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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 721 records · Page 40
All sourcesNASA NTRSDOE OSTI
NASA NTRS2012

Validation of Aquarius Measurements Using Radiative Transfer Models at L-Band

Aquarius/SAC-D was launched in June 2011 by NASA and CONAE (Argentine space agency). Aquarius includes three L-band (1.4 GHz) radiometers dedicated to measuring sea surface salinity. We report detailed comparisons of Aquarius measurements with radiative transfer model predictions. These comparisons were used as part ofthe initial assessment of Aquarius data. In particular, they were used successfully to estimate the radiometer calibration bias and stability. Further comparisons are being performed to assess the performance of models in the retrieval algorithm for correcting the effect of sources of geophysical "noise" (e.g. the galactic background, atmospheric attenuation and reflected signal from the Sun). Such corrections are critical in bringing the error in retrieved salinity down to the required 0.2 practical salinity unit (psu) on monthly global maps at 150 km by 150 km resolution. The forward models making up the Aquarius simulator have been very useful for preparatory studies in the years leading to Aquarius' launch. The simulator includes various components to compute effects ofthe following processes on the measured signal: 1) emission from Earth surfaces (ocean, land, ice), 2) atmospheric emission and absorption, 3) emission from the Sun, Moon and celestial Sky (directly through the antenna sidelobes or after reflection/scattering at the Earth surface), 4) Faraday rotation, and 5) convolution of the scene by the antenna gain patterns. Since the Aquarius radiometers tum-on in late July 2011, the simulator has been used to perform a first order validation of the data. This included checking the order of magnitude ofthe signal over ocean, land and ice surfaces, checking the relative amplitude of signal at different polarizations, and checking the variation with incidence angle. The comparisons were also used to assess calibration bias and monitor instruments calibration drift. The simulator is also being used in the salinity retrieval. For example, initial assessments of the salinity retrieved from Aquarius data showed degradation in accuracy at locations where glint from the galactic sky background was important. This was traced to an inaccurate correction for the Sky glint. We present comparisons of the simulator prediction to the Aquarius data in order to assess the performances of the models of various physical processes impacting the measurements, such as the effect of sea surface roughness, the impact of the celestial Sky and the Sun emission scattered at the rough ocean surface. We discuss what components of the simulator appear reliable and which ones need improvements. Improved knowledge on the radiative transfer models at L-band will not only lead to better salinity retrieved from Aquarius data, it will also allow be beneficial for SMOS or the upcoming SMAP mission.

Dinnat, E.↗
NASA NTRS1992

Analyzing high dimensional data

Problems encountered in analyzing high dimensional data are discussed and possible solutions are proposed. The increased importance of second-order statistics in analyzing high dimensional data and the shortcoming of the minimum distance classifier in high dimensional data are recognized. By investigating characteristics of high dimensional data, it is shown that second-order statistics must be taken into account in high dimensional data. There is a need to represent second order statistics effectively. As the data dimensionality increases, it becomes more difficult to perceive and compare information present in statistics derived from data. In order to overcome this problem, a method to visualize statistics using color code is proposed. By representing statistics using a color code, the first and the second statistics can be more readily compared.

Lee, Chulhee↗
NASA NTRS1989

The determination of third order linear models from a seventh order nonlinear jet engine model

Results are presented that demonstrate how good reduced-order models can be obtained directly by recursive parameter identification using input/output (I/O) data of high-order nonlinear systems. Three different methods of obtaining a third-order linear model from a seventh-order nonlinear turbojet engine model are compared. The first method is to obtain a linear model from the original model and then reduce the linear model by standard reduction techniques such as residualization and balancing. The second method is to identify directly a third-order linear model by recursive least-squares parameter estimation using I/O data of the original model. The third method is to obtain a reduced-order model from the original model and then linearize the reduced model. Frequency responses are used as the performance measure to evaluate the reduced models. The reduced-order models along with their Bode plots are presented for comparison purposes.

Lalonde, Rick J.↗
NASA NTRS1972

Space station data flow

The results of the space station data flow study are reported. Conceived is a low cost interactive data dissemination system for space station experiment data that includes facility and personnel requirements and locations, phasing requirements and implementation costs. Each of the experiments identified by the operating schedule is analyzed and the support characteristics identified in order to determine data characteristics. Qualitative and quantitative comparison of candidate concepts resulted in a proposed data system configuration baseline concept that includes a data center which combines the responsibility of reprocessing, archiving, and user services according to the various agencies and their responsibility assignments. The primary source of data is the space station complex which provides through the Tracking Data Relay Satellite System (TDRS) and by space shuttle delivery data from experiments in free flying modules and orbiting shuttles as well as from the experiments in the modular space station itself.

Source record↗
NASA NTRS1989

Hybrid current driver designed for a space-borne laser transmitter

NASA Goddard is developing a free-space laser communication transmitter. Each of the 10 GaAlAs diode lasers in the transmitter must be digitally modulated by individual current drivers from a common data source. In order to fit the miniature laser header modules, a hybrid integrated laser current driver was required. The hybrid, smaller than a postage stamp, can drive 100 mA modulation current at a data rate of 200 Mbit/s NRZ.

Zimmerman, Robert K., Jr.↗
DOE OSTI2020

PersGNN: Applying Topological Data Analysis and Geometric Deep Learning to Structure-Based Protein Function Prediction

Understanding protein structure-function relationships is a key challenge in computational biology, with applications across the biotechnology and pharmaceutical industries. While it is known that protein structure directly impacts protein function, many functional prediction tasks use only protein sequence. In this work, we isolate protein structure to make functional annotations for proteins in the Protein Data Bank in order to study the expressiveness of different structure-based prediction schemes. We present PersGNN - an end-to-end trainable deep learning model that combines graph representation learning with topological data analysis to capture a complex set of both local and global structural features. While variations of these techniques have been successfully applied to proteins before, we demonstrate that our hybridized approach, PersGNN, outperforms either method on its own as well as a baseline neural network that learns from the same information. PersGNN achieves a 9.3% boost in area under the precision recall curve (AUPR) compared to the best individual model, as well as high F1 scores across different gene ontology categories, indicating the transferability of this approach.

Swenson, Nicolas↗
NASA NTRS1984

A method for computing the leading-edge suction in a higher-order panel method

Experimental data show that the phenomenon of a separation induced leading edge vortex is influenced by the wing thickness and the shape of the leading edge. Both thickness and leading edge shape (rounded rather than point) delay the formation of a vortex. Existing computer programs used to predict the effect of a leading edge vortex do not include a procedure for determining whether or not a vortex actually exists. Studies under NASA Contract NAS1-15678 have shown that the vortex development can be predicted by using the relationship between the leading edge suction coefficient and the parabolic nose drag. The linear theory FLEXSTAB was used to calculate the leading edge suction coefficient. This report describes the development of a method for calculating leading edge suction using the capabilities of the higher order panel methods (exact boundary conditions). For a two dimensional case, numerical methods were developed using the double strength and downwash distribution along the chord. A Gaussian quadrature formula that directly incorporates the logarithmic singularity in the downwash distribution, at all panel edges, was found to be the best method.

Ehlers, F. E.↗
DOE OSTI2024

Physics-constrained machine learning for electrodynamics without gauge ambiguity based on Fourier transformed Maxwell’s equations

We utilize a Fourier transformation-based representation of Maxwell’s equations to develop physics-constrained neural networks for electrodynamics without gauge ambiguity, which we label the Fourier–Helmholtz–Maxwell neural operator method. In this approach, both of Gauss’s laws and Faraday’s law are built in as hard constraints, as well as the longitudinal component of Ampère–Maxwell in Fourier space, assuming the continuity equation. An encoder–decoder network acts as a solution operator for the transverse components of the Fourier transformed vector potential, $\hat{A}_⟂(k,t)$, whose two degrees of freedom are used to predict the electromagnetic fields. This method was tested on two electron beam simulations. Among the models investigated, it was found that a U-Net architecture exhibited the best performance as it trained quicker, was more accurate and generalized better than the other architectures examined. We demonstrate that our approach is useful for solving Maxwell’s equations for the electromagnetic fields generated by intense relativistic charged particle beams and that it generalizes well to unseen test data, while being orders of magnitude quicker than conventional simulations. We show that the model can be re-trained to make highly accurate predictions in as few as 20 epochs on a previously unseen data set.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1984

The pilot climate data system

The Pilot Climate Data System (PCDS) is an interactive scientific information management system for locating, obtaining, manipulating, and displaying climate-research data. The PCDS was developed to manage a large collection of data of interest to the National Aeronautics and Space Administration's (NASA) research community and currently provides such support for approximately twenty data sets. In order to provide the PCDS capabilities, NASA's Goddard Space Flight Center (NASA/GSFC) has integrated the capabilities of several general-purpose software packages with specialized software for reading and reformatting the supported data sets. These capabilities were integrated in a manner which allows the PCDS to be easily expanded, either to provide support for additional data sets or to provide additional functional capabilities. This also allows the PCDS to take advantage of new technology as it becomes available, since parts of the system can be replaced with more powerful components without significantly affecting the user interface.

Reph, M. G.↗
NASA NTRS2000

BOREAS TF-10 NSA-YJP Tower Flux, Meteorological, and Porometry Data

The BOREAS TF-10 team collected tower flux and meteorological data at two sites, a fen and a young jack pine forest, near Thompson, Manitoba, Canada, as part of BOREAS. A preliminary data set was assembled in August 1993 while field testing the instrument packages, and at both sites data were collected from 15-Aug to 31-Aug. The main experimental period was in 1994, when continuous data were collected from the young jack pine site from 23-May to 20-Sep. Upon examination of the 1994 data set, it became clear that the behavior of the heat, water, and carbon dioxide fluxes throughout the whole growing season was an important scientific question, and that the 1994 data record was not sufficiently long to capture the character of the seasonal behavior of the fluxes. Thus, the young jack pine site was operated from 08-May to 07-Nov in 1996 in order to collect data from spring melt to autumn freeze-up. All variables are presented as 30-minute averages. Supporting data were also collected to describe the surface#s state and to provide the information, in association with the flux data, to build SVAT models. For the young jack pine site, these supporting data included stomatal conductance measurements. The data are stored in tabular ASCII files.

McCaughey, J. Harry↗
NASA NTRS2012

Autonomous Information Unit for Fine-Grain Data Access Control and Information Protection in a Net-Centric System

As communication and networking technologies advance, networks will become highly complex and heterogeneous, interconnecting different network domains. There is a need to provide user authentication and data protection in order to further facilitate critical mission operations, especially in the tactical and mission-critical net-centric networking environment. The Autonomous Information Unit (AIU) technology was designed to provide the fine-grain data access and user control in a net-centric system-testing environment to meet these objectives. The AIU is a fundamental capability designed to enable fine-grain data access and user control in the cross-domain networking environments, where an AIU is composed of the mission data, metadata, and policy. An AIU provides a mechanism to establish trust among deployed AIUs based on recombining shared secrets, authentication and verify users with a username, X.509 certificate, enclave information, and classification level. AIU achieves data protection through (1) splitting data into multiple information pieces using the Shamir's secret sharing algorithm, (2) encrypting each individual information piece using military-grade AES-256 encryption, and (3) randomizing the position of the encrypted data based on the unbiased and memory efficient in-place Fisher-Yates shuffle method. Therefore, it becomes virtually impossible for attackers to compromise data since attackers need to obtain all distributed information as well as the encryption key and the random seeds to properly arrange the data. In addition, since policy can be associated with data in the AIU, different user access and data control strategies can be included. The AIU technology can greatly enhance information assurance and security management in the bandwidth-limited and ad hoc net-centric environments. In addition, AIU technology can be applicable to general complex network domains and applications where distributed user authentication and data protection are necessary. AIU achieves fine-grain data access and user control, reducing the security risk significantly, simplifying the complexity of various security operations, and providing the high information assurance across different network domains.

Chow, Edward T.↗
NASA NTRS1994

High resolution visible to short-wave near-infrared CCD spectra of Mars during 1990

The 0.4 to 1.0 micron spectrum of Mars is dominated by a steep red, relatively featureless spectral slope. Earlier lower spectral observations interpreted the red color and the lack of absorption features in the spectra as evidence of poorly crystalline ferric oxide minerals. More recent higher spectral resolution observations and reinterpretations of older data sets have revealed measureable spectral structure, however. For example, absorption features near 0.65 and 0.86 micron were detected and spatially mapped in data obtained during the 1988 opposition. These absorptions were interpreted as evidence for crystalline hematite on Mars, occuring as an accessory phase in abundances of 3 to 6 percent in the soil. We are attempting to verify the existence of these subtle crystalline Fe(3+) absorption features and to map their spatial distribution in regions of the planet not imaged in 1988. During the 1990 opposition, we obtained imaging spectroscopic data of Mars from the University of Hawaii 2.24 m telescope at Mauna Kea Observatory. The data were obtained with the Wide Field Grism Spectrograph (WFGS), which uses an 800 x 800 CCD and a transmission grating ruled on a prism. We used a grating blazed at 4800 A in first order to obtain data from 0.50 to 0.94 micron at a spectral resolution of R = 200 to 350. The moon/Mars slit design used had projected dimensions of 0.29 x 153 inches, allowing for high spectral resolution and adequate cross-slit spatial sampling of the Martian disk.

Bell, James F., III↗
DOE OSTI2023

Blockchain Empowered Provenance Framework for Sensor Identity Management and Data Flow Security in Fossil-based Power Plants

The overall goals of this project are divided into 3 important phases. First, a peer-to-peer SCADA network is to be established where identity profile of sensors from fossil-power plants will be stored in an immutable manner in order to verify data flow integrity in real time. Second, it is aimed to develop a Blockchain-based provenance platform to audit equipment operations along with data and process integrity violations. In this phase, various operational rules will be incorporated in the ledger on behalf of the operating sensor so its abnormal use can be easily detected. In addition, it is aimed to achieve provenance when the rate of transactions is exceedingly high, thus enabling to design a scalable provenance scheme that can work in real time when number of data collecting points or sensor units increase in fossil-based power plants. Finally, a working testbed will be developed to integrate the Blockchain platform with sensor-based fossil power plant comprising of Remote Terminal Units (RTU) and SCADA devices. Using multiple Raspberry-PIs mimicking the role of RTUs that are interfaced with multiple sensors devices will be deployed to serve as a critical component of fossil power plant and the performance metrics such as throughput, latency, bootstrapping time, etc., will be evaluated on the testbed.

20 FOSSIL-FUELED POWER PLANTS↗
NASA NTRS1980

Mars sample return: Site selection and sample acquisition study

Various vehicle and mission options were investigated for the continued exploration of Mars; the cost of a minimum sample return mission was estimated; options and concepts were synthesized into program possibilities; and recommendations for the next Mars mission were made to the Planetary Program office. Specific sites and all relevant spacecraft and ground-based data were studied in order to determine: (1) the adequacy of presently available data for identifying landing sities for a sample return mission that would assure the acquisition of material from the most important geologic provinces of Mars; (2) the degree of surface mobility required to assure sample acquisition for these sites; (3) techniques to be used in the selection and drilling of rock a samples; and (4) the degree of mobility required at the two Viking sites to acquire these samples.

Nickle, N.↗
NASA NTRS1988

Modeling and estimation of a low degree geopotential model from terrestrial gravity data

The development of appropriate modeling and adjustment procedures for the estimation of harmonic coefficients of the geopotential, from surface gravity data was studied, in order to provide an optimum way of utilizing the terrestrial gravity information in combination solutions currently developed at NASA/Goddard Space Flight Center, for use in the TOPEX/POSEIDON mission. The mathematical modeling was based on the fundamental boundary condition of the linearized Molodensky boundary value problem. Atmospheric and ellipsoidal corrections were applied to the surface anomalies. Terrestrial gravity solutions were found to be in good agreement with the satellite ones over areas which are well surveyed (gravimetrically), such as North America or Australia. However, systematic differences between the terrestrial only models and GEMT1, over extended regions in Africa, the Soviet Union, and China were found. In Africa, gravity anomaly differences on the order of 20 mgals and undulation differences on the order of 15 meters, over regions extending 2000 km in diameter, occur. Comparisons of the GEMT1 implied undulations with 32 well distributed Doppler derived undulations gave an RMS difference of 2.6 m, while corresponding comparison with undulations implied by the terrestrial solution gave RMS difference on the order of 15 m, which implies that the terrestrial data in that region are substantially in error.

Pavlis, Nikolaos K.↗
NASA NTRSDate not supplied

Assessment of Artemis-1 Pogo Flight Instrumentation System

As the space industry continues to strive for more efficient launch vehicles, it must relyon increasingly accurate predictive models. Verification of models typically requires physical testing. Flight data measurements offer the most real and therefore the most accurate data for model correlation. As NASA prepares for the inaugural launch of Space Launch System(SLS), Artemis-1, they must rely heavily on predictive system models to ensure flight safety.NASA has implemented a Development Flight Instrumentation (DFI) system in hopes of recovering useful flight data to aid in model correlation. Historically, some of the most important flight measurements are those that monitor the potentially destructive dynamic interaction of the structural and propellant modes – a phenomenon known as pogo. Pogo is a dynamic instability that can occur on a launch vehicle during any phase of ascent. During this investigation an end-to-end assessment of the Artemis-I Pogo-related DFI was performed to identify any obstacles inherent in the current instrumentation system which may prevent successful measurement of the data necessary to validate the current predictive fluid-structural models. Input drive signals were approximated and applied to a state-space system model to derive predicted pressure and acceleration responses. These predicted responses were then fed through a simulation of the data acquisition process in order to recover predicted measurements. Finally, a mock Flight Data Analysis (FDA) was performed to assess the ability of these measurements to meet the Flight Test Objectives(FTO).

Adam Johnson↗
NASA NTRSDate not supplied

Assessment of Artemis-1 Pogo Flight Instrumentation System

As the space industry continues to strive for more efficient launch vehicles, it must rely on increasingly accurate predictive models. Verification of models typically requires physical testing. Flight data measurements offer the most real and therefore the most accurate data for model correlation. As NASA prepares for the inaugural launch of Space Launch System (SLS), Artemis-1, they must rely heavily on predictive system models to ensure flight safety. NASA has implemented a Development Flight Instrumentation (DFI) system in hopes of recovering useful flight data to aid in model correlation. Historically, some of the most important flight measurements are those that monitor the potentially destructive dynamic interaction of the structural and propellant modes – a phenomenon known as pogo. Pogo is a dynamic instability that can occur on a launch vehicle during any phase of ascent. During this investigation an end-to-end assessment of the Artemis-I Pogo-related DFI was performed to identify any obstacles inherent in the current instrumentation system which may prevent successful measurement of the data necessary to validate the current predictive models of the Main Propulsion System (MPS). Input drive signals were approximated and applied to a system-level SLS state-space model to derive predicted pressure and acceleration responses. These predicted responses were then fed through a simulation of the data acquisition process in order to recover predicted measurements. Finally, a mock Flight Data Analysis (FDA) was performed to assess the ability of these measurements to meet the Flight Test Objectives (FTO).

Adam Johnson↗
DOE OSTI2021

SIRIUS: Science-Driven Data Management for Multi-Tiered Storage

The data sets being generated by large applications on very large-scale systems are increasing in both size and complexity. At the same time, there are new ways available to store and access these data sets. The goal in this project is to develop software that applications can use to make use of new and existing storage technologies in more sophisticated ways. One challenge in scientific data management is handling ‘hot’ vs ‘cold’ data. Data that is hot is data that is needed (or will be needed soon) in order for the program to continue progressing, while cold data is either output (and so will not be need further during the life of the program) or will not be needed until significantly later in the program’s run. Hot data should be stored in a way that allows fast access. On most systems, economic factors lead to an inverse relationship between storage performance and storage capacity and so fast access storage is limited. This makes it important to correctly place hot and cold data and avoid cold data unnecessarily consuming precious resources. In this reporting period, we addressed this challenge in various ways and at various levels. Data management frameworks offer only limited control to applications in how data is stored. We have added software capabilities for seamlessly moving data between layers of the storage technology using promote and demote functions to existing software frameworks. This gives direct control to applications in deciding what priority data receives. Additionally, we integrated different storage layer management frameworks in order to allow data to be exchanged and moved between storage layers in a consistent way across the application. Further, applications are not always able to directly decide what storage level makes sense for a given piece of data without an understanding of the underlying storage technologies. Data storage frameworks are often positioned to make these sorts of decisions in service of the application. We have added machine-learning based capabilities to data staging frameworks in order to make intelligent decisions about where data should be stored given learning about patterns in previous usage of similar data.

97 MATHEMATICS AND COMPUTING↗