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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 1,243 records · Page 69
All sourcesNASA NTRSDOE OSTI
NASA NTRS1991

Preliminary results of investigations into the use of artificial neural networks for discriminating gas chromatograph mass spectra of remote samples

Neural networks trained using mass spectra data from the National Institute of Standards and Technology (NIST) are studied. The investigations also included sample data from the gas chromatograph mass spectrometer (GCMS) instrument aboard the Viking Lander, obtained from the National Space Science Data Center. The work performed to data and the preliminary results from the training and testing of neural networks are described. These preliminary results are presented for the purpose of determining the viability of applying artificial neural networks in discriminating mass spectra samples from remote instrumentation such as the Mars Rover Sample Return Mission and the Cassini Probe.

Geller, Harold A.↗
DOE OSTI2022

Evaluation of artificial neural network performance for classification of potato plants infected with potato virus Y using spectral data on multiple varieties and genotypes

Potato virus Y (Potyviridae, PVY) is a plant virus that poses a significant threat to potato producers on a global basis. The pathogen has disrupted seed potato supplies and negatively impacted yield and quality of commercial potato crops. The potato industry currently manages PVY infection levels via insecticide applications, regional seed certification programs that rely on field scouting to visually assess individual plants for infection status, and destructive and costly tissue sampling coupled with laboratory assays. Despite these efforts, PVY continues to confound potato industry stakeholders resulting in economic harm. Remote sensing and machine learning provide for the development of new tools to more accurately detect and spatially quantify PVY-infected plants versus the current state of the art. However, there is a need to understand how the occurrence of many different potato varieties impact the dynamics of developing models to detect potato plants impacted with PVY and their potential effectiveness. This study evaluates classification modelling outcomes using spectral datasets collected in different temporal and spatial environments (greenhouse and a production field) on multiple potato varieties consisting of labelled instances of plants infected with PVY and those not infected with the virus. A modelling framework was developed to support iterative modelling runs using artificial neural network (ANN) architectures configured as binary classifiers to develop sample populations to support statistical analysis on model performance using specific spectral subsets. When using spectral data to detect PVY-infected plants, ANN models achieved the highest mean accuracy of 0.894 on a single variety. Conversely, the same ANN model architecture only achieved a mean accuracy of 0.575 on a spectral data set representing 29 potato breeding lines. Additionally, statistical analysis indicates spectral regions including the red edge, near infrared and shortwave infrared contain more important spectral features for the ANN classifier introduced in this research.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Learning continuous scattering length density profiles from neutron reflectivities using convolutional neural networks

Interpreting neutron reflectivity (NR) data using ad hoc multi-layer models and physics-based models provides information about spatially resolved neutron scattering length density (NSLD) profiles. Recent improvements in data acquisition systems have allowed acquiring thousands of NR curves in a couple of hours, which has led to a need for automated data analysis tools to interpret NR measurements in real-time. Here, we present a machine learning analysis workflow that uses a series of models, based on a convolutional neural network (CNN), to learn the relation between the NSLDs and the NRs, and subsequently produce continuous NSLD profiles directly from NRs. The usefulness of our CNN-based models is demonstrated by constructing NSLDs from NRs of several films containing homopolymer polyzwitterions and diblock copolymers mixed with different types of salts. Comparisons of the NSLDs with those constructed using ad hoc multi-layer models reveal a very good agreement, suggesting the potential of CNN-based models for real-time automated data analysis of NRs.

36 MATERIALS SCIENCE↗
NASA NTRS1991

High-speed, cross-continental networks - A necessity

The networking requirements that the Earth Observing System (EOS) program has levied on NASA and the national and international operational networking communities is addressed. The objectives of the EOS program are listed and include the development and operation of an observing system to acquire essential, global earth science data on a long-term, sustained basis and in a manner which maximizes the scientific utility of the data and simplifies data analysis. Network design issues are also discussed, including protocol selection, the Transport Control Protocol/Internet Protocol suite, the Open Systems Interconnect network suite, and the internet evolution. Open and closed network issues are also discussed. A number of networks now in place are assessed including NASNet, and ESNet. These offer possible options and/or solutions to be considered by the NASA Headquarters EOS Data and Information Systems Program.

Wong, C. M.↗
DOE OSTI2022

Low-abundance populations distinguish microbiome performance in plant cell wall deconstruction

Abstract Background Plant cell walls are interwoven structures recalcitrant to degradation. Native and adapted microbiomes can be particularly effective at plant cell wall deconstruction. Although most understanding of biological cell wall deconstruction has been obtained from isolates, cultivated microbiomes that break down cell walls have emerged as new sources for biotechnologically relevant microbes and enzymes. These microbiomes provide a unique resource to identify key interacting functional microbial groups and to guide the design of specialized synthetic microbial communities. Results To establish a system assessing comparative microbiome performance, parallel microbiomes were cultivated on sorghum ( Sorghum bicolor L. Moench) from compost inocula. Biomass loss and biochemical assays indicated that these microbiomes diverged in their ability to deconstruct biomass. Network reconstructions from gene expression dynamics identified key groups and potential interactions within the adapted sorghum-degrading communities, including Actinotalea , Filomicrobium , and Gemmatimonadetes populations. Functional analysis demonstrated that the microbiomes proceeded through successive stages that are linked to enzymes that deconstruct plant cell wall polymers. The combination of network and functional analysis highlighted the importance of cellulose-degrading Actinobacteria in differentiating the performance of these microbiomes. Conclusions The two-tier cultivation of compost-derived microbiomes on sorghum led to the establishment of microbiomes for which community structure and performance could be assessed. The work reinforces the observation that subtle differences in community composition and the genomic content of strains may lead to significant differences in community performance.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Finalizing Transition to the New Data Center at BNL

Computational science, data management and analysis have been key factors in the success of Brookhaven National Laboratory's scientific programs at the Relativistic Heavy Ion Collider (RHIC), the National Synchrotron Light Source (NSLS-II), the Center for Functional Nanomaterials (CFN), and in biological, atmospheric, and energy systems science, Lattice Quantum Chromodynamics (LQCD) and Materials Science, as well as our participation in international research collaborations, such as the ATLAS Experiment at Europe's Large Hadron Collider (LHC) at CERN (Switzerland) and the Belle II Experiment at KEK (Japan). The construction of a new data center is an acknowledgement of the increasing demand for computing and storage services at BNL in the near term and enable the Lab to address the needs of the future experiments at the High-Luminosity LHC at CERN and the Electron-Ion Collider (EIC) at BNL in the long term. The Computing Facility Revitalization (CFR) project is aimed at repurposing the former National Synchrotron Light Source (NSLS-I) building as the new data center for BNL. The construction of the new data center was finished in 2021Q3, and it was delivered for production in early FY2022 for all collaborations supported by the Scientific Data and Computing Center (SDCC), including STAR, PHENIX and sPHENIX experiments at RHIC collider at BNL, the Belle II Experiment at KEK (Japan), and the Computational Science Initiative at BNL (CSI). This paper highlights the key mechanical, electrical, and networking components of the new data center in its final configuration as used in production since 2021Q4 and gives an overview for the extension of the central network systems into the new data center and the migration of a significant portion of IT load and services from the old data center to the new data center carried out in 20212023, with expected completion of the main phase of the gradual IT equipment replacement and migration from the old data center into the new one set to the end of FY2023 (Sep 30, 2023).

99 GENERAL AND MISCELLANEOUS↗
NASA NTRS1983

The Telecommunications and Data Acquisition Report

Developments in programs in telecommunication and data acquisition in space communications, radio navigation, radio science, and ground based radio astronomy are reported. Activities of the deep space network (DSN) and its associated ground communication facility (GCF) in planning, supporting research and technology, implementation, and in operations are outlined. The publication of reports on the application of radio interferometry at microwave frequencies for geodynamic measurements are presented. Implementation and operation for searching the microwave spectrum is reported.

Posner, E. C.↗
NASA NTRS1988

The Telecommunications and Data Acquisition Report

In space communications, radio navigation, radio science, and ground based radio and radar astronomy, activities of the Deep Space Network and its associated Ground Communications Facility in planning, in supporting research and technology, in implementation, and in operations are reported. Also included is TDA funded activity at JPL on data and information systems and reimbursable DSN work performed for other space agencies through NASA.

Posner, E. C.↗
NASA NTRS1991

The Telecommunications and Data Acquisition Report

A compilation is presented of articles on developments in programs managed by JPL's Office of Telecommunications and Data Acquisition. In space communications, radio navigation, radio science, and ground based radio and radar astronomy, activities of the Deep Space Network are reported in planning, in supporting research and technology, in implementation, and in operations. Also included is standards activity at JPL for space data and information systems and reimbursable DSN work performed for other space agencies through NASA. In the search for extraterrestrial intelligence (SETI), implementation and operations are reported for searching the microwave spectrum.

Posner, Edward C.↗
NASA NTRS2005

Antennas for the array-based Deep Space Network: current status and future designs

Development of very large arrays1,2 of small antennas has been proposed as a way to increase the downlink capability of the NASA Deep Space Network DSN) by two or three orders of magnitude thereby enabling greatly increased science data from currently configured missions or enabling new mission concepts. The current concept is for an array of 400 x 12-m antennas at each of three longitudes. The DSN array will utilize radio astronomy sources for phase calibration and will have wide bandwidth correlation processing for this purpose. NASA has undertaken a technology program to prove the performance and cost of a very large DSN array. Central to that program is a 3-element interferometer to be completed in 2005. This paper describes current status of the low cost 6-meter breadboard antenna to be used as part of the interferometer and the RF design of the 12-meter antenna.

antennas↗
NASA NTRS2011

Feature Acquisition with Imbalanced Training Data

This work considers cost-sensitive feature acquisition that attempts to classify a candidate datapoint from incomplete information. In this task, an agent acquires features of the datapoint using one or more costly diagnostic tests, and eventually ascribes a classification label. A cost function describes both the penalties for feature acquisition, as well as misclassification errors. A common solution is a Cost Sensitive Decision Tree (CSDT), a branching sequence of tests with features acquired at interior decision points and class assignment at the leaves. CSDT's can incorporate a wide range of diagnostic tests and can reflect arbitrary cost structures. They are particularly useful for online applications due to their low computational overhead. In this innovation, CSDT's are applied to cost-sensitive feature acquisition where the goal is to recognize very rare or unique phenomena in real time. Example applications from this domain include four areas. In stream processing, one seeks unique events in a real time data stream that is too large to store. In fault protection, a system must adapt quickly to react to anticipated errors by triggering repair activities or follow- up diagnostics. With real-time sensor networks, one seeks to classify unique, new events as they occur. With observational sciences, a new generation of instrumentation seeks unique events through online analysis of large observational datasets. This work presents a solution based on transfer learning principles that permits principled CSDT learning while exploiting any prior knowledge of the designer to correct both between-class and withinclass imbalance. Training examples are adaptively reweighted based on a decomposition of the data attributes. The result is a new, nonparametric representation that matches the anticipated attribute distribution for the target events.

Thompson, David R.↗
NASA NTRS2011

Cloud Macroscopic Organization: Order Emerging from Randomness

Clouds play a central role in many aspects of the climate system and their forms and shapes are remarkably diverse. Appropriate representation of clouds in climate models is a major challenge because cloud processes span at least eight orders of magnitude in spatial scales. Here we show that there exists order in cloud size distribution of low-level clouds, and that it follows a power-law distribution with exponent gamma close to 2. gamma is insensitive to yearly variations in environmental conditions, but has regional variations and land-ocean contrasts. More importantly, we demonstrate this self-organizing behavior of clouds emerges naturally from a complex network model with simple, physical organizing principles: random clumping and merging. We also demonstrate symmetry between clear and cloudy skies in terms of macroscopic organization because of similar fundamental underlying organizing principles. The order in the apparently complex cloud-clear field thus has its root in random local interactions. Studying cloud organization with complex network models is an attractive new approach that has wide applications in climate science. We also propose a concept of cloud statistic mechanics approach. This approach is fully complementary to deterministic models, and the two approaches provide a powerful framework to meet the challenge of representing clouds in our climate models when working in tandem.

Yuan, Tianle↗
NASA NTRSDate not supplied

A Deeper Dive Into the Meaning and Implications of Interoperability for LunaNet Communications and Navigation Services

As part of planning efforts for cislunar exploration and science missions, space agencies have been collaborating with each other to enable communications, networking, Position, Navigation, and Timing (PNT) systems to exchange information and provide services to spacecraft and space systems in transit, in orbit, and on the surface, thus helping each other to achieve their common goals. To achieve commonality and lower cost for mutual benefit, the strategy of interoperability is being adopted to help all the pieces fit together and function smoothly. Interoperability gives cislunar users the ability to operate in a collaborative environment similar to the terrestrial Internet, allowing them to share information, navigate safely despite increasing radio frequency congestion, and follow common processes and procedures for effective joint operations. Unlike prior government-dominated efforts, this ecosystem is expected to include commercial for-profit businesses, non-profit organizations, and academic institutions. Ultimately, the goal is to enable a cislunar ecosystem of service providers and users to contribute and/or utilize infrastructure and capabilities to accomplish mission objectives spanning the full range of human endeavours while supporting a variety of business models. This paper reports on the results of an effort to assist in efforts to frame the development of the international LunaNet architecture by providing a canonical definition of interoperability broad enough to meet these needs, examine architectural and operational implications of the definition, and explore interoperability strategies and tactics for deploying and evolving these services. It describes key systems-of-systems (SoS) (Network-of-Networks) interoperability concepts in the context of sustainment of the ecosystem over time as systems evolve in technologies, standards and Standards Development Organizations, component and subsystem upgrades, and user applications

LunaNet↗
NASA NTRS2024

HDTN 7150.2D Class B Software Requirements Specification (SRS)

Space Communications and Navigation (SCaN) is developing new communications technologies to increase the amount of science data returned on future space missions. The High-Rate Delay Tolerant Networking (HDTN) project at NASA Glenn Research Center (GRC) will provide reliable internetworking as a high-speed path for moving data between spacecraft payloads and across communication systems that operate at various rates. This document describes the requirements that will be implemented in the HDTN software.

Delay Tolerant Networking↗
DOE OSTI2021

Dynamic, risk informed decision support systems and methods

The present disclosure is directed to a decision support system or tool based on a Bayesian Network (BN) framework. The diagnostic support tool is created by using advanced Probabilistic Risk Assessment (PRA) method(s) to construct Bayesian Networks (BNs) that form a Bayesian Decision Support Process (BDSP) to provide science-based decision support for understanding and managing events in complex systems. In an embodiment, the PRA method(s) may include Discrete Dynamic Event Trees (DDETs) and simulations.

Groth, Katrina↗
DOE OSTI2020

Allometric Trophic Networks From Individuals to Socio-Ecosystems: Consumer–Resource Theory of the Ecological Elephant in the Room

A well-known parable is that of the blind men studying an elephant each of which assert the elephant is the part they first hold in their hands, e.g., “rope!” says the tail holder while the leg holder asserts “tree!” The various subdisciplines of ecology appear similar in that we each engage in our enthusiastic but at least somewhat myopic study with remarkably limited agreement or even discussion about the overall system which we all study. Allometric trophic network (ATN) theory offers a path out of this dilemma by integrating across scales, taxa, habitats and organizational levels from physiology to ecosystems based on consumer-resource interactions among co-existing organisms. The network architecture and the metabolic and behavioral processes that determine the structure and dynamics of these interactions form the first principles of ATN theory, which in turn provides a synthetic overview and powerfully predictive framework for ecology from organisms to ecosystems. Beyond ecology, ATN theory also synthesizes eco-evolutionary and socio-ecological research still largely based on consumer-resource mechanisms but respectively integrated with different processes including natural selection and market mechanisms. This paper briefly describes foundations, advances, and future directions of ATN theory including predicting an ecosystem’s phenotype from its community’s genotype in order to accelerate more predictive and unified understanding of the complex systems studied by ecologists and other environmental scientists.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

A network-enabled pipeline for gene discovery and validation in non-model plant species

Identifying key regulators of important genes in non-model crop species is challenging due to limited multi-omics resources. To address this, we introduce the network-enabled gene discovery pipeline NEEDLE, a user-friendly tool that systematically generates coexpression gene network modules, measures gene connectivity, and establishes network hierarchy to pinpoint key transcriptional regulators from dynamic transcriptome datasets. After validating its accuracy with two independent datasets, we applied NEEDLE to identify transcription factors (TFs) regulating the expression of cellulose synthase-like F6 ( CSLF6 ), a crucial cell wall biosynthetic gene, in Brachypodium and sorghum. Our analyses uncover regulators of CSLF6 and also shed light on the evolutionary conservation or divergence of gene regulatory elements among grass species. These results highlight NEEDLE’s capability to provide biologically relevant TF predictions and demonstrate its value for non-model plant species with dynamic transcriptome datasets.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2000

IsoWAN: A NASA Science and Engineering Information and Services Framework

We believe that the next evolutionary step in supporting wide-area application and services delivery to customers is a network framework that provides for collocation of applications and services at distinct sites in the network, an interconnection between these sites that is performance optimized for these applications, and value-added services for applications.

IsoWAN↗