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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 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
NASA NTRS2013

Chemical Heterogeneity of a Large Cluster IDP: Clues to its Formation History Using X-ray Fluorescence Mapping and XANES Spectroscopy

Chondritic porous IDPs may be among the most primitive objects found in our solar system [1]. They consist of many micron to submicron minerals, glasses and carbonaceous matter [2,3,4,5,6,7] with > 10(exp 4) grains in a 10 micron cluster [8]. Speculation on the environment where these fine grained, porous IDPs formed varies with possible sources being presolar dusty plasma clouds, protostellar condensation, solar asteroids or comets [4,6,9]. Also, fine grained dust forms in our solar system today [10,11]. Isotopic anomalies in some particles in IDPs suggest an interstellar source[4,7,12]. IDPs contain relic particles left from the dusty plasma that existed before the protostellar disk formed and other grains in the IDPs formed later after the cold dense nebula cloud collapsed to form our protostar and other grains formed more recently. Fe and CR XANES spectroscopy is used here to investigate the oxygen environment in a large (>50 10 micron or larger sub-units) IDP. Conclusions: Analyzing large (>50 10 micron or larger sub-units) CP IDPs gives one a view on the environments where these fine dust grains formed which is different from that found by only analyzing the small, 10 micron IDPs. As with cluster IDP L2008#5 [3], L2009R2 cluster #13 appears to be an aggregate of grains that sample a diversity of solar and perhaps presolar environments. Sub-micron, grain by grain measurement of trace element contents and elemental oxidation states determined by XANES spectroscopy offers the possibility of understanding the environments in which these grains formed when compared to standard spectra. By comparing thermodynamic modeling of condensates with analytical data an understanding of transport mechanisms operating in the early solar system may be attained.

Wirick, S.↗
NASA NTRS2015

Emerging Materials Technologies That Matter to Manufacturers

A brief overview of emerging materials technologies. Exploring the weight reduction benefit of replacing Carbon Fiber with Carbon Nanotube (CNT) in Polymer Composites. Review of the benign purification method developed for CNT sheets. The future of manufacturing will include the integration of computational material design and big data analytics, along with Nanomaterials as building blocks.

nanomaterials↗
NASA NTRS2015

Using Earth Observations to Understand and Predict Infectious Diseases

This presentation discusses the processes from data collection and processing to analysis involved in unraveling patterns between disease outbreaks and the surrounding environment and meteorological conditions. We used these patterns to estimate when and where disease outbreaks will occur. As a case study, we will present our work on assessing the relationship between meteorological conditions and influenza in Central America. Our work represents the discovery, prescriptive and predictive aspects of data analytics.

public health↗
NASA NTRS2016

Empirical Analysis and Automated Classification of Security Bug Reports

With the ever expanding amount of sensitive data being placed into computer systems, the need for effective cybersecurity is of utmost importance. However, there is a shortage of detailed empirical studies of security vulnerabilities from which cybersecurity metrics and best practices could be determined. This thesis has two main research goals: (1) to explore the distribution and characteristics of security vulnerabilities based on the information provided in bug tracking systems and (2) to develop data analytics approaches for automatic classification of bug reports as security or non-security related. This work is based on using three NASA datasets as case studies. The empirical analysis showed that the majority of software vulnerabilities belong only to a small number of types. Addressing these types of vulnerabilities will consequently lead to cost efficient improvement of software security. Since this analysis requires labeling of each bug report in the bug tracking system, we explored using machine learning to automate the classification of each bug report as a security or non-security related (two-class classification), as well as each security related bug report as specific security type (multiclass classification). In addition to using supervised machine learning algorithms, a novel unsupervised machine learning approach is proposed. An ac- curacy of 92%, recall of 96%, precision of 92%, probability of false alarm of 4%, F-Score of 81% and G-Score of 90% were the best results achieved during two-class classification. Furthermore, an accuracy of 80%, recall of 80%, precision of 94%, and F-score of 85% were the best results achieved during multiclass classification.

Cybersecurity↗
NASA NTRS2017

Quantitative EPMA Compositional Mapping of NWA 2995: Characterization, and Petrologic Interpretation of Mafic Clasts

We present the first fully quantitative compositional maps of lunar meteorite NWA 2995 using electron microprobe stage mapping, and compare selected clast mineralogy and chemistry. NWA 2995 is a feldspathic fragmental breccia containing numerous highland fine grained lithologies, including anorthosite, norite, olivine basalt, subophitic basalt, gabbro, KREEP-like basalt, granulitic and glassy impact melts, coarse-grained mineral fragments, Fe-Ni metal, and glassy matrix [1]. Chips of NWA 2995, representing these diverse materials, were analyzed by INAA and fused-bead electron-probe microanalysis (EPMA); comparison of analytical data suggests grouping of lunar meteorites NWA 2995, 2996, 3190, 4503, 5151, and 5152. The mean composition of NWA 2995 corresponds to a 2:1 mixture of feldspathic and mare material, with approximately 5% KREEP component [2]. Clast mineral chemistry and petrologic interpretation of paired stone NWA 2996 has been reported by Mercer et al. [3], and Gross et al. [4]. This study combines advances in quantitative EPMA compositional mapping and data analysis, as applied to selected mafic clasts in a polished section of NWA 2995, to investigate the origin of mafic lithic components and to demonstrate a procedural framework for petrologic analysis.

Carpenter, P. K.↗
NASA NTRS2017

Advanced Software V&V for Civil Aviation and Autonomy

With the advances in high-computing platform (e.g., advanced graphical processing units or multi-core processors), computationally-intensive software techniques such as the ones used in artificial intelligence or formal methods have provided us with an opportunity to further increase safety in the aviation industry. Some of these techniques have facilitated building safety at design time, like in aircraft engines or software verification and validation, and others can introduce safety benefits during operations as long as we adapt our processes. In this talk, I will present how NASA is taking advantage of these new software techniques to build in safety at design time through advanced software verification and validation, which can be applied earlier and earlier in the design life cycle and thus help also reduce the cost of aviation assurance. I will then show how run-time techniques (such as runtime assurance or data analytics) offer us a chance to catch even more complex problems, even in the face of changing and unpredictable environments. These new techniques will be extremely useful as our aviation systems become more complex and more autonomous.

software assurance↗
NASA NTRS2017

The Challenges of Human-Autonomy Teaming

Machine intelligence is improving rapidly based on advances in big data analytics, deep learning algorithms, networked operations, and continuing exponential growth in computing power (Moores Law). This growth in the power and applicability of increasingly intelligent systems will change the roles humans, shifting them to tasks where adaptive problem solving, reasoning and decision-making is required. This talk will address the challenges involved in engineering autonomous systems that function effectively with humans in aeronautics domains.

artificial intelligence↗
NASA NTRS2017

The Challenges of Human-Autonomy Teaming

Machine intelligence is improving rapidly based on advances in big data analytics, deep learning algorithms, networked operations, and continuing exponential growth in computing power (Moores Law). This growth in the power and applicability of increasingly intelligent systems will change the roles humans, shifting them to tasks where adaptive problem solving, reasoning and decision-making is required. This talk will address the challenges involved in engineering autonomous systems that function effectively with humans in aeronautics domains.

Human-Autonomy teaming↗
NASA NTRS2018

Digital Technologies at NASA for Science and Engineering

While scientific and engineering advancements used to rely primarily on theoretical studies and physical experiments, today digital technology enabled by petaflops-scale supercomputers is an equal, if not a greater, contributor to such achievements. In addition, computational modeling and simulation serves as a predictive tool that is not otherwise available. As a result, the use of high performance computing is integral to NASA's work in all mission areas such as space exploration, aeronautics, and scientific discovery. But traditional supercomputing alone is not sufficient for all of the space agency's needs. The success of many NASA missions depends on solving complex computing challenges, some of which are NP-hard (decision theory) if using classical solution methods. Quantum computing promises an unprecedented ability to solve such intractable problems by harnessing quantum mechanical effects such as tunneling, superposition, and entanglement. Another disruptive digital technology is neuromorphic computing that uses brain-inspired lessons to generate new architectures that are much more energy efficient, and capable of massive parallel processing and learning in-situ. Finally, with large amounts of observational and computational data sets, the opportunities of big data and data analytics can be leveraged to enable deep learning and knowledge discovery - it's all a massive digital transformation. This talk will be an overview how NASA utilizes digital technologies for its science and engineering efforts.

Biswas, Rupak↗
NASA NTRS2015

Advanced Computing Support at NASA Advanced Supercomputing (NAS) Division

NAS (NASA Advanced Supercomputing) Division: Advanced Computing: High-End Computing Capability (HECC) Project; Quantum Artificial Intelligence Lab (QuAIL); NASA Earth Exchange (NEX); Data Analytics Infrastructure for NASA; Cloud Services for Science & Engineering Projects.

Advanced Computing↗
NASA NTRS2018

Overview of Artificial Intelligence (AI) at NASA Goddard

Artificial Intelligence (AI) is a collection of advanced technologies that allows machines to think and act, both humanly and rationally, through sensing, comprehending, acting and learning. AI's foundations lie at the intersection of several traditional fields Philosophy, Mathematics, Economics, Neuroscience, Psychology and Computer Science. Although the inception of AI started in the 1950's, it has recently made a strong comeback in all aspects of society and all over the world; this is mainly due to the timely combination of increased data volumes, advanced and mature algorithms, and improvements in computing power and storage. Current AI applications include big data analytics, robotics, intelligent sensing, assisted decision making, and speech recognition just to name a few. During the Tour, we will show a few examples of the current AI activities at NASA Goddard.

Le Moigne, Jacqueline↗
NASA NTRS2019

Modal Testing of a Flexible Wing on a Dynamically Active Test Fixture Using Fixed Base Correction Method - IFASD 2019

In modal testing and finite element model correlation, analysts desire modal results using free-free or rigid boundary conditions to ease comparisons of test versus analytical data. It is often expensive both in cost and schedule to build and test with boundary conditions that replicate the free-free or rigid boundaries. Static test fixtures for load testing are often large, heavy, and unyielding, but do not provide adequate boundaries for modal tests because they are dynamically too flexible and often contain natural frequencies within the test article frequency range of interest. The dynamic coupling between the test article and test fixture complicates the model updating process because significant effort needs to be spent on modeling the test fixture and boundary conditions in addition to the test article. If the modal results could be corrected for fixture coupling, then setups used for other structural testing could be adequate for modal testing and would allow significant schedule and cost savings by eliminating a unique setup for only modal testing. To simplify future modal tests, this paper reports on a fixed base correction method that was investigated during modal testing of a full-scale, half-span, flexible wing cantilevered from a static test fixture. The results of this fixed base correction approach look very promising. The method aided in producing similar wing modal characteristics for two different physical boundary configurations of a dynamically active test fixture.

modal testing↗
NASA NTRS2019

NASA Electronic Parts and Packaging (NEPP) Program Status and Technology Investments Overview

The presentation provides an updated, high-level overview of the NEPP Program. The latest organizational chart is presented that shows the names of the Program and Assistant Program Managers. Additionally, the recent work that is on-going with the updating of several NASA NPDs, NPRs and technical standards is reviewed. Internal and external organizational interfaces are described. Finally, the current technology focus areas are described. These areas include passives, wide-band gap power devices, processor units (CPUs and GPUs), 2.5D and 3D device architectures, memories, and data analytics.

NEPAG↗
NASA NTRS2019

Retrieval of Vegetation Water Content Using Brightness Temperatures from the Soil Moisture Active Passive (SMAP) Mission

In this paper, we explore a time series approach to using the tau-omega (τ-ω) model to retrieve vegetation water content (kg/m2) with minimal use of ancillary data. Analytically, this approach calls for nonlinear optimization in two steps. First, multiple days of co-located brightness temperature observations are used to retrieve the effective vegetation opacity, which incorporates the combined radiometric and polarization effects of surface roughness and vegetation opacity. The resulting effective vegetation opacity is then used to retrieve vegetation water content to within a gain factor α and an offset factor β. By using a climatological vegetation water content ancillary database as the one adopted in the development of the SMAP standard and enhanced soil moisture products, α and β can be determined globally using the annual minimum and annual maximum of vegetation water content. The resulting values of α and β can then be used to reconstruct the retrieved vegetation water content. Formulation, assumptions, and limitations of this approach are presented alongside the preliminary global retrieval of vegetation water content using one year (2016) ofSMAP brightness temperature observations.

radiative transfer↗
NASA NTRS2020

Passive Aeroelastic Tailored Wing Modal Test Using the Fixed Base Correction Method

In modal testing and finite element model correlation, analysts desire modal results using free-free or rigid boundary conditions to ease comparisons of test versus analytical data. It is often expensive both in cost and schedule to build and test with boundary conditions that replicate the free-free or rigid boundaries. Static test fixtures for load testing are often large, heavy, and unyielding, but do not provide adequate boundaries for modal tests because they are dynamically too flexible and often contain natural frequencies within the frequency range of interest of the test article. Dynamic coupling between the test article and test fixture complicates the model updating process because significant effort is required to model the test fixture and boundary conditions in addition to the test article. If there were a way to correct the modal results for fixture coupling, then setups used for other structural testing could be adequate for modal testing. In the case described in this paper, a partial static loads testing setup was used, which allowed significant schedule and cost savings by eliminating a unique setup for a modal test. A fixed base correction technique was investigated during modal testing of a flexible wing cantilevered from part of a static test fixture. The technique was successfully used to measure the wing modes de-coupled from the dynamically active test fixture. The technique is promising for future aircraft applications, but more research is needed.

structural dynamics↗