the separation bubbles are smaller. For the highest Reynolds number cases with 2.5% and 10% FSTI, transition is of the attached boundary layer and no separation exists. Flow separation with shear flow transition is observed for the lower-Re cases. Models for intermittency and transition length and location from the modern literature are assessed.

Qiu, Songgang↗
DOE OSTI2024

Shrubs Strongly Influence Snow Properties in Two Subarctic Watersheds

Understanding changes in snow distribution in permafrost ecosystems is fundamental to predicting their response to future climate change. The expansion of tall shrubs into tundra ecosystems can trap snow and insulate permafrost ecosystems during the winter, but the overall insulation effect is dependent upon many ecosystem properties. To study shrub–snow–ground interactions, small temperature sensors were deployed at two research sites on the Seward Peninsula of Alaska, USA, during the 2019–2020 winter. Snow temperatures were used to extrapolate multiple metrics, including freezing n-factors, the snow insulation effect, snow cover duration, and the length of the snowmelt period. Statistical and spatial analysis showed that shrub patches were a dominant control on all snow metrics. Within shrub patches, average ground temperatures were 2.1°C warmer, snow persisted 50 days longer, snow insulation was double, and a longer, later spring snowmelt period occurred compared to nonshrubby areas. Site-level differences contributed relatively little to variation in snow metrics, indicating that shrub presence is an overarching driver of snow–ground interactions at the locations examined. Shrub expansion, which is anticipated under climate change, will strongly impact future permafrost distribution and Arctic energy, water, and carbon cycles through snow–shrub–ground feedbacks.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Sequences of seismic and aseismic slip on bimaterial faults show dominant rupture asymmetry and potential for elevated seismic hazard

Here we perform numerical simulations of sequences of earthquake and aseismic slip on planar rate and state faults separating dissimilar material within the 2-D plane strain approximation. We resolve all stages of the earthquake cycle from aseismic slip to fast ruptures while incorporating full inertia effects during seismic event propagation. We show that bimaterial coupling results in favorable nucleation site and subsequent asymmetric rupture propagation. We demonstrate that increasing the material contrast enhances this asymmetry leading to higher slip rates and normal stress drops in the preferred rupture propagation direction. The normal stress drop, induced by the bimaterial effect, leads to strong dynamic weakening of the fault and may destabilize the creeping region on a heterogeneous rate and state fault, resulting in extended rupture propagation. Such rupture penetration into creeping patches may lead to more frequent opening of earthquake gates, causing increased seismic hazard. Furthermore, bimaterial coupling may lead to irregular seismicity pattern in terms of event length, peak slip rates, and hypocenter location, depending on the properties of the creeping patches bordering the seismogenically active part of the fault. Our results highlight robust characteristics of bimaterial interfaces that persist over long sequence of events and suggest the need for further exploration of the role of material contrast in earthquake physics and models of seismic hazard.

58 GEOSCIENCES↗
DOE OSTI2022

Deep Convolutional Neural Networks Exploit High-Spatial- and -Temporal-Resolution Aerial Imagery to Phenotype Key Traits in Miscanthus

Miscanthus is one of the most promising perennial crops for bioenergy production, with high yield potential and a low environmental footprint. The increasing interest in this crop requires accelerated selection and the development of new screening techniques. New analytical methods that are more accurate and less labor-intensive are needed to better characterize the effects of genetics and the environment on key traits under field conditions. We used persistent multispectral and photogrammetric UAV time-series imagery collected 10 times over the season, together with ground-truth data for thousands of Miscanthus genotypes, to determine the flowering time, culm length, and biomass yield traits. We compared the performance of convolutional neural network (CNN) architectures that used image data from single dates (2D-spatial) versus the integration of multiple dates by 3D-spatiotemporal architectures. The ability of UAV-based remote sensing to rapidly and non-destructively assess large-scale genetic variation in flowering time, height, and biomass production was improved through the use of 3D-spatiotemporal CNN architectures versus 2D-spatial CNN architectures. The performance gains of the best 3D-spatiotemporal analyses compared to the best 2D-spatial architectures manifested in up to 23% improvements in R2, 17% reductions in RMSE, and 20% reductions in MAE. The integration of photogrammetric and spectral features with 3D architectures was crucial to the improved assessment of all traits. In conclusion, our findings demonstrate that the integration of high-spatiotemporal-resolution UAV imagery with 3D-CNNs enables more accurate monitoring of the dynamics of key phenological and yield-related crop traits. This is especially valuable in highly productive, perennial grass crops such as Miscanthus, where in-field phenotyping is especially challenging and traditionally limits the rate of crop improvement through breeding.

47 OTHER INSTRUMENTATION↗
NASA NTRS1985

Cryogenic operation of pseudomorphic AlGaAs/InGaAs single-quantum-well MODFETs

The 77 K operation of AlGaAs/InGaAs MODFETs has been investigated. The structures, grown by MBE, make use of a 200 A undoped In(0.15)Ga(0.85)As quantum well for electron confinement and an Si-doped Al(0.15)Ga(0.85)As top barrier. The MODFETs with 1 micron gate lengths exhibit extrinsic transconductances of 360 mS/mm and maximum currents of 310 mA/mm at 77 K. The use of a low Al mole fraction AlGaAs/InGaAs heterojunction makes it possible to avoid the persistent trapping effects encountered in AlGaAs/GaAs MODFETs without sacrificing device performance.

Masselink, W. T.↗
NASA NTRS2019

Statistical Hypothesis Testing in Wavelet Analysis: Theoretical Developments and Applications to Indian Rainfall

Statistical hypothesis tests in wavelet analysis are methods that assess the degree to which a wavelet quantity(e.g., power and coherence) exceeds background noise. Commonly, a point-wise approach is adopted in which a wavelet quantity at every point in a wavelet spectrum is individually compared to the critical level of the point-wise test. However, because adjacent wavelet coefficients are correlated and wavelet spectra often contain many wavelet quantities, the point-wise test can produce many false positive results that occur in clusters or patches. To circumvent the point-wise test drawbacks, it is necessary to implement the recently developed area-wise, geometric, cumulative area-wise, and topological significance tests, which are reviewed and developed in this paper. To improve the computational efficiency of the cumulative area-wise test, a simplified version of the testing procedure is created based on the idea that its output is the mean of individual estimates of statistical significance calculated from the geometric test applied at a set of point-wise significance levels. Ideal examples are used to show that the geometric and cumulative area-wise tests are unable to differentiate wavelet spectral features arising from singularity-like structures from those associated with periodicities. A cumulative arc-wise test is therefore developed to strictly test for periodicities by using normalized arc length, which is defined as the number of points composing a cross section of a patch divided by the wavelet scale in question. A previously proposed topological significance test is formalized using persistent homology profiles (PHPs) measuring the number of patches and holes corresponding to the set of all point-wise significance values. Ideal examples show that the PHPs can be used to distinguish time series containing signal components from those that are purely noise. To demonstrate the practical uses of the existing and newly developed statistical methodologies, a first comprehensive wavelet analysis of Indian rainfall is also provided. An R software package has been written by the author to implement the various testing procedures.

Wind speed↗
NASA NTRS1982

Vortices in turbulence

Theoretical and experimental results of studies to determine the flow parameters and structures of plane mixing layers are reported. Smoke visualization, combined with hot-wire anemometry, sheets of laser light, and photography were used to gather data from the wall flow. The behavior of vortex rods was examined, noting that the rods persisted only if new vortex energy was supplied from the sublayer. A power spectral density was defined for the velocity fluctuations, as was a hierarchy of velocity scales for geometrically similar vortices. The length scale grows linearly with downstream distance, where the flow structures are fed by longitudinal vortices. A model is developed for vortex pairing in sequential order from the bottom of the mixing layer outward in a repetitive process involving vortex stretching. The model is actually a migration strategy that satisfies the flow self-preservation constraints.

Perry, A. E.↗
DOE OSTI2020

The C‐Terminal Domain of α‐Synuclein Confers Steric Stabilization on Synaptic Vesicle‐Like Surfaces

Abstract While α‐synuclein, an intrinsically disordered protein linked to Parkinson's disease, has been shown to associate with membrane organelles, its overall cellular function remains nebulous. α‐Synuclein binds to membranes through its amino‐terminal domain (first ≈100 residues), but there is no consensus on the biophysical function of the carboxyl‐terminal domain (last ≈40 residues) due, in part, to its lack of strong interaction partners and persisting intrinsic disorder even when membrane bound. Here, by directly applying force on α‐synuclein bound to spherical nanoparticle‐supported lipid bilayers (SSLBs) and tracking higher‐order structural changes through small‐angle X‐ray scattering, strong evidence is presented that α‐synuclein sterically stabilizes membrane surfaces through its carboxyl‐terminal domain. Full‐length α‐synuclein dramatically increases the critical osmotic pressure at which SSLBs cluster ( P C ≈ 1.3 × 10 5 Pa) compared to α‐synuclein without the carboxyl‐terminal domain ( P C ≈ 1.9 × 10 4 Pa) at physiological salt and temperature conditions. This clustering of α‐synuclein‐bound SSLBs is shown to be reversible and sensitive to monovalent/divalent salt, both features of grafted polyelectrolyte‐mediated steric stabilization. In elucidating the biophysical function of α‐synuclein in the framework of polymer science, it is demonstrated that the carboxyl‐terminal domain can potentially utilize its persisting intrinsic disorder to functionalize membrane surfaces.

Chung, Peter J.↗
DOE OSTI2023

Prevailing Charge Order in Overdoped La 2 – x Sr x CuO 4 beyond the Superconducting Dome

The extremely overdoped cuprates are generally considered to be Fermi liquid metals without exotic orders, whereas the underdoped cuprates harbor intertwined states. Contrary to this conventional wisdom, using Cu L 3 -edge and O K-edge resonant x-ray scattering, we reveal a charge order (CO) correlation in overdoped La 2–x⁢ Sr x ⁢CuO 4 (0.35 ≤ x ≤0.6) beyond the superconducting dome. This CO has a periodicity of ~6 lattice units with correlation lengths of ~20 lattice units. It shows similar in-plane momentum and polarization dependence and dispersive excitations as the CO of underdoped cuprates, but its maximum intensity differs along the c direction and persists up to 300 K. This CO correlation cannot be explained by the Fermi surface instability and its origin remains to be understood. Finally, our results suggest that CO is prevailing in the overdoped metallic regime and requires a reassessment of the picture of overdoped cuprates as weakly correlated Fermi liquids.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Active Sites in the Dealuminated Beta Zeolite-Supported Cobalt Catalyst for Non-Oxidative Ethane Dehydrogenation

Dispersed metal species in siliceous zeolites have been actively studied for non-oxidative dehydrogenation of ethane (NDE). Fundamental insights into the dynamics of metal species in zeolites under reaction conditions have rarely been explored. Herein, we report an atomic level understanding of the dynamics and activity of cobalt (Co) sites in dealuminated Beta zeolite (DeAl-BEA) for NDE during induction and reaction conditions with extensive characterization techniques such as diffuse reflectance UV–vis, solid state nuclear magnetic resonance and X-ray photoelectron, X-ray diffraction along with in situ Fourier transform infrared and X-ray absorption spectroscopy. For a catalyst with 0.5 mass % Co loading, tetrahedral Co 2+ mononuclear sites, di-coordinated to the zeolite framework and with two silanol groups in vicinity (i.e., (≡SiO) 2 Co(HO–Si≡) 2 ), form upon exposure to hydrogen during induction and persist through the NDE reaction. Increasing the Co loading to 3.0 mass % yielded Co sites with similar electronic and coordination structures but slightly elongated Co–O bonds. Upon cooling to room temperature, the Co sites persisted in the same coordination environment, though the disappearance of a feature in the Co K-edge near-edge region revealed changes in the active site’s electronic structure coinciding with modest shifts in bond lengths. The electronic structure and activity of (≡SiO) 2 Co(HO–Si≡) 2 sites were studied comparatively to a few other hypothetical Co 2+ coordination structures, using electronic structure calculations and microkinetic simulations. The simulations showed that NDE is controlled by β-hydride elimination following C–H bond activation and that Co-sites possessing flexibility because of neighboring silanol defects are more active. Interestingly, dinuclear Co–O–Co sites (i.e., (≡SiO)Co(HO–Si≡) 2 –O–(HO–Si≡) 2 Co(≡SiO)) were more active than the mononuclear (≡SiO) 2 Co(HO–Si≡) 2 sites because of favorable hydrogen bonding with the vicinal silanol groups. In conclusion, the present study bridges the gap between the knowledge acquired by ex-situ characterizations and the active sites under the reaction conditions in alkane dehydrogenation chemistry.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Quantum-Accurate Multiscale Modeling of Shock Hugoniots, Ramp Compression Paths, Structural and Magnetic Phase Transitions, and Transport Properties in Highly Compressed Metals

Fully characterizing high energy density (HED) phenomena using pulsed power facilities (Z machine) and coherent light sources is possible only with complementary numerical modeling for design, diagnostic development, and data interpretation. The exercise of creating numerical tests, that match experimental conditions, builds critical insight that is crucial for the development of a strong fundamental understanding of the physics behind HED phenomena and for the design of next generation pulsed power facilities. The persistence of electron correlation in HED materials arising from Coulomb interactions and the Pauli exclusion principle is one of the greatest challenges for accurate numerical modeling and has hitherto impeded our ability to model HED phenomena across multiple length and time scales at sufficient accuracy. An exemplar is a ferromagnetic material like iron, while familiar and widely used, we lack a simulation capability to characterize the interplay of structure and magnetic effects that govern material strength, kinetics of phase transitions and other transport properties. Herein we construct and demonstrate the Molecular-Spin Dynamics (MSD) simulation capability for iron from ambient to earth core conditions, all software advances are open source and presently available for broad usage. These methods are multi-scale in nature, direct comparisons between high fidelity density functional theory (DFT) and linear-scaling MSD simulations is done throughout this work, with advancements made to MSD allowing for electronic structure changes being reflected in classical dynamics. Main takeaways for the project include insight into the role of magnetic spins on mechanical properties and thermal conductivity, development of accurate interatomic potentials paired with spin Hamiltonians, and characterization of the high pressure melt boundary that is of critical importance to planetary modeling efforts.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Salinity and hydraulic retention time induce membrane phospholipid acyl chain remodeling in Halanaerobium congolense WG10 and mixed cultures from hydraulically fractured shale wells

Bacteria remodel their plasma membrane lipidome to maintain key biophysical attributes in response to ecological disturbances. For Halanaerobium and other anaerobic halotolerant taxa that persist in hydraulically fractured deep subsurface shale reservoirs, salinity, and hydraulic retention time (HRT) are important perturbants of cell membrane structure, yet their effects remain poorly understood. Membrane-linked activities underlie in situ microbial growth kinetics and physiologies which drive biogeochemical reactions in engineered subsurface systems. Hence, we used gas chromatography–mass spectrometry (GC–MS) to investigate the effects of salinity and HRT on the phospholipid fatty acid composition of H. congolense WG10 and mixed enrichment cultures from hydraulically fractured shale wells. We also coupled acyl chain remodeling to membrane mechanics by measuring bilayer elasticity using atomic force microscopy (AFM). For these experiments, cultures were grown in a chemostat vessel operated in continuous flow mode under strict anoxia and constant stirring. Our findings show that salinity and HRT induce significant changes in membrane fatty acid chemistry of H. congolense WG10 in distinct and complementary ways. Notably, under nonoptimal salt concentrations (7% and 20% NaCl), H. congolense WG10 elevates the portion of polyunsaturated fatty acids (PUFAs) in its membrane, and this results in an apparent increase in fluidity (homeoviscous adaptation principle) and thickness. Double bond index (DBI) and mean chain length (MCL) were used as proxies for membrane fluidity and thickness, respectively. These results provide new insight into our understanding of how environmental and engineered factors might disrupt the physical and biogeochemical equilibria of fractured shale by inducing physiologically relevant changes in the membrane fatty acid chemistry of persistent microbial taxa. GRAPHICAL ABSTRACT Salinity significantly alters membrane bilayer fluidity and thickness in Halanaerobium congolense WG10.

03 NATURAL GAS↗
DOE OSTI2025

Observation of Persistent Zero Modes and Superconducting Vortex Doublets in UTe 2

Superconducting vortices can reveal electron pairing details and nucleate topologically protected states. Yet, vortices of bulk spin-triplet superconductors have never been visualized at the atomic scale. Recently, UTe 2 has emerged as a prime spin-triplet superconductor, but its superconducting order parameter is elusive, and whether time-reversal symmetry (TRS) is broken remains unsettled. Here, in this work, we visualize vortices on the (011) surface of ultraclean UTe 2 single crystals (T c = 2.1 K) using scanning tunneling microscopy (STM). We introduce $\frac{d^{2}𝐼}{d𝑉^{2}}$ imaging as an effective technique for vortex visualization in superconductors with substantial residual zero-energy density of states (DOS), as in UTe 2 . Anisotropic single-flux-quantum vortices, with coherence lengths of ∼12 nm (4 nm) parallel (perpendicular) to the a -axis, form a triangular vortex lattice (VL) under a small out-of-plane magnetic field. The invariance of vortex structures and VL under changes of field polarity and cooling history strongly supports time-reversal invariant superconductivity under zero field. At vortex cores (VCs), nonsplit, spectrally sharp zero-bias conductance peaks (ZBPs) persist up 8 T that are consistent with symmetry-protected Majorana zero modes (MZMs) in a topological vortex line. Close examination of vortex structures reveals a mirror-asymmetric doublet─one with ZBPs and another with an enhanced apparent gap, possibly originating from a field-induced multicomponent order parameter.

UTe2↗
DOE OSTI2025

Effects of Temperature Fluctuations on Surface Mobility of Atomic Steps and Oxidation Dynamics in High-Temperature Alloys

In contrast to the traditional perspective that thermal fluctuations are insignificant in surface dynamics, here we report their influence on surface reaction dynamics. Using real-time low-energy electron microscopy imaging of NiAl(100) under both vacuum and O 2 atmospheres, we demonstrate that transient temperature variations substantially alter the direction of atom diffusion between the surface and bulk, leading to markedly different oxidation outcomes. During heating, substantial outward diffusion of atoms from the bulk to the surface results in step growth. Conversely, cooling induces considerable inward diffusion of adatoms, producing a distinct oxide morphology. In both scenarios, initially formed oxide islands impede local atomic step mobility, thereby increasing step length due to mass transfer between the surface and bulk, with atomic steps acting as adatom sinks during heating and sources during cooling. Furthermore, we show that this pinning effect on atomic step mobility can be mitigated by applying persistent temperature fluctuations. As a result, understanding these nuances is vital for accurately predicting and dynamically manipulating the performance of active materials in various chemical processes under transient thermal conditions.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Estimating Drizzle Parameters by Aircraft Sampling

In-cloud supersaturation is calculated from aircraft derived measurements of the in-cloud vertical gradient of liquid water content, vertical velocity, the pt and 3 rd cloud droplet radius moments and a parameter related to the heat and mass transport during condensation and evaporation of cloud droplets. The aircraft data where taken during the VOCALS 2008 study in marine stratocumulus clouds off the coast of Chile. Approximately 16000 discrete samples, 2.5 meter in length, were used in the present analysis of in-cloud supersaturation and its variability, both of which are indicative of turbulent processes within the cloud and their significant impact on drizzle formation. Two additional drizzle parameters, the eddy persistence time and the variance of fluctuations in in-cloud droplet growth rate were also estimated from this data set. These results will help to constrain parameterizations of underlying turbulent microphysical processes of clouds and thereby advance the future development of warm cloud and precipitation models for climate simulation.

54 ENVIRONMENTAL SCIENCES↗