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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 NTRS2000

Metastable Eutectic Equilibrium in Natural Environments: Recent Developments and Research Opportunities

Chemical ordering at metastable eutectics was recognized in non-equilibrium gas-to- solid condensation experiments to constrain 'silicate' dust formation in O-rich circumstellar environments. The predictable metastable eutectic behavior successfully predicted the observed ferromagnesiosilica, compositions of circumstellar dust, presolar and solar nebula grains in the matrix of the collected aggregate IDPs. Many of the experimentally determined metastable eutectic solids match the fundamental building blocks of common rock-forming layer silicates: this could have implications for the origin of Life. The physical conditions conducive to metastable eutectic behavior, i.e. high temperature and (ultra)fast quenching, lead to unique amorphous, typically nano- to micrometer-sized, materials. The new paradigm of metastable eutectic behavior opens the door to new and exciting research opportunities in uncovering the many implications of these unique amorphous and typically nano- to micrometer-sized, metastable eutectic materials.

Rietmeijer, Fans J. M.↗
DOE OSTI2023

Mean Field Theory of Self‐Organizing Memristive Connectomes

Abstract Biological neuronal networks are characterized by nonlinear interactions and complex connectivity. Given the growing impetus to build neuromorphic computers, understanding physical devices that exhibit structures and functionalities similar to biological neural networks is an important step toward this goal. Self‐organizing circuits of nanodevices are at the forefront of the research in neuromorphic computing, as their behavior mimics synaptic plasticity features of biological neuronal circuits. However, an effective theory to describe their behavior is lacking. This study provides for the first time an effective mean field theory for the emergent voltage‐induced polymorphism of circuits of a nanowire connectome, showing that the behavior of these circuits can be explained by a low‐dimensional dynamical equation. The equation can be derived from the microscopic dynamics of a single memristive junction in analytical form. The effective model is tested on experiments of nanowire networks and show that it fits both the potentiation and depression of these synapse‐mimicking circuits. It is shown that this theory applies beyond the case of nanowire networks by formulating a general mean‐field theory of conductance transitions in self‐organizing memristive connectomes.

Caravelli, Francesco↗
DOE OSTI2021

Thermo-mechanical characterization of shale using nanoindentation

Abstract Shale can be a potential buffer for high-level radioactive nuclear wastes. To be an effective buffer while subject to waste heat, shale's mechanical response at elevated temperature must be known. Many researchers have experimentally characterized the mechanical behavior of various shales at different length scales in adiabatic conditions. However, its mechanical performance at elevated temperatures at the nano-scale remains unknown. To investigate the temperature dependency of nanomechanical properties of shale, we conducted both experimental and numerical studies. In this study, we measured mechanical and fracture properties of shale, such as hardness, elastic modulus, anisotropy, and fracture toughness from 25 °C up to 300 °C at different bedding planes. Statistical analysis of the results suggests that hardness and fracture toughness significantly increased at temperatures from 100 to 300 °C; while, temperature does not have a significant impact on elastic modulus. Data also shows that the bedding plane orientations have a substantial impact on both mechanical and fracture properties of shale at the nano-scale leading to distinct anisotropic behavior at elevated temperature below 100 °C. Additionally, we numerically investigated the mechanical performance of the shale samples at room temperature to gain an insight into its mechanical response through the thickness. Numerical results were validated against the experimental results, confirming the simulation can be used to predict shale deformation at the nano-scale or potentially be used in multi-scale simulations.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Boiling peak heat flux for steady inhomogeneous heat transfer in superfluid He 4

Superfluid helium-4 (He II) is a widely adopted coolant in scientific and engineering applications owing to its exceptional heat transfer capabilities. However, boiling can spontaneously occur on a heating surface in He II when the heat flux exceeds a threshold value $q^*$, referred to as the peak heat flux. While the parameter $q^*$ holds paramount importance in the design of He II based cooling systems, extensive research has primarily focused on its behavior in steady homogeneous heat transfer from a flat heating surface. For inhomogeneous heat transfer from curved surfaces, $q^*$ exhibits intricate dependance on parameters such as the He II bath temperature $T_b$, the immersion depth $h$, and the curvature radius $R_0$ of the heating surface. A comprehensive understanding on how $q^*$ depends on these parameters remains elusive. In this paper, we report our systematic study on $q^*$ for steady heat transfer from cylindrical and spherical heaters in He II. We compute $q^*$ for a wide range of parameter combinations $(T_b, h, R_0)$ by solving the He II two-fluid equations of motion. The generated data have allowed us to develop a robust correlation that accurately reproduces $q^*$ for all the parameter combinations we explored. Furthermore, our findings, particularly the establishment of the correlation, carry valuable implications for emergent applications that involve steady inhomogeneous heat transfer in He II systems.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Strym: A Python Package for Real-time CAN Data Logging, Analysis and Visualization to Work with USB-CAN Interface

In this report, we describe a data analysis tool developed for decoding and analyzing vehicle data obtained from a passenger vehicle’s onboard controller area network (CAN) bus. The tool developed in this paper provides a timeseries framework to perform domain-specific analysis at scale when interpreting data from a vehicle or a collection of vehicles in light of how to design intelligent vehicle applications. The tool, called Strym, exploits the CAN bus mechanism of modern vehicles to capture data using commercially available CAN-to-USB hardware Comma.ai Panda devices, managed through open-source software Libpanda. Strym permits the decoding of vendor-specific CAN messages in a vehicle-agnostic manner. Through this, a researcher can characterize data throughput, assess data quality, and perform analyses. Such analyses are useful in a number of research such as studying human driving behavior in mixed-autonomy, new driver models, rare-event detection, traffic flow estimation, and custom control of vehicles.

Performance evaluation, Smart cities, Intelligent ↗
DOE OSTI2020

Modular Growth and Nucleation Formulations in Modular Plasticity Models

Recent investigations like the second and third Sandia Fracture Challenges have characterized and demonstrated the performance of a variety of failure techniques and models. These surveys have considered a wide breadth of models encapsulating both general failure criteria as well as those focusing on pore nucleation and growth. Extensive reviews exist on both topics. The former category generally consists of classic models like the Johnson-Cook or Wilkins criteria. These models were recently added to modular plasticity models in the Library of Advanced Materials for Engineering (LAME) as criteria for use with element death capabilities. The latter category was not treated in that effort. There exists a large class of failure models based on predicting the evolution of pores and failure associated with such microstructures. While the exact mechanisms and corresponding impact on the macroscale behavior remain an active area of research, a large suite of formulations have been proposed combining different features of both pore nucleation and subsequent growth. The most famous of these are based on the popular Gurson model of pore growth derived via micromechanical analysis assuming a plastically incompressible matrix. Numerous other models exist for both growth and nucleation and the Cocks-Ashby growth and Horstemeyer-Gokhale nucleation models have been used successfully in recent Sandia Fracture Challenges. This specific combination is colloquially referred to as the "BCJ-failure model as it has been frequently used with the Bammann-Chisea-Johnson plasticity model.

36 MATERIALS SCIENCE↗
DOE OSTI2020

How Low Can You Go? Using Synthetic 3D Imagery to Drastically Reduce Real-World Training Data for Object Detection

Deep convolutional neural networks (DCNNs) currently provide state-of-the-art performance on image classification and object detection tasks, and there are many global security mission areas where such models could be extremely useful. Crucially, the success of these models is driven in large part by the widespread availability of high-quality open source data sets such as Image Net, Common Objects in Context (COCO), and KITTI, which contain millions of images with thousands of unique labels. However, global security relevant objects-of-interest can be difficult to obtain: relevant events are low frequency and high consequence; the content of relevant images is sensitive; and adversaries and proliferators seek to obscure their activities. For these cases where exemplar data is hard to come-by, even fine-tuning an existing model with available data can be effectively impossible. Recent work demonstrated that models can be trained using a combination of real-world and synthetic images generated from 3D representations; that such models can exceed the performance of models trained using real-world data alone; and that the generated images need not be perfectly realistic (Tremblay, et al., 2018). However, this approach still required hundreds to thousands of real-world images for training and fine tuning, which for sparse, global security-relevant datasets can be an unrealistic hurdle. In this research, we validate the performance and behavior of DCNN models as we drive the number of real-world images used for training object detection tasks down to a minimal set. We perform multiple experiments to identify the best approach to train DCNNs from an extremely small set of real-world images. In doing so, we: Develop state-of-the-art, parameterized 3D models based on real-world images and sample from their parameters to increase the variance in synthetic image training data; Use machine learning explainability techniques to highlight and correct through targeted training the biases that result from training using completely synthetic images; and Validate our results by comparing the performance of the models trained on synthetic data to one another, and to a control model created by fine-tuning an existing ImageNet-trained model with a limited number (hundreds) of real-world images.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

From Chaos to Clarity: Autonomous Materials Discovery for Extreme Environments [Slides]

The pursuit of advanced functional materials for energy applications demands an understanding of their behavior under the most challenging conditions. Extreme environments, characterized by intense radiation, high temperatures, and corrosive chemistries, push materials to their limits, often revealing unexpected behaviors and degradation pathways. Traditional materials research approaches, relying on trial-and-error experimentation, are often slow and resource-intensive, ill-suited to the complexities of extreme environments. This talk will explore the transformative potential of autonomous materials science in revolutionizing our understanding of materials synthesis and degradation in extreme environments. By integrating advanced microscopy techniques, artificial intelligence, and robotic experimentation, we can accelerate the discovery and design of resilient materials for a sustainable future. The presentation will highlight recent breakthroughs in autonomous microscopy, computer vision, and machine learning, showcasing their ability to unravel complex material transformations at the atomic scale. The talk will also delve into the challenges and opportunities associated with deploying autonomous systems to probe extreme environments, emphasizing the importance of robust algorithms, real-time data analysis, and adaptive experimentation. The ultimate goal is to empower scientists with unprecedented capabilities to explore, understand, and engineer materials that can withstand the harshest conditions, paving the way for innovations in energy, aerospace, and beyond.

14 SOLAR ENERGY↗
NASA NTRS1966

Information Flow in an R and D Laboratory

Statistical analysis of hypotheses concerning roles of technological gatekeeper and primary groups in flow of information in small research and development laboratory

EXPECTANCY HYPOTHESIS↗
NASA NTRS1976

Experiments on the properties of superfluid helium in zero gravity

The paper describes a research program designed to study the behavior of superfluid liquid helium in low and zero gravity in order to determine the properties which are critically important to its use as a stored cryogen for cooling scientific instruments aboard spacecraft for periods up to several months. The experiment program consists of a series of flights of an experiment package on a free-fall trajectory both on an aircraft and on a rocket. The objectives are to study thickness of thin films of helium as a function of acceleration, heat transfer in thin films, heat transfer across copper-liquid helium interfaces, fluid dynamics of bulk helium in high and low accelerations and under various conditions of rotations, alternate methods of separation of liquid and vapor phases and of efficient venting of the vapor, and undesirable thermomechanical oscillations in the vent pipes. Preliminary results from aircraft tests are discussed.

Mason, P.↗
NASA NTRS1985

The space station and human productivity: An agenda for research

Organizational problems in permanent organizations in outer space were analyzed. The environment of space provides substantial opportunities for organizational research. Questions about how to organize professional workers in a technologically complex setting with novel dangers and uncertainties present in the immediate environment are examined. It is suggested that knowledge from organization theory/behavior is an underutilized resource in the U.S. space program. A U.S. space station will be operable by the mid-1990's. Organizational issues will take on increasing importance, because a space station requires the long term organization of human and robotic work in the isolated and confined environment of outer space. When an organizational analysis of the space station is undertaken, there are research implications at multiple levels of analysis: for the individual, small group, organizational, and environmental levels of analysis. The research relevant to organization theory and behavior is reviewed.

Schoonhoven, C. B.↗
NASA NTRS1986

Planetary spectroscopy

Infrared spectroscopic studies of the solar system in support of spacecraft investigations were researched. The studies include the physical behavior of comets, the atmospheres of the gaseous planets, and the solid surfaces of satellites and asteroids. Studies of the gaseous and solid emanations of comets using the techniques of CCD spectroscopy and imaging were focused on. An intensive observational effort was mounted, to observe comet Halley with the recently developed state of the art CCD camera system. Comet P/Giacobini-Zinner was observed. The major emphasis was placed on spectroscopy and a synoptic spectrum at least once a month was obtained. A large number of images of Halley for particular emission species and continuum regions were also obtained. The species in vestigated were: C3 (4060 A), CO+ (4505), C2 (5139), NH2 (5980), H2O+ (6185), OI (6300) and CN (9180).

Fink, U.↗
NASA NTRS1988

Spacecraft Fire Detection and Extinguishment: A Bibliography

Pertinent fire detection and extinguishment references have been identified to further the knowledge of spacecraft fire safety. To broaden the scope of the bibliography, other unusual environments, e.g., aircraft, submarine, ship, have been included. In addition, for a more comprehensive view of the spacecraft fire safety problem, selected subjects are included, e.g., materials flammability, smoke, human behavior. The references will provide the researcher with access to state-of-the-art and historic works. Selected references from the 1960's have been included, but the emphasis is on references published from 1975 to 1987. The references are arranged by very broad categories. Often a paper will cover more than one topic, but for the purposes of this bibliography it will be cited only once.

Jason, Nora H.↗
NASA NTRS1988

Environment assisted degradation mechanisms in advanced light metals

The general goals of the research program are to characterize alloy behavior quantitatively and to develop predictive mechanisms for environmental failure modes. Successes in this regard will provide the basis for metallurgical optimization of alloy performance, for chemical control of aggressive environments, and for engineering life prediction with damage tolerance and long term reliability.

Gangloff, Richard P.↗
NASA NTRS1991

Manipulation strategies for massive space payloads

The industrial and environmental applications for robots with a relatively large workspace has increased significantly in the last few years. To accommodate the demands, the manipulator is usually designed with long, lightweight links that are inherently flexible. Ongoing research at Georgia Tech into the behavior and design of these flexible links is discussed.

Book, Wayne J.↗
NASA NTRS1991

Effects of floor location on response of composite fuselage frames

Experimental and analytical results are presented which show the effect of floor placement on the structural response and strength of circular fuselage frames constructed of graphite-epoxy composite material. The research was conducted to study the behavior of conventionally designed advanced composite aircraft components. To achieve desired new designs which incorporate improved energy absorption capabilities requires an understanding of how these conventional designs behave under crash type loadings. Data are presented on the static behavior of the composite structure through photographs of the frame specimen, experimental strain distributions, and through analytical data from composite structural models. An understanding of this behavior can aid dynamist in predicting the crash behavior of these structures and may assist the designer achieve improved designs for energy absorption and crash behavior of future structures.

Carden, Huey D.↗
NASA NTRS1993

Droplet turbulence interactions under subcritical and supercritical conditions

The goal of this research is to experimentally characterize the behavior of droplets in vaporizing liquid sprays under conditions typical of those encountered in high pressure combustion systems such as liquid fueled rocket engines. Of particular interest are measurements of droplet drag, droplet heating, droplet vaporization, droplet distortion, and secondary droplet breakup, under both subcritical and supercritical conditions. The paper presents a brief description of the specific accomplishments which have been made over the past year.

Coy, E. B.↗