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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 541 records · Page 30

Development of Aerodynamic Loads Databases for the Space Launch System Booster Separation Event

Booster separation is a mission-critical event within the orbital ascent of the Space Launch System (SLS). The complexity of the engine plume-affected, multibody, supersonic aerodynamics is compounded by the large span of the likely trajectory space. Characterization of the multiple input, multiple output system requires a combination of wind tunnel testing and computational simulation, but additional data processing is also required before the sparse, high-fidelity data can be fused into a continuous database with acceptable uncertainty quantification. This paper outlines the state of this approach as it has been applied to the most recent SLS booster separation aerodynamic loads database: that of the Artemis II launch vehicle.

Michael W Lee↗

Development of Aerodynamic Loads Databases for the Space Launch System Booster Separation Event

Booster separation is a mission-critical event within the orbital ascent of the Space Launch System (SLS). The complexity of the engine plume-affected, multibody, supersonic aerodynamics is compounded by the large span of the likely trajectory space. Characterization of the multiple input, multiple output system requires a combination of wind tunnel testing and computational simulation, but additional data processing is also required before the sparse, high-fidelity data can be fused into a continuous database with acceptable uncertainty quantification. This paper outlines the state of this approach as it has been applied to the most recent SLS booster separation aerodynamic loads database: that of the Artemis II launch vehicle.

Michael Lee↗

Computational Techniques to Generate Space Launch System Aerodynamic Databases

This document describes the reasoning and trade studies used to evaluate tools for constructing the aerodynamic lineload databases for the liftoff and transition phases of flight for the Space Launch System. Three computational fluid dynamics codes (USM3D, FUN3D, Kestrel) were investigated with various turbulence models, as well as detached eddy simulation variants for the launch vehicle in free air and in proximity to the tower. Decisions were made mostly based on results from brief developmental studies performed in response to specific, unforeseen challenges that were encountered in the analysis of a given configuration. The need to develop databases in a timely manner, as well as accurately capture the expected leeward-wake flowfield characteristics, led to the selection of the Kestrel flow solver with its delayed detached eddy simulation method, the Spalart-Allmaras turbulence model, and the adaptive mesh refinement capability in the off-body Cartesian grid region.

Karen A. Deere↗

The UCLA Cosmochemistry Database

The UCLA Cosmochemistry Database was initiated as part of a data-rescue and -storage project aimed at archiving a variety of cosmochemical data acquired at University of California, Los Angeles (UCLA). The data collection includes elemental compositions of extraterrestrial materials analyzed by UCLA cosmochemists over the last five decades. The analytical techniques include atomic absorption spectrometry (AAS) and neutron activation analysis (NAA) at UCLA. The data collection is stored on the Astromaterials Data System (Astromat). We provide both interactive tables and downloadable datasheets for users to access all data. The UCLA Cosmochemistry Database archives cosmochemical data that are essential tools for increasing our understanding of the nature and origin of extraterrestrial materials. Future studies can reference the data collection in the examination, analysis, and classification of newly acquired extraterrestrial samples.

Bidong Zhang↗

RadLab: A Comprehensive Database and Graphical and Programming Interfaces for Space Radiation Data

RadLab, a component of the NASA Open Science Data Repository (OSDR), is a database of radiation measurements from multiple instruments and spacecraft that provides visual and programmatic interfaces for interrogation and retrieval of these data. The attributes of data available through RadLab include spacecraft, types of radiation sensing instruments, locations within the spacecraft (e.g. ISS modules), associated celestial bodies, trajectories, and spacecraft coordinates; the primary type of data is the absorbed dose rate, as well as flux and dose equivalent rate where available. The application programming interface (API) implements a request syntax for retrieval of timestamped data filtered by various combinations of such attributes; the graphical user interface (GUI) extends this functionality with visualizations (time series plots, comparison plots, geospatial visualizations) which provide easy means to assess data availability, iteratively refine search parameters, interactively inspect the data, and export target data subsets. Datasets are continuously being added to the RadLab database as part of the rolling release process. Investigators from multiple countries, including the US, Canada, Germany, Bulgaria, Hungary, Italy, Japan, Russia and the Czech Republic, have committed to provide data from their instruments in and beyond low Earth orbit. The current release contains datasets provided by US and international collaborators and includes readings from multiple modules of the ISS, the BioSentinel CubeSat, Chang’e 4, the Lunar Reconnaissance Orbiter, the ExoMars Orbiter, and the Curiosity rover. Datasets are associated with respective RadLab knowledgebase articles which include instrument descriptions and provide bibliographical references. RadLab aims to provide a comprehensive, dynamic compendium of space radiation data, enabling the scientific community to perform analyses of data from multiple detectors and to determine the radiation environment of research missions and experiments. Some of its applications include inference of absorbed radiation dose for NASA GeneLab payloads, and training predictive models as part of the 2024 FDL-X challenge. The platform is actively expanding and seeking additional data, with plans to also cover past (e.g. Shuttle, Mir) and future (e.g. Artemis) missions. The RadLab Working Group has been created to aid in this process as well as to foster collaborations among data contributors and users, to develop standards for data harmonization, and to guide the development of the platform, with the goal to establish the use of RadLab in space radiation research and to advance our understanding of the radiation environment in outer space.

Kirill Grigorev↗

Baseline Medical System Translation for the Impact Medical Database

NASA has developed a new evidence-based data-driven probabilistic risk assessment and tradespace analysis tool as a successor to the Integrated Medical Model (IMM). This updated decision support tool is known as IMPACT (Informing Mission Planning via Analysis of Complex Tradespaces). Whereas IMM focuses on the resources and risks associated with International Space Station (ISS) and Low Earth Orbit (LEO) missions, IMPACT estimates the frequency and consequences of medical conditions that might arise during exploration missions. One of the services offered by IMM is a series of generic or baseline medical systems associated with typical mission types or DRMs (Design Reference Missions), such that requestors may prioritize questions pertaining to the mission itself over the medical supplies indicated by the model outputs for that DRM. In a mission focused request, the appropriate baseline medical system is used in place of a prepared or optimized medical kit. In preparation, an effort was undertaken to create baseline systems of medical resources within IMPACT suitable for typical DRMs. Using an existing baseline medical system within IMM’s Integrated Medical Evidence Database (iMED) as a starting point, the resources found within the medical kit were compared to and substituted for equivalent resources available within the IMPACT MD (Medical Database). In consultation with clinicians with knowledge of IMPACT’s MD, each resource was matched as closely as possible to a similarly purposed resource in IMPACT, seeking to preserve the treatment capabilities and procedures offered by the IMM medical system while reconciling the differences in modeled resources and medical conditions between the models. To demonstrate the efficacy of this work, a prototype ISS medical system in IMPACT was translated from the baseline used in the IMM. The appropriate medical system was then run through its associated medical model to compare and validate the resultant risks and risk mitigation provided by each baseline ISS medical kit.

S Schwartz↗

RadLab: A Comprehensive Database and Graphical and Programming Interfaces for Space Radiation Data

RadLab, a component of the NASA Open Science Data Repository (OSDR), is a database of radiation measurements from multiple instruments and spacecraft that provides visual and programmatic interfaces for interrogation and retrieval of these data. The attributes of data available through RadLab include spacecraft, types of radiation sensing instruments, locations within the spacecraft (e.g. ISS modules), associated celestial bodies, trajectories, and spacecraft coordinates; the primary type of data is the absorbed dose rate, as well as flux and dose equivalent rate where available. The application programming interface (API) implements a request syntax for retrieval of timestamped data filtered by various combinations of such attributes; the graphical user interface (GUI) extends this functionality with visualizations (time series plots, comparison plots, geospatial visualizations) which provide easy means to assess data availability, iteratively refine search parameters, interactively inspect the data, and export target data subsets. Datasets are continuously being added to the RadLab database as part of the rolling release process. Investigators from multiple countries, including the US, Canada, Germany, Bulgaria, Hungary, Italy, Japan, Russia and the Czech Republic, have committed to provide data from their instruments in and beyond low Earth orbit. The current release contains datasets provided by US and international collaborators and includes readings from multiple modules of the ISS, the BioSentinel CubeSat, Chang’e 4, the Lunar Reconnaissance Orbiter, the ExoMars Orbiter, and the Curiosity rover. Datasets are associated with respective RadLab knowledgebase articles which include instrument descriptions and provide bibliographical references. RadLab aims to provide a comprehensive, dynamic compendium of space radiation data, enabling the scientific community to perform analyses of data from multiple detectors and to determine the radiation environment of research missions and experiments. Some of its applications include inference of absorbed radiation dose for NASA GeneLab payloads, and training predictive models as part of the 2024 FDL-X challenge. The platform is actively expanding and seeking additional data, with plans to also cover past (e.g. Shuttle, Mir) and future (e.g. Artemis) missions. The RadLab Working Group has been created to aid in this process as well as to foster collaborations among data contributors and users, to develop standards for data harmonization, and to guide the development of the platform, with the goal to establish the use of RadLab in space radiation research and to advance our understanding of the radiation environment in outer space.

Kirill Grigorev↗

A Database of CFD-Based Buffet Forcing Functions for Artemis I Structural Response Evaluation

Time-accurate FUN3D simulations are utilized to estimate buffet-induced unsteady forces experienced by the Space Launch System during the Artemis I (AR01) flight. A set of FUN3D simulations was developed that employed time-accurate mesh translations to simulate the changing velocity and attitude based on the AR01 best estimated trajectory. In these simulations, referred to as accelerating-flow simulations, the freestream Mach number increased from 0.80 to 1.92. Additional time-accurate simulations were obtained at constant freestream Mach number equal to 0.95, 1.18, 1.70, thereby simulating stationary conditions experienced by the flow in a wind-tunnel. On the grounds of favorable comparisons between simulated and flight-measured environments, the FUN3D-based surface pressures were utilized to develop a buffet forcing function (BFF) database. This BFF database was analyzed to characterize the spatial distribution and frequency content of the buffet forces during transonic and supersonic portions of the AR01 flight. The region of interest is located downstream of the forward attachment (FA) hardware between the core stage and the solid rocket boosters where vortex shedding off the FA protuberance produces significant unsteadiness. The analysis reveals that, at transonic and supersonic conditions, buffet forces that are based on constant freestream Mach number data are a good approximation of those based on accelerating-flow simulations.

FUN3D↗

A Database of CFD-Based Buffet Forcing Functions for Artemis I Structural Response Evaluation

Time-accurate FUN3D simulations are utilized to estimate buffet-induced unsteady forces experienced by the Space Launch System during the Artemis I (AR01) flight. A set of FUN3D simulations was developed that employed time-accurate mesh translations to simulate the changing velocity and attitude based on the AR01 best estimated trajectory. In these simulations, referred to as accelerating-flow simulations, the freestream Mach number increased from 0.80 to 1.92. Additional time-accurate simulations were obtained at constant freestream Mach number equal to 0.95, 1.18, 1.70, thereby simulating stationary conditions experienced by the flow in a wind-tunnel. On the grounds of favorable comparisons between simulated and flight-measured environments, the FUN3D-based surface pressures were utilized to develop a buffet forcing function (BFF) database. This BFF database was analyzed to characterize the spatial distribution and frequency content of the buffet forces during transonic and supersonic portions of the AR01 flight. The region of interest is located downstream of the forward attachment (FA) hardware between the core stage and the solid rocket boosters where vortex shedding off the FA protuberance produces significant unsteadiness. The analysis reveals that, at transonic and supersonic conditions, buffet forces that are based on constant freestream Mach number data are a good approximation of those based on accelerating-flow simulations.

transonic buffet↗

CoRE MOF DB: A curated experimental metal-organic framework database with machine-learned properties for integrated material-process screening

Here, we present an updated version of the Computation-Ready, Experimental (CoRE) Metal-Organic Framework (MOF) database, which includes a curated set of computation-ready MOF crystal structures designed for high-throughput computational materials discovery. Data collection and curation procedures were improved from the previous version to enable more frequent updates in the future. Machine-learning-predicted properties, such as stability metrics and heat capacities, are included in the dataset to streamline screening activities. An updated version of MOFid was developed to provide detailed information on metal nodes, organic linkers, and topologies of an MOF structure. DDEC6 partial atomic charges of MOFs were assigned based on a machine-learning model. Gibbs ensemble Monte Carlo simulations were used to classify the hydrophobicity of MOFs. The finalized dataset was subsequently used to perform integrated material-process screening for various carbon-capture conditions using high-fidelity temperature-swing adsorption (TSA) simulations. Our workflow identified multiple MOF candidates that are predicted to outperform CALF-20 for these applications.

CoRE MOF database↗

Database of Nonaqueous Proton-Conducting Materials

This work presents the assembly of 48 papers, representing 74 different compounds and blends, into a machine-readable database of nonaqueous proton-conducting materials. SMILES was used to encode the chemical structures of the molecules, and we tabulated the reported proton conductivity, proton diffusion coefficient, and material composition for a total of 3152 data points. The data spans a broad range of temperatures ranging from -70 to 260 °C. To explore this landscape of nonaqueous proton conductors, DFT was used to calculate the proton affinity of 18 unique proton carriers. The results were then compared to the activation energy derived from fitting experimental data to the Arrhenius equation. It was found that while the widely recognized positive correlation between the activation energy and proton affinity may hold among closely related molecules, this correlation does not necessarily apply across a broader range of molecules. This work serves as an example of the potential analyses that can be conducted using literature data combined with emerging research tools in computation and data science to address specific materials design problems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Metallic fuel transient fuel-cladding interface liquefaction model assessment platform enabled by integrating BISON with databases

A novel platform has been developed within the BISON fuel performance code to assess models of fuel-cladding interface liquefaction for sodium-cooled fast reactor (SFR) metallic fuels. Here, this platform is crucial because liquefaction at the fuel-cladding interface significantly impacts fuel performance and may compromise fuel pin integrity during transient events. To ensure accurate predictions, the platform integrates data collected during the Integral Fast Reactor (IFR) program, now archived in metallic fuel databases. This integration supports verification and validation (V&V) of the models in BISON. Leveraging the extensive US experience with metallic fuel liquefaction and the collections of preserved legacy data, the platform serves as a powerful tool for evaluating existing models and advancing the development of new ones.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Autogenerating a Domain-Specific Question-Answering Data Set from a Thermoelectric Materials Database to Enable High-Performing BERT Models

We present a method for autogenerating a large domain-specific question-answering (QA) dataset from a thermoelectric materials database. We show that a small language model, BERT, once fine-tuned on this automatically generated dataset of 99,757 QA pairs about thermoelectric materials, affords better performance in the field of thermoelectric materials compared to a BERT model fine-tuned on the generic English-language QA data set, SQuAD-v2. We further show that mixing the two data sets (ours and SQuAD-v2), which have significantly different syntactic and semantic scopes, allows the BERT model to achieve even better performance. The best-performing BERT model fine-tuned on the mixed data set outperforms the models fine-tuned on the other two data sets by scoring an exact match of 67.93% and an F1 score of 72.29% when evaluated on our test data set. This has important implications as it demonstrates the ability to realize high-performing small language models, with modest computational resources, empowered by domain-specific materials data sets which can be generated according to our method.

biological databases↗

JINAbase: A database for chemical abundances of metal-poor stars

CeNAM maintains the Stellar Abundance Database JINAbase provides detailed abundance information of 2766 stars from 173 publications. The user interface enables easy graphing of user selected element ratios to explore trends and scatter.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Of red planets and indigo computers: Mars database visualization as an example of platform downsizing

The last decade has witnessed tremendous advancements in the computer hardware and software used to perform scientific visualization. In this paper, we consider how the visualization of a particular data set, the digital terrain model derived from the Viking orbiter imagery, has been realized in four distinct projects over this period. These examples serve to demonstrate how the vast improvements in computational performance both decrease the cost of such visualization efforts and permit an increasing level of interactivity. We then consider how even today's graphical systems require the visualization designer to make intelligent choices and tradeoffs in database rendering. Finally, we discuss how insights gleaned from an understanding of human visual perception can guide these design decisions, and suggest new options for visualization hardware and software.

NASA Center ARC↗

The Ribosomal Database Project

The Ribosomal Database Project (RDP) complies ribosomal sequences and related data, and redistributes them in aligned and phylogenetically ordered form to its user community. It also offers various software packages for handling, analyzing and displaying sequences. In addition, the RDP offers (or will offer) certain analytic services. At present the project is in an intermediate stage of development.

Non-NASA Center↗

Object-Oriented Geographical Database Model

Terbase is an Object-Oriented database system under development at the Jet Propulsion Laboratory (JPL). Terbase is designed for flexibility, reusability, maintenace ease, multi-user collaboration and independence, and efficiency. This paper details the design and development of Terbase as a geographic data server...

Terbase Object-Oriented database system Tactical M↗