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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
NASA NTRS1977

Tornado detection data reduction and analysis

Data processing and analysis was provided in support of tornado detection by analysis of radio frequency interference in various frequency bands. Sea state determination data from short pulse radar measurements were also processed and analyzed. A backscatter simulation was implemented to predict radar performance as a function of wind velocity. Computer programs were developed for the various data processing and analysis goals of the effort.

Davisson, L. D.↗
DOE OSTI2021

Deep Dive Topic: Analysis

This section focuses on analysis of I/O behavior and the feedback resulting from that analysis. We define analysis of I/O behavior as interpreting and deriving meaning from I/O instrumentation data. We define feedback as the product of the analysis process. Feedback can be thought of as the link between analysis and the subsequent response to that analysis, such as I/O tuning or policy decisions (see Section 4.4).Analysis and feedback may be consumed by either human stakeholders or machine algorithms. If it is to be consumed by human stakeholders, then the analysis process will likely emphasize understandable language and visualization techniques. If it is to be consumed by machine algorithms, then it will likely emphasize the use of machine-parsable, consistent formats that are suitable for ingestion by policy engines and data-mining tools.

Snyder, Shane↗
NASA NTRS2016

Development of a Prototype Model-Form Uncertainty Knowledge Base

Uncertainties are generally classified as either aleatory or epistemic. Aleatory uncertainties are those attributed to random variation, either naturally or through manufacturing processes. Epistemic uncertainties are generally attributed to a lack of knowledge. One type of epistemic uncertainty is called model-form uncertainty. The term model-form means that among the choices to be made during a design process within an analysis, there are different forms of the analysis process, which each give different results for the same configuration at the same flight conditions. Examples of model-form uncertainties include the grid density, grid type, and solver type used within a computational fluid dynamics code, or the choice of the number and type of model elements within a structures analysis. The objectives of this work are to identify and quantify a representative set of model-form uncertainties and to make this information available to designers through an interactive knowledge base (KB). The KB can then be used during probabilistic design sessions, so as to enable the possible reduction of uncertainties in the design process through resource investment. An extensive literature search has been conducted to identify and quantify typical model-form uncertainties present within aerospace design. An initial attempt has been made to assemble the results of this literature search into a searchable KB, usable in real time during probabilistic design sessions. A concept of operations and the basic structure of a model-form uncertainty KB are described. Key operations within the KB are illustrated. Current limitations in the KB, and possible workarounds are explained.

Green, Lawrence L.↗
DOE OSTI2025

Developing A Custom-Built Metal Aerosol Processing Chamber: Analysis of Aerosol Coagulation at Low Humidities

We have developed an intermediate size (906 L) aerosol processing chamber, and this work reports on the design and initial characterization of dry aerosol experiments. Specifically, we are determining wall-loss and coagulation correction factors using the observed size distribution measurements for surrogates of common aerosol classes: sodium chloride, sucrose, and biomass burning aerosol smoke. Results show that, on average, sodium chloride, sucrose, and smoke wall-loss rates converge to similar values on relatively short time scales (< 1 h). The fitted coagulation correction factor, W C -1 , for smoke particles (1.23 ± 0.312), indicates that on average they adhere to each other more than sodium chloride (0.969 ± 0.524) and sucrose (1.16 ± 1.38). The relative uncertainty is high for the coagulation correction, but it is consistent with our Monte Carlo error analysis. This study lays the foundation for future experiments at elevated humidity and supersaturation conditions to characterize the influence of particle shape on coagulation and cloud parameters.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Understanding the transient large amplitude oscillatory shear behavior of yield stress fluids

A full understanding of the sequence of processes exhibited by yield stress fluids under large amplitude oscillatory shearing is developed using multiple experimental and analytical approaches. A novel component rate Lissajous curve, where the rates at which strain is acquired unrecoverably and recoverably are plotted against each other, is introduced and its utility is demonstrated by application to the analytical responses of four simple viscoelastic models. Using the component rate space, yielding and unyielding are identified by changes in the way strain is acquired, from recoverably to unrecoverably and back again. The behaviors are investigated by comparing the experimental results with predictions from the elastic Bingham model that is constructed using the Oldroyd–Prager formalism and the recently proposed continuous model by Kamani, Donley, and Rogers in which yielding is enhanced by rapid acquisition of elastic strain. The physical interpretation gained from the transient large amplitude oscillatory shear (LAOS) data is compared to the results from the analytical sequence of physical processes framework and a novel time-resolved Pipkin space. The component rate figures, therefore, provide an independent test of the interpretations of the sequence of physical processes analysis that can also be applied to other LAOS analysis frameworks. Each of these methods, the component rates, the sequence of physical processes analysis, and the time-resolved Pipkin diagrams, unambigiously identifies the same material physics, showing that yield stress fluids go through a sequence of physical processes that includes elastic deformation, gradual yielding, plastic flow, and gradual unyielding.

Kamani, Krutarth M. (ORCID:0000000338975420)↗
NASA NTRS2015

Stratospheric Aerosol and Gas Experiment, SAGE III on ISS, An Earth Science Mission on the International Space Station, Schedule Risk Analysis, A Project Perspective

The presentation provides insight into the schedule risk analysis process used by the Stratospheric Aerosol and Gas Experiment III on the International Space Station Project. The presentation focuses on the schedule risk analysis process highlighting the methods for identification of risk inputs, the inclusion of generic risks identified outside the traditional continuous risk management process, and the development of tailored analysis products used to improve risk informed decision making.

Bonine, Lauren↗
NASA NTRSDate not supplied

Analysis of a Dynamic Flexed Flat Cable Harness

A dynamic flex test was performed on a spacecraft instrument harness composed of multiple individual flex cables, with each flex cable containing multiple copper traces. The purpose of the test was to demonstrate the capability of the harness to survive the number of expected flex cycles during the planned mission with appropriate margin. However, during testing, increased trace resistances and open circuits were observed beginning at approximately 10% of the total number of planned flex cycles. This paper discusses the various proximate causes that contributed to increased and open resistance in the flex cables and the subsequent redesign, manufacturing, reliability, and quality-related changes that were instituted. An analysis process, including failure analysis, non-destructive evaluation, digital imaging correlation, and parametric modeling, will also be discussed. The paper will cover the development of a robust dynamic flex harness design and include recommendations to extend flex harness life; make changes to the flex harness life test; and improve flex cable manufacturing, quality, and reliability.

Flexible PCB↗
NASA NTRSDate not supplied

Analysis of a Dynamic Flexed Flat Cable Harness

A dynamic flex test was performed on a spacecraft instrument harness composed of multiple individual flex cables, with each flex cable containing multiple copper traces. The purpose of the test was to demonstrate the capability of the harness to survive the number of expected flex cycles during the planned mission with appropriate margin. However, during testing, increased trace resistances and open circuits were observed beginning at approximately 10% of the total number of planned flex cycles. This paper discusses the various proximate causes that contributed to increased and open resistance in the flex cables and the subsequent redesign, manufacturing, reliability, and quality-related changes that were instituted. An analysis process, including failure analysis, non-destructive evaluation, digital imaging correlation, and parametric modeling, will also be discussed. The paper will cover the development of a robust dynamic flex harness design and include recommendations to extend flex harness life; make changes to the flex harness life test; and improve flex cable manufacturing, quality, and reliability.

Flexible PCB↗
NASA NTRS1975

Laser Doppler velocimeter system simulation for sensing aircraft wake vortices. Part 2: Processing and analysis of LDV data (for runs 1023 and 2023)

A data analysis program constructed to assess LDV system performance, to validate the simulation model, and to test various vortex location algorithms is presented. Real or simulated Doppler spectra versus range and elevation is used and the spatial distributions of various spectral moments or other spectral characteristics are calculated and displayed. Each of the real or simulated scans can be processed by one of three different procedures: simple frequency or wavenumber filtering, matched filtering, and deconvolution filtering. The final output is displayed as contour plots in an x-y coordinate system, as well as in the form of vortex tracks deduced from the maxima of the processed data. A detailed analysis of run number 1023 and run number 2023 is presented to demonstrate the data analysis procedure. Vortex tracks and system range resolutions are compared with theoretical predictions.

Meng, J. C. S.↗
NASA NTRS1995

Integration of design, structural, thermal and optical analysis: And user's guide for structural-to-optical translator (PATCOD)

Electronic integration of design and analysis processes was achieved and refined at Langley Research Center (LaRC) during the development of an optical bench for a laser-based aerospace experiment. Mechanical design has been integrated with thermal, structural and optical analyses. Electronic import of the model geometry eliminates the repetitive steps of geometry input to develop each analysis model, leading to faster and more accurate analyses. Guidelines for integrated model development are given. This integrated analysis process has been built around software that was already in use by designers and analysis at LaRC. The process as currently implemented used Pro/Engineer for design, Pro/Manufacturing for fabrication, PATRAN for solid modeling, NASTRAN for structural analysis, SINDA-85 and P/Thermal for thermal analysis, and Code V for optical analysis. Currently, the only analysis model to be built manually is the Code V model; all others can be imported for the Pro/E geometry. The translator from PATRAN results to Code V optical analysis (PATCOD) was developed and tested at LaRC. Directions for use of the translator or other models are given.

Amundsen, R. M.↗
NASA NTRS2006

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

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

Robinson, Jeffrey S.↗
NASA NTRS2003

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

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

Stumpf, Richard P.↗
NASA NTRS2005

Extending the LWS Data Environment: Distributed Data Processing and Analysis

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

Narock, Thomas↗
DOE OSTI2022

Process-oriented analysis of dominant sources of uncertainty in the land carbon sink

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

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2022

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

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

Attribution↗