Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “data analytic”

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 829 records · Page 46
All sourcesNASA NTRSDOE OSTI
NASA NTRS1979

Surface pressure data on a series of analytic forebodies at Mach numbers from 1.70 to 4.50 and combined angles of attack and sideslip

Tabulated surface pressure data for a series of four forebodies which have analytically defined cross sections and which are based on a parabolic arc profile having a 20 deg half angle at the nose are presented without analysis. The first forebody has a circular cross section, and the second has a cross section which is an ellipse with an axis ratio of 2/1. The third has a cross section defined by a lobed analytic curve. The fourth forebody has cross sections which develop smoothly from circular at the pointed nose through the lobed analytic curve and back to circular at the aft end. The data generally cover angles of attack from -5 deg to 20 deg at angles of sideslip from 0 deg to 5 deg for Mach numbers of 1.70, 2.50, 3.95, and 4.50 at a constant Reynolds number.

Townsend, J. C.↗
DOE OSTI2023

A Processing and Analytics System for Microscopy Data Workflows: The Pycroscopy Ecosystem of Packages

Major advancements in fields as diverse as biology and quantum computing have relied on a multitude of microscopy techniques. Despite the considerable proliferation of these instruments, significant bottlenecks remain in terms of processing, analysis, storage, and retrieval of the acquired datasets. Aside from lack of file standards, individual domain-specific analysis packages are often disjoint from the underlying datasets, and thus keeping track of analysis and processing steps remains tedious for the end-user, hampering reproducibility. Here, in this study, the pycroscopy ecosystem of packages is introduced, an open-source python-based ecosystem underpinned by a common data model. The data model, termed the N-dimensional spectral imaging data format, is realized in pycroscopy's sidpy package. This package is built on top of dask arrays, thus leveraging dask array attributes, but expanding them to accelerate microscopy relevant analysis and visualization. Several examples of the use of the pycroscopy ecosystem to create workflows for data ingestion and analysis of scanning transmission electron microscopy (STEM) and scanning probe microscopy data are shown. Adoption of such standardized routines will be critical to usher in the next generation of autonomous instruments where processing, computation, and meta-data storage will be critical to overall experimental operations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Cross-property deep transfer learning framework for enhanced predictive analytics on small materials data

Abstract Artificial intelligence (AI) and machine learning (ML) have been increasingly used in materials science to build predictive models and accelerate discovery. For selected properties, availability of large databases has also facilitated application of deep learning (DL) and transfer learning (TL). However, unavailability of large datasets for a majority of properties prohibits widespread application of DL/TL. We present a cross-property deep-transfer-learning framework that leverages models trained on large datasets to build models on small datasets of different properties. We test the proposed framework on 39 computational and two experimental datasets and find that the TL models with only elemental fractions as input outperform ML/DL models trained from scratch even when they are allowed to use physical attributes as input, for 27/39 (≈ 69%) computational and both the experimental datasets. We believe that the proposed framework can be widely useful to tackle the small data challenge in applying AI/ML in materials science.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Data from: 'Abiotic influences on continuous conifer forest structure across a subalpine watershed'

This package archives the core data used for analysis and inference in 'Abiotic influences on continuous conifer forest structure across a subalpine watershed' (Worsham et al., 2025). All data were collected in the East River, Washington Gulch, Slate River, and Coal Creek watersheds of Colorado. In the paper, we quantified the relative influence of climate, topographic, edaphic, and geologic factors on conifer stand structure and composition, and their functional relationships, at the watershed scale. We used waveform LiDAR data to derive spatially continuous stand structure metrics. We fused these with a species-level classification map to estimate tree species abundance. We applied generalized additive and generalized boosted models to evaluate the covariability of structural and compositional metrics with abiotic variables. The package contains the essential products required for reproducing our analysis and the tables and figures reported in the publication. The products comprise four classes: (1) geospatial data, (2) tabular data used for inferential analysis, (3) tabular data describing analytical results and performance statistics, and (4) a data user guide. (1) includes discretized waveform LiDAR data, locations and attributes of individual tree crowns, sampling locations and domain boundaries, a canopy height model, and raster files of estimated forest structural and compositional metrics at 100 m grid scale. (2) includes all response and explanatory variable values applied in inferential models. Response variables include conifer forest stand density, basal area, 95th percentile height, quadratic mean diameter, and others. Explanatory variables include climatic water deficit, actual evapotranspiration, elevation, heat load, soil available water content, and others. (3) includes results of training and testing several individual tree detection (ITD) algorithms, as well as inferential modeling results. (4) is a PDF user guide for this data package, including detailed descriptions and data dictionaries for all files. The data package root contains 17 assets: 8 compressed tape archive (.tar.gz) files, 5 comma-separated values (.csv) files, 3 Geographic Tagged Image File Format (GeoTIFF) (.tif) files, and 1 Portable Document Format (.pdf) file. The compressed .tar.gz archives contain ESRI shapefiles (.shp) .tif, compressed LASer (.laz), and .csv files. The archives must first be decompressed using the widely distributed command-line software utility TAR. All other files, including constituent files within the .tar.gz archives, can be opened in the open-source R statistical computing environment. Alternatively, .csv files may also be read in any simple text editor software or Microsoft Excel. Geospatial files including .shp and .tif files can also be opened in GIS software, such as QGIS (open-source) or ESRI ArcGIS (proprietary). The .pdf Data User Guide can be read with Adobe Acrobat Reader or other compatible readers.

2018 NEON and 2025 CHESS Campaigns↗
DOE OSTI2024

Analytical methods for online data quality assessment

This chapter provides a comprehensive overview of the main steps for algorithmic sensor signal quality assessment, which can enhance the decision-making process for water resource recovery facility (WRRF) operation and optimization. It introduces the concept of redundancy as the basis for data quality assessment. It also explains the typical data processing pipeline, which consists of preliminary analysis, data pre-processing, and specific algorithmic approaches. Each of these processes is presented and discussed in three separate sections. Importantly, this chapter introduces the main approaches for data quality assessment, provides guidelines for selecting the most suitable one and the key performance indicators to evaluate them and explains how to collect metadata through such an algorithmic approach.

Aguado, Daniel↗
NASA NTRS1995

A field- and laboratory-based quantitative analysis of alluvium: Relating analytical results to TIMS data

Thermal Infrared Multispectral Scanner (TIMS) data were acquired over the McDowell Mountains northeast of Scottsdale, Arizona during August 1994. The raw data were processed to emphasize lithologic differences using a decorrelation stretch and assigning bands 5, 3, and 1 to red, green, and blue, respectively. Processed data of alluvium flanking the mountains exhibit moderate color variation. The objective of this study was to determine, using a quantitative approach, what environmental variable(s), in the absence of bedrock, is/are responsible for influencing the spectral properties of the desert alluvial surface.

Wenrich, Melissa L.↗
NASA NTRSDate not supplied

Analytical Framework for Rodent/NHP Data Set Utilization to Inform Human CNS Risk Estimation

Objectives Review and inform on tactics to analyze & communicate data from animal research (e.g., rodents, mini-pigs, NHPs, et al) exposed to single and combinations of spaceflight hazards, using NASA’s Human System Risk Board (HSRB) process for the Behavioral Medicine Risk - To quantitatively inform Behavioral Medicine Risk posture - i.e., likelihood (L) and consequence (C) - To help inform estimation of crew health standards for operational task performance (i.e., Fitness For Duty, Space Permissible Exposure Levels, Permissible Operational Limits).

Brain↗
DOE OSTI2022

Translytics: A Novel Approach for Runtime Selection of Database Layout Based on User’s Context

Currently, organizations have to maintain separate systems for transactions and analytics inside the company. Notably, different vendors provide the capabilities for either of these tasks that require specialized hardware or software. Data engineers are required to retrieve data from one source and transform it into another format to obtain the maximum benefit in a minimum time. Organizations strive for a competitive advantage that is achieved by fetching data from their customers and getting insights earliest for timely decision making. Present practices do not permit the view of the latest data for analytics since the first data have to be fetched from the source, transformed, and loaded to other systems to be utilized for analysis by relevant teams. This paper introduces a single system for both transactions and analytics. Our proposed solution would permit companies to seamlessly adapt our solution without the need to shift all of their data to newer systems and allow all the teams. It would grant all the teams to have a view of the latest available data without extra expertise and budget.

Tanvir, Muhammad Makhshif↗
NASA NTRS2018

Benchmark Comparison of Cloud Analytics Methods Applied to Earth Observations

Earth Observation data are a vital resource for studying long term changes, but the large data volumes can be challenging to analyze. Time series analysis in particular is hampered by the typical thin-time-slice file organization. We examine several potential solutions inspired in large part by the data-parallel methods that have arisen with cloud computing. These solutions include various combinations of data re-organization, spatial indexing, distributed storage and pre-computation that we term "Analytics Optimized Data Stores" (AODS). We find that even simple solutions (such as a data cube) produce more than an order of magnitude improvement; the best provide two to three orders of magnitude improvement. The most performant solutions have tradeoffs in terms of generality or storage footprint, but may nonetheless be useful components in data analytics frameworks where performance is critical.

parallel processing (computers)↗
NASA NTRS1978

Analytical models and system topologies for remote multispectral data acquisition and classification

Simple analytical models are presented of the radiometric and statistical processes that are involved in multispectral data acquisition and classification. Also presented are basic system topologies which combine remote sensing with data classification. These models and topologies offer a preliminary but systematic step towards the use of computer simulations to analyze remote multispectral data acquisition and classification systems.

Huck, F. O.↗
NASA NTRS1974

Experimental investigation of the landing dynamics of three-legged spacecraft models

An experimental investigation was conducted to obtain accurate data from two three-legged spacecraft landing systems for purposes of validating current and future computer programs for legged landers. Two landing-gear systems were investigated: an inverted tripod system and a cantilever system. Tests were conducted for eight landing conditions chosen to obtain stability data, maximum loads, and maximum strokes for correlation with analytical results. Data from the two models are not directly comparable because of geometry and mass differences, but both are considered to be typical models of the respective landing-gear systems. Results indicate that maximum accelerations for both models, which occurred during a nearly flat landing on a horizontal surface, were nearly the same (approximately minus 18g). Maximum primary strut forces occurred for landings into a 20 deg slope and were 40 kiloNewtons (9000 lbf) and 47 kiloNewtons (10 500 lbf) for the inverted tripod and cantilever models, respectively; and maximum primary strut strokes for both models were 19 cm (7.4 in.). The inverted tripod model was slightly more stable than the cantilever model because of a larger ratio of footpad radius to center-of-gravity height.

Stubbs, S. M.↗
NASA NTRS1992

Development of and flight results from the Space Acceleration Measurement System (SAMS)

Described here is the development of and the flight results from the Space Acceleration Measurement System (SAMS) flight units used in the Orbiter middeck, Spacelab module, and the Orbitercargo bay. The SAMS units are general purpose microgravity accelerometers designed to support a variety of science experiments with microgravity acceleration measurements. A total of six flight units have been fabricated; four for use in the Orbiter middeck and Spacelab module, and two for use in the Orbiter cargo bay. The design of the units is briefly described. The initial two flights of SAMS units on STS-40 (June 1991) and STS-43 (August 1991) resulted in 371 megabytes and 2.6 gigabytes of data respectively. Analytical techniques developed to examine this quantity of acceleration data are described and sample plots of analyzed data are illustrated. Future missions for the SAMS units are listed.

Delombard, Richard↗
NASA NTRS1992

Development of and flight results from the Space Acceleration Measurement System (SAMS)

This paper describes the development of and flight results from the Space Acceleration Measurement System (SAMS) flight units used in the Orbiter middeck, Spacelab module and the Orbiter cargo bay. The SAMS units are general purpose microgravity accelerometers designed to support a variety of science experiments with microgravity acceleration measurements. A total of six flight units have been fabricated; four for use in the Orbiter middeck and Spacelab module, and two for use in the Orbiter cargo bay. The design of the units is briefly described. The initial two flights of SAMS units on STS-40 (June 1991) and STS-43 (August 1991) resulted in 371 megabytes and 2.6 gigabytes of data, respectively. Analytical techniques developed to examine this quantity of acceleration data are described and sample plots of analyzed data are illustrated. Future missions for the SAMS units are listed.

Delombard, Richard↗
NASA NTRS1993

Topex Microwave Radiometer thermal control - Post-system-test modifications and on-orbit performance

The Topex Microwave Radiometer has had an excellent thermal performance since launch. The instrument, however, went through a hardware modification right before launch to correct for a thermal design inadequacy that was uncovered during the spacecraft thermal vacuum test. This paper reports on how the initially obscure problem was tracked down, and how the thermal models were revised, validated, and utilized to investigate the solution options and guide the hardware modification decisions. Details related to test data interpretation, analytical uncertainties, and model-prediction vs. test-data correlation, are documented. Instrument/spacecraft interface issues, where the problem originated and where in general pitfalls abound, are dealt with specifically. Finally, on-orbit thermal performance data are presented, which exhibit good agreement with flight predictions, and lessons learned are discussed.

Lin, Edward I.↗