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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 37 records · Page 2

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↗

BEAST: Expanding Sustainable Data Infrastructure for High-Enthalpy Facilities

Reproducible, data-driven thermal protection system (TPS) research requires that experimental records from high-enthalpy testing be consistently structured, traceable, and accessible across campaigns and institutions. In practice, however, arcjet and plasma facilities data remain largely fragmented: raw diagnostics are stored in ad hoc formats, material sample histories are disconnected from test conditions, and metadata standards are absent, precluding systematic cross-campaign analysis and long-term reuse. BEAST (Backend for Experiment Analysis, Storage, and Traceability) is an open-source, web-based platform that addresses these limitations by providing a unified, queryable infrastructure for high-enthalpy ground-test data [1]. First presented at the 15th Ablation Workshop [2], BEAST has since undergone significant development. The platform ingests and structures multi-channel time-series diagnostics, facility configurations, and material property records within a common provenance model, ensuring end-to-end traceability from raw sensor acquisition to reduced experimental quantities. A versioned material library links specimen identity and processing history to the specific runs in which each sample was tested. An integrated modeling workbench enables training and evaluation of regression models directly on archived experimental data, supporting condition interpolation and the construction of empirical material response databases. Beyond its original deployment at NASA Ames Research Center, BEAST has been designed to be facility-agnostic, with ongoing efforts to extend its adoption to other facilities. Its modular architecture accommodates heterogeneous diagnostic setups and facility types, and its future open-source distribution allows institutions to build on a common data standard rather than maintaining isolated, bespoke solutions. BEAST is further integrated within a broader ecosystem of companion tools: arcjetCV [3] extracts recession rates and shock standoff distances from high-speed video using computer vision, and miniSTARscan [4] provides sub-minute, portable photogrammetric surface reconstruction of test articles before and after exposure. All tools share a common data schema, enabling seamless ingestion of surface geometry, imagery, and time-series data into a single, coherent experimental record.

Database↗

BEAST: Expanding Sustainable Data Infrastructure for High-Enthalpy Facilities

Reproducible, data-driven thermal protection system (TPS) research requires that experimental records from high-enthalpy testing be consistently structured, traceable, and accessible across campaigns and institutions. In practice, however, arcjet and plasma facilities data remain largely fragmented: raw diagnostics are stored in ad hoc formats, material sample histories are disconnected from test conditions, and metadata standards are absent, precluding systematic cross-campaign analysis and long-term reuse. BEAST (Backend for Experiment Analysis, Storage, and Traceability) is an open-source, web-based platform that addresses these limitations by providing a unified, queryable infrastructure for high-enthalpy ground-test data [1]. First presented at the 15th Ablation Workshop [2], BEAST has since undergone significant development. The platform ingests and structures multi-channel time-series diagnostics, facility configurations, and material property records within a common provenance model, ensuring end-to-end traceability from raw sensor acquisition to reduced experimental quantities. A versioned material library links specimen identity and processing history to the specific runs in which each sample was tested. An integrated modeling workbench enables training and evaluation of regression models directly on archived experimental data, supporting condition interpolation and the construction of empirical material response databases. Beyond its original deployment at NASA Ames Research Center, BEAST has been designed to be facility-agnostic, with ongoing efforts to extend its adoption to other facilities. Its modular architecture accommodates heterogeneous diagnostic setups and facility types, and its future open-source distribution allows institutions to build on a common data standard rather than maintaining isolated, bespoke solutions. BEAST is further integrated within a broader ecosystem of companion tools: arcjetCV [3] extracts recession rates and shock standoff distances from high-speed video using computer vision, and miniSTARscan [4] provides sub-minute, portable photogrammetric surface reconstruction of test articles before and after exposure. All tools share a common data schema, enabling seamless ingestion of surface geometry, imagery, and time-series data into a single, coherent experimental record.

Database↗

DspaceOgre 3D Graphics Visualization Tool

This general-purpose 3D graphics visualization C++ tool is designed for visualization of simulation and analysis data for articulated mechanisms. Examples of such systems are vehicles, robotic arms, biomechanics models, and biomolecular structures. DspaceOgre builds upon the open-source Ogre3D graphics visualization library. It provides additional classes to support the management of complex scenes involving multiple viewpoints and different scene groups, and can be used as a remote graphics server. This software provides improved support for adding programs at the graphics processing unit (GPU) level for improved performance. It also improves upon the messaging interface it exposes for use as a visualization server.

Jain, Abhinandan↗

Detecting and Characterizing Semantic Inconsistencies in Ported Code

Adding similar features and bug fixes often requires porting program patches from reference implementations and adapting them to target implementations. Porting errors may result from faulty adaptations or inconsistent updates. This paper investigates (1) the types of porting errors found in practice, and (2) how to detect and characterize potential porting errors. Analyzing version histories, we define five categories of porting errors, including incorrect control- and data-flow, code redundancy, inconsistent identifier renamings, etc. Leveraging this categorization, we design a static control- and data-dependence analysis technique, SPA, to detect and characterize porting inconsistencies. Our evaluation on code from four open-source projects shows that SPA can detect porting inconsistencies with 65% to 73% precision and 90% recall, and identify inconsistency types with 58% to 63% precision and 92% to 100% recall. In a comparison with two existing error detection tools, SPA improves precision by 14 to 17 percentage points.

Semantic Errors↗

Multidisciplinary Tool for Systems Analysis of Planetary Entry, Descent, and Landing

Systems analysis of a planetary entry (SAPE), descent, and landing (EDL) is a multidisciplinary activity in nature. SAPE improves the performance of the systems analysis team by automating and streamlining the process, and this improvement can reduce the errors that stem from manual data transfer among discipline experts. SAPE is a multidisciplinary tool for systems analysis of planetary EDL for Venus, Earth, Mars, Jupiter, Saturn, Uranus, Neptune, and Titan. It performs EDL systems analysis for any planet, operates cross-platform (i.e., Windows, Mac, and Linux operating systems), uses existing software components and open-source software to avoid software licensing issues, performs low-fidelity systems analysis in one hour on a computer that is comparable to an average laptop, and keeps discipline experts in the analysis loop. SAPE uses Python, a platform-independent, open-source language, for integration and for the user interface. Development has relied heavily on the object-oriented programming capabilities that are available in Python. Modules are provided to interface with commercial and government off-the-shelf software components (e.g., thermal protection systems and finite-element analysis). SAPE currently includes the following analysis modules: geometry, trajectory, aerodynamics, aerothermal, thermal protection system, and interface for structural sizing.

Samareh, Jamshid A.↗

Detecting and Characterizing Semantic Inconsistencies in Ported Code

Adding similar features and bug fixes often requires porting program patches from reference implementations and adapting them to target implementations. Porting errors may result from faulty adaptations or inconsistent updates. This paper investigates (I) the types of porting errors found in practice, and (2) how to detect and characterize potential porting errors. Analyzing version histories, we define five categories of porting errors, including incorrect control- and data-flow, code redundancy, inconsistent identifier renamings, etc. Leveraging this categorization, we design a static control- and data-dependence analysis technique, SPA, to detect and characterize porting inconsistencies. Our evaluation on code from four open-source projects shows thai SPA can dell-oct porting inconsistencies with 65% to 73% precision and 90% recall, and identify inconsistency types with 58% to 63% precision and 92% to 100% recall. In a comparison with two existing error detection tools, SPA improves precision by 14 to 17 percentage points

Ray, Baishakhi↗

Injecting Artificial Memory Errors Into a Running Computer Program

Single-event upsets (SEUs) or bitflips are computer memory errors caused by radiation. BITFLIPS (Basic Instrumentation Tool for Fault Localized Injection of Probabilistic SEUs) is a computer program that deliberately injects SEUs into another computer program, while the latter is running, for the purpose of evaluating the fault tolerance of that program. BITFLIPS was written as a plug-in extension of the open-source Valgrind debugging and profiling software. BITFLIPS can inject SEUs into any program that can be run on the Linux operating system, without needing to modify the program s source code. Further, if access to the original program source code is available, BITFLIPS offers fine-grained control over exactly when and which areas of memory (as specified via program variables) will be subjected to SEUs. The rate of injection of SEUs is controlled by specifying either a fault probability or a fault rate based on memory size and radiation exposure time, in units of SEUs per byte per second. BITFLIPS can also log each SEU that it injects and, if program source code is available, report the magnitude of effect of the SEU on a floating-point value or other program variable.

Bornstein, Benjamin J.↗

[Development and Use of Hidrosig]

The NASA portion of this joint NSF-NASA grant consists of objective 2 and a part of objective 3. A major effort was made on objective 2, and it consisted of developing a numerical GIs environment called Hidrosig. This major research tool is being developed by the University of Colorado for conducting river-network-based scaling analyses of coupled water-energy-landform-vegetation interactions including water and energy balances, and floods and droughts, at multiple space-time scales.Objective 2: To analyze the relevant remotely sensed products from satellites, radars and ground measurements to compute the transported water mass for each complete Strahler stream using an 'assimilated water balance equation' at daily and other appropriate time scales. This objective requires analysis of concurrent data sets for Precipitation (PPT), Evapotranspiration (ET) and stream flows (Q) on river networks. To solve this major problem, our decision was to develop Hidrosig, a new Open-Source GIs software. A research group in Colombia, South America, developed the first version of Hidrosig, and Ricardo Mantilla was part of this effort as an undergraduate student before joining the graduate program at the University of Colorado in 2001. Hydrosig automatically extracts river networks from large DEMs and creates a "link-based" data structure, which is required to conduct a variety of analyses under objective 2. It is programmed in Java, which is a multi-platform programming language freely distributed by SUN under a GPL license. Some existent commercial tools like Arc-Info, RiverTools and others are not suitable for our purpose for two reasons. First, the source code is not available that is needed to build on the network data structure. Second, these tools use different programming languages that are not most versatile for our purposes. For example, RiverTools uses an IDL platform that is not very efficient for organizing diverse data sets on river networks. Hidrosig establishes a clear data organization framework that allows a simultaneous analysis of spatial fields along river network structures involving Horton- Strahler framework. Software tools for network extraction from DEMs and network-based analysis of geomorphologic and topologic variables were developed during the first year and a part of second year.

Gupta, Vijay K.↗

A Multidisciplinary Tool for Systems Analysis of Planetary Entry, Descent, and Landing (SAPE)

SAPE is a Python-based multidisciplinary analysis tool for systems analysis of planetary entry, descent, and landing (EDL) for Venus, Earth, Mars, Jupiter, Saturn, Uranus, Neptune, and Titan. The purpose of SAPE is to provide a variable-fidelity capability for conceptual and preliminary analysis within the same framework. SAPE includes the following analysis modules: geometry, trajectory, aerodynamics, aerothermal, thermal protection system, and structural sizing. SAPE uses the Python language-a platform-independent open-source software for integration and for the user interface. The development has relied heavily on the object-oriented programming capabilities that are available in Python. Modules are provided to interface with commercial and government off-the-shelf software components (e.g., thermal protection systems and finite-element analysis). SAPE runs on Microsoft Windows and Apple Mac OS X and has been partially tested on Linux.

Samareh, Jamshid A.↗

HDF-EOS Web Server

A shell script has been written as a means of automatically making HDF-EOS-formatted data sets available via the World Wide Web. ("HDF-EOS" and variants thereof are defined in the first of the two immediately preceding articles.) The shell script chains together some software tools developed by the Data Usability Group at Goddard Space Flight Center to perform the following actions: Extract metadata in Object Definition Language (ODL) from an HDF-EOS file, Convert the metadata from ODL to Extensible Markup Language (XML), Reformat the XML metadata into human-readable Hypertext Markup Language (HTML), Publish the HTML metadata and the original HDF-EOS file to a Web server and an Open-source Project for a Network Data Access Protocol (OPeN-DAP) server computer, and Reformat the XML metadata and submit the resulting file to the EOS Clearinghouse, which is a Web-based metadata clearinghouse that facilitates searching for, and exchange of, Earth-Science data.

Ullman, Richard↗

Ensemble: an Architecture for Mission-Operations Software

Ensemble is the name of an open architecture for, and a methodology for the development of, spacecraft mission operations software. Ensemble is also potentially applicable to the development of non-spacecraft mission-operations- type software. Ensemble capitalizes on the strengths of the open-source Eclipse software and its architecture to address several issues that have arisen repeatedly in the development of mission-operations software: Heretofore, mission-operations application programs have been developed in disparate programming environments and integrated during the final stages of development of missions. The programs have been poorly integrated, and it has been costly to develop, test, and deploy them. Users of each program have been forced to interact with several different graphical user interfaces (GUIs). Also, the strategy typically used in integrating the programs has yielded serial chains of operational software tools of such a nature that during use of a given tool, it has not been possible to gain access to the capabilities afforded by other tools. In contrast, the Ensemble approach offers a low-risk path towards tighter integration of mission-operations software tools.

Norris, Jeffrey↗

Provenance in Data Interoperability for Multi-Sensor Intercomparison

As our inventory of Earth science data sets grows, the ability to compare, merge and fuse multiple datasets grows in importance. This requires a deeper data interoperability than we have now. Efforts such as Open Geospatial Consortium and OPeNDAP (Open-source Project for a Network Data Access Protocol) have broken down format barriers to interoperability; the next challenge is the semantic aspects of the data. Consider the issues when satellite data are merged, cross-calibrated, validated, inter-compared and fused. We must match up data sets that are related, yet different in significant ways: the phenomenon being measured, measurement technique, location in space-time or quality of the measurements. If subtle distinctions between similar measurements are not clear to the user, results can be meaningless or lead to an incorrect interpretation of the data. Most of these distinctions trace to how the data came to be: sensors, processing and quality assessment. For example, monthly averages of satellite-based aerosol measurements often show significant discrepancies, which might be due to differences in spatio- temporal aggregation, sampling issues, sensor biases, algorithm differences or calibration issues. Provenance information must be captured in a semantic framework that allows data inter-use tools to incorporate it and aid in the intervention of comparison or merged products. Semantic web technology allows us to encode our knowledge of measurement characteristics, phenomena measured, space-time representation, and data quality attributes in a well-structured, machine-readable ontology and rulesets. An analysis tool can use this knowledge to show users the provenance-related distrintions between two variables, advising on options for further data processing and analysis. An additional problem for workflows distributed across heterogeneous systems is retrieval and transport of provenance. Provenance may be either embedded within the data payload, or transmitted from server to client in an out-of-band mechanism. The out of band mechanism is more flexible in the richness of provenance information that can be accomodated, but it relies on a persistent framework and can be difficult for legacy clients to use. We are prototyping the embedded model, incorporating provenance within metadata objects in the data payload. Thus, it always remains with the data. The downside is a limit to the size of provenance metadata that we can include, an issue that will eventually need resolution to encompass the richness of provenance information required for daata intercomparison and merging.

Lynnes, Chris↗

HOPE: An On-Line Piloted Handling Qualities Experiment Data Book

A novel on-line database for capturing most of the information obtained during piloted handling qualities experiments (either flight or simulated) is described. The Hyperlinked Overview of Piloted Evaluations (HOPE) web application is based on an open-source object-oriented Web-based front end (Ruby-on-Rails) that can be used with a variety of back-end relational database engines. The hyperlinked, on-line data book approach allows an easily-traversed way of looking at a variety of collected data, including pilot ratings, pilot information, vehicle and configuration characteristics, test maneuvers, and individual flight test cards and repeat runs. It allows for on-line retrieval of pilot comments, both audio and transcribed, as well as time history data retrieval and video playback. Pilot questionnaires are recorded as are pilot biographies. Simple statistics are calculated for each selected group of pilot ratings, allowing multiple ways to aggregate the data set (by pilot, by task, or by vehicle configuration, for example). Any number of per-run or per-task metrics can be captured in the database. The entire run metrics dataset can be downloaded in comma-separated text for further analysis off-line. It is expected that this tool will be made available upon request

Jackson, E. B.↗

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.↗

Combustion Branch Website Development

The NASA combustion branch is a leader in developing and applying combustion science to focused aerospace propulsion systems concepts. It is widely recognized for unique facilities, analytical tools, and personnel. In order to better communicate the outstanding research being done in this Branch to the public and other research organization, a more substantial website was desired. The objective of this project was to build an up-to-date site that reflects current research in a usable and attractive manner. In order to accomplish this, information was requested from all researchers in the Combustion branch, on their professional skills and on the current projects. This information was used to fill in the Personnel and Research sections of the website. A digital camera was used to photograph all personnel and these photographs were included in the personnel section as well. The design of the site was implemented using the latest web standards: xhtml and external css stylesheets. This implementation conforms to the guidelines recommended by the w3c. It also helps to ensure that the web site is accessible by disabled users, and complies with Section 508 Federal legislation (which mandates that all Federal websites be accessible). Graphics for the new site were generated using the gimp (www.gimp.org) an open-source graphics program similar to Adobe Photoshop. Also, all graphics on the site were of a reasonable size (less than 20k, most less than 2k) so that the page would load quickly. Technologies such as Macromedia Flash and Javascript were avoided, as these only function on some clients which have the proper software installed or enabled. The website was tested on different platforms with many different browsers to ensure there were no compatibility issues. The website was tested on windows with MS IE 6, MSIE 5 , Netscape 7, Mozilla and Opera. On a Mac, the site was tested with MS IE 5 , Netscape 7 and Safari.

Bishop, Eric↗

Elucidating Microbial Adaptation Dynamics via Autonomous Exposure and Sampling

The adaptation of micro-organisms to their environments is a complex process of interaction between the pressures of the environment and of competition. Reducing this multifactorial process to environmental exposure in the laboratory is a common tool for elucidating individual mechanisms of evolution, such as mutation rates. Although such studies inform fundamental questions about the way adaptation and even speciation occur, they are often limited by labor-intensive manual techniques. Current methods for controlled study of microbial adaptation limit the length of time, the depth of collected data, and the breadth of applied environmental conditions. Small idiosyncrasies in manual techniques can have large effects on outcomes; for example, there are significant variations in induced radiation resistances following similar repeated exposure protocols. We describe here a project under development to allow rapid cycling of multiple types of microbial environmental exposure. The system allows continuous autonomous monitoring and data collection of both single species and sampled communities, independently and concurrently providing multiple types of controlled environmental pressure (temperature, radiation, chemical presence or absence, and so on) to a microbial community in dynamic response to the ecosystem's current status. When combined with DNA sequencing and extraction, such a controlled environment can cast light on microbial functional development, population dynamics, inter- and intra-species competition, and microbe-environment interaction. The project's goal is to allow rapid, repeatable iteration of studies of both natural and artificial microbial adaptation. As an example, the same system can be used both to increase the pH of a wet soil aliquot over time while periodically sampling it for genetic activity analysis, or to repeatedly expose a culture of bacteria to the presence of a toxic metal, automatically adjusting the level of toxicity based on the number or growth rate of surviving cells. We are on our second prototype iteration, with demonstrated functions of microbial growth monitoring and dynamic exposure to UV-C radiation and temperature. We plan to add functionality for general chemical presence or absence by Nov. 2013. By making the project low-cost and open-source, we hope to encourage others to use it as a basis for future development of a common microbial environmental adaptation testbed.

Microbiology↗

Data-Driven Software Framework for Web-Based ISS Telescience

Software that enables authorized users to monitor and control scientific payloads aboard the International Space Station (ISS) from diverse terrestrial locations equipped with Internet connections is undergoing development. This software reflects a data-driven approach to distributed operations. A Web-based software framework leverages prior developments in Java and Extensible Markup Language (XML) to create portable code and portable data, to which one can gain access via Web-browser software on almost any common computer. Open-source software is used extensively to minimize cost; the framework also accommodates enterprise-class server software to satisfy needs for high performance and security. To accommodate the diversity of ISS experiments and users, the framework emphasizes openness and extensibility. Users can take advantage of available viewer software to create their own client programs according to their particular preferences, and can upload these programs for custom processing of data, generation of views, and planning of experiments. The same software system, possibly augmented with a subset of data and additional software tools, could be used for public outreach by enabling public users to replay telescience experiments, conduct their experiments with simulated payloads, and create their own client programs and other custom software.

Tso, Kam S.↗