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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 451 records · Page 25
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Observations and Machine-Learned Models of Near-Surface Permafrost along the Koyukuk River, Alaska, USA

This dataset contains GeoTIFs (raster) and GeoPackages (vector) that map observations of near-surface permafrost and not-permafrost from a field campaign conducted near the village of Huslia, AK along the Koyukuk River and its floodplain in July 2018. These data were collected as part of a campaign to understand if and how permafrost impacts riverbank erosion. This problem cannot be assessed without knowing where permafrost exists. Permafrost was observed via frost probing (to a maximum depth of one meter), coring (to a maximum depth of two meters) and bank/bar excavations. An additional boat survey was performed wherein expert (Joel Rowland) judgment assessed the presence or absence of distinctive permafrost features (e.g., overhanging tundra mats, thermoerosional niching, ice wedges, active drainage of ice melt from soils). This dataset also contains the input features and results of two machine learning models (random forest and convolutional neural network) that extrapolate the observations to the full floodplain that may be useful for building, testing, or validating other machine-learned permafrost models. Permafrost data are provided as georasters of the same shape and geovectors (polylines/polygons) and are all projected into EPSG:32605. All data can be visualized with a GIS (QGIS, ArcGIS, etc.).

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1982

The fabrication and surface tolerance measurements of the JPL clear aperture microwave antenna

Present ground station microwave antennas of the Deep Space Network are of the symmetric dual reflector (cassegrainian) type. An investigation is being made of alternative high-performance offset antenna designs which have a clear aperture (no reflector or structural blockage) with shaped reflector surfaces. A 1.5-m, 32-GHz clear aperture model was built for experimental studies. The unique processes of fabrication, surface measurement, and alignment are described.

Carpenter, J.↗
NASA NTRS1990

Toward modeling a dynamic biological neural network

The organization of a mammalian macular endorgan is interpreted on physical and engineering principles. Having accomplished this task, it is possible to mathematically and symbolically model information processing by the macular neural network. A complex symbolic model is produced through use of mathematical notations that describe the functioning system. The model, consisting of six tiers, is constructed to mimic the neural system. On the basis of initial simulations, it is concluded that the network functions best when some of the detecting elements (i.e., type I hair cells) are weakly inhibitory. The simulations also illustrate the importance of disinhibition of receptors located in the third tier in shaping nerve discharge patterns at the sixth tier in the model system.

Ross, M. D.↗
NASA NTRS1996

Holographic Vibration Testing With Video/Computer Imaging

In improved system for holographic vibration testing, holographic interferograms indicating shapes of vibrational modes recorded by video camera under computer control. Results available almost immediately, and images distributed simultaneously to multiple computer terminals connected to vibration-testing computer via local-area network. Designed to replace prior photography-based system for identifying natural vibrational modes of propfan blades; adaptable to similar vibration testing of other objects.

Miller, Christopher J.↗
NASA NTRS2002

A satellite view of aerosols in the climate system

Anthropogenic aerosols are intricately linked to the climate system and to the hydrologic cycle. The net effect of aerosols is to cool the climate system by reflecting sunlight. Depending on their composition, aerosols can also absorb sunlight in the atmosphere, further cooling the surface but warming the atmosphere in the process. These effects of aerosols on the temperature profile, along with the role of aerosols as cloud condensation nuclei, impact the hydrologic cycle, through changes in cloud cover, cloud properties and precipitation. Unravelling these feedbacks is particularly difficult because aerosols take a multitude of shapes and forms, ranging from desert dust to urban pollution, and because aerosol concentrations vary strongly over time and space. To accurately study aerosol distribution and composition therefore requires continuous observations from satellites, networks of ground-based instruments and dedicated field experiments. Increases in aerosol concentration and changes in their composition, driven by industrialization and an expanding population, may adversely affect the Earth's climate and water supply.

Review, Tutorial↗
NASA NTRSDate not supplied

The Impact of Transition-Edge Sensor Design on Internal Thermal Fluctuation Noise and Thermal Conductance

The measured noise in transition-edge sensor (TES) microcalorimeters with a Mo/Au bilayer has been shown to have a significant contribution from internal thermal fluctuation noise (ITFN) between the absorber and the TES. Previous measurements showed the relevant thermal link leading to the noise was the thermal conductance of the TES bilayer, and ITFN has been shown to correlate with the sheet resistance of the TES. As a result, ITFN is particularly significant in devices with a large bilayer sheet resistance. However, because of more favorable transition shapes, such high resistance devices have recently been shown to be preferable under alternating current bias, which is required for the frequency division multiplexed readout baselined for the X-ray Integral Field Unit (X-IFU) instrument on the ATHENA satellite. Therefore, it is important to investigate how else to minimize the ITFN beyond changes to the sheet resistance. In this presentation, we will discuss our investigation of how changes to the TES design can affect ITFN for a fixed sheet resistance. We will present how ITFN is altered by changes to the aspect ratio of the TES, the addition of normal metal banks parallel to the TES current direction, and the size and position of the connections between the absorber and the TES. We will also discuss how these design changes impact the superconducting transition shape, and the thermal conductance from the TES to the thermal bath. These results may provide routes for further improvements of TES performance, and a deeper understanding of the physics of the thermal network in a TES microcalorimeter.

Nicholas A Wakeham↗
NASA NTRSDate not supplied

Toward an IMU-Based Space Suit Motion Capture System

Spacesuits are complex engineering systems that sustain human health and enable performance outside Earth-like environments. These systems must support human mobility and physical workload demands while minimizing injury risk during extravehicular activity (EVA). Future EVA operations on the Lunar surface are expected to be more frequent and require higher physical workloads than previously during the ISS, Shuttle, and Apollo programs. To characterize the workloads and ergonomics needs a suit must support, the kinematics of the space suit must be measured during operationally-relevant tasks in ground analog environments. Kinematics capture of the suit is challenging for traditional optical motion capture (OMC) approaches due to marker occlusion, harsh lighting or environmental conditions, and tests with suit surrogates in outdoor field environments. To this end, engineers at NASA are developing the Augmented Suit Inverse Kinematics (ASIK) system, a complete motion capture method and inverse kinematics solver which relies solely on a network of wireless inertial measurement units (IMUs) attached to the major kinematic segments of the spacesuit. The ASIK modeling language allows for the simple inclusion of probabilistic priors such as suit size and shape or IMU poses. The ASIK system was tested in a 7-subject pilot study. Each subject donned NASA’s new prototype exploration spacesuit in the Active Response Gravity Offload System (ARGOS) facility at Johnson Space Center in Houston, TX. The suits were outfitted with 12 IMUs to estimate lower body and trunk kinematics. The suits were also outfitted with a set of reflective OMC markers, and traditional OMC data was collected and processed. Characterization of the ASIK-derived suit joint angles’ accuracy against an optical motion capture datum will be presented. Discussion of these results, as well as discussion of system calibration and nuances of mathematical observability, will be included.

IMU↗
DOE OSTI2022

Surface‐Enforced Alignment of Reprogrammable Liquid Crystalline Elastomers

Abstract Liquid crystalline elastomers (LCEs) are stimuli‐responsive materials capable of undergoing large deformations. The thermomechanical response of LCEs is attributable to the coupling of polymer network properties and disruption of order between liquid crystalline mesogens. Complex deformations have been realized in LCEs by either programming the nematic director via surface‐enforced alignment or localized mechanical deformation in materials incorporating dynamic covalent chemistries. Here, the preparation of LCEs via thiol‐Michael addition reaction is reported that are amenable to surface‐enforced alignment. Afforded by the thiol‐Michael addition reaction, dynamic covalent bonds are uniquely incorporated in chemistries subject to surface‐enforce alignment. Accordingly, LCEs prepared with complex director profiles are able to be programmed and reprogrammed by (re)activating the dynamic covalent chemistry to realize distinctive shape transformations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Investigating the crust of neutron stars with neural-network quantum states

An accurate description of low-density nuclear matter is crucial for explaining the physics of neutron star crusts. In the density range between approximately 0.01 fm −3 and 0.1 fm −3 , matter transitions from neutron-rich nuclei to various higher-density pasta shapes, before ultimately reaching a uniform liquid. In this work, we introduce a variational Monte Carlo method based on a neural Pfaffian-Jastrow quantum state, which allows us to model the transition from the liquid phase to neutron-rich nuclei microscopically. At low densities, nuclear clusters dynamically emerge from the microscopic interactions among protons and neutrons, which we model based on pionless effective field theory. Our variational Monte Carlo approach represents a significant improvement over the state-of-the-art auxiliary-field diffusion Monte Carlo method, which is severely hindered by the fermion-sign problem in this low-density regime and cannot capture the onset of clusters. In addition to computing the energy per particle of symmetric nuclear matter and pure neutron matter, we analyze an intermediate isospin-asymmetry configuration to elucidate the formation of nuclear clusters. We also provide evidence that the presence of such nuclear clusters influences the amount of protons in the crust compared to protons in beta-equilibrated, neutrino-transparent matter.

Nuclear astrophysics↗
DOE OSTI2024

Accessing pluripotent materials through tempering of dynamic covalent polymer networks

Pluripotency, which is defined as a system not fixed as to its developmental potentialities, is typically associated with biology and stem cells. Here, inspired by this concept, we report synthetic polymers that act as a single “pluripotent” feedstock and can be differentiated into a range of materials that exhibit different mechanical properties, from hard and brittle to soft and extensible. To achieve this, we have exploited dynamic covalent networks that contain labile, dynamic thia-Michael bonds, whose extent of bonding can be thermally modulated and retained through tempering, akin to the process used in metallurgy. In addition, we show that the shape memory behavior of these materials can be tailored through tempering and that these materials can be patterned to spatially control mechanical properties.

36 MATERIALS SCIENCE↗
NASA NTRS2015

Numerical Modeling of Self-Pressurization and Pressure Control by Thermodynamic Vent System in a Cryogenic Tank

This paper presents a numerical model of a system-level test bed - the multipurpose hydrogen test bed (MHTB) using Generalized Fluid System Simulation Program (GFSSP). MHTB is representative in size and shape of a fully integrated space transportation vehicle liquid hydrogen (LH2) propellant tank and was tested at Marshall Space Flight Center (MSFC) to generate data for cryogenic storage. GFSSP is a finite volume based network flow analysis software developed at MSFC and used for thermo-fluid analysis of propulsion systems. GFSSP has been used to model the self-pressurization and ullage pressure control by Thermodynamic Vent System (TVS). A TVS typically includes a Joule-Thompson (J-T) expansion device, a two-phase heat exchanger, and a mixing pump and spray to extract thermal energy from the tank without significant loss of liquid propellant. Two GFSSP models (Self-Pressurization & TVS) were separately developed and tested and then integrated to simulate the entire system. Self-Pressurization model consists of multiple ullage nodes, propellant node and solid nodes; it computes the heat transfer through Multi-Layer Insulation blankets and calculates heat and mass transfer between ullage and liquid propellant and ullage and tank wall. TVS model calculates the flow through J-T valve, heat exchanger and spray and vent systems. Two models are integrated by exchanging data through User Subroutines of both models. The integrated models results have been compared with MHTB test data of 50% fill level. Satisfactory comparison was observed between test and numerical predictions.

Majumdar, Alok↗
NASA NTRS1993

Parametric motion control of robotic arms: A biologically based approach using neural networks

A neural network based system is presented which is able to generate point-to-point movements of robotic manipulators. The foundation of this approach is the use of prototypical control torque signals which are defined by a set of parameters. The parameter set is used for scaling and shaping of these prototypical torque signals to effect a desired outcome of the system. This approach is based on neurophysiological findings that the central nervous system stores generalized cognitive representations of movements called synergies, schemas, or motor programs. It has been proposed that these motor programs may be stored as torque-time functions in central pattern generators which can be scaled with appropriate time and magnitude parameters. The central pattern generators use these parameters to generate stereotypical torque-time profiles, which are then sent to the joint actuators. Hence, only a small number of parameters need to be determined for each point-to-point movement instead of the entire torque-time trajectory. This same principle is implemented for controlling the joint torques of robotic manipulators where a neural network is used to identify the relationship between the task requirements and the torque parameters. Movements are specified by the initial robot position in joint coordinates and the desired final end-effector position in Cartesian coordinates. This information is provided to the neural network which calculates six torque parameters for a two-link system. The prototypical torque profiles (one per joint) are then scaled by those parameters. After appropriate training of the network, our parametric control design allowed the reproduction of a trained set of movements with relatively high accuracy, and the production of previously untrained movements with comparable accuracy. We conclude that our approach was successful in discriminating between trained movements and in generalizing to untrained movements.

Bock, O.↗
NASA NTRS1981

Effects of diffusion and mass flows on C IV and Si IV lines formed in the solar atmosphere

A model for the transition region is derived from an initial interpretation of EUV observations, assuming ionization equilibrium and constant elemental abundance with height. The effects of diffusion and mass flows are then included in the initial model and the emergent profiles of several C IV and Si IV lines are computed. It is found that diffusion and mass flows have a strong effect on both the emergent intensity and spectral shape of these lines. Diffusion acts to deplete the transition region of heavy ions to an extent which depends on the detailed temperature and density structure. The net effect is a weighting of the coronal emission relative to that in the transition. On the basis of the results, it is suggested that the downflows observed in the network in lines of C IV and Si IV could be due to gravitational settling of the ions following their injection, via diffusion, into the corona from spicules. When flows are superposed on the basic diffusion model, the rapid change in elemental abundance characteristic of the model is virtually eliminated and the coronal contribution to the emission in C IV and Si IV lines becomes negligible relative to that in the transition region. Flows have a strong effect on the computed line intensities and introduce large asymmetries into the line shapes.

Roussel-Dupre, R.↗
DOE OSTI2021

An Artificial Neural Network System for Photon-Based Active Interrogation Applications

Active interrogation (AI) is a promising technique to detect shielded special nuclear materials (SNMs). At the University of Michigan, we are developing a photon-based AI system that uses bremsstrahlung radiation from an electron linear accelerator (linac) as an ionizing source and stilbene organic scintillating detectors for neutron detection. Stilbene scintillators are sensitive to fast neutrons and photons and have excellent pulse shape discrimination (PSD) capabilities. The traditional charge integration (CI) method commonly used for PSD analysis eliminates piled-up pulses and relies on a particle discrimination line to separate neutrons and photons. The presence of the intense photon flux during AI creates a significant number of piled-up events in the stilbene scintillator, thereby posing a great challenge to the traditional CI method. Identifying true single neutron pulses becomes challenging due to the presence of a pile-up cloud and overlapping neutron, photon and pile-up clouds in the PSD analysis. To mitigate the effect of pulse pile up and identify true single neutron pulses from stilbene scintillators, an artificial neural network (ANN) system is developed. The developed ANN system identifies single neutron pulses and neutron-photon combinations from piled-up events. The results obtained from a 252Cf measurement in the presence of the intense photon flux show that the developed ANN system outperforms the traditional CI method. Since many piled-up events lie above the particle discrimination line, they get misclassified as neutrons by the traditional CI method resulting in 25% overestimation of the net neutron count rate during the linac pulse. The overall net neutron count rate (single and restored neutrons) during the linac pulse, estimated by the ANN system is 60% of the ground truth. Energy spectroscopy of the ANN attributed single neutron pulses further provides evidence on the detection of prompt fission neutrons from the 252Cf fission source.

42 ENGINEERING↗
DOE OSTI2022

The X-shaped Radio Galaxy J0725+5835 is Associated with an AGN Pair

X-shaped radio galaxies (XRGs) are those that exhibit two pairs of unaligned radio lobes (main radio lobes and wings). One of the promising models for the peculiar morphology is jet reorientation. To clarify this, we conducted a 5 GHz observation with the European VLBI Network (EVN) of XRG J0725+5835, which resembles the archetypal binary active galactic nuclei (AGNs) 0402+379 in radio morphology, but it is larger in angular size. In our observation, two milliarcsecond-scale radio components with nonthermal radio emission are detected. Each of them coincides with an optical counterpart with similar photometric redshift and (optical and infrared) magnitude, corresponding to dual active nuclei. Furthermore, with the improved Very Large Array (VLA) images, we find a bridge between the two radio cores and a jet bending in the region surrounding the companion galaxy. This further supports the interplay between the main and companion galaxies. In addition, we also report the discovery of an arcsecond-scale jet in the companion. Given the projected separation of ~100 kpc between the main and companion galaxies, XRG J0725+5835 is likely associated with a dual jetted-AGN system. In both EVN and VLA observations, we find signatures that the jet is changing its direction, which is likely responsible for the X-shaped morphology. For the origin of jet reorientation, several scenarios are discussed.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Sol-gel processing of a covalent organic framework for the generation of hierarchically porous monolithic adsorbents

Covalent organic frameworks (COFs) have emerged as a versatile material platform for such applications as chemical separations, chemical reaction engineering, and energy storage. Their inherently low mechanical stability, however, frequently renders existing methods of pelletization ineffective, contributing to pore collapse, pore blockage, or insufficient densification of crystallites. Here, we present a process for the shaping and densifying of COFs into robust centimeter-scale porous monoliths without the need for templates, additives, or binders. This process minimizes mechanical damage from shear-induced plastic deformation and further provides a network of interparticle mesopores that we exploit in accessing analyte capacities above those achievable from the intrinsic COF structure. Using a lattice-gas model, we accurately capture the monolithic structure across the mesoporous range and tie pore architecture to performance in both gas-storage and -separation applications. Collectively, these results represent a substantial step in the practical applicability of COFs and other mechanically weak porous materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Multisubstrate specificity shaped the complex evolution of the aminotransferase family across the tree of life

Aminotransferases (ATs) are an ancient enzyme family that play central roles in core nitrogen metabolism, essential to all organisms. However, many of the AT enzyme functions remain poorly defined, limiting our fundamental understanding of the nitrogen metabolic networks that exist in different organisms. Here, we traced the deep evolutionary history of the AT family by analyzing AT enzymes from 90 species spanning the tree of life (ToL). We found that each organism has maintained a relatively small and constant number of ATs. Mapping the distribution of ATs across the ToL uncovered that many essential AT reactions are carried out by taxon-specific AT enzymes due to wide-spread nonorthologous gene displacements. This complex evolutionary history explains the difficulty of homology-based AT functional prediction. Biochemical characterization of diverse aromatic ATs further revealed their broad substrate specificity, unlike other core metabolic enzymes that evolved to catalyze specific reactions today. Interestingly, however, we found that these AT enzymes that diverged over billion years share common signatures of multisubstrate specificity by employing different nonconserved active site residues. These findings illustrate that AT family enzymes had leveraged their inherent substrate promiscuity to maintain a small yet distinct set of multifunctional AT enzymes in different taxa. This evolutionary history of versatile ATs likely contributed to the establishment of robust and diverse nitrogen metabolic networks that exist throughout the ToL. The study provides a critical foundation to systematically determine diverse AT functions and underlying nitrogen metabolic networks across the ToL.

59 BASIC BIOLOGICAL SCIENCES↗