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 181 records · Page 10

Revalidation of the Volatile Organic Analyzer Following a Major On-Orbit Maintenance Activity

The Volatile Organic Analyzer (VOA) contributes to the assessment of air quality aboard the International Space Station (ISS) by identifying and quantifying target airborne volatile organic contaminants in the module air. This on-orbit contaminant monitoring capability becomes particularly important during an air quality degradation event such as a system leak. During several ISS air quality degradations, the VOA has generated near real-time data that was used to make decisions or to better understand the contingency. The VOA was operational from January 2002 through June 2003, during which time it was validated by comparing VOA data to simultaneously acquired grab sample containers (GSCs). In January 2003, one of the two analytical channels of the VOA was shutdown because of a component failure, but a redundant channel continued to supply the necessary analytical data. In June 2003, the sole remaining channel was deactivated. Initial assessments of the channel shutdowns pointed to failed fuses or heaters, but neither was considered repairable on orbit. In 2005, it was determined that failed fuses could be replaced on orbit and the crew conducted a diagnostic procedure to identify the failed component. The crew discovered that both channels incurred failed fuses, which lead to a subsequent on orbit maintenance activity and return of the VOA to operational status in December 2005. The VOA has been providing data on the ISS atmosphere since its reactivation in 2005 and this paper will present the VOA data collected during 2006. Special emphasis will be placed upon the revalidation of the repaired VOA using GSCs as well as a summary of the diagnostic and repair procedures.

Limero, Thomas↗

Data for Machado-Silva et al. (2024), "Short-Term Groundwater Level Fluctuations Drive Subsurface Redox Variability"

This dataset contains the analytical data reported in Machado-Silva et al. (2024) as part of the COMPASS-FME project, which seeks to advance a scalable, predictive understanding of the fundamental biogeochemical processes, ecological structure, and ecosystem dynamics that distinguish coastal terrestrial-aquatic interfaces from the purely terrestrial or aquatic systems to which they are coupled. The dataset consists of water quality parameters as well as redox potential, water content, and electrical conductivity. These data were collected in 2022 in Crane Creek (CRC), Portage River (PTR), and Old Woman Creek (OWC). Each of these sites included uplands (UP), transitions (TR), wetland-transition edge (WTE), and wetland (W) zones. The sites represent replicates of the Lake Erie terrestrial-aquatic interface under fluctuating water levels and are located in well-preserved areas with natural or restored marsh and forest cover.This dataset consists of a single data file (Machado_Silva_et_al_2024_EST_data.csv) that is in comma-separated value (CSV) format. No special software is required to read it.This dataset uses the ESS-DIVE Hydrologic Monitoring Reporting Format 1.0.

54 ENVIRONMENTAL SCIENCES↗

A co-registered in-situ and ex-situ dataset from wire arc additive manufacturing process

Recent progress in sensing techniques and data analytics tools have significantly accelerated the development of Wire Arc Additive Manufacturing (WAAM) systems. This data-centric approach emphasizes leveraging sensor data available throughout the production process to optimize performance. Integration of extensive data analysis provides opportunities for improving precision, reducing waste, and enhancing the quality of produced parts. This method relies on AI/ML models and optimization techniques, which are developed using the data collected from various sources, including in-situ sensors, ex-situ imaging, and manufacturing process parameters. The quality and diversity of this data, along with the alignment between different data streams (achieved through spatiotemporal registration) are critical for the successful development of AI/ML and optimization models. In this work, we present a spatiotemporally registered dataset generated during the WAAM process of deposition of a rectangular block. The dataset includes a comprehensive description of the deposition process, process parameters, welding characteristics and acoustic data collected in-situ, and X-Ray Computed Tomography data of the build.

42 ENGINEERING↗

GraphAide: Advanced Graph-Assisted Query and Reasoning System

Curating knowledge from multiple siloed sources that contain both structured and unstructured data is a major challenge in many real-world applications. Pattern matching and querying represent fundamental tasks in modern data analytics that leverage this curated knowledge. The development of such applications necessitates overcoming several research challenges, including data extraction, named entity recognition, data modeling, and designing query interfaces. Moreover, the explainability of these functionalities is critical for their broader adoption. The emergence of Large Language Models (LLMs) has accelerated the development lifecycle of new capabilities. Nonetheless, there is an ongoing need for domain-specific tools tailored to user activities. The creation of digital assistants has gained considerable traction in recent years, with LLMs offering a promising avenue to develop such assistants utilizing domain-specific knowledge and assumptions. In this context, we introduce an advanced query and reasoning system, GraphAide, which constructs a knowledge graph (KG) from diverse sources and allows to query and reason over the resulting KG. GraphAide harnesses both the KG and LLMs to rapidly develop domain-specific digital assistants. It integrates design patterns from retrieval augmented generation (RAG) and the semantic web to create an agentic LLM application. GraphAide underscores the potential for streamlined and efficient development of specialized digital assistants, thereby enhancing their applicability across various domains.

Purohit, Sumit [BATTELLE (PACIFIC NW LAB)] (ORCID:↗

Thermal conductivity of Rene 41 honeycomb panels

Effective thermal conductivities of Rene 41 panels suitable for advanced space transportation vehicle structures were determined analytically and experimentally for temperature ranges between 20.4K (423 F) and 1186K (1675 F). The cryogenic data were obtained using a cryostat whereas the high temperature data were measured using a heat flow meter and a comparative thermal conductivity instrument respectively. Comparisons were made between analysis and experimental data. Analytical methods appear to provide reasonable definition of the honeycomb panel effective thermal conductivities.

Deriugin, V.↗

Analytic model approach to the inversion of scattering data

An analytic model approach is applied to several simple atmospheric inversion problems. This method gives a sharp determination of aerosol size distribution parameters. It is shown that this analytic approach, together with ground level point sampling data measurements, can be used to infer information on the tropospheric ozone profile.

Green, A. E. S.↗

EDX ClaiMM: Digital Resources for the Critical Minerals and Materials Community

Securing critical mineral supply chains is essential for transitioning to a clean energy economy and for maintaining national security. Big-data analytics can serve as a cost-effective means of identifying new domestic critical mineral resources but only if data can be easily located and digested. Using ArcGIS Enterprise Sites, EDX ClaiMM was developed to increase the accessibility of critical minerals data, reducing time spent on data collection and integration. Hosted tools provide rapid visualization and exploration of key datasets, unlocking insights to support resource assessments.

Yesenchak, Rachel↗

Utilizing HDF4 File Content Maps for the Cloud

We demonstrate a prototype study that HDF4 file content map can be used for efficiently organizing data in cloud object storage system to facilitate cloud computing. This approach can be extended to any binary data formats and to any existing big data analytics solution powered by cloud computing because HDF4 file content map project started as long term preservation of NASA data that doesn't require HDF4 APIs to access data.

Elastic Search↗

What Can We Learn from One Billion Ground System Log Messages?

Shortage of log-based data in a ground system they have traditionally been the under achievers in a satellite ground system. This is due to several factors: Once log messages scroll out of view on the TTC event console window they are soon forgotten. Application and system log files are scattered across directories within a system, across a multitude of servers, and across one or more databases making access cumbersome. Typical tools to perform log file content searching are generally crude and typically only employed as part of trouble-shooting exercises.As we move towards satellite constellations and fleets and add even more status information, the number of messages keeps growing. One mission now estimates that they could generate 3,000,000 messages per day 1 billion per year - for the life of their mission. What to do with those 1 billion messages? That is the challenge. With the recent technological advances in the management of large data sets, text-based processing, and data analytics, there are now capabilities that we can provide to the ground system engineers and satellite operators to address what we postulate are missed opportunities. Advanced real-time log analysis can allow us to be less reactionary in favor of being more proactive. Analytics goals include the ability to: Identify root cause of unexpected events, failures or error conditions enabled by correlating disparate data. Detect security breaches attempts before they are successful. Help admins ensure IT resources continue running optimally. Identify trends and patterns that may indicate impending failures or error conditions for valuable assets before they happen. Compare satellites in a fleet or constellation in terms of number of alarms, number of command sent to them, etc.. Answer questions like "Are the operations support needs increasing over the past year?" or "Have we seen this combination of alarm conditions before?" But really, once the tools are readily available the users will start realizing what can be done with their new powers. In this presentation we will show the results of analyzing millions of actual mission operations log messages, how the results can be displayed to the user, and how new products now available as open source can be applied to the challenges of large scale time-tagged text-based mission operations messages. Flight operations team members believe that this is a powerful new option for how they assess overall system and space asset health. Technical descriptions of the design, tools, and storage will be provided. One billion messages? Bring'em on!

Orsborne, Sharon↗

Rate and time dependent failure of structural adhesives

Studies on two adhesives (Metlbond 1113 and 1113-2) identified as having important applications in the bonding of composite materials are presented. A testing program to ascertain stress-strain, strain-rate, time, yield, and/or failure behavior of these materials in bulk form using uniaxial tensile constant strain-rate, creep, and relaxation tests is described. The stress-strain behavior of each material is shown to be significantly rate dependent. A rate dependent stress whitening (crazing) phenomenon occurs prior to either yield or fracture. A region of linear elasticity, a region of viscoelasticity, and the onset of yielding are identified in the stress-strain behavior. The linear elastic limit and the yield point are shown to be rate dependent and agree well with an empirical equation proposed by Ludwik. A creep to failure phenomenon is shown to exist and is correlated with a delayed yield equation proposed by Crochet. Analytical predictions based on a modified Bingham model are shown to agree well with experimental stress-strain strain-rate data. Analytical predictions based on a modified Ramberg-Osgood equation are also shown for comparison purposes.

Brinson, H. F.↗

Determination of the effects of heating on modal characteristics of an aluminum plate with application to hypersonic vehicles

The structural integrity of proposed high speed aircraft can be seriously affected by the extremely high surface temperatures and large temperature gradients throughout the vehicle's structure. Variations in the structure's elastic characteristics as a result of thermal effects can be seen by changes in vibration characteristics. Analysis codes that predict these changes must be correlated and verified with experimental data. Analytical and experimental modal test results are given from uniform, nonuniform, and transient thermoelastic vibration tests of a 12 x 50 x 0.19 aluminum plate. The data show the effect of heat on the modal characteristics of the plate. The results showed that frequencies decreased, damping increased, and mode shapes remained unchanged as the temperature of the plate increased. Analytical predictions provided good correlation with experimental results.

Snyder, H. Todd↗

Reliable and Efficient Machine Learning (Final Technical Report)

Modern scientific experiments generate massive amounts of data at a pace much faster than humans can manually analyze. While machine learning has revolutionized commercial data analysis (such as recommending movies or recognizing faces), applying these tools to complex scientific discovery is challenging because scientific answers must be precise, interpretable, and adhere to physical laws. The research under this project aims to develop new mathematical tools and computer algorithms specifically designed for scientific applications. Major progress has been made in automatically cleaning and deconstructing messy experimental data, analyzing the visual information of physical phenomena, determining the underlying physical variables, and providing rig orous mathematical analysis of interesting algorithms and concepts widely used in machine learning. This project addressed the critical gap between our ability to generate massive scientific data and our ability to extract interpretable information from it. We established mathematical foundations for Scientific Machine Learning (SciML) aimed at effective data analytics and automated discovery. Our work focused on three core objectives: (1) developing reliable feature extraction methods for dynamic high-dimensional data, (2) establishing mathematical foundations for discovering dynamics via neural networks, and (3) creating rigorous optimization techniques for these models. Key outcomes come from two fronts. On the practical side, they include the development of algorithms that significantly enhance the extraction of signals from field data, as well as the capability to handle situations that exhibit smooth variations or physical stretching due to temperature changes. They also include the creation of an automated framework for discovering fundamental state variables from raw experimental data, demonstrating the ability to identify intrinsic physical dimensions without prior knowledge of the governing laws. On the theoretical front, the research results in theoretical advances in Optimal Transport, a widely used notion in SciML, specifically regarding functions with fixed-size nodal sets, provide sharp bounds relevant to uncertainty quantification. Meanwhile, the outcomes also include the establishment of convergence theories for nonlocal gradient descent methods, enabling robust optimization with noisy data in high-dimensional settings commonly encountered in scientific modeling. The project also helps creating opportunities to train the next generation of researchers, equipping them with the necessary technical skills for today’s workplace and preparing them for future advances.

97 MATHEMATICS AND COMPUTING↗

X-ray Mapping of Terrestrial and Extraterrestrial Materials Using the Electron Microprobe

Lunar samples returned from the Apollo program motivated development of the Bence-Albee algorithm for the rapid and accurate analysis of lunar materials, and established interlaboratory comparability through its common use. In the analysis of mineral and rock fragments it became necessary to combine micro- and macroscopic analysis by coupling electron-probe microanalysis (EPMA) with automated stage point counting. A coarse grid that included several thousand points was used, and initially wavelength-dispersive (WDS) and later energydispersive (EDS) data were acquired at discrete stage points using approx. 5 sec count times. A approx 50 micrometer beam diameter was used for WDS and up to 500 micrometer beam diameter for EDS analysis. Average analyses of discretely sampled phases were coupled with the point count data to calculate the bulk composition using matrix algebra. Use of a defocused beam resulted in a contribution from multiple phases to each analytical point, and the analytical data were deconvolved relative to end-member phase chemistry on the fly. Impressive agreement was obtained between WDS and EDS measurements as well as comparison with bulk chemistry obtained by other methods. In the 30 years since these methods were developed, significant improvements in EPMA automation and computer processing have taken place. Digital beam control allows routine collection of x-ray maps by EDS, and stage mapping for WDS is conducted continuously at slew speed and incrementally by sampling at discrete points. Digital pulse processing in EDS systems has significantly increased the throughput for EDS mapping, and the ongoing development of Si-drift detector systems promises mapping capabilities rivaling WDS systems. Spectrum imaging allows a data cube of EDS spectra to be acquired and sophisticated processing of the original data is possible using matrix algebra techniques. The study of lunar and meteoritic materials includes the need to conveniently: (1) Characterize the sample at microscopic and macroscopic scales with relatively high sensitivity, (2) Determine the modal abundance of minerals, and (3) Identify and relocate discrete features of interest in terms of size and chemistry. The coupled substitution of cations in minerals can result in significant variation in mineral chemistry, but at similar average Z, leading to poor backscattered-electron (BSE) contrast discrimination of mineralogy. It is necessary to discriminate phase chemistry at both the trace element level and the major element level. To date, the WDS of microprobe systems is preferred for mapping due to high throughput and the ability to obtain the necessary intensity to discriminate phases at both trace and major element concentrations. It is desirable to produce fully quantitative compositional maps of geological materials, which requires the acquisition of k-ratio maps that are background and dead-time corrected, and which have been corrected by phi(delta z> or an equivalent algorithm at each pixel. To date, turnkey systems do not allow the acquisition of k-ratio maps and the rigorous correction in this manner. X-ray maps of a chondrule from the Ourique meteorite, and a comb-layered xenolith from the San Francisco volcanic field, have been analyzed and processed to extract phase information. The Ourique meteorite presents a challenge due to relatively low BSE contrast, and has been studied using spectrum imaging. X-ray maps for Si, Mg, and FeK(alpha) were used to produce RGB images. The xenolith sample contains sector-zoned augite, olivine, plagioclase, and basaltic glass. X-ray maps were processed using Lispix and ImageJ software to produce mineral phase maps. The x-ray maps for Mg, Ca, and Ti were used with traceback to generate binary images that were converted to RGB images. These approaches are successful in discriminating phases, but it is desirable to achieve the methods that were used on lunar samples 30 years ago on current microprobe systems. Curnt research includes x-ray mapping analysis of the Dalgety Downs chondrite by micro x-ray fluorescence and spectrum imaging, in collaboration with Kenny Witherspoon of IXRF Systems and Dale Newbury of NIST.

Carpenter, P.↗

Roadmap on data-centric materials science

Science is and always has been based on data, but the terms ‘data-centric’ and the ‘4th paradigm’ of materials research indicate a radical change in how information is retrieved, handled and research is performed. It signifies a transformative shift towards managing vast data collections, digital repositories, and innovative data analytics methods. The integration of artificial intelligence and its subset machine learning, has become pivotal in addressing all these challenges. This Roadmap on Data-Centric Materials Science explores fundamental concepts and methodologies, illustrating diverse applications in electronic-structure theory, soft matter theory, microstructure research, and experimental techniques like photoemission, atom probe tomography, and electron microscopy. While the roadmap delves into specific areas within the broad interdisciplinary field of materials science, the provided examples elucidate key concepts applicable to a wider range of topics. The discussed instances offer insights into addressing the multifaceted challenges encountered in contemporary materials research.

36 MATERIALS SCIENCE↗

A Comparison of Analytical and Experimental Data for a Magnetic Actuator

Theoretical and experimental force-displacement and force-current data are compared for two configurations of a simple horseshoe, or bipolar, magnetic actuator. One configuration utilizes permanent magnet wafers to provide a bias flux and the other configuration has no source of bias flux. The theoretical data are obtained from two analytical models of each configuration. One is an ideal analytical model which is developed under the following assumptions: (1) zero fringing and leakage flux, (2) zero actuator coil mmf loss, and (3) infinite permeability of the actuator core and suspended element flux return path. The other analytical model, called the extended model, is developed by adding loss and leakage factors to the ideal model. The values of the loss and leakage factors are calculated from experimental data. The experimental data are obtained from a magnetic actuator test fixture, which is described in detail. Results indicate that the ideal models for both configurations do not match the experimental data very well. However, except for the range around zero force, the extended models produce a good match. The best match is produced by the extended model of the configuration with permanent magnet flux bias.

Groom, Nelson J.↗

Site preferences of Ni/2+/ and Co/2+/ in clinopyroxene and olivine - Limitations of the statistical approach.

Criticism of a statistical approach used by Dasgupta (1972) in analyzing Snyder's (1959) chemical data for minerals from the Duluth Complex in Minnesota. Apart from obvious mathematical objections to citing correlation coefficients to four significant figures from Snyder's relatively inaccurate analytical data, several more fundamental criticisms are leveled at the statistical approach of Dasgupta. These relate to compositional zoning and disequilibrium in the minerals, inhomogeneities of the samples caused by inclusions and exsolved phases, measured site population data for the major cations in olivines and pyroxenes, and the importance of coupled substitutions in the crystal structures. It is concluded that the crystal field predictions of relative enrichments of Ni(2+) and Co(2+) ions in olivine and pyroxene structures have not been disproved by Dasgupta's statistical approach.

Burns, R. G.↗

Correlation and assessment of structural airplane crash data with flight parameters at impact

Crash deceleration pulse data from a crash dynamics program on general aviation airplanes and from transport crash data were analyzed. Structural airplane crash data and flight parameters at impact were correlated. Uncoupled equations for the normal and longitudinal floor impulses in the cabin area of the airplane were derived, and analytical expressions for structural crushing during impact and horizontal slide out were also determined. Agreement was found between experimental and analytical data for general aviation and transport airplanes over a relatively wide range of impact parameter. Two possible applications of the impulse data are presented: a postcrash evaluation of crash test parameters and an assumed crash scenario.

Carden, H. D.↗

Verification of a landing dynamics computer program using Viking Lander data

An investigation was conducted to verify the accuracy of the Landing Dynamics Computer Program (LDCP) used to simulate the landing event of the Viking Lander (VL) on to the Martian surface. This verification was achieved by comparing the analytical data with results from a test program involving a dynamically scaled model of a VL configuration. A secondary objective of this study was to evaluate the sensitivity of the VL to initial rates and orientations, configuration modifications, and footpad friction.

Muraca, R. J.↗