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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 757 records · Page 42
All sourcesNASA NTRSDOE OSTI
NASA NTRS2012

Revamping Spacecraft Operational Intelligence

The EPOXI flight mission has been testing a new commercial system, Splunk, which employs data mining techniques to organize and present spacecraft telemetry data in a high-level manner. By abstracting away data-source specific details, Splunk unifies arbitrary data formats into one uniform system. This not only reduces the time and effort for retrieving relevant data, but it also increases operational visibility by allowing a spacecraft team to correlate data across many different sources. Splunk's scalable architecture coupled with its graphing modules also provide a solid toolset for generating data visualizations and building real-time applications such as browser-based telemetry displays.

Hwang, Victor↗
NASA NTRS2010

Process Improvement Through Tool Integration in Aero-Mechanical Design

Emerging capabilities in commercial design tools promise to significantly improve the multi-disciplinary and inter-disciplinary design and analysis coverage for aerospace mechanical engineers. This paper explores the analysis process for two example problems of a wing and flap mechanical drive system and an aircraft landing gear door panel. The examples begin with the design solid models and include various analysis disciplines such as structural stress and aerodynamic loads. Analytical methods include CFD, multi-body dynamics with flexible bodies and structural analysis. Elements of analysis data management, data visualization and collaboration are also included.

Integrated design and analysis↗
NASA NTRS2018

STEM Engagement with NASA's Solar System Treks Portals for Lunar and Planetary Mapping and Modeling

This presentation will provide an overview of the uses and capabilities of NASA's Solar System Treks family of online mapping and modeling portals. While also designed to support mission planning and scientific research, this presentation will focus on the Science, Technology, Engineering, and Math (STEM) engagement and public outreach capabilities of these web based suites of data visualization and analysis tools.

Law, E. S.↗
NASA NTRS2018

HYPERS Software Development

Providing software support for HYPERS and creating internal tools. NASA has a long and decorated history of spaceflight innovation and achievements. The next great endeavor is NASA’s Journey to Mars, which will be achieved with the Space Launch System (SLS) and Orion capsule. Developing and testing these systems is no easy feat. Commercial-off-the-shelf (COTS) tools do not always provide enough functionality for engineers to do their job efficiently, making internal custom-made tools is necessary to meet the expected launch date. The purpose of this internship was to provide software support to the Storable Propellants and Hydraulic Systems Branch, specifically the Hypergolics Software (HYPERS) team. This included developing tools to parse unique measurements from the vehicle into the format specified by the HYPERS team. Displays were also created per requirements. Another major component of this internship was to create an intuitive interactive offline graphing application. The current tool for plotting vehicle data does not have all the functionality and features that HYPERS would like. By inputting a vehicle data file, the application plots the data based on the time range and components the user would like to view. After the graph is generated, the user is able to zoom in, pan horizontally, add comments, hover over data points, and take a snapshot of the current state of the graph. These additional features will help engineers quickly investigate the relationship between vehicle components through data visualization.

Internal Tools↗
NASA NTRS2018

Biocene 2018 - Welcome to the Period of New Life

Biocene is the period of new life. When our descendants look back at this period in time, they will see evidence, in the geologic and electronic record, of anthropic climate change, growing population, and scarcity of resources. But they will also see the rebirth of human ingenuity as we overcame the challenges that faced us through nature-inspired exploration. The Periodic Table of Life (PeTaL) is a proposed tool and open source framework that uses artificial intelligence to aid in the systematic inquiry of biology for its application to human systems. This presentation defines the PeTaL concept and workflow. Biomimicry, biophysics, biomimetics, bionics and numerous other terms refer to the use of biology and biological principles to inform practices in other disciplines. For the most part, the domain of inquiry in these fields have been confined to extant biological models with the proponents of biomimicry often citing the evolutionary success of extant organisms relative to extinct ones. The primary objective of this paper is to expand the domain of inquiry for human processes that seek to model those that are, were or could be found in nature with examples that relate to the field of aerospace and to spur development of tools that can work together to accelerate the use of artificial intelligence in problem solving. Specifically specialized fields such as paleomimesis, anthropomimesis and physioteleology are proposed in conjunction with artificial evolution. Blockchain technology may be vital in allowing open source design tools such as PeTaL to democratize design and yet protect intellectual property. The overarching philosophy outlined here can be thought of as physiomimetics, a holistic and systematic way of learning from natural history. The backbone of PeTaL integrates an unstructured database with an ontological model consisting of function, morphology, environment, state of matter and ecosystem. Tools include text classification, thesaurus, data visualization, and analysis. Applications of PeTaL include guiding human space exploration, understanding human and geological history, and discovering new or extinct life.

Biocene↗
NASA NTRS2019

IMERG Reaching for 20 Years

The new V06 IMERG is briefly reviewed, then key data visualizations are shown, including the zonal profile of calibration by GPCP, the long-term time series of ocean estimates for the Final Run (with comparison to TMPA and GPCP SG), the time series of tropical ocean rainrate histogram, diurnal cycle, and atoll validation at the monthly time scale.

Huffman, George J.↗
NASA NTRSDate not supplied

Flow and Noise from Supersonic Plug Nozzles

Nozzles with external plugs are candidates for propulsion of future supersonic aircraft. A model-scale experimental study is conducted exploring the flow and noise characteristics of various plug nozzles. For a given outer nozzle, the plug geometry is varied from conic with various half-angles (lengths) to plugs designed by the method of characteristics (MoC) as well as truncated and porous plugs. So far, noise characteristics and schlieren flow visualization data have been acquired. Limited numerical simulations have also been done addressing thrust performance. The simulations show that the MoC plugs out-perform the conic cases, especially around high Mach number cruise conditions. The experimental data, however, show that the MoC plugs are noisy relative to the conic cases at low Mach number landing and takeoff (LTO) conditions. The increased noise (with MoC at LTO) is accompanied by unsteady turbulent structures and increased jet spreading, as seen in schlieren pictures. At LTO, the longest conic plug is found to be the least noisy. Furthermore, a porous surface on the long conic plug effectively suppresses broadband shock associated noise (BBSN) at higher Mach numbers. Thus, a dilemma remains. MoC design gives best thrust performance at cruise but it is noisy at LTO. A long conic plug, on the other hand, is quieter at LTO but may have unacceptable thrust at cruise.

jets↗
NASA NTRSDate not supplied

Distributed Lunar Data Platform with Advanced Machine Learning Capabilities in Support of Lunar Science and Exploration

The United States 2020 Space Policy directive declares that NASA, in cooperation with private industry, will “extend human economic activity into deep space by establishing a permanent human presence on the Moon”. This goal will require advanced data management, as well as analysis, modeling and representation of lunar information in order to prepare for Artemis human missions, lunar science investigations and exploration. To meet this requirement, we conceptualize and present an implementation strategy for a distributed platform for lunar data retrieval, inferencing and analysis, which will be based on federated learning and the NASA Celestial Mapping System (CMS). In addition to demonstrating the imperative of enabling lunar-borne data to remain in-situ but still accessible, this presentation will also include examples of how third parties could contribute both datasets and new functionality into this platform using an AI-based data import pipeline and a plug-in architecture respectively.

Artificial Intelligence↗
NASA NTRSDate not supplied

Flow and noise from supersonic plug nozzles

Nozzles with external plugs are candidates for propulsion of future supersonic aircraft. A model-scale experimental study is conducted exploring the flow and noise characteristics of various plug nozzles. For a given outer nozzle, the plug geometry is varied from conic with various half-angles (lengths) to plugs designed by the method of characteristics (MoC) as well as truncated and porous plugs. So far, noise characteristics and schlieren flow visualization data have been acquired. Limited numerical simulations have also been done addressing thrust performance. The simulations show that the MoC plugs out-perform the conic cases, especially around high Mach number cruise conditions. The experimental data, however, show that the MoC plugs are noisy relative to the conic cases at low Mach number landing and takeoff (LTO) conditions. The increased noise (with MoC at LTO) is accompanied by unsteady turbulent structures and increased jet spreading, as seen in schlieren pictures. At LTO, the longest conic plug is found to be the least noisy. Furthermore, a porous surface on the long conic plug effectively suppresses broadband shock associated noise (BBSN) at higher Mach numbers. Thus, a dilemma remains. MoC design gives best thrust performance at cruise but it is noisy at LTO. A long conic plug, on the other hand, is quieter at LTO but may have unacceptable thrust at cruise.

jets↗
NASA NTRSDate not supplied

Mining the Gravity Mutants of Arabidopsis

Gravity mutants are a valuable resource for understanding gravity perception, signaling, and response in plants. A review of 190 publications resulted in a list of 97 loci with mutations that caused a gravitropic phenotype. While all these mutants show some form of gravity phenotype, several are also generally defective in growth. After removing these nonspecific mutants, 76 loci were deemed to have true gravity mutants. The gene list was then used to create a sortable database containing key factors of gravity signaling as well as data on methodologies and the development of mutant lines. Indexing this database has allowed us to pull out trends that were not visible in individual publications. For example, mutants that are unable to rearrange starch statoliths make up a larger proportion of the described inflorescence stems mutants than any other organ. Comparing these statolith mutants across organs shows that root and inflorescence stems consistently display different phenotypes for the same class of defect. The more severe gravity defects are most commonly described in root tissue while other tissues are more likely to show only a delayed or reduced response to gravity. The experience of members of the GeneLab plant Analytics Working Group (AWG) in data visualization and gene mapping have sparked new ideas for utilizing this database. Knowledge of shared traits, mutant development, and growth can provide a new resource for the production of seed lines specialized for their response to gravity.

gravitropism↗
NASA NTRSDate not supplied

Flow Physics Study of Sweeping Jet Actuation on a NACA 0015 Swept Wing Configuration

Preliminary results from a recently completed active flow control (AFC) experiment on a 30 deg swept, semispan wing are presented. The constant chord NACA 0015 wing is configured with sweeping jet actuators at the flap shoulder to study the effects of excitation introduced into a separated, three-dimensional flowfield. The research is aimed at developing efficient active flow control approaches for swept wing configurations. Oil and tuft flow visualization data, steady and unsteady pressure data, particle image velocimetry (PIV), oil flow interferometry (OFI), and force and moment data are used to compare the flowfields with and without AFC. The parameters that were varied include freestream velocity, actuator momentum coefficient, and flap deflection angle.

active flow control↗
NASA NTRSDate not supplied

Flow Physics Study of Sweeping Jet Actuation on an NACA 0015 Swept Wing Configuration

Results from a recently completed active flow control (AFC) experiment on a low aspect ratio, AR = 4.35, 30 degree swept, semispan wing with a 30% chord trailing edge flap are presented. The constant chord NACA 0015 wing is configured with sweeping jet actuators at the flap shoulder to facilitate our study of three-dimensional, swept wing separated and AFC controlled flowfields on the flap. Two flap deflection angles (delta_f = 0 degrees and 20 degrees) are examined. Oil and tuft flow visualization data, steady and unsteady pressure data, and particle image velocimetry (PIV) complement the balance lift and drag data. These results are used to examine smooth body separation, fixed separation, and the AFC-controlled flap flowfield downstream of a sweeping jet actuator. A momentum coefficient of 1.1% reattaches the flow to the flap surface when flap delta_f = 20 degrees increasing lift by approximately 0.26. This fundamental study is a first step in a research effort focused on improving the efficiency of AFC systems for swept wing applications.

active flow control↗
NASA NTRSDate not supplied

Risks of Increased Earth Independence

As human space exploration begins to extend beyond the immediate vicinity of Earth, the ability of expertise on the ground to support operations will progressively decrease. Ground control expertise has been the primary countermeasure preventing loss of life and mission over the past sixty years and it will be gradually stripped away as expeditions reach further into space. The large, flexible and adaptive teams of experts on the ground, provide not only engineering analysis and problem-solving but also greatly increased work capacity. Monitoring of the large and fast moving stream of telemetry data is carried out around the clock by 20-30 flight controllers per shift. Analysis of that data and troubleshooting is carried out by an additional 50-100 engineers per shift. Artificial intelligence capabilities will need to be part of the solution but will not the entire solution. As progress continues to be made on intelligent systems, especially those for use in complex, dynamic environments where humans will remain a part of the activity, there is an ever increasing need to focus on how those systems will interact with the humans. Although capabilities such as natural language processing and facial recognition have become common place, even basic aspects of problem-solving, causal reasoning and generative decision-making remain well-beyond of our current capabilities. Advanced data visualization, procedure execution support, and new training approaches will be needed to close the gap between what is currently provided by experts on the ground and what the crew will need to do in increasingly autonomous ways with greater distance from Earth.

human-systems integration architecture↗
NASA NTRS2004

Accessing and visualizing scientific spatiotemporal data

This paper discusses work done by JPL's Parallel Applications Technologies Group in helping scientists access and visualize very large data sets through the use of multiple computing resources, such as parallel supercomputers, clusters, and grids.

rendering↗
NASA NTRS1989

Correlative visualization techniques for multidimensional data

Critical to the understanding of data is the ability to provide pictorial or visual representation of those data, particularly in support of correlative data analysis. Despite the advancement of visualization techniques for scientific data over the last several years, there are still significant problems in bringing today's hardware and software technology into the hands of the typical scientist. For example, there are other computer science domains outside of computer graphics that are required to make visualization effective such as data management. Well-defined, flexible mechanisms for data access and management must be combined with rendering algorithms, data transformation, etc. to form a generic visualization pipeline. A generalized approach to data visualization is critical for the correlative analysis of distinct, complex, multidimensional data sets in the space and Earth sciences. Different classes of data representation techniques must be used within such a framework, which can range from simple, static two- and three-dimensional line plots to animation, surface rendering, and volumetric imaging. Static examples of actual data analyses will illustrate the importance of an effective pipeline in data visualization system.

Treinish, Lloyd A.↗
NASA NTRS2014

Federated Giovanni: A Distributed Web Service for Analysis and Visualization of Remote Sensing Data

The Geospatial Interactive Online Visualization and Analysis Interface (Giovanni) is a popular tool for users of the Goddard Earth Sciences Data and Information Services Center (GES DISC) and has been in use for over a decade. It provides a wide variety of algorithms and visualizations to explore large remote sensing datasets without having to download the data and without having to write readers and visualizers for it. Giovanni is now being extended to enable its capabilities at other data centers within the Earth Observing System Data and Information System (EOSDIS). This Federated Giovanni will allow four other data centers to add and maintain their data within Giovanni on behalf of their user community. Those data centers are the Physical Oceanography Distributed Active Archive Center (PO.DAAC), MODIS Adaptive Processing System (MODAPS), Ocean Biology Processing Group (OBPG), and Land Processes Distributed Active Archive Center (LP DAAC). Three tiers are supported: Tier 1 (GES DISC-hosted) gives the remote data center a data management interface to add and maintain data, which are provided through the Giovanni instance at the GES DISC. Tier 2 packages Giovanni up as a virtual machine for distribution to and deployment by the other data centers. Data variables are shared among data centers by sharing documents from the Solr database that underpins Giovanni's data management capabilities. However, each data center maintains their own instance of Giovanni, exposing the variables of most interest to their user community. Tier 3 is a Shared Source model, in which the data centers cooperate to extend the infrastructure by contributing source code.

Giovanni↗
NASA NTRS2018

The CEOS Data Cube Portal: A User-Friendly, Open Source Software Solution for the Distribution, Exploration, Analysis, and Visualization of Analysis Ready Data

There is an urgent need to increase the capacity of developing countries to take part in the study and monitoring of their environments through remote sensing and space-based Earth observation technologies. The Open Data Cube (ODC) provides a mechanism for efficient storage and a powerful framework for processing and analyzing satellite data. While this is ideal for scientific research, the expansive feature space can also be daunting for end-users and decision-makers who simply require a solution which provides easy exploration, analysis, and visualization of Analysis Ready Data (ARD). Utilizing innovative web-design and a modular architecture, the Committee on Earth Observation Satellites (CEOS) has created a web-based user interface (UI) which harnesses the power of the ODC yet provides a simple and familiar user experience: the CEOS Data Cube (CDC). This paper presents an overview of the CDC architecture and the salient features of the UI. In order to provide adaptability, flexibility, scalability, and robustness, we leverage widely-adopted and well-supported technologies such as the Django web framework and the AWS Cloud platform. The fully-customizable source code of the UI is available at our public repository. Interested parties can download the source and build their own UIs. The UI empowers users by providing features that assist with streamlining data preparation, data processing, data visualization, and sub-setting ARD products in order to achieve a wide variety of Earth imaging objectives through an easy to use web interface.

User Interface↗