Search NASA⌕ Search

SEARCH · Search NASA

Results for “data analytics”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
NASA NTRS1986

Modal characteristics of a stiffened composite cylinder with open and closed end conditions

The structural and acoustic modal frequencies and the loss factors of a composite fuselage model under free-free end and support-end conditions are evaluated. The fuselage model is a composite filament wound, cylindrical structure composed of carbon fibers embedded in an epoxy resin and has a ply orientation of +,-45, +,-32, 0, -,+32, and -,+45. A computer aided test system was utilized to obtain resonance frequencies, modal damping, and mode shape coefficients. Sound pressure and phase survey data are utilized to estimate acoustic modal freuencies and reverberation time was measured to calculate the acoustic loss factors. The derived structural and acoustic modal parameters are compared to analytical data from a computer prediction model. The data reveal that the acoustic modal frequencies and mode shape correlate well with predicted data, and there is fair agreement between structural modal frequencies and mode shape for the two data sets.

Grosveld, F. W.↗
NASA NTRS2018

Practical Aspects of the Frequency Domain Approach for Aircraft System Identification

Practical aspects of the frequency-domain approach for aircraft system identification are explained and demonstrated. Topics related to experiment design, flight data analysis, and dynamic modeling are included. For demonstration purposes, simulated time series data and simulated flight data from an F-16 nonlinear simulation with realistic noise are used. This approach enables detailed evaluations of the techniques and results, because the true characteristics of the data and aircraft dynamics are known for the simulated data. Analytical techniques and practical considerations are examined for the finite Fourier transform, nonparametric frequency response estimation, parametric modeling in the frequency domain, experiment design for frequency-domain modeling, data analysis and modeling in the frequency domain, and real-time calculations. Flight data from a subscale jet transport aircraft are used to demonstrate some of the techniques and technical issues.

Morelli, Eugene A.↗
NASA NTRS1974

Results of geodetic processing and analysis of Skylab altimetry data

A geodetic analysis of Skylab S-193 altimeter preliminary data from mission SL/2 and EREP pass 9 is considered. The overall objective of the investigation was a demonstration of the feasibility of a use of altimeter data for the determination of the geoid in ocean areas. The geoid is the equipotential surface that would coincide with an 'undisturbed' mean sea level of the earth's gravity field. Analytical data handling formulations are discussed.

Fubara, D. M. J.↗
NASA NTRSDate not supplied

The BioMole Facility: Advancement of In Situ Microbiome Analysis for the International Space Station

Characterization of the International Space Station (ISS) microbiome has been enabled by sample return and Earth-based analysis. As human exploration pushes beyond low-Earth orbit, microbial-related crew health, planetary protection, and space research requires in situ capabilities. Steps toward reducing Earth-dependence for complex sample analysis began in 2016 with the amplification of DNA within the miniPCR thermal cycler and DNA sequencing with the MinION sequencer onboard the ISS; for both, samples were prepared on Earth. In 2017, these platforms synergistically enabled the in-situ identification of unknown bacteria collected and cultured from ISS surfaces, thereby shifting the paradigm that microbial cultures had to be returned to Earth. The following year, a culture-independent, swab-to-sequencer method further advanced spaceflight microbiology, demonstrating that culturing could be excluded and provided enhanced insight into the bacterial profile of ISS surfaces. Based on the success of these payloads in confirming the ability to meet crew health identification requirements and the benefits accompanying a culture-independent method, the BioMole Facility was established by the medical operations Crew Health Care Systems team. BioMole is the set of hardware, consumables, and procedures required to support sample preparation and nanopore sequencing onboard the ISS. BioMole goals include expanding sample sources, comparing data to previous methods, demonstrating onboard data analytics, and validating new hardware. To date, comparative surface analysis, molecular- and culture-based, has been completed. Additionally, the demonstration of a sample-to-answer process was achieved when BioMole data was processed onboard using the IBM Open Data and AI Edge software platform installed on the ISS-residing Spaceborne Computer-2. The taxonomic profiles generated from the edge analysis were as expected and paralleled that of the downlinked processed data. Future BioMole efforts involve microbial profiling of the ISS water system, ISS validation of the MinION Mk1C, and an expansion to a research facility available to investigators.

Sarah L. Castro-Wallace↗
NASA NTRS2019

Accelerated Simulation of Air Pollution Using NVIDIA RAPIDS

Atmospheric chemistry models are a central tool to study and forecast the impact of air pollution on the environment, vegetation, and human health. However, the numerical simulation of chemical kinetics is computationally expensive due to the stiffness of the system of ordinary differential equations that describes atmospheric chemistry. Here we present an alternative approach to the computation of atmospheric chemistry based on machine learning. Our training data set is produced using the NASA Goddard Earth Observing System (GEOS) model with GEOS-Chem chemistry, run on the NASA Center for Climate Simulation (NCCS) Discover supercomputing cluster on 384 Intel Xeon Haswell cores. This model spends more than 50% of total run time on solving atmospheric chemistry. The data set contains as input features the air pollution concentrations before solving the differential equations, together with some key physical parameters such as temperature and sun intensity. As target variables we define the air pollution concentrations after solving the differential equations. Using Dask-cuDF and Dask-XGBoost on the NVIDIA RAPIDS platform on 8 Tesla V100 GPUs, we generate from this training set gradient boosted decision tree models that can reproduce the simulation of chemical kinetics. We do this on the NCCS Advanced Data Analytics Platform (ADAPT) science cloud environment. Our application takes full advantage of recent advances in Dask-XGBoost, such as multi-node and multi-GPU scaling for distributed training with large data sets. The increase in training data size enabled by this is critical to capture the full range of chemical environments encountered across the globe and all annual seasons.The boosted tree models offer good predictability and show many of the features of the full chemistry reference simulation. Further improvements can be achieved through mass balance considerations and by accounting for error correlations. We incorporate the boosted tree models into the GEOS reference model using XGBoost's C API. This enables a seamless integration of the GPU trained models into GEOS-Chem, which is written in Fortran and optimized for use in a massively parallel CPU environment. We show the benefits of this approach and discuss the potential speedup of this machine learning accelerated atmospheric chemistry model.

Keller, Christoph A.↗
NASA NTRS2018

Introduction to NASA Goddard Workshop on Artificial Intelligence

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.This workshop will be investigating how AI technologies can be adapted or developed to address the following challenges: Discover events of interest and correlations in large amounts of science data; improve the outcomes of science modeling and data assimilation using improved data processing, integration, and analysis. Design advisors for mission planning and operations, including anomaly detection and spacecraft health monitoring. Develop tools for engineering support, including advanced manufacturing, orbit determination, new component design and system engineering. Customize intelligent user interfaces, including visual analytics and natural language processing.

Le Moigne, Jacqueline↗
NASA NTRS2003

The Development of the Ducted Fan Noise Propagation and Radiation Code CDUCT-LaRC

The development of the ducted fan noise propagation and radiation code CDUCT-LaRC at NASA Langley Research Center is described. This code calculates the propagation and radiation of given acoustic modes ahead of the fan face or aft of the exhaust guide vanes in the inlet or exhaust ducts, respectively. This paper gives a description of the modules comprising CDUCT-LaRC. The grid generation module provides automatic creation of numerical grids for complex (non-axisymmetric) geometries that include single or multiple pylons. Files for performing automatic inviscid mean flow calculations are also generated within this module. The duct propagation is based on the parabolic approximation theory of R. P. Dougherty. This theory allows the handling of complex internal geometries and the ability to study the effect of non-uniform (i.e. circumferentially and axially segmented) liners. Finally, the duct radiation module is based on the Ffowcs Williams-Hawkings (FW-H) equation with a penetrable data surface. Refraction of sound through the shear layer between the external flow and bypass duct flow is included. Results for benchmark annular ducts, as well as other geometries with pylons, are presented and compared with available analytical data.

Nark, Douglas M.↗
NASA NTRS1998

Throughput of the Composite Infrared Spectrometer (CIRS) Mid Infrared (MIR) Channel for the Cassini Mission to Saturn

The Composite Infrared Spectrometer (CIRS) of the Cassini mission to Saturn has two interferometers covering the far infrared and mid infrared wavelength region. The instrument was aligned at ambient temperature, but operates at 170 Kelvin and has challenging interferometric alignment tolerances. Cryogenic alignment tests of the instrument indicate that it should suffer minimal degradation due to the cooldown from ambient to operational temperature. System level tests performed by the calibration team indicated a lower than expected signal level on the MIR channel, while providing ambiguous optical throughput data. Therefore it became imperative to develop a metric that could be used to determine the instrument performance at both the instrument and system levels, at ambient and cryogenic temperature. Modulation efficiency and throughput measurements were performed and new analytical models developed to evaluate the status of the instrument. Empirical and analytical data were eventually reconciled and deviations from the design values explained.

Hagopian, John G.↗
NASA NTRSDate not supplied

Earth System Digital Twins (ESDT) Technology for NASA Earth Science

For NASA's Advanced Information Systems Technology (AIST) Program, an Earth System Digital Twin (ESDT) is defined as an interactive and integrated multidomain, multiscale, digital replica of the state and temporal evolution of Earth systems. It dynamically integrates: relevant Earth system models and simulations; other relevant models (e.g., related to the world's infrastructure); continuous and timely (including near real time and direct readout) observations (e.g., space, air, ground, over/underwater, Internet of Things (IoT), socioeconomic); long-time records; as well as analytics and artificial intelligence tools. Effective ESDTs enable users to run hypothetical scenarios to improve the understanding, prediction of and mitigation/response to Earth system processes, natural phenomena and human activities as well as their many interactions. An ESDT is a type of integrated information system that, for example, enables continuous assessment of impact from naturally occurring and/or human activities on physical and natural environments. AIST ESDT strategic goals are to: 1. Develop information system frameworks to provide continuous and accurate representations of systems as they change over time; 2. Mirror various Earth Science systems and utilize the combination of Data Analytics, Artificial Intelligence, Digital Thread, and state-of-the-art models to help predict the Earth’s response to various phenomena; 3. Provide the tools to conduct "what if" investigations that can result in actionable predictions. The AIST ESDT thrust is developing capabilities toward the development of future digital twins of the Earth or of subcomponents of the Earth. This will enable the development of an overarching framework that will integrate New Observing Strategies (NOS) to enable new observation measurements, i.e., multi-source, coordinated, dynamic and responsive to needs and requests defined by Analytic Collaborative Frameworks (ACF) that enable agile science investigations fusing and analyzing very large amounts of diverse data. NOS and ACF capabilities along with open access to various science, infrastructure and human data, interconnected modeling, data assimilation, simulations, surrogate modeling, high-performance computing and advanced visualization, will define a powerful framework that could be utilized for local, regional or global and/or thematic digital twins. This presentation will describe a general overview of the AIST ESDT vision including prior work done in the areas of NOS and ACF as well as current and upcoming ESDT projects.

Jacqueline Le Moigne↗
NASA NTRS2014

Analyzing a 35-Year Hourly Data Record: Why So Difficult?

At the Goddard Distributed Active Archive Center, we have recently added a 35-Year record of output data from the North American Land Assimilation System (NLDAS) to the Giovanni web-based analysis and visualization tool. Giovanni (Geospatial Interactive Online Visualization ANd aNalysis Infrastructure) offers a variety of data summarization and visualization to users that operate at the data center, obviating the need for users to download and read the data themselves for exploratory data analysis. However, the NLDAS data has proven surprisingly resistant to application of the summarization algorithms. Algorithms that were perfectly happy analyzing 15 years of daily satellite data encountered limitations both at the algorithm and system level for 35 years of hourly data. Failures arose, sometimes unexpectedly, from command line overflows, memory overflows, internal buffer overflows, and time-outs, among others. These serve as an early warning sign for the problems likely to be encountered by the general user community as they try to scale up to Big Data analytics. Indeed, it is likely that more users will seek to perform remote web-based analysis precisely to avoid the issues, or the need to reprogram around them. We will discuss approaches to mitigating the limitations and the implications for data systems serving the user communities that try to scale up their current techniques to analyze Big Data.

computational performance↗
NASA NTRS1974

Spectral mapping of soil organic matter

Multispectral remote sensing data were examined for use in the mapping of soil organic matter content. Computer-implemented pattern recognition techniques were used to analyze data collected in May 1969 and May 1970 by an airborne multispectral scanner over a 40-km flightline. Two fields within the flightline were selected for intensive study. Approximately 400 surface soil samples from these fields were obtained for organic matter analysis. The analytical data were used as training sets for computer-implemented analysis of the spectral data. It was found that within the geographical limitations included in this study, multispectral data and automatic data processing techniques could be used very effectively to delineate and map surface soils areas containing different levels of soil organic matter.

Kristof, S. J.↗
NASA NTRS1982

Lunar regolith - Petrology of the less than 10 micron fraction

Petrographic data for the less than 10 micron fraction from four lunar surface soils are presented in an attempt to characterize the modal mineralogy of this fraction. Individual grains were studied with a scanning/transmission electron microscope with an attached energy dispersive spectrometer. Energy dispersive analytical data are presented, and comparative modal petrology of the soils is shown. Also presented are grain size histograms and diagrammatic representation of comparative modal data for the soils, as well as the feldspathic glass/mafic glass ratio, plagioclase/mafic mineral ratio, and SiO2 modal percent for different size fractions of the four types of soil. The modal results are consistent with chemical data regarding feldspathic and KREEP enrichment in the finest fraction. Grain-size distributions are inconsistent with a fine-grained exotic component derived from distant sources.

Devine, J. M.↗
NASA NTRS1992

Report of investigations into charge cadmium reactivity: Nickel-cadmium cell ESD 91-86

In Aug. 1990, a presentation was given at the 25th Ann. IECEC meeting on the results of Destructive Physical Analysis (DPA) on two successive sets of Ni-Cd cells. The cells were of two different separator types, Pellon 2505 and 2536. One cell of each separator type was analyzed on two occasions; the first pair were analyzed to establish baseline data on essentially new cells; the second pair were analyzed after the cells had been on charge-discharge cycling for a year in connection with a satellite simulation study. The gas composition found in the cells, the absence of charged cadmium in the analytical data, and the appearance of dried out portions on the Cd plates in the one year cell S/N 7 which used Pellon 2505 as its separator material, were questions which arose. These concerns are answered and the observational results are clarified.

Lewis, Harlan L.↗
NASA NTRS2018

Efficient Unsteady Model Estimation Using Computational and Experimental Data

Improving aircraft simulations for pilot training in loss-of-control and stalled conditions is one goal of NASA research in the System Wide Safety Program. One part of this effort is to develop appropriate generic aerodynamic models that provide representative responses in simulation for a given class of aircraft. In this part of the flight envelope nonlinear unsteady responses are often present and may require an extended aerodynamic model compared to that used in the conventional flight envelope. In this preliminary study, two objectives are addressed. First, to obtain a representative model for a NASA generic aircraft at an unsteady condition in the flight envelope and second, to evaluate the techniques involved. To meet these objectives, two different generic aircraft configurations are modeled using both experimental and analytical data. With these results, an initial assessment of the efficiency and quality of the tools and test techniques are evaluated to develop guidance for analytical and experimental approaches to unsteady modeling.

Murphy, Patrick C.↗
NASA NTRS1980

Development of biological and nonbiological explanations for the Viking label release data

The plausibility that hydrogen peroxide, widely distributed within the Mars surface material, was responsible for the evocative response obtained by the Viking Labeled Release (LR) experiment on Mars was investigated. Although a mixture of gamma Fe2O3 and silica sand stimulated the LR nutrient reaction with hydrogen peroxide and reduced the rate of hydrogen decomposition under various storage conditions, the Mars analog soil prepared by the Viking Inorganic Analysis Team to match the Mars analytical data does not cause such effects. Nor is adequate resistance to UV irradiation shown. On the basis of the results and consideration presented while the hydrogen peroxide theory remains the most, if not only, attractive chemical explanation of the LR data, it remains unconvincing on critical points. Until problems concerning the formation and stabilization of hydrogen peroxide on the surface of Mars can be overcome, adhere to the scientific evidence requires serious consideration of the biological theory.

Source record↗
NASA NTRS1973

A study of the dynamic tire properties over a range of tire constructions

The dynamic properties of four model aircraft tires of various construction were evaluated experimentally and compared with available theory. The experimental investigation consisted of measuring the cornering force and the self-aligning torque developed by the tires undergoing sinusoidal steering inputs while operating on a small scale, road-wheel tire testing apparatus. The force and moment data from the different tires are compared with both finite- and point-contact patch string theory predictions. In general, agreement between finite contact patch theory and experimental observation is good. A modified string theory is also presented in which coefficients for cornering force and self-aligning torque are determined separately. This theory improves the correspondence between the experimental and analytical data, particularly on tires with relatively high self-aligning torques.

Nybakken, G. H.↗
NASA NTRS2004

Materials Analysis: A Key to Unlocking the Mystery of the Columbia Tragedy

Materials analyses of key forensic evidence helped unlock the mystery of the loss of space shuttle Columbia that disintegrated February 1, 2003 while returning from a 16-day research mission. Following an intensive four-month recovery effort by federal, state, and local emergency management and law officials, Columbia debris was collected, catalogued, and reassembled at the Kennedy Space Center. Engineers and scientists from the Materials and Processes (M&P) team formed by NASA supported Columbia reconstruction efforts, provided factual data through analysis, and conducted experiments to validate the root cause of the accident. Fracture surfaces and thermal effects of selected airframe debris were assessed, and process flows for both nondestructive and destructive sampling and evaluation of debris were developed. The team also assessed left hand (LH) airframe components that were believed to be associated with a structural breach of Columbia. Analytical data collected by the M&P team showed that a significant thermal event occurred at the left wing leading edge in the proximity of LH reinforced carbon carbon (RCC) panels 8 and 9. The analysis also showed exposure to temperatures in excess of 1,649 C, which would severely degrade the support structure, tiles, and RCC panel materials. The integrated failure analysis of wing leading edge debris and deposits strongly supported the hypothesis that a breach occurred at LH RCC panel 8.

Mayeaux, Brian M.↗
NASA NTRS2022

NASA Satellites and Data Fusion: A Case Study with Coral Reefs

As the world is experiencing a significant rise in both AI, Climate, and Space start-up companies, we are in a new wave of limitless innovation. NASA's statutory responsibility is to "provide for the widest practicable and appropriate dissemination of information concerning its activities and the results thereof." (51 U.S.C. § 20112) In particular, through machine learning, the public data drawn from NASA’s space assets can provide insights for addressing climate-related problems here on Earth. And many climate start-up companies can benefit from leveraging this data, either for proof of concepts or their own missions. In the Fall of 2021, several scientists from NASA and Coral Vita led a Practicum with the Georgia Institute of Technology Masters in Data Analytics program. The Practicum saw two teams of students develop and implement machine learning models to infer, from CALIPSO satellite imagery, vitality properties upon satellite pass. This kind of capability can lead to real-time mapping of coral health around the world, giving organization an understanding of where to prioritize reef reconstitution.. In this presentation, we will highlight this use case and discuss other concrete applications in which space data is used to solve problems here on Earth.

Earth Sciences↗