SEARCH · Engineering Papers

Results for “Open Framework”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 163 records · Page 9

All sources NASA NTRS DOE OSTI

NASA NTRS2012

Development of Waypoint Planning Tool in Response to NASA Field Campaign Challenges

Airborne real time observations are a major component of NASA 's Earth Science research and satellite ground validation studies. Multiple aircraft are involved in most NASA field campaigns. The coordination of the aircraft with satellite overpasses, other airplanes and the constantly evolving, dynamic weather conditions often determines the success of the campaign. Planning a research aircraft mission within the context of meeting the science objectives is a complex task because it requires real time situational awareness of the weather conditions that affect the aircraft track. A flight planning tools is needed to provide situational awareness information to the mission scientists, and help them plan and modify the flight tracks. Scientists at the University of Alabama ]Huntsville and the NASA Marshall Space Flight Center developed the Waypoint Planning Tool, an interactive software tool that enables scientists to develop their own flight plans (also known as waypoints) with point -and-click mouse capabilities on a digital map filled with real time raster and vector data. The development of this Waypoint Planning Tool demonstrates the significance of mission support in responding to the challenges presented during NASA field campaigns. Analysis during and after each campaign helped identify both issues and new requirements, and initiated the next wave of development. Currently the Waypoint Planning Tool has gone through three rounds of development and analysis processes. The development of this waypoint tool is directly affected by the technology advances on GIS/Mapping technologies. From the standalone Google Earth application and simple KML functionalities, to Google Earth Plugin on web platform, and to the rising open source GIS tools with New Java Script frameworks, the Waypoint Planning Tool has entered its third phase of technology advancement. Adapting new technologies for the Waypoint Planning Tool ensures its success in helping scientist reach their mission objectives.

He, Matt↗

NASA NTRS2014

Design Environment for Multifidelity and Multidisciplinary Components

One of the greatest challenges when developing propulsion systems is predicting the interacting effects between the fluid loads, thermal loads, and structural deflection. The interactions between technical disciplines often are not fully analyzed, and the analysis in one discipline often uses a simplified representation of other disciplines as an input or boundary condition. For example, the fluid forces in an engine generate static and dynamic rotor deflection, but the forces themselves are dependent on the rotor position and its orbit. It is important to consider the interaction between the physical phenomena where the outcome of each analysis is heavily dependent on the inputs (e.g., changes in flow due to deflection, changes in deflection due to fluid forces). A rigid design process also lacks the flexibility to employ multiple levels of fidelity in the analysis of each of the components. This project developed and validated an innovative design environment that has the flexibility to simultaneously analyze multiple disciplines and multiple components with multiple levels of model fidelity. Using NASA's open-source multidisciplinary design analysis and optimization (OpenMDAO) framework, this multifaceted system will provide substantially superior capabilities to current design tools.

Platt, Michael↗

NASA NTRS2015

Big Software for SmallSats: Adapting CFS to CubeSat Missions

Expanding capabilities and mission objectives for SmallSats and CubeSats is driving the need for reliable, reusable, and robust flight software. While missions are becoming more complicated and the scientific goals more ambitious, the level of acceptable risk has decreased. Design challenges are further compounded by budget and schedule constraints that have not kept pace. NASA's Core Flight Software System (cFS) is an open source solution which enables teams to build flagship satellite level flight software within a CubeSat schedule and budget. NASA originally developed cFS to reduce mission and schedule risk for flagship satellite missions by increasing code reuse and reliability. The Lunar Reconnaissance Orbiter, which launched in 2009, was the first of a growing list of Class B rated missions to use cFS. Large parts of cFS are now open source, which has spurred adoption outside of NASA. This paper reports on the experiences of two teams using cFS for current CubeSat missions. The performance overheads of cFS are quantified, and the reusability of code between missions is discussed. The analysis shows that cFS is well suited to use on CubeSats and demonstrates the portability and modularity of cFS code.

Open Source↗

NASA NTRS2018

Earthdata User Interface (EUI) Library

As more remote sensing data moves to the cloud, the design tools we use to build user experiences and visualizations need to change and adapt to make the best use this new data reality. EUI 2.0, the next major iteration of the Earthdata User Interface Library, aims to make creating rich user experiences around NASA's Earth Observation System Data and Information System (EOSDIS) data easy and user-friendly. Building on a solid framework of design components, EUI 2.0 will be open source and have off-the-shelf integration with the Common Metadata Repository (CMR), basic mapping and visualization tools, a refreshed design toolkit for building apps and websites that fit the Earthdata design theme and guidelines. EUI 2.0 will allow for the rapid development of websites and applications based on EOSDIS tools and data holdings. It will also make use of cloud data availability to enable data visualization and analysis without the need to download and sync data.

Siarto, Jeff↗

NASA NTRSDate not supplied

Optimization Algorithms as Quantum Performance Benchmarks

Combinatorial optimization is anticipated to be one of the primary use cases for quantum computation in the coming years. The Quantum Approximate Optimization Algorithm (QAOA) and Quantum Annealing (QA) have the potential to demonstrate significant run-time performance benefits over current state-of-the-art solutions. Using existing methods for characterizing classical optimization algorithms, we analyze solution quality obtained by solving Max-Cut problems using a quantum annealing device and gate-model quantum simulators and devices. This is used to guide the development of an advanced benchmarking framework for quantum computers designed to evaluate the trade-off between run-time execution performance and the solution quality for iterative hybrid quantum-classical applications. The framework generates performance profiles through effective visualizations that show performance progression as a function of time for various problem sizes and illustrates algorithm limitations uncovered by the benchmarking approach. The framework is an enhancement to the existing open-source QED-C Application-Oriented Benchmark suite and can connect to the open-source analysis libraries. The suite can be executed on various quantum simulators and quantum hardware systems.

benchmarking↗

NASA NTRS2016

The Matsu Wheel: A Cloud-Based Framework for Efficient Analysis and Reanalysis of Earth Satellite Imagery

Project Matsu is a collaboration between the Open Commons Consortium and NASA focused on developing open source technology for cloud-based processing of Earth satellite imagery with practical applications to aid in natural disaster detection and relief. Project Matsu has developed an open source cloud-based infrastructure to process, analyze, and reanalyze large collections of hyperspectral satellite image data using OpenStack, Hadoop, MapReduce and related technologies. We describe a framework for efficient analysis of large amounts of data called the Matsu "Wheel." The Matsu Wheel is currently used to process incoming hyperspectral satellite data produced daily by NASA's Earth Observing-1 (EO-1) satellite. The framework allows batches of analytics, scanning for new data, to be applied to data as it flows in. In the Matsu Wheel, the data only need to be accessed and preprocessed once, regardless of the number or types of analytics, which can easily be slotted into the existing framework. The Matsu Wheel system provides a significantly more efficient use of computational resources over alternative methods when the data are large, have high-volume throughput, may require heavy preprocessing, and are typically used for many types of analysis. We also describe our preliminary Wheel analytics, including an anomaly detector for rare spectral signatures or thermal anomalies in hyperspectral data and a land cover classifier that can be used for water and flood detection. Each of these analytics can generate visual reports accessible via the web for the public and interested decision makers. The result products of the analytics are also made accessible through an Open Geospatial Compliant (OGC)-compliant Web Map Service (WMS) for further distribution. The Matsu Wheel allows many shared data services to be performed together to efficiently use resources for processing hyperspectral satellite image data and other, e.g., large environmental datasets that may be analyzed for many purposes.

0↗

NASA NTRS2011

Generic, Extensible, Configurable Push-Pull Framework for Large-Scale Science Missions

The push-pull framework was developed in hopes that an infrastructure would be created that could literally connect to any given remote site, and (given a set of restrictions) download files from that remote site based on those restrictions. The Cataloging and Archiving Service (CAS) has recently been re-architected and re-factored in its canonical services, including file management, workflow management, and resource management. Additionally, a generic CAS Crawling Framework was built based on motivation from Apache s open-source search engine project called Nutch. Nutch is an Apache effort to provide search engine services (akin to Google), including crawling, parsing, content analysis, and indexing. It has produced several stable software releases, and is currently used in production services at companies such as Yahoo, and at NASA's Planetary Data System. The CAS Crawling Framework supports many of the Nutch Crawler's generic services, including metadata extraction, crawling, and ingestion. However, one service that was not ported over from Nutch is a generic protocol layer service that allows the Nutch crawler to obtain content using protocol plug-ins that download content using implementations of remote protocols, such as HTTP, FTP, WinNT file system, HTTPS, etc. Such a generic protocol layer would greatly aid in the CAS Crawling Framework, as the layer would allow the framework to generically obtain content (i.e., data products) from remote sites using protocols such as FTP and others. Augmented with this capability, the Orbiting Carbon Observatory (OCO) and NPP (NPOESS Preparatory Project) Sounder PEATE (Product Evaluation and Analysis Tools Elements) would be provided with an infrastructure to support generic FTP-based pull access to remote data products, obviating the need for any specialized software outside of the context of their existing process control systems. This extensible configurable framework was created in Java, and allows the use of different underlying communication middleware (at present, both XMLRPC, and RMI). In addition, the framework is entirely suitable in a multi-mission environment and is supporting both NPP Sounder PEATE and the OCO Mission. Both systems involve tasks such as high-throughput job processing, terabyte-scale data management, and science computing facilities. NPP Sounder PEATE is already using the push-pull framework to accept hundreds of gigabytes of IASI (infrared atmospheric sounding interferometer) data, and is in preparation to accept CRIMS (Cross-track Infrared Microwave Sounding Suite) data. OCO will leverage the framework to download MODIS, CloudSat, and other ancillary data products for use in the high-performance Level 2 Science Algorithm. The National Cancer Institute is also evaluating the framework for use in sharing and disseminating cancer research data through its Early Detection Research Network (EDRN).

Foster, Brian M.↗

NASA NTRSDate not supplied

Big-data Efficient and Automated Science Transfer (BEAST): An Open-Source Software Architecture for Arc Jet Data Management, Modeling, and Automation

Big-data Efficient and Automated Science Transfer (BEAST) is a facility data management application developed for the NASA Ames arc jet facilities. The current decentralized data management practices limit statistical tracking, synchronization between video/time series, search capability, data throughput, and data processing speed/efficiency. Consequently, BEAST was developed to provide a new data infrastructure with streamlined data collection, processing, transfer, and analysis. This new framework also seeks to implement the FAIR principles of data stewardship: Findable, Accessible, Interoperable, and Reusable. The BEAST framework is based on a combination of the Python Django web framework and the Python data stack to provide a monolithic, open-source platform for data management, automation, and machine learning. This architecture was chosen for maintainability and scalability for a small, in-house development team. This paper will describe the application framework, deployment, and discuss the benefits and future plans for the system.

Data management↗

NASA NTRSDate not supplied

Big-data Efficient and Automated Science Transfer (BEAST): An Open-Source Software Architecture for Arc Jet Data Management, Modeling, and Automation

Big-data Efficient and Automated Science Transfer (BEAST) was conceived to address the existing ground testing data management of the NASA Ames arc jet facilities (e.g., manually entered Excel files and USB drive data transfers). These data management practices were seen as a choke point for future thermal protection system (TPS) development as they limit statistical tracking, resolution of diagnostics, coordination between video/time series, data throughput, and data processing speed/efficiency. Consequently, BEAST was developed to provide a new data infrastructure with streamlined data collection, processing, transfer, and analysis. This new framework also seeks to implement the FAIR principles of data stewardship: Findable, Accessible, Interoperable, and Reusable. The BEAST framework is based on a combination of the Python Django web framework and the Python data stack to provide a monolithic, open-source platform for data management, automation, and machine learning. This architecture was chosen for maintainability and scalability for a small, in-house development team. This paper will describe the application framework, deployment, and discuss the benefits and future plans for the system.

Data management↗

NASA NTRSDate not supplied

Big-data Efficient Automated Science Transfer (BEAST): an open-source software architecture for arc jet data management, modeling, and automation

Data management↗

NASA NTRS2001

Interrelation Between Safety Factors and Reliability

An evaluation was performed to establish relationships between safety factors and reliability relationships. Results obtained show that the use of the safety factor is not contradictory to the employment of the probabilistic methods. In many cases the safety factors can be directly expressed by the required reliability levels. However, there is a major difference that must be emphasized: whereas the safety factors are allocated in an ad hoc manner, the probabilistic approach offers a unified mathematical framework. The establishment of the interrelation between the concepts opens an avenue to specify safety factors based on reliability. In cases where there are several forms of failure, then the allocation of safety factors should he based on having the same reliability associated with each failure mode. This immediately suggests that by the probabilistic methods the existing over-design or under-design can be eliminated. The report includes three parts: Part 1-Random Actual Stress and Deterministic Yield Stress; Part 2-Deterministic Actual Stress and Random Yield Stress; Part 3-Both Actual Stress and Yield Stress Are Random.

Elishakoff, Isaac↗

NASA NTRS2006

Adaptive Modeling Language and Its Derivatives

Adaptive Modeling Language (AML) is the underlying language of an object-oriented, multidisciplinary, knowledge-based engineering framework. AML offers an advanced modeling paradigm with an open architecture, enabling the automation of the entire product development cycle, integrating product configuration, design, analysis, visualization, production planning, inspection, and cost estimation.

Chemaly, Adel↗

NASA NTRSDate not supplied

Integrated System for Autonomous and Adaptive Caretaking (ISAAC): Phase 1 Low-Fidelity Demo

This presentation describes the ISAAC phase 1 low-fidelity demonstration results. The demonstration satisfied the milestone from the Gateway-ISAAC Memorandum of Understanding to "Demonstrate spatial and logical data registration between robotics and spacecraft". It integrated many new ISAAC components, including a spatially linked model, Astrobee multi-sensor mapping, and an integrated data interface. It advanced ISAAC key performance parameters related to mapping, in a lab setting. Areas for phase 1 forward work include: improve maturity toward the high-fidelity demo on the ISS; demonstrate mapping with more sensor modalities; expand initial anomaly detection implementation into a flexible framework with multiple detection algorithms for different tasks; begin open source software release process for releasable ISAAC components.

robotics↗

NASA NTRSDate not supplied

Open e2e Testing Initiative with Open MCT

Open MCT (Open Mission Control Technologies) is a next-generation mission control framework for visualization of data on desktop and mobile devices. It is developed at NASA’s Ames Research Center, and is being used by NASA for data analysis of spacecraft missions, as well as planning and operation of experimental rover systems. This advanced application needs an advanced battery of tests… and you! In this talk, we’ll outline how the Open MCT project is leveraging the testing community to write mission critical e2e tests. We’ll start with the unique (and not so unique) requirements of Open MCT test automation and how they’re addressed with Playwright. Next, we’ll detail the approach to open sourcing the tests and associated challenges. We’ll end with some lessons learned and detail how you can get started testing NASA Open MCT — no previous experience with javascript or web testing required!

John Hill↗

NASA NTRSDate not supplied

A Partitioned - Task Parallel Implementation of the NASA Multiscale Analysis Tool for High Performance Computing

The NASA Multiscale Analysis Tool (NASMAT) is a platform for multiscale modeling of composites which can perform analysis of materials with any arbitrary number of length scales. The platform supports modularity, scalability, and interoperability using recursive procedures and data structures. A Macro solver driven parallelization scheme often limits the capability of NASMAT to scale as it has access to limited memory and number of cores (often one core/thread) and often forces to implement macro solver specific changes to the platform. In this work, a partitioned task-parallel approach is adopted, where the parallelization strategy adopted for NASMAT is independent of the macro solver and the computational resources are managed independently. The programming architecture takes into account the hierarchy of multiple scales (task-dependence) and the heterogeneous nature (dynamic load balancing) of computation through implementation of a hierarchy-informed task parallel model. The partitioned nature of the framework further extends the “plug and play” capability of NASMAT. preCICE, an open-source library for coupling multiphysics solver in a partitioned manner, is adopted to integrate NASMAT with an external macro solver by implementing a NASMAT adapter for preCICE. Speedup and scalability of the framework is studied for micromechanical models of varying size.

task-parallel↗

NASA NTRS1999

On Heating the Sun's Corona by Magnetic Explosions: Feasibility in Active Regions and prospects for Quiet Regions and Coronal Holes

We build a case for the persistent strong coronal heating in active regions and the pervasive quasi-steady heating of the corona in quiet regions and coronal holes being driven in basically the same way as the intense transient heating in solar flares: by explosions of sheared magnetic fields in the cores of initially closed bipoles. We begin by summarizing the observational case for exploding sheared core fields being the drivers of a wide variety of flare events, with and without coronal mass ejections. We conclude that the arrangement of an event's flare heating, whether there is a coronal mass ejection, and the time and place of the ejection relative to the flare heating are all largely determined by four elements of the form and action of the magnetic field: (1) the arrangement of the impacted, interacting bipoles participating in the event, (2) which of these bipoles are active (have sheared core fields that explode) and which are passive (are heated by injection from impacted active bipoles), (3) which core field explodes first, and (4) which core-field explosions are confined within the closed field of their bipoles and which ejectively open their bipoles. We then apply this magnetic-configuration framework for flare heating to the strong coronal heating observed by the Yohkoh Soft X-ray Telescope in an active region with strongly sheared core fields observed by the MSFC vector magnetograph. All of the strong coronal heating is in continually microflaring sheared core fields or in extended loops rooted against the active core fields. Thus, the strong heating occurs in field configurations consistent with the heating being driven by frequent core-field explosions that are smaller but similar to those in confined flares and flaring arches. From analysis of the thermal and magnetic energetics of two selected core-field microflares and a bright extended loop, we find that (1) it is energetically feasible for the sheared core fields to drive all of the coronal heating in the active region via a staccato of magnetic microexplosions, (2) the microflares at the feet of the extended loop behave as the flares at the feet of flaring arches in that more coronal heating is driven within the active bipole than in the extended loop, (3) the filling factor of the X-ray plasma in the core field microflares and in the extended loop is approximately 0.1, and (4) to release enough magnetic energy for a typical microflare (10^27 - 10^28 erg), a microflaring strand of sheared core field need expand and/or untwist by only a few percent at most. Finally, we point out that (1) the field configurations for strong coronal heating in our example active region (i.e., neutral-line core fields, many embedded in the feet of extended loops) are present in abundance in the magnetic network in quiet regions and coronal holes, and (2) it is known that many network bipoles do microflare and that many produce detectable coronal heating. We therefore propose that exploding sheared core fields are the drivers of most of the heating and dynamics of the solar atmosphere, ranging from the largest and most powerful coronal mass ejections and flares, to the vigorous microflaring and coronal heating in active regions, to the multitude of fine-scale explosive events in the magnetic network. The low-lysing exploding core fields in the network drive microflares, spicules, global coronal heating, and ,consequently, the solar wind.

Moore, Ronald L.↗

NASA NTRS2002

Experimental OAI-Based Digital Library Systems

The objective of Open Archives Initiative (OAI) is to develop a simple, lightweight framework to facilitate the discovery of content in distributed archives (http://www.openarchives.org). The focus of the workshop held at the 5th European Conference on Research and Advanced Technology for Digital Libraries (ECDL 2001) was to bring researchers in the area of digital libraries who are building OAI based systems so as to share their experiences, problems they are facing, and approaches they are taking to address them. The workshop consisted of invited talks from well-established researchers working in building OAI based digital library system along with short paper presentations.

Nelson, Michael L.↗

NASA NTRS2013

The Thermal Hogan - A Means of Surviving the Lunar Night

document describes the Thermal Hogan, a new shelter concept that would be used on the Moon to moderate the extreme nighttime temperatures, allowing survival of equipment with minimal heater power. It is lightweight, has few mechanical parts, and would be relatively easy to deploy on the Moon. The Lunar Hogan has two parts: an insulated shelter and a thermal mass. The shelter is constructed of multilayer insulation (MLI) draped over a structural framework. Entry and egress are accomplished either by raising the structure or via a door constructed of the same MLI material as the shelter. The thermal mass can be manufactured from locally available materials, either by piling substantially sized rocks to a depth of 0.25 meter, or by filling a 0.25-meter-deep conductive honeycomb-like structure with lunar dust. For ease of transport, the structural framework and honeycomb can be collapsible. The door can be opened by pushing on it in either direction. Gravity would cause it to close and it could be sealed via magnetic strips on the doorframe.

Fruitwala, Neelay↗