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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 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
NASA NTRS2003

Technology Development Activities for the Space Environment and its Effects on Spacecraft

Reducing size and weight of spacecraft, along with demanding increased performance capabilities, introduces many uncertainties in the engineering design community on how emerging microelectronics will perform in space. The engineering design community is forever behind on obtaining and developing new tools and guidelines to mitigate the harmful effects of the space environment. Adding to this complexity is the push to use Commercial-off-the-shelf (COTS) and shrinking microelectronics behind less shielding and the potential usage of unproven technologies such as large solar sail structures and nuclear electric propulsion. In order to drive down these uncertainties, various programs are working together to avoid duplication, save what resources are available in this technical area and possess a focused agenda to insert these new developments into future mission designs. This paper will describe the relationship between the Living With a Star (LWS): Space Environment Testbeds (SET) Project and NASA's Space Environments and Effects (SEE) Program and their technology development activities funded as a result from the recent SEE Program's NASA Research Announcement.

Kauffman, Billy↗
NASA NTRS2008

Parts Selection for Space Systems - An Overview and Radiation Perspective

This viewgraph presentation describes the selection of electronic parts for aerospace systems from a space radiation perspective. The topics include: 1) The Trade Space Involved with Part Selection; 2) Understanding Risk; 3) Technical/Design Aspects; 4) Programmatic Overview; 5) Radiation Perspective; 6) Reliability Considerations; 7) An Example Ad hoc Battle; and 8) Sources of Radiation Data.

LaBel, Kenneth A.↗
NASA NTRS2017

NASA Past, Present, and Future: The Use of Commercial Off The Shelf (COTS) Electronics in Space

NASA has a long history of using commercial grade electronics in space. In this presentation we will provide a brief history of NASA's trends and approaches to commercial grade electronics focusing on processing and memory systems. This will include providing summary information on the space hazards to electronics as well as NASA mission trade space. We will also discuss developing recommendations for risk management approaches to Electrical, Electronic and Electromechanical (EEE) parts usage in space. Two examples will be provided focusing on a near-earth Polar-orbiting spacecraft as well as a mission to Mars. The final portion will discuss emerging trends impacting usage.

Commercial off the Shelf (COTS); Electronic and El↗
NASA NTRS2017

NASA Past, Present, and Future: The Use of Commercial Off The Shelf (COTS) Electronics in Space

NASA has a long history of using commercial grade electronics in space. In this presentation we will provide a brief history of NASA's trends and approaches to commercial grade electronics focusing on processing and memory systems. This will include providing summary information on the space hazards to electronics as well as NASA mission trade space. We will also discuss developing recommendations for risk management approaches to Electrical, Electronic and Electromechanical (EEE) parts usage in space. Two examples will be provided focusing on a near-earth Polar-orbiting spacecraft as well as a mission to Mars. The final portion will discuss emerging trends impacting usage.

Electronic and Electromechanical (EEE) parts↗
NASA NTRS1975

Acreage estimation, feature selection, and signature extension dependent upon the maximum likelihood decision rule

A maximum likelihood estimation technique is used for the analysis of agricultural remote sensor data. The m-class probability of misclassification is estimated using unlabeled test samples and labeled training samples. A bound on the variance of a proposed unbiased estimator of the m-class probability of error is derived. The particular case in which each class density is assumed to be a mixture of multivariate normal densities is considered. The extension of spectral signatures in space and time is discussed.

Quirein, J. A.↗
NASA NTRS1998

Preliminary Flight Results of the Microelectronics and Photonics Test Bed: NASA DR1773 Fiber Optic Data Bus Experiment

NASA Goddard Spare Flight Center's (GSFC) Dual Rate 1773 (DR1773) Experiment on the Microelectronic and Photonic Test Bed (MPTB) has provided valuable information on the performance of the AS 1773 fiber optic data bus in the space radiation environment. Correlation of preliminary experiment data to ground based radiation test results show the AS 1773 bus is employable in future spacecraft applications requiring radiation tolerant communication links.

Jackson, George L.↗
NASA NTRS2004

Assurance Against Radiation Effects on Electronics

Contents include the following: The Space Radiation Environment. The Effects on Electronics. The Environment in Action. NASA Approaches to Commercial Electronics: the mission mix, flight projects, and proactive research. Final Thoughts: atomic interactions, direct ionization, interaction with nucleus.

LaBel, Kenneth A.↗
NASA NTRS1995

Hair-cell counts and afferent innervation patterns in the cristae ampullares of the squirrel monkey with a comparison to the chinchilla

1. The numbers of type I and type II hair cells were estimated by dissector techniques applied to semithin, stained sections of the horizontal, superior, and posterior cristae in the squirrel monkey and the chinchilla. 2. The crista in each species was divided into concentrically arranged central, intermediate, and peripheral zones of equal areas. The three zones can be distinguished by the sizes of individual hair cells and calyx endings, by the density of hair cells, and by the relative frequency of calyx endings innervating single or multiple type I hair cells. 3. In the monkey crista, type I hair cells outnumber type II hair cells by a ratio of almost 3:1. The ratio decreases from 4-5:1 in the central and intermediate zones to under 2:1 in the peripheral zone. For the chinchilla, the ratio is near 1:1 for the entire crista and decreases only slightly between the central and peripheral zones. 4. Nerve fibers supplying the cristae in the squirrel monkey were labeled by extracellular injections of horseradish peroxidase (HRP) into the vestibular nerve. Peripheral terminations of individual fibers were reconstructed and related to the zones of the cristae they innervated and to the sizes of their parent axons. Results were similar for the horizontal, superior, and posterior cristae. 5. Axons seldom bifurcate below the neuroepithelium. Most fibers begin branching shortly after crossing the basement membrane. Their terminal arbors are compact, usually extending no more than 50-100 microns from the parent exon. A small number of long intraepithelial fibers enter the intermediate and peripheral zones of the cristae near its base, then run unbranched for long distances through the neuroepithelium to reach the central zone. 6. There are three classes of afferent fibers innervating the monkey crista. Calyx fibers terminate exclusively on type I hair cells, and bouton fibers end only on type II hair cells. Dimorphic fibers provide a mixed innervation, including calyx endings to type I hair cells and bouton endings to type II hair cells. Long intraepithelial fibers are calyx and dimorphic units, whose terminal fields are similar to those of other fibers. The central zone is innervated by calyx and dimorphic fibers; the peripheral zone, by bouton and dimorphic fibers; and the intermediate zone, by all three kinds of fibers. Internal (axon) diameters are largest for calyx fibers and smallest for bouton fibers. Of the entire sample of 286 labeled fibers, 52% were dimorphic units, 40% were calyx units, and 8% were bouton units.(ABSTRACT TRUNCATED AT 400 WORDS).

Non-NASA Center↗
NASA NTRS1994

Refining fuzzy logic controllers with machine learning

In this paper, we describe the GARIC (Generalized Approximate Reasoning-Based Intelligent Control) architecture, which learns from its past performance and modifies the labels in the fuzzy rules to improve performance. It uses fuzzy reinforcement learning which is a hybrid method of fuzzy logic and reinforcement learning. This technology can simplify and automate the application of fuzzy logic control to a variety of systems. GARIC has been applied in simulation studies of the Space Shuttle rendezvous and docking experiments. It has the potential of being applied in other aerospace systems as well as in consumer products such as appliances, cameras, and cars.

Berenji, Hamid R.↗
NASA NTRS1990

The vestibular nerve of the chinchilla. III. Peripheral innervation patterns in the utricular macula

1. Nerve fibers supplying the utricular macula of the chinchilla were labeled by extracellular injection of horseradish peroxidase into the vestibular nerve. The peripheral terminations of individual fibers were reconstructed and related to the regions of the end organ they innervated and to the sizes of their parent axons. 2. The macula is divided into medial and lateral parts by the striola, a narrow zone that runs for almost the entire length of the sensory epithelium. The striola can be distinguished from the extrastriolar regions to either side of it by the wider spacing of its hair cells. Calyx endings in the striola have especially thick walls, and, unlike similar endings in the extrastriola, many of them innervate more than one hair cell. The striola occupies 10% of the sensory epithelium; the lateral extrastriola, 50%; and the medial extrastriola, 40%. 3. The utricular nerve penetrates the bony labyrinth anterior to the end organ. Axons reaching the anterior part of the sensory epithelium run directly through the connective tissue stroma. Those supplying more posterior regions first enter a fiber layer located at the bottom of the stroma. Approximately one-third of the axons bifurcate below the epithelium, usually within 5-20 microns of the basement membrane. Bifurcations are more common in fibers destined for the extrastriola than for the striola. 4. Both calyx and bouton endings were labeled. Calyces can be simple or complex. Simple calyces innervate individual hair cells, whereas complex calyces supply 2-4 adjacent hair cells. Complex endings are more heavily concentrated in the striola than in the extrastriola. Simple calyces and boutons are found in all parts of the epithelium. Calyces emerge from the parent axon or one of its thick branches. Boutons, whether en passant or terminal, are located on thin collaterals. 5. Fibers can be classified into calyx, bouton, or dimorphic categories. The first type only has calyx endings; the second, only bouton endings; and the third, both kinds of endings. Calyx units make up 6% of the labeled fibers, bouton units less than 2%, and dimorphic units greater than 92%. The three fiber types differ in the macular zones they supply and in the diameters of their parent axons. Calyx units were restricted to the striola. The few bouton units were found in the extrastriola.(ABSTRACT TRUNCATED AT 400 WORDS).

NASA Discipline Neuroscience↗
DOE OSTI2021

Tensorized Feature Spaces for Feature Explosion

In this paper 1 1 This manuscript has been authored by UT-Battelle, LLC under Contract No. DE-AC05-000R22725 with the U.S. Department of Energy. The United States Government retains and the publisher, by accepting the article for publication, acknowledges that the United States Government retains a nonexclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this manuscript, or allow others to do so, for United States Government purposes. The Department of Energy will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan (http://energy.gov/downloads/doe-public-access-plan) This research used resources of the Oak Ridge Leadership Computing Facility, which is a DOE Office of Science User Facility supported under Contract DE-AC05-000R22725., we present a novel framework that uses tensor factorization to generate richer feature spaces for pixel classification in hyperspectral images. In particular, we assess the performance of different tensor rank decomposition methods as compared to the traditional kernel-based approaches for the hyperspectral image classification problem. We propose Orion, which takes as input a hyperspectral image tensor and a rank and outputs an enhanced feature space from the factor matrices of the decomposed tensor. Our method is a feature explosion technique that inherently maps low dimensional input space in $\mathbb{R}^{K}$ to high dimensional space in $\mathbb{R}^{R}$ , where $R\gg K$ , say in the order of 1000x, like a kernel. We show how the proposed method exploits the multi-linear structure of hyperspectral three dimensional tensor. We demonstrate the effectiveness of our method with experiments on three publicly available hyperspectral datasets with labeled pixels and compare their classification performance against traditional linear and non-linear supervised learning methods such as SVM with Linear, Polynomial, RBF kernels, and the Multi-Layer Perceptron model. Finally, we explore the relationship between the rank of the tensor decomposition and the classification accuracy using several hyperspectral datasets with ground truth.

Pasricha, Ravdeep Singh↗
DOE OSTI2024

Convolutional Variational Autoencoder-based Unsupervised Learning for Power Systems Faults

Classification of power system event data is a growing need, particularly where non-protective relaying-based sensors are used to monitor grid performance. Given the high burden of obtaining event data with appropriate labeling, an unsupervised approach is highly valuable. This approach enables using event data without labeling, which is far easier to obtain. This paper presents an unsupervised learning method to classify and label transients observed in the distribution grid. A Convolutional Variational Autoencoder (CVAE) was developed for this purpose. We demonstrate the efficacy of our approach using the transient data generated from the simulations. The simulation data is used to train the CVAE that identifies different faults as different clusters in the latent space. The clusters are then used as the foundation model to categorize the real-world data.

Alam, Maksudul↗
DOE OSTI2021

Label-free DNA biosensing by topological light confinement

Large-area and transparent all-dielectric metasurfaces sustaining photonic bound states in the continuum (BICs) provide a set of fundamental advantages for ultrasensitive biosensing. BICs bridge the gap of large effective mode volume with large experimental quality factor. Relying on the transduction mechanism of reactive sensing principle, herein, we first numerically study the potential of subwavelength confinement driven by topological decoupling from free space radiation for BIC-based biosensing. Then, we experimentally combine this capability with minimal and low-cost optical setup, applying the devised quasi-BIC resonator for PNA/DNA selective biosensing with real-time monitoring of the binding event. A sensitivity of 20 molecules per micron squared is achieved, i.e. ≃0.01 pg. Further enhancement can easily be envisaged, pointing out the possibility of single-molecule regime. This work aims at a precise and ultrasensitive approach for developing low-cost point-of-care tools suitable for routine disease prescreening analyses in laboratory, also adaptable to industrial production control.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Creating ground truth for nanocrystal morphology: a fully automated pipeline for unbiased transmission electron microscopy analysis

Control over colloidal nanocrystal morphology (size, size distribution, and shape) is important for tailoring the functionality of individual nanocrystals and their ensemble behavior. Despite this, traditional methods to quantify nanocrystal morphology are laborious. New developments in automated morphology classification will accelerate these analyses but the assessment of machine learning models is limited by human accuracy for ground truth, causing even unsupervised machine learning models to have inherent bias. Herein, we introduce synthetic image rendering to solve the ground truth problem of nanocrystal morphology classification. By simulating 2D images of nanocrystal shapes via a function of high-dimensional parameter space, we trained a convolutional neural network to link unique morphologies to their simulated parameters, defining nanocrystal morphology quantitatively rather than qualitatively. An automated pipeline then processes, quantitatively defines, and classifies nanocrystal morphology from experimental transmission electron microscopy (TEM) images. Using improved computer vision techniques, 42,650 nanocrystals were identified, assessed, and labeled with quantitative parameters, offering a 600-fold improvement in efficiency over best-practice manual measurements. Further, a classification algorithm was trained with a prediction accuracy of 99.5%, which can successfully analyze a range of concave, convex, and irregular nanocrystal shapes. The resulting pipeline was applied to differentiating two syntheses of nominally cuboidal CsPbBr 3 nanocrystals and uniquely classifying binary nickel sulfide nanocrystal phase based on morphology. This pipeline provides a simple, efficient, and unbiased method to quantify nanocrystal morphology and represents a practical route to construct large datasets with an absolute ground truth for training unbiased morphology-based machine learning algorithms.

77 NANOSCIENCE AND NANOTECHNOLOGY↗