Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “science data processing”

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 739 records · Page 41
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Atomic kinetics of laboratory photoionized plasmas relevant to astrophysics. Final report

The major goal of this project was to study the atomic and radiation physics of photoionized plasmas driven by a broadband x-ray flux and its impact on plasma x-ray heating and ionization, emissivity and opacity, and radiation-hydrodynamics. This problem is relevant to the physics of accretion disks surrounding black holes, x-ray binaries, and active galactic nuclei in astrophysics. In addition, it is also important for understanding non-equilibrium laboratory plasmas driven by a distribution of photons. To this end, and motivated by previous and ongoing gas-cell experiments performed by the PI at the Z facility of Sandia National Laboratories, we developed a new experimental platform at the 1MA Zebra pulsed power accelerator of the University of Nevada, Reno based on using a gas jet produced by a supersonic nozzle. The gas jet is turned into a photoionized plasma driven by the x- ray flux from a wire-array z-pinch. Establishing this new experimental platform at Zebra was a major goal of this project. In addition, we have also dedicated effort to continue complementary experiments at the Z facility using the gas-cell photoionized plasma set up with support from the Fundamental Science Program at Z as well as to perform data processing and analysis, and theory and modeling simulations, including electron kinetics and radiation-hydrodynamics. Since we seek to test and establish what physics models are needed to describe photoionized plasma guided by experimental observation, these complementary experimental efforts were central to achieving the goals of this project.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

NANT Site - ASSIST / Processed Data

This dataset contains processed summary data from the ASSIST operated by NOAA Physical Science Laboratory on Nantucket Island for WFIP3.

17 WIND ENERGY↗
DOE OSTI2017

HEP Analysis Ecosystem Workshop Report

Over the past 20 years the HEP community has developed and gravitated around an analysis ecosystem centered on ROOT. ROOT and its ecosystem both dominate HEP analysis and impact the full event processing chain, providing foundation libraries, I/O services etc. that have prevalence in the field. The analysis tools landscape is however evolving in ways that can have a durable impact on the analysis ecosystem and a strong influence on the analysis and core software landscape a decade from now, a timescale currently in an intensive planning round with the HEP Software Foundation(HSF) Community White Paper process. Data intensive analysis is growing in importance in other sciences and in the wider world. Powerful tools and new development initiatives, both within our field and in the wider open source community, have emerged. Creative developers have an ever more powerful open source toolkit available and are applying it towards innovations that leverage both open source and the ROOT ecosystem. ROOT itself is approaching a major re-engineering with ROOT 7, leveraging the powerful evolution of C++, with a major overhaul in its interfaces as seen both by its users and by satellite tools in the ROOT ecosystem.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS1990

Applications of ISES for geology

The principal applications for onboard data processing and real-time data transmission in the geological sciences are the detection of early warning signs of potential catastrophic events and the rapid assessment of impact and damage following major events. Also, the opportunity for quick look and supporting data during field investigations should not be disregarded. The Eos platforms are ideal for these applications because of the variety of earth sensing instruments and their differing modes of operation. Further study is required to define the role for each instrument and to assess how they can aid each other in establishing an improved output product.

Bowker, David E.↗
NASA NTRS2000

Earth Radiation Measurement Science

This document is the final report for NASA Grant NAG1-1959, 'Earth Radiation Measurement Science'. The purpose of this grant was to perform research in this area for the needs of the Clouds and Earth Radiant Energy System (CERES) project and for the Earth Radiation Budget Experiment (ERBE), which are bing conducted by the Radiation and Aerosols Branch of the Atmospheric Sciences Division of Langley Research Center. Earth Radiation Measurement Science investigates the processes by which measurements are converted into data products. Under this grant, research was to be conducted for five tasks: (1) Point Response Function Measurements; (2) Temporal Sampling of Outgoing Longwave Radiation; (3) Spatial Averaging of Radiation Budget Data; (4) CERES Data Validation and Applications; and (5) ScaRaB Data Validation and Application.

Smith, G. Louis↗
NASA NTRS2000

Earth Science Enterprise Scientific Data Purchase Project: Verification and Validation

This paper presents viewgraphs on the Earth Science Enterprise Scientific Data Purchase Project's verification,and validation process. The topics include: 1) What is Verification and Validation? 2) Why Verification and Validation? 3) Background; 4) ESE Data Purchas Validation Process; 5) Data Validation System and Ingest Queue; 6) Shipment Verification; 7) Tracking and Metrics; 8) Validation of Contract Specifications; 9) Earth Watch Data Validation; 10) Validation of Vertical Accuracy; and 11) Results of Vertical Accuracy Assessment.

Jenner, Jeff↗
NASA NTRS2019

Automated Fiber Placement Manufactured Composites for Science Applications

What automated composite laminate manufacturing isWhy automation is of interest in science applicationsHow composite automation is being considered for science instrument applicationsAnd, about test data showing high stiffness materials processed with automation results in reduced material strength while stiffness and coefficient of thermal expansion are mostly unaffected.

Segal, Ken↗
NASA NTRS2007

Understanding Local Structure Globally in Earth Science Remote Sensing Data Sets

Empirical probability distributions derived from the data are the signatures of physical processes generating the data. Distributions defined on different space-time windows can be compared and differences or changes can be attributed to physical processes. This presentation discusses on ways to reduce remote sensing data in a way that preserves information, focusing on the rate-distortion theory and using the entropy-constrained vector quantization algorithm.

massive data sets↗
NASA NTRS2011

An Interim Report on NASA's Draft Space Technology Roadmaps

NASA has developed a set of 14 draft roadmaps to guide the development of space technologies under the leadership of the NASA Office of the Chief Technologist (OCT). Each of these roadmaps focuses on a particular technology area (TA). The roadmaps are intended to foster the development of advanced technologies and concepts that address NASA's needs and contribute to other aerospace and national needs. OCT requested that the National Research Council conduct a study to review the draft roadmaps, gather and assess relevant community input, and make recommendations and suggest priorities to inform NASA's decisions as it finalizes its roadmaps. The statement of task states that "based on the results of the community input and its own deliberations, the steering committee will prepare a brief interim report that addresses high-level issues associated with the roadmaps, such as the advisability of modifying the number or technical focus of the draft NASA roadmaps." This interim report, which does not include formal recommendations, addresses that one element of the study charge. NASA requested this interim report so that it would have the opportunity to make an early start in modifying the draft roadmaps based on feedback from the panels and steering committee. The final report will address all other tasks in the statement of task. In particular, the final report will include a prioritization of technologies, will describe in detail the prioritization process and criteria, and will include specific recommendations on a variety of topics, including many of the topics mentioned in this interim report. In developing both this interim report and the final report to come, the steering committee draws on the work of six study panels organized by technical area, loosely following the organization of the 14 roadmaps, as follows: A Panel 1: Propulsion and Power TA01 Launch Propulsion Systems TA02 In-Space Propulsion Technologies TA03 Space Power and Energy Storage Systems TA13 Ground and Launch Systems Processing B Panel 2: Robotics, Communications, and Navigation TA04 Robotics, TeleRobotics, and Autonomous Systems TA05 Communication and Navigation Systems C Panel 3: Instruments and Computing TA08 Science Instruments, Observatories, and Sensor Systems TA11 Modeling, Simulation, Information Technology, and Data Processing D Panel 4: Human Health and Surface Exploration TA06 Human Health, Life Support, and Habitation Systems TA07 Human Exploration Destination Systems E Panel 5: Materials Panel TA10 Nanotechnology TA12 Materials, Structures, Mechanical Systems, and Manufacturing TA14 Thermal Management Systems F Panel 6: Entry, Descent, and Landing Panel TA09 Entry, Descent, and Landing Systems In addition to drawing on the expertise represented on the steering committee and panels, the committee obtained input from each of 14 public workshops held on each of the 14 roadmaps. At these 1-day workshops, invited speakers, guests, and members of the public engaged in discussions on the different technology areas and their value to NASA. Broad community input was also solicited from a public website, where more than 240 public comments were received on the draft roadmaps in response to application of criteria (such as benefit, risk and reasonableness, and alignment with NASA and national goals) that the steering committee established. This interim report reflects the results of deliberations by the steering committee in light of these public inputs as well as additional inputs from the six panels. The steering committee's final report will be completed early in 2012. That report will prioritize the technologies that span the entire scope of the 14 roadmaps and provide additional guidance on crosscutting themes and other relevant topics.

Source record↗
NASA NTRS2015

Assessing the Amazon Cloud Suitability for CLARREO's Computational Needs

In this document we compare the performance of the Amazon Web Services (AWS), also known as Amazon Cloud, with the CLARREO (Climate Absolute Radiance and Refractivity Observatory) cluster and assess its suitability for computational needs of the CLARREO mission. A benchmark executable to process one month and one year of PARASOL (Polarization and Anistropy of Reflectances for Atmospheric Sciences coupled with Observations from a Lidar) data was used. With the optimal AWS configuration, adequate data-processing times, comparable to the CLARREO cluster, were found. The assessment of alternatives to the CLARREO cluster continues and several options, such as a NASA-based cluster, are being considered.

Goldin, Daniel↗
NASA NTRS2016

Achieving Fast Operational Intelligence in NASA's Deep Space Network Through Complex Event Processing

NASA’s Deep Space Network (DSN) is a complex, global project, in which the expertise of human operators remain crucial for its successful operation. To find ways to save costs in operations and to improve its services, a number of modernization efforts are underway in the DSN. One such effort is a research and technology development task at the Jet Propulsion Laboratory that is investigating the use of complex event processing (CEP) for intelligent assessment of situations, trend analysis, and advanced automation. The technology leverages the significant business intelligence (BI) and data science advancements made in the enterprise industries over the last several years. The open source big data processing engine Apache SparkTM and the high-throughput, distributed messaging system Apache Kafka form the core of the DSN Complex Event Processing (DCEP) framework. This paper discusses the system engineering perspective of why achieving efficient, lower-cost operations in the DSN is a challenging problem, how the DCEP system handles the use cases that help realize intelligent operations, and how this solution fits into the overall model of the planned DSN Follow-the- Sun Operations (FtSO).

Choi, Joshua S.↗
NASA NTRSDate not supplied

Fostering Better Collaboration in Software Development Cycles Between Scientists and Programmers to Ensure the Integrity of and Promote the Development of New Scientific Data Products.

Misaligned incentives lead to reduced interaction between scientists and programmers on modern NASA science data-product development teams. Typically, situations arise where the scientist is not incentivized to learn modern coding practices and the programmer does not understand the science algorithms in the code. A programmer is responsible for the deliverable code thus setting a tradeoff between the desire for code improvement versus fear of compromising the integrity of data-product while the scientist continues to rely on their legacy codebases owing to the complexity of using the delivered code outside the processing environment and lack of validation modules. The NASA/CERES-TISA project has adopted a collaborative approach, with scientists and programmers both utilizing the same software repository with multiple branches, some optimized for delivery to a processing datacenter and others for scientific product development and validation. A team of scientists and programmers jointly review any new science code updates for integration into the codebase and strive to improve practices through promoting algorithm understanding, better institutional knowledge exchange and documentation, modularization, and developing data processing flow-dictated validation and debugging methods. This leads to a reduction in the personnel single point failures and reduced development time for creation of new science data-products.

CERES↗
NASA NTRS2006

Draft Plan for Characterizing Commercial Data Products in Support of Earth Science Research

This presentation introduces a draft plan for characterizing commercial data products for Earth science research. The general approach to the commercial product verification and validation includes focused selection of a readily available commercial remote sensing products that support Earth science research. Ongoing product verification and characterization will question whether the product meets specifications and will examine its fundamental properties, potential and limitations. Validation will encourage product evaluation for specific science research and applications. Specific commercial products included in the characterization plan include high-spatial-resolution multispectral (HSMS) imagery and LIDAR data products. Future efforts in this process will include briefing NASA headquarters and modifying plans based on feedback, increased engagement with the science community and refinement of details, coordination with commercial vendors and The Joint Agency Commercial Imagery Evaluation (JACIE) for HSMS satellite acquisitions, acquiring waveform LIDAR data and performing verification and validation.

Ryan, Robert E.↗
DOE OSTI2021

ARM Aerosol Measurement Science Group 2019 Strategic Planning Workshop Report

This report summarizes the results of a U.S. Department of Energy Atmospheric Radiation Measurement (ARM) user facility workshop held in November 2019 to advance a science-based strategy for ARM’s aerosol measurement program. This was the second such workshop since the Aerosol Measurement Science Group (AMSG) was chartered in 2015 to enhance coordination of ARM observations of aerosols and atmospheric trace gases with the needs of ARM users. The results presented here reflect the AMSG’s focus in recent years on science-based strategies that will contribute to the increased use of ARM data to fulfill its mission of improving process representations and predictability in climate models. Sessions held during the workshop range from interfacing with models through aerosol sampling strategies to calibration protocols and data products. The strategies set forth here were also developed to be directly relevant to ARM’s updated Decadal Vision. The AMSG workshops have been designed to recommend actions that will enable ARM to evolve and continue to meet its mission. To that end, the AMSG will develop an actionable plan from the recommendations outlined here. Some are well defined and can reasonably be accomplished in the short term. Others are less definite or of a larger scope that calls for a longer-term implementation. Further discussion will be required to develop and prioritize actionable items related to such areas. Task teams comprising the appropriate expertise and perspective from the AMSG and other members of the community will be formed to achieve this outcome. Some particular topics are recognized as high priority, so plans are underway to develop task teams and to hold follow-on discussions to address them. Four areas currently being considered for short, focused discussion are 1) aerosol measurements on the North Slope of Alaska, 2) improving data usability for modeling, 3) strategies for advancing remote sensing, vertical profiling, and distributed measurements of aerosols, and 4) aerosol sampling strategies at existing ARM sites to provide intensive modes of operation to promote data usage for process and modeling studies.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

ARM Aerosol Measurement Science Group 2019 Strategic Planning Workshop Report

This report summarizes the results of a U.S. Department of Energy Atmospheric Radiation Measurement (ARM) user facility workshop held in November 2019 to advance a science-based strategy for ARM’s aerosol measurement program. This was the second such workshop since the Aerosol Measurement Science Group (AMSG) was chartered in 2015 to enhance coordination of ARM observations of aerosols and atmospheric trace gases with the needs of ARM users. The results presented here reflect the AMSG’s focus in recent years on science-based strategies that will contribute to the increased use of ARM data to fulfill its mission of improving process representations and predictability in climate models. Sessions held during the workshop range from interfacing with models through aerosol sampling strategies to calibration protocols and data products. The AMSG workshops have been designed to recommend actions that will enable ARM to evolve and continue to meet its mission. To that end, the AMSG will develop an actionable plan from the recommendations outlined here. Some are well defined and can reasonably be accomplished in the short term. Others are less definite or of a larger scope that calls for a longer-term implementation. Further discussion will be required to develop and prioritize actionable items related to such areas. Task teams comprising the appropriate expertise and perspective from the AMSG and other members of the community will be formed to achieve this outcome. Some particular topics are recognized as high priority, so plans are underway to develop task teams and to hold follow-on discussions to address them. Four areas currently being considered for short, focused discussion are 1) aerosol measurements on the North Slope of Alaska, 2) improving data usability for modeling, 3) strategies for advancing remote sensing, vertical profiling, and distributed measurements of aerosols, and 4) aerosol sampling strategies at existing ARM sites to provide intensive modes of operation to promote data usage for process and modeling studies.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Pattern-matching indexing of Laue and monochromatic serial crystallography data for applications in materials science

Serial crystallography data can be challenging to index, as each frame is processed individually, rather than being processed as a whole like in conventional X-ray single-crystal crystallography. An algorithm has been developed to index still diffraction patterns arising from small-unit-cell samples. The algorithm is based on the matching of reciprocal-lattice vector pairs, as developed for Laue microdiffraction data indexing, combined with three-dimensional pattern matching using a nearest-neighbors approach. As a result, large-bandpass data (e.g. 5–24 keV energy range) and monochromatic data can be processed, the main requirement being prior knowledge of the unit cell. Furthermore, angles calculated in the vicinity of a few theoretical and experimental reciprocal-lattice vectors are compared, and only vectors with the highest number of common angles are selected as candidates to obtain the orientation matrix. Global matching on the entire pattern is then checked. Four indexing options are available, two for the ranking of the theoretical reciprocal-lattice vectors and two for reducing the number of possible candidates. Furthermore, the algorithm has been used to index several data sets collected under different experimental conditions on a series of model samples. Additionally, knowing the crystallographic structure of the sample and using this information to rank the theoretical reflections based on the structure factors helps the indexing of large-bandpass data for the largest-unit-cell samples. For small-bandpass data, shortening the candidate list to determine the orientation matrix should be based on matching pairs of reciprocal-lattice vectors instead of triplet matching.

36 MATERIALS SCIENCE↗
NASA NTRS2011

Application of ESE Data and Tools to Air Quality Management: Services for Helping the Air Quality Community use ESE Data (SHAirED)

The goal of this REASoN applications and technology project is to deliver and use Earth Science Enterprise (ESE) data and tools in support of air quality management. Its scope falls within the domain of air quality management and aims to develop a federated air quality information sharing network that includes data from NASA, EPA, US States and others. Project goals were achieved through a access of satellite and ground observation data, web services information technology, interoperability standards, and air quality community collaboration. In contributing to a network of NASA ESE data in support of particulate air quality management, the project will develop access to distributed data, build Web infrastructure, and create tools for data processing and analysis. The key technologies used in the project include emerging web services for developing self describing and modular data access and processing tools, and service oriented architecture for chaining web services together to assemble customized air quality management applications. The technology and tools required for this project were developed within DataFed.net, a shared infrastructure that supports collaborative atmospheric data sharing and processing web services. Much of the collaboration was facilitated through community interactions through the Federation of Earth Science Information Partners (ESIP) Air Quality Workgroup. The main activities during the project that successfully advanced DataFed, enabled air quality applications and established community-oriented infrastructures were: develop access to distributed data (surface and satellite), build Web infrastructure to support data access, processing and analysis create tools for data processing and analysis foster air quality community collaboration and interoperability.

Falke, Stefan↗
DOE OSTI2019

High-Resolution Mass Spectrometry Quantification: Impact of Differences in Data Processing of Centroid and Continuum Data

High-resolution mass spectrometry (HRMS) in full scan mode acquires all ions present in the sample of interest offering a lot of qualitative information. This, in combination with the improved performance of the new generation HRMS systems, triggers more (bio) analysts to switch from triple quad MS systems to HRMS for quantitative analysis. Quantitative processing of HRMS data is performed based on narrow mass extraction windows rather than on nominal mass product ion chromatograms (SRM or MRM). Optimal processing of HRMS data requires different considerations and software tools and can have an impact on data processing and final results. The selection of centroid versus continuum/profile data for processing, selection of the optimal narrow mass extraction window, using theoretical versus measured accurate mass for the extraction of the ion chromatograms as well as differences in calculations and data handling residing in the different vendor software packages are tackled in the presented manuscript. These differences are illustrated on HRMS data acquired for the same plasma samples on three different platforms, i.e., a Sciex QToF, a Waters QToF, and a Thermo Orbitrap system, and processed in four different software packages, i.e., Sciex Analyst® TF, Waters Masslynx, Waters Unifi, and Thermo Xcalibur. The impact of these differences on quantitative HRMS performance was evaluated on calibration curves of eight small molecule compounds in plasma using four different ways of processing. Simple guidelines are provided for the selection of an optimal mass extraction window for continuum and centroided data. .

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗