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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
NASA NTRS2006

An Overview of the Role of Systems Analysis in NASA's Hypersonics Project

NASA's Aeronautics Research Mission Directorate recently restructured its Vehicle Systems Program, refocusing it towards understanding the fundamental physics that govern flight in all speed regimes. Now called the Fundamental Aeronautics Program, it is comprised of four new projects, Subsonic Fixed Wing, Subsonic Rotary Wing, Supersonics, and Hypersonics. The Aeronautics Research Mission Directorate has charged the Hypersonics Project with having a basic understanding of all systems that travel at hypersonic speeds within the Earth's and other planets atmospheres. This includes both powered and unpowered systems, such as re-entry vehicles and vehicles powered by rocket or airbreathing propulsion that cruise in and accelerate through the atmosphere. The primary objective of the Hypersonics Project is to develop physics-based predictive tools that enable the design, analysis and optimization of such systems. The Hypersonics Project charges the systems analysis discipline team with providing it the decision-making information it needs to properly guide research and technology development. Credible, rapid, and robust multi-disciplinary system analysis processes and design tools are required in order to generate this information. To this end, the principal challenges for the systems analysis team are the introduction of high fidelity physics into the analysis process and integration into a design environment, quantification of design uncertainty through the use of probabilistic methods, reduction in design cycle time, and the development and implementation of robust processes and tools enabling a wide design space and associated technology assessment capability. This paper will discuss the roles and responsibilities of the systems analysis discipline team within the Hypersonics Project as well as the tools, methods, processes, and approach that the team will undertake in order to perform its project designated functions.

Robinson, Jeffrey S.↗
NASA NTRS2003

Algorithms for Processing and Analysis of Ocean Color Satellite Data for Coastal Case 2 Waters

SeaWiFS has the ability to enhance our understanding of many oceanographic processes. However, its utility in the coastal zone has been limited by valid bio-optical algorithms and by the determination of accurate water reflectances, particularly in the blue bands (412-490 nm), which have a significant impact on the effectiveness of all bio-optical algorithms. We have made advances in three areas: algorithm development (Table 16.1), field data collection, and data applications.

Stumpf, Richard P.↗
NASA NTRS2005

Extending the LWS Data Environment: Distributed Data Processing and Analysis

The final stages of this work saw changes to the original framework, as well as the completion and integration of several data processing services. Initially, it was thought that a peer-to-peer architecture was necessary to make this work possible. The peer-to-peer architecture provided many benefits including the dynamic discovery of new services that would be continually added. A prototype example was built and while it showed promise, a major disadvantage was seen in that it was not easily integrated into the existing data environment. While the peer-to-peer system worked well for finding and accessing distributed data processing services, it was found that its use was limited by the difficulty in calling it from existing tools and services. After collaborations with members of the data community, it was determined that our data processing system was of high value and that a new interface should be pursued in order for the community to take full advantage of it. As such; the framework was modified from a peer-to-peer architecture to a more traditional web service approach. Following this change multiple data processing services were added. These services include such things as coordinate transformations and sub setting of data. Observatory (VHO), assisted with integrating the new architecture into the VHO. This allows anyone using the VHO to search for data, to then pass that data through our processing services prior to downloading it. As a second attempt at demonstrating the new system, a collaboration was established with the Collaborative Sun Earth Connector (CoSEC) group at Lockheed Martin. This group is working on a graphical user interface to the Virtual Observatories and data processing software. The intent is to provide a high-level easy-to-use graphical interface that will allow access to the existing Virtual Observatories and data processing services from one convenient application. Working with the CoSEC group we provided access to our data processing tools from within their software. This now allows the CoSEC community to take advantage of our services and also demonstrates another means of accessing our system.

Narock, Thomas↗
NASA NTRS2022

Process-Oriented Analysis of Dominant Sources of Uncertainty in the Land Carbon Sink

The observed global net land carbon sink is captured by current land models. All models agree that atmospheric CO 2 and nitrogen deposition driven gains in carbon stocks are partially offset by climate and land-use and land-cover change (LULCC) losses. However, there is a lack of consensus in the partitioning of the sink between vegetation and soil, where models do not even agree on the direction of change in carbon stocks over the past 60 years. This uncertainty is driven by plant productivity, allocation, and turnover response to atmospheric CO 2 (and to a smaller extent to LULCC), and the response of soil to LULCC (and to a lesser extent climate). Overall, differences in turnover explain ~70% of model spread in both vegetation and soil carbon changes. Further analysis of internal plant and soil (individual pools) cycling is needed to reduce uncertainty in the controlling processes behind the global land carbon sink.

Attribution↗
NASA NTRS2015

NASA's Meteoroid Environments Office's Response to Three Significant Bolide Events Over North America

Being the only U.S. Government entity charged with monitoring the meteor environment, the Meteoroid Environment Office has deployed a network of all sky and wide field meteor cameras, along with the appropriate software tools to quickly analyze data from these systems. However, the coverage of this network is still quite limited, forcing the incorporation of data from other cameras posted to the internet in analyzing many of the fireballs reported by the public and media. A procedure has been developed that determines the analysis process for a given fireball event based on the types and amount of data available. The differences between these analysis process will be explained and outlined by looking at three bolide events, all of which were large enough to produce meteorites. The first example is an ideal event - a bright meteor that occurred over NASA's All Sky Camera Network on August 2, 2014. With clear video of the event from various angles, a high-accuracy trajectory, beginning and end heights, orbit and approximate brightness/size of the event are able to be found very quickly using custom software. The bolide had the potential to have dropped meteorites, so dark flight analysis and modeling was performed, allowing potential fall locations to be mapped as a function of meteorite mass. The second case study was a bright bolide that occurred November 3, 2014 over West Virginia. This was just north of the NASA southeastern all-sky network, and just south of the Ohio-Pennsylvania network. This case study showcases the MEO's ability to use social media and various internet sources to locate videos of the event from obscure sources (including the Washington Monument) for anything that will permit a determination of a basic trajectory and fireball light curve The third case study will highlight the ability to use doppler weather radar in helping locate meteorites, which enable a definitive classification of the impactor. The input data and analysis steps differ for each case study, but the goals remain the same - a trajectory, orbit, and mass estimate for the bolide within hours of the event, and, for events with a high probability of producing meteorites, a location of the strewn field within a day.

Blaauw, Rhiannon C.↗
NASA NTRS2015

When the Sky Falls NASA's Response to Bright Bolide Events Over Continental USA

Being the only U.S. Government entity charged with monitoring the meteor environment, the Meteoroid Environment Office (MEO) has deployed a network of allsky and wide field meteor cameras, along with the appropriate software tools to quickly analyze data from these systems. However, the coverage of this network is still quite limited, forcing the incorporation of data from other cameras posted to the internet in analyzing many of the fireballs reported by the public and media. Information on these bright events often needs to be reported to NASA Headquarters by noon the following day; thus a procedure has been developed that determines the analysis process for a given fireball event based on the types and amount of data available. The differences between these analysis processes are shown by looking at four meteor events that the MEO responded to, all of which were large enough to produce meteorites.

Blaauw, R. C.↗
NASA NTRS1982

Containerless processing technology analysis

Research on acoustic levitation, air-jet levitation, and heat transfer from molten samples is reported. The goal was to obtain a better understanding and improving the quality of containerless processing systems. These systems are applied to the processing of materials in situations in which contact with a container must be avoided, and have potential application in both ground based and orbiting laboratories. Containerless processing is reviewed. The development of glasses from materials which normally crystallize upon cooling, are studied.

Rush, J. E.↗
NASA NTRS2005

State Analysis: A Control Architecture View of Systems Engineering

A viewgraph presentation on the state analysis process is shown. The topics include: 1) Issues with growing complexity; 2) Limits of common practice; 3) Exploiting a control point of view; 4) A glimpse at the State Analysis process; 5) Synergy with model-based systems engineering; and 6) Bridging the systems to software gap.

state analysis↗
DOE OSTI2024

HydraGNN_Predictive_GFM_2024 - Ensemble of predictive graph foundation models for ground state atomistic materials modeling

We provide the ensemble of fifteen pre-trained graph foundation models (GFMs) for atomistic materials modeling applications. Each one of the fifteen GFMs has been trained on five open-source datasets that (once aggregated) amount to over 154 million atomistic structures, which cover over two-thirds of the natural elements of the periodic table and that comprises a broad set of organic and inorganic compounds. This vast set of atomistic structures comprises ground state configurations that are dynamically stable (i.e., equilibrated structures with atomic forces approximately close to zero values) as well as dynamically unstable structures (i.e., non-equilibrium structures with non-negligible non-zero values of atomic forces). The ensemble of datasets aggregated does NOT include excited states. The datasets have been curated to remove atomistic structures with spectral norm of the force tensor above 100 eV/angstrom. Moreover, a linear term of the energy was computed for each dataset using a linear regression model that uses the chemical concentration of each natural element as regressor. The linear term predicted by the linear regression model has been subtracted from each original energy value to perform a re-alignment of the energy values across different electronic structures approximation theories performed to generate the diverse multi-source, multi-fidelity datasets. The folder "ADIOS_files" contains the set of pre-processed datasets in Adaptable I/O System (ADIOS) format (https://www.exascaleproject.org/research-project/adios/) that have been used for the development and training of GFMs in this work. The "ADIOS_files" directory contains 6 sub-directories named as follows: - ANI1x-v3.bp - MPTrj-v3.bp - OC2020-20M-v3.bp - OC2020-v3.bp - OC2022-v3.bp - qm7x-v3.bp Each sub-directory contains the pre-processed datasets converted in Adaptable I/O System (ADIOS) format (https://www.exascaleproject.org/research-project/adios/) that have been used to the development, training, and performance testing of the ensemble go predictive graph foundation models. Each GFM was developed using HydraGNN (https://github.com/ORNL/HydraGNN) as underlying graph neural network (GNN) architecture. The multi-task learning (MTL) capability of HydraGNN was used to simultaneously train the GFMs on labeled values for direct predictions of energy (a total system property of an atomistic structure that measures the chemical stability) and atomic forces (an atomic level property of an atomistic structure that measures the dynamical stability). The hyper parameters of the GFM have been tuned using scalable hyperparameter optimization (HPO) algorithms implemented in the software DeepHyper (https://github.com/deephyper/deephyper). The pre-training of each HPO trial was performed using distributed data parallelism (DDP) to scale the training across 128 compute nodes of the exascale OLCF supercomputer Frontier. Each HPO trial was trained only for 10 epochs and an early stopping was performed to avoid wasting significant computational resources on GNN architectures that were clearly underperforming. For each HPO trial, the 'omnistat' tool developed by (AMD Research - Advanced Micro Device) was used to measure the total energy consumption in kWh. The ensemble of GFMs was obtained by selecting the fifteen best performing HPO trials. Four models have been selected for their clear advantage in accuracy, and these are the GFMs with IDs 229, 156, 147, 260. Additional eleven models have been selected based on judicious balance between accuracy and energy consumption needed for training, and these are the GFMs with IDs 165, 78, 137, 1, 175, 171, 181, 67, 179, 167, 351. Each selected GFM of the ensemble was continued to cumulate a total of at most 30 epochs. In some cases, the total number of epochs actually performed was les than 30 due to two combined factors: (1) the size of the GFM (i.e., the number of model parameters to train) and (2) the total wall-clock time for which the computational resources could be allocated on OLCF-Frontier. The "Ensemble_of_models" directory contains 15 sub-directories named as follows: - gfm_0.229 - gfm_0.156 - gfm_0.147 - gfm_0.260 - gfm_0.165 - gfm_0.78 - gfm_0.137 - gfm_0.1 - gfm_0.175 - gfm_0.171 - gfm_0.181 - gfm_0.67 - gfm_0.179 - gfm_0.167 - gfm_0.351 Each one of these sub-directories refers to one of the fifteen HPO trials that have been selected to continue the pre-training with at most 30 epochs. With each sub-directory associated with a specific HPO trial, the following files can be found: - config.json: file for argument parsing to develop and train an HydraGNN architecture - gfm_0.ID_epoch_N.pk: file with model parameters for HPO ID trial after N epochs of training The ensemble of fifteen GFM architectures was used for (1) ensemble averaging to stabilize the predictions of energy and atomic forces after pre-training for post-processing analysis and (2) ensemble uncertainty quantification (UQ). The code used to develop, pre-train, and load the pre-trained models for post-processing analysis is available on the ORNL-GitHub at the following link: https://github.com/ORNL/HydraGNN/tree/Predictive_GFM_2024

36 MATERIALS SCIENCE↗
NASA NTRS2015

Analysis of Process Gases and Trace Contaminants in Membrane-Aerated Gaseous Effluent Streams.

In membrane-aerated biofilm reactors (MABRs), hollow fibers are used to supply oxygen to the biofilms and bulk fluid. A pressure and concentration gradient between the inner volume of the fibers and the reactor reservoir drives oxygen mass transport across the fibers toward the bulk solution, providing the fiber-adhered biofilm with oxygen. Conversely, bacterial metabolic gases from the bulk liquid, as well as from the biofilm, move opposite to the flow of oxygen, entering the hollow fiber and out of the reactor. Metabolic gases are excellent indicators of biofilm vitality, and can aid in microbial identification. Certain gases can be indicative of system perturbations and control anomalies, or potentially unwanted biological processes occurring within the reactor. In confined environments, such as those found during spaceflight, it is important to understand what compounds are being stripped from the reactor and potentially released into the crew cabin to determine the appropriateness or the requirement for additional mitigation factors. Reactor effluent gas analysis focused on samples provided from Kennedy Space Center's sub-scale MABRs, as well as Johnson Space Center's full-scale MABRs, using infrared spectroscopy and gas chromatography techniques. Process gases, such as carbon dioxide, oxygen, nitrogen, nitrogen dioxide, and nitrous oxide, were quantified to monitor reactor operations. Solid Phase Microextraction (SPME) GC-MS analysis was used to identify trace volatile compounds. Compounds of interest were subsequently quantified. Reactor supply air was examined to establish target compound baseline concentrations. Concentration levels were compared to average ISS concentration values and/or Spacecraft Maximum Allowable Concentration (SMAC) levels where appropriate. Based on a review of to-date results, current trace contaminant control systems (TCCS) currently on board the ISS should be able to handle the added load from bioreactor systems without the need for secondary mitigation.

Gaseous Effluent Streams↗
NASA NTRS1976

Radar data processing and analysis

Digitized four-channel radar images corresponding to particular areas from the Phoenix and Huntington test sites were generated in conjunction with prior experiments performed to collect X- and L-band synthetic aperture radar imagery of these two areas. The methods for generating this imagery are documented. A secondary objective was the investigation of digital processing techniques for extraction of information from the multiband radar image data. Following the digitization, the remaining resources permitted a preliminary machine analysis to be performed on portions of the radar image data. The results, although necessarily limited, are reported.

Ausherman, D.↗
NASA NTRS1986

User's guide to image processing applications of the NOAA satellite HRPT/AVHRR data. Part 1: Introduction to the satellite system and its applications. Part 2: Processing and analysis of AVHRR imagery

The use of NOAA Advanced Very High Resolution Radar/High Resolution Picture Transmission (AVHRR/HRPT) imagery for earth resource applications is provided for the applications scientist for use within the various Earth science, resource, and agricultural disciplines. A guide to processing NOAA AVHRR data using the hardware and software systems integrated for this NASA project is provided. The processing steps from raw data on computer compatible tapes (1B data format) through usable qualitative and quantitative products for applications are given. The manual is divided into two parts. The first section describes the NOAA satellite system, its sensors, and the theoretical basis for using these data for environmental applications. Part 2 is a hands-on description of how to use a specific image processing system, the International Imaging Systems, Inc. (I2S) Model 75 Array Processor and S575 software, to process these data.

Huh, Oscar Karl↗
NASA NTRS2001

SIMBIOS Project Data Processing and Analysis Results

The Sensor Intercomparison and Merger for Biological and Interdisciplinary Oceanic Studies (SIMBIOS) Project is concerned with ocean color satellite sensor data intercomparison and merger for biological and interdisciplinary studies of the global oceans. Imagery from different ocean color sensors can now be processed by a single software package using the same algorithms, adjusted by different sensor spectral characteristics, and the same ancillary meteorological and environmental data. This enables cross-comparison and validation of the data derived from satellite sensors and, consequently, creates continuity in ocean color information on both the temporal and spatial scale. The next step in this process is the integration of in situ ocean and atmospheric parameters to enable cross-validation and further refinement of the ocean color methodology. The SIMBIOS Project Office accomplishments during 2000 year are summarized under satellite data processing, data product validation, SeaWiFS Bio-Optical Archive and Storage System (SeaBASS) database, supporting services, sun photometers and calibration activities, and calibration round robins. These accomplishments are described.

Ainsworth, Ewa↗
NASA NTRS2010

Software Development to Assist in the Processing and Analysis of Data Obtained Using Fiber Bragg Grating Interrogation Systems

A fiber Bragg grating is a portion of a core of a fiber optic stand that has been treated to affect the way light travels through the strand. Light within a certain narrow range of wavelengths will be reflected along the fiber by the grating, while light outside that range will pass through the grating mostly undisturbed. Since the range of wavelengths that can penetrate the grating depends on the grating itself as well as temperature and mechanical strain, fiber Bragg gratings can be used as temperature and strain sensors. This capability, along with the light-weight nature of the fiber optic strands in which the gratings reside, make fiber optic sensors an ideal candidate for flight testing and monitoring in which temperature and wing strain are factors. A team of NASA Dryden engineers has been working to advance the fiber optic sensor technology since the mid 1990 s. The team has been able to improve the dependability and sample rate of fiber optic sensor systems, making them more suitable for real-time wing shape and strain monitoring and capable of rivaling traditional strain gauge sensors in accuracy. The sensor system was recently tested on the Ikhana unmanned aircraft and will be used on the Global Observer unmanned aircraft. Since a fiber Bragg grating sensor can be placed every halfinch on each optic fiber, and since fibers of approximately 40 feet in length each are to be used on the Global Observer, each of these fibers will have approximately 1,000 sensors. A total of 32 fibers are to be placed on the Global Observer aircraft, to be sampled at a rate of about 50 Hz, meaning about 1.6 million data points will be taken every second. The fiber optic sensors system is capable of producing massive amounts of potentially useful data; however, methods to capture, record, and analyze all of this data in a way that makes the information useful to flight test engineers are currently limited. The purpose of this project is to research the availability of software capable of processing massive amounts of data in both real-time and post-flight settings, and to produce software segments that can be integrated to assist in the task as well. The selected software must be able to: (1) process massive amounts of data (up to 4GB) at a speed useful in a real-time settings (small fractions of a second); (2) process data in post-flight settings to allow test reproduction or further data analysis, inclusive; (3) produce, or make easier to produce, three-dimensional plots/graphs to make the data accessible to flight test engineers; and (4) be customized to allow users to use their own processing formulas or functions and display the data in formats they prefer. Several software programs were evaluated to determine their utility in completing the research objectives. These programs include: OriginLab, Graphis, 3D Grapher, Visualization Sciences Group (VSG) Avizo Wind, Interactive Analysis and Display System (IADS), SigmaPlot, and MATLAB.

Hicks, Rebecca↗
NASA NTRS1978

Applications of modeling to analysis and processing of Landsat data

The Suits bidirectional reflectance model (1972) for vegetation canopies was used to calculate reflectance values for the four Landsat spectral bands under a variety of canopy and observation conditions. Relationships between characteristics of developing wheat fields and associated reflectances were studied. Coincident measurements of crop reflectance and Landsat signals were compared using regression analysis techniques. The model was also applied to forest situations both to help establish the extent to which Landsat may provide direct information about conditions occurring beneath forest overstories and to help develop methods for reducing the effects of terrain slope and aspect in the processing of Landsat data. Finally, a relationship based on model calculations was used to adjust Landsat signal values and was found to reduce topography-related variability and improve subsequent classification performance.

Malila, W. A.↗
NASA NTRS2007

An Investigation of the Characterization of Cloud Contamination in Hyperspectral Radiances

In regions lacking direct observations, the assimilation of radiances from infrared and microwave sounders is the primary method for characterizing the atmosphere in the analysis process. In recent years, technological advances have led to the launching of more advanced sounders, particularly in the thermal infrared spectrum. With the advent of these hyperspectral sounders, the amount of data available for the analysis process has and will continue to be dramatically increased. However, the utilization of infrared radiances in variational assimilation can be problematic in the presence of clouds; specifically the assessment of the presence of clouds in an instantaneous field of view (IFOV) and the contamination in the individual channels within the IFOV. Various techniques have been developed to determine if a channel is contaminated by clouds. The work presented in this paper and subsequent presentation will investigate traditional techniques and compare them to a new technique, the C02 sorting technique, which utilizes the high spectral resolution of the Atmospheric Infrared Sounder (AIRS) within the framework of the Gridpoint Statistical Interpolation (GSI) 3DVAR system. Ultimately, this work is done in preparation for the assessment of short-term forecast impacts with the regional assimilation of AIRS radiances within the analysis fields of the Weather Research and Forecast Nonhydrostatic Mesoscale Model (WRF-NMM) at the NASA Short-term Prediction Research and Transition (SPORT) Center.

McCarty, William↗
NASA NTRS1975

Apollo experience report: Spacecraft relative motion and recontact analyses

Potential collision or accidental recontact problems between the spacecraft and other space vehicles (or components) existed during most of the Apollo missions. These problems were identified before each Apollo flight, and appropriate solutions for eliminating or minimizing the chance of collision were determined through relative motion analyses. A summary of the identification, solution, and analysis process for some of the more significant of these separation problems is presented. In addition, the scope of responsibility, the development of the study effort, and the computer simulation development, which supported the analysis process, are described.

Mcadams, R. E.↗