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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 649 records · Page 36
All sourcesNASA NTRSDOE OSTI
NASA NTRS1972

Development of automatic through-insulation welding for microelectric interconnections

The capability to automatically route, remove insulation from, and weld small-diameter solid conductor wire is presented. This would facilitate the economical small-quantity production of complex miniature electronic assemblies. An engineering model of equipment having this capability was developed and evaluated. Whereas early work in the use of welded magnet wire interconnections was concentrated on opposed electrode systems, and generally used heat to melt the wire insulation, the present method is based on a concentric electrode system and a wire feed system which splits the insulation by application of pressure prior to welding. The work deals with the design, fabrication, and evaluation testing of an improved version of this concentric electrode system. Two different approaches to feeding the wire to the concentric electrodes were investigated. It was concluded that the process is feasible for the interconnection of complex miniature electronic assemblies.

Arnett, J. C.↗
NASA NTRS2016

Hybrid Reality Lab Capabilities - Video 2

Our Hybrid Reality and Advanced Operations Lab is developing incredibly realistic and immersive systems that could be used to provide training, support engineering analysis, and augment data collection for various human performance metrics at NASA. To get a better understanding of what Hybrid Reality is, let's go through the two most commonly known types of immersive realities: Virtual Reality, and Augmented Reality. Virtual Reality creates immersive scenes that are completely made up of digital information. This technology has been used to train astronauts at NASA, used during teleoperation of remote assets (arms, rovers, robots, etc.) and other activities. One challenge with Virtual Reality is that if you are using it for real time-applications (like landing an airplane) then the information used to create the virtual scenes can be old (i.e. visualized long after physical objects moved in the scene) and not accurate enough to land the airplane safely. This is where Augmented Reality comes in. Augmented Reality takes real-time environment information (from a camera, or see through window, and places digitally created information into the scene so that it matches with the video/glass information). Augmented Reality enhances real environment information collected with a live sensor or viewport (e.g. camera, window, etc.) with the information-rich visualization provided by Virtual Reality. Hybrid Reality takes Augmented Reality even further, by creating a higher level of immersion where interactivity can take place. Hybrid Reality takes Virtual Reality objects and a trackable, physical representation of those objects, places them in the same coordinate system, and allows people to interact with both objects' representations (virtual and physical) simultaneously. After a short period of adjustment, the individuals begin to interact with all the objects in the scene as if they were real-life objects. The ability to physically touch and interact with digitally created objects that have the same shape, size, location to their physical object counterpart in virtual reality environment can be a game changer when it comes to training, planning, engineering analysis, science, entertainment, etc. Our Project is developing such capabilities for various types of environments. The video outlined with this abstract is a representation of an ISS Hybrid Reality experience. In the video you can see various Hybrid Reality elements that provide immersion beyond just standard Virtual Reality or Augmented Reality.

Delgado, Francisco J.↗
NASA NTRSDate not supplied

A Cradle to Grave Testbed: Formulating and Screening Solid Rocket Motor Insulation Using In-House Capabilities

Since 2013, NASA and Jacobs contractors have worked together to develop the capability to mix rubber insulation for solid rocket motors. This capability was born out of the need to replace obsolete materials in the original rubber insulation used in full scale boosters. As a result of this effort, EM41 currently has the capability of mixing a variety of rubber insulations and characterizing them rheologically, mechanically and thermally completely in house and with minimal turnaround time.

Spencer Griffin↗
NASA NTRS1977

Development of a curved pipe capability for the NASTRAN finite element program

A curved pipe element capability for the NASTRAN structural analysis program is developed using the NASTRAN dummy element feature. A description is given of the theory involved in the subroutines which describe stiffness, mass, thermal and enforced deformation loads, and force and stress recovery for the curved pipe element. Incorporation of these subroutines into NASTRAN is discussed. Test problems are proposed. Instructions on use of the new element capability are provided.

Jeter, J. W., Jr.↗
DOE OSTI2020

2018 LDRD Annual Report (Argonne National Laboratory)

Argonne National Laboratory’s Laboratory Directed Research and Development (LDRD) program encourages the development of novel technical concepts, enhances the Laboratory’s research and development (R&D) capabilities, and enables pursuit of strategic laboratory goals. Argonne’s LDRD projects are proposal based and peer reviewed, supporting ideas that require advanced exploration so they can be sufficiently developed to pursue support through normal programmatic channels. Among the aims of the projects supported by the LDRD program are the establishment of engineering proofs of principle, assessment of design feasibility for prospective facilities, development of instrumentation or computational methods or systems, and discoveries in fundamental science and exploratory development. All LDRD projects have demonstrable ties to one or more of the science, energy, environment, and national security missions of the U.S. Department of Energy (DOE) and its National Nuclear Security Administration (NNSA), and many are also relevant to the missions of other federal agencies that sponsor work at Argonne. A natural consequence of the more “applied” type projects is their concurrent relevance to industry. The LDRD program is managed in overarching portfolios, each containing multiple projects each fiscal year. The LDRD Prime portfolio is further divided into strategic focus areas aligned with Argonne’s strategic plan. The largest component of Argonne’s program is LDRD Prime, which emphasizes R&D explicitly aligned with Laboratory major initiatives in support of Argonne’s strategic plan. The choice of Focus Areas under the LDRD Prime component reflects the major initiatives; the state of development of relevant technical fields; the potential value of advancing those fields to DOE/NNSA and the nation; and the compatibility of the fields with existing facilities, capabilities, and staff expertise at Argonne. Focus Areas with projects that ended in FY18 are: Advanced Computing, Biological and Environmental Science Capability Development, Energy Manufacturing Science and Engineering, Hard X-ray Sciences, Materials and Chemistry, Securing Energy and Critical Resources, and The Universe as Our Laboratory (ULab).

99 GENERAL AND MISCELLANEOUS↗
NASA NTRS2010

Use of Traditional and Novel Methods to Evaluate the Influence of an EVA Glove on Hand Performance

The gloved hand is one of an astronaut s primary means of interacting with the environment, and any restrictions imposed by the glove can strongly affect performance during extravehicular activity (EVA). Glove restrictions have been the subject of study for decades, yet previous studies have generally been unsuccessful in quantifying glove mobility and tactility. Past studies have tended to focus on the dexterity, strength, and functional performance of the gloved hand; this provides only a circumspect analysis of the impact of each type of restriction on the glove s overall capability. The aim of this study was to develop novel capabilities to provide metrics for mobility and tactility that can be used to assess the performance of a glove in a way that could enable designers and engineers to improve their current designs. A series of evaluations were performed to compare unpressurized and pressurized (4.3 psi) gloved conditions with the ungloved condition. A second series of evaluations were performed with the Thermal Micrometeoroid Garment (TMG) removed. This series of tests provided interesting insight into how much of an effect the TMG has on gloved mobility - in some cases, the presence of the TMG restricted glove mobility as much as pressurization did. Previous hypotheses had assumed that the TMG would have a much lower impact on mobility, but these results suggest that an improvement in the design of the TMG could have a significant impact on glove performance. Tactility testing illustrated the effect of glove pressurization, provided insight into the design of hardware that interfaces with the glove, and highlighted areas of concern. The metrics developed in this study served to benchmark the Phase VI EVA glove and to develop requirements for the next-generation glove for the Constellation program.

Benson, Elizabeth A.↗
DOE OSTI2020

Development of a predictive capability of short-pulse laser-driven broadband x-ray radiography

High intensity, short-pulse laser interaction with a solid metal target produces broadband hard x-rays potentially for various applications of x-ray radiography. In this work, experimental benchmarking of numerical modelling for short-pulse laser-driven broadband x-ray radiography is presented. Angular dependent x-ray spectra are first calculated with a hybrid particle-in-cell code, Large Scale Plasma (LSP), using fast electron parameters inferred from an analysis of measured bremsstrahlung signals. Subsequently, a calculated x-ray spectrum in the direction of radiography is used in photon transport calculations using a Monte Carlo code, Particle and Heavy Ion Transport code System (PHITS), to simulate a radiographic image including a modelled 3D test object, an x-ray attenuation filter and an image plate detector. Simulated radiographic images are compared with measurements obtained in an experiment using a 50-TW Leopard short-pulse laser at the University of Nevada Reno. Results show that simulations reproduce the experimental images well for three different attenuation filters (plastic, aluminium, and brass), while 1D transmission profiles for the plastic and aluminium filters are quantitatively in good agreement. The modelling approach established in this work could be used as a predictive tool to simulate radiographic images of complex 3D solid objects at any arbitrary angular position or to optimize experimental components such as the source spectrum, x-ray attenuation filters and a detector type depending on a radiographic object without carrying out radiographic experiments.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Anticipating Technical Expertise and Capability Evolution in Research Communities Using Dynamic Graph Transformers

The ability to anticipate global technical expertise and capability evolution trends is essential for national and global security, especially in safety-critical domains such as nuclear nonproliferation (NN) and rapidly emerging fields like artificial intelligence (AI). Here, in this work, we extend traditional statistical relational learning approaches (e.g., link prediction in collaboration networks) and formulate a problem of anticipating technical expertise and capability evolution using dynamic heterogeneous graph representations. We develop novel capabilities to forecast collaboration patterns, authorship behavior, and technical capability evolution at different granularities (e.g., scientist and institution levels) in two distinct research fields. We implement a dynamic graph transformer (DGT) neural architecture, which pushes the state-of-the-art graph neural network models by: 1) forecasting heterogeneous (rather than homogeneous) nodes and edges; and 2) relying on both discrete- and continuous-time inputs. We demonstrate that our DGT models predict collaboration, partnership, and expertise patterns with 0.26, 0.73, and 0.53 mean reciprocal rank values for AI and 0.48, 0.93, and 0.22 for NN domains. DGT model performance exceeds the best-performing static graph baseline models by 30%–80% across AI and NN domains. Our findings demonstrate that DGT models boost inductive task performance when previously unseen nodes appear in the test data for the domains with emerging collaboration patterns (e.g., AI). Specifically, models accurately predict which established scientists will collaborate with early career scientists and vice versa in the AI domain.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Quantifying the Known Unknown: Including Marine Sources of Greenhouse Gases in Climate Modeling

Researchers have recently estimated that Arctic submarine permafrost currently traps 60 billion tons of methane and contains 560 billion tons of organic carbon in seafloor sediments and soil, a giant pool of carbon with potentially large feedbacks on the climate system. Unlike terrestrial permafrost, the submarine permafrost system has remained a “known unknown” because of the difficulty in acquiring samples and measurements. Consequently, this potentially large carbon stock never yet considered in global climate models or policy discussions, represents a real wildcard in our understanding of Earth’s climate. This report summarizes our group’s effort at developing a numerical modeling framework designed to produce a first-of-its-kind estimate of Arctic methane gas releases from the marine sediments to the water column, and potentially to the atmosphere, where positive climate feedback may occur. Newly developed modeling capability supported by the Laboratory Directed Research and Development (LDRD) program at Sandia National Laboratories now gives us the ability to probabilistically map gas distribution and quantity in the seabed by using a hybrid approach of geospatial machine learning, and predictive numerical thermodynamic ensemble modeling. The novelty in this approach is its ability to produce maps of useful data in regions that are only sparsely sampled, a common challenge in the Arctic, and a major obstacle to progress in the past. By applying this model to the circum-Arctic continental shelves and integrating the flux of free gas from in situ methanogenesis and dissociating gas hydrates from the sediment column under climate forcing, we can provide the most reliable estimate of a spatially and temporally varying source term for greenhouse gas flux that can be used by global oceanographic circulation and Earth system models (such as DOE’s E3SM). The result will allow us to finally tackle the wildcard of the submarine permafrost carbon system, and better inform us about the severity of future national security threats that sustained climate change poses.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1976

Development of automated analytical capability for the early detection of diabetes mellitus

The total profile of volatile metabolites in urine of patients with diabetes mellitus was studied. Because of the drastic abnormalities in the metabolism of carbohydrates, lipids, and proteins connected with diabetes it was expected that apart from acetone further characteristic abnormalities occur in the profiles if volatile urinary metabolites in cases of diabetes mellitus. Quantitative and qualitative changes were found in these urines as compared to the urines of normal subjects.

Zlatkis, A.↗
NASA NTRS1987

Numerical modelling of cryogenic propellant behavior in low-G

A partial survey is presented of recent research, sponsored by the NASA Lewis Research Center, into the computational modelling of cryogenic propellant behavior in a low gravity environment. This presentation is intended to provide insight into some of the specific problems being studied and into how these studies are part of an integrated plan to develop predictive capabilities. A brief description of the computational models developed to analyze jet induced mixing in cryogenic propellant tankage is presented along with representative results. Similar information is presented for a recent examination of on-orbit self-pressurization. A study of propellant reorientation has recently been initiated and preliminary results are included. The presentation concludes with a list of ongoing efforts and projected goals.

Hochstein, John I.↗
NASA NTRS2018

An Educational Platform for Small Satellite Development with Proximity Operation Capabilities

An alternative to ground testing of small satellites is presented here, where the kinematics of a 3U underactuated CubeSat operating in 3 degrees-of-freedom (DOF) is reproduced by an omnidirectional wheeled platform, while satellite dynamics are simulated in real-time. The system is equipped with a relative navigation sensor in the form factor of a smartphone, the Smartphone Video Guidance Sensor (SVGS), allowing the platform to reproduce proximity operation maneuvers. The wheeled platform is used as an educational tool for students over a large range of academic levels, from high school to graduate school. A derivation of the kinematic relationship from satellite dynamics to rotacaster wheel velocities is presented, along with the guidance and control laws of the system. Simulation and experimental results demonstrate that the wheeled platform was able to successfully replicate detumble, slew, and attitude hold maneuvers of a 3U CubeSat.

Bertaska, Ivan R.↗