Search NASASearch

SEARCH · Search NASA

Results for “Provenance graph”

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.

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

36 records · Page 2

Interpretable Tree-Based and Graph Neural Network Approaches for Novel Solid State Electrolyte Design

All-solid-state batteries with Li metal anode can address the safety issues surrounding traditional Li-ion batteries as well as the demand for higher energy densities. However, the development of solid electrolytes simultaneously possessing high ionic conductivity and good chemical and electrochemical stabilities has proven to be a challenge. I will present our informatics approach to explore the Li compound space for promising solid electrolytes using high-throughput multi-property screening and interpretable machine learning. This is accomplished through the generation of a large database of battery-related materials properties of Li compounds. We use tree-based ensemble learning methods and graph neural network approaches to accurately learn relationships between crystal structures and corresponding thermodynamic and kinetic properties, with interpretability being a major focus. Our models give us the ability to enable rapid discovery and design of novel solid-state battery chemistries.

Materials discovery

Computer-Based Mathematics Instructions for Engineering Students

Almost every engineering course involves mathematics in one form or another. The analytical process of developing mathematical models is very important for engineering students. However, the computational process involved in the solution of some mathematical problems may be very tedious and time consuming. There is a significant amount of mathematical software such as Mathematica, Mathcad, and Maple designed to aid in the solution of these instructional problems. The use of these packages in classroom teaching can greatly enhance understanding, and save time. Integration of computer technology in mathematics classes, without de-emphasizing the traditional analytical aspects of teaching, has proven very successful and is becoming almost essential. Sample computer laboratory modules are developed for presentation in the classroom setting. This is accomplished through the use of overhead projectors linked to graphing calculators and computers. Model problems are carefully selected from different areas.

Khan, Mustaq A.

On the Current State of Sheaf Theoretic Networking

Advancing the Delay Tolerant Networking (DTN) effort has proven to be a unique and difficult challenge. In the journey to implementing space networking, NASA has considered several strategies. From direct translations of Internet Protocol (IP) to satellite networks to pre-planned routing structures in Contact Graph Routing (CGR), each potential solution for DTN has come with its fair share of setbacks and challenges. Frequently, these challenges can be traced back to specific assumptions made in the development of each protocol that do not carry over from ground networks to space networks. To address these fundamental assumptions, a more general and foundational networking theory is required. In this paper, we survey a novel mathematical foundation for networking using the theory of cellular sheaves. Sheaves form a mathematical tool for modeling local phenomenon that leads to global effects. Sheaves have been introduced a number of times, and our goal here is to summarize the applications and point towards important future work that must be done to build a stronger, cohesive theory for networking.

Sheaves

Adaptive Distributed Environment for Procedure Training (ADEPT)

ADEPT (Adaptive Distributed Environment for Procedure Training) is designed to provide more effective, flexible, and portable training for NASA systems controllers. When creating a training scenario, an exercise author can specify a representative rationale structure using the graphical user interface, annotating the results with instructional texts where needed. The author's structure may distinguish between essential and optional parts of the rationale, and may also include "red herrings" - hypotheses that are essential to consider, until evidence and reasoning allow them to be ruled out. The system is built from pre-existing components, including Stottler Henke's SimVentive instructional simulation authoring tool and runtime. To that, a capability was added to author and exploit explicit control decision rationale representations. ADEPT uses SimVentive's Scalable Vector Graphics (SVG)- based interactive graphic display capability as the basis of the tool for quickly noting aspects of decision rationale in graph form. The ADEPT prototype is built in Java, and will run on any computer using Windows, MacOS, or Linux. No special peripheral equipment is required. The software enables a style of student/ tutor interaction focused on the reasoning behind systems control behavior that better mimics proven Socratic human tutoring behaviors for highly cognitive skills. It supports fast, easy, and convenient authoring of such tutoring behaviors, allowing specification of detailed scenario-specific, but content-sensitive, high-quality tutor hints and feedback. The system places relatively light data-entry demands on the student to enable its rationale-centered discussions, and provides a support mechanism for fostering coherence in the student/ tutor dialog by including focusing, sequencing, and utterance tuning mechanisms intended to better fit tutor hints and feedback into the ongoing context.

Domeshek, Eric

Plant Bioengineering Atlas: A Knowledge Graph of Genes, DNA Constructs, and Plant Traits.

Plant bioengineering has generated tens of thousands of genotype-to-phenotype relationships, but this knowledge remains fragmented across narrative literature and difficult to use computationally. Inconsistent descriptions of DNA constructs, host species, and traits, including variable species names, omitted regulatory elements, and inconsistent gene symbols, impede data reuse, comparative analysis, and design-build-test-learn cycles. Here, we present the Plant Bioengineering Atlas, a literature-mined, ontology-grounded knowledge base assembled using an artificial intelligence (AI)-aided extraction pipeline. A large language model parsed open-access primary research articles to generate structured, provenance-anchored records of engineered genes, modification types, promoter-gene-terminator constructs, host species, target traits, and reported phenotypes, with every record traceable to its source. The current release contains 14,358 curated records encompassing 6,998 distinct genes across 436 plant species from 6,452 papers published between 2000 and 2026. Corpus analysis reveals that experiments are concentrated in a small group of model and crop species, disease and pathogen resistance is the most frequently engineered trait class, and constitutive regulatory parts (particularly the CaMV 35S promoter and NOS terminator) remain pervasive. Two in five records omit one or both flanking regulatory elements (i.e., promoter and terminator), while only 23.4% describe cassettes in which both elements resolve to named part classes, exposing a systematic reproducibility gap. We organize these data into a knowledge graph linking genes, constructs, species, and traits; provide access through an interactive web portal; and propose an AI-compatible documentation standard for AI-ready reporting. The Plant Bioengineering Atlas provides a foundation for data-driven hypothesis generation and AI-aided plant biodesign.

, Genes, DNA Constructs

Announcing the Biomedical Data Translator: Initial Public Release

ABSTRACT The growing availability of biomedical data offers vast potential to improve human health, but the complexity and lack of integration of these datasets often limit their utility. To address this, the Biomedical Data Translator Consortium has developed an open‐source knowledge graph–based system—Translator—designed to integrate, harmonize, and make inferences over diverse biomedical data sources. We announce here Translator's initial public release and provide an overview of its architecture, standards, user interface, and core features. Translator employs a scalable, federated, knowledge graph framework for the integration of clinical, genomic, pharmacological, and other biomedical knowledge sources, enabling query retrieval, inference, and hypothesis generation. Translator's user interface is designed to support the exploration of knowledge relationships and the generation of insights, without requiring deep technical expertise and gradually revealing more detailed evidence, provenance, and confidence information, as needed by a given user. To demonstrate Translator's application and impact, we highlight features of the user interface in the context of three real‐world use cases: suggesting potential therapeutics for patients with rare disease; explaining the mechanism of action of a pipeline drug; and screening and validating drug candidates in a model organism. We discuss strengths and limitations of reasoning within a largely federated system and the need for rich concept modeling and deep provenance tracking. Finally, we outline future directions for enhancing Translator's functionality and expanding its data sources. Translator represents a significant step forward in making complex biomedical knowledge more accessible and actionable, aiming to accelerate translational research and improve patient care.

Research & Experimental Medicine

Interpretable ML Approaches for Novel Solid State Electrolyte Design

All-solid-state batteries with Li metal anode can address the safety issues surrounding traditional Li-ion batteries as well as the demand for higher energy densities. However, the development of solid electrolytes simultaneously possessing high ionic conductivity and good chemical and electrochemical stabilities has proven to be a challenge. I will present our informatics approach to explore the Li compound space for promising solid electrolytes using high-throughput multi-property screening and interpretable machine learning. This is accomplished through the generation of a large database of battery-related materials properties of Li compounds. We use tree-based ensemble learning methods and graph neural network approaches to accurately learn relationships between crystal structures and corresponding thermodynamic and kinetic properties, with interpretability being a major focus. Our models give us the ability to enable rapid discovery and design of novel solid-state battery chemistries.

Shreyas J Honrao

Power Flow Geometry and Approximation

Here, the power flow equations are important in numerous power systems problems of practical interest which consider alternating current power flow (ACPF) physics. Perhaps the most well studied being the alternating current optimal power flow problem (ACOPF), seeking to optimize the operation of an electric power system. Due to their non-linearity, problems which include the power flow equations are typically challenging, particularly in optimization. Interestingly, the set of solutions to the power flow equations forms a smooth manifold. As a result, differential geometry can be used to describe and analyze this set of equations. This approach has proven effective in several engineering applications (e.g., solving ACOPF and analyzing the solution space boundary). Central to the success of this approach is an understanding of the power flow manifold's geometry. In this work, we develop the geometric and topological properties of this manifold using concepts from differential geometry. After demonstrating the convenience of this manifold's representation as a function's graph, computational methods are emphasized: we develop retractions, error bounds for linear approximation, and formulas for evaluating the Riemannian metric (including associated objects such as geodesics and the curvature tensor). Scalar curvature and the second fundamental form play a new role in quantifying the quality of linear approximations, like the popular direct current approximation. All functions are implemented in Julia and available in an online repository. Proofs are included for completeness.

24 POWER TRANSMISSION AND DISTRIBUTION

Autonomous Cryogenic Load Operations: KSC Autonomous Test Engineer

The KSC Autonomous Test Engineer (KATE) program has a long history at KSC. Now a part of the Autonomous Cryogenic Load Operations (ACLO) mission, this software system has been sporadically developed over the past 20+ years. Originally designed to provide health and status monitoring for a simple water-based fluid system, it was proven to be a capable autonomous test engineer for determining sources of failure in. the system, As part.of a new goal to provide this same anomaly-detection capability for a complicated cryogenic fluid system, software engineers, physicists, interns and KATE experts are working to upgrade the software capabilities and graphical user interface. Much progress was made during this effort to improve KATE. A display ofthe entire cryogenic system's graph, with nodes for components and edges for their connections, was added to the KATE software. A searching functionality was added to the new graph display, so that users could easily center their screen on specific components. The GUI was also modified so that it displayed information relevant to the new project goals. In addition, work began on adding new pneumatic and electronic subsystems into the KATE knowledgebase, so that it could provide health and status monitoring for those systems. Finally, many fixes for bugs, memory leaks, and memory errors were implemented and the system was moved into a state in which it could be presented to stakeholders. Overall, the KATE system was improved and necessary additional features were added so that a presentation of the program and its functionality in the next few months would be a success.

Shrading, Nicholas J.

Autonomous Cryogenic Load Operations: Knowledge-Based Autonomous Test Engineer

The Knowledge-Based Autonomous Test Engineer (KATE) program has a long history at KSC. Now a part of the Autonomous Cryogenic Load Operations (ACLO) mission, this software system has been sporadically developed over the past 20 years. Originally designed to provide health and status monitoring for a simple water-based fluid system, it was proven to be a capable autonomous test engineer for determining sources of failure in the system. As part of a new goal to provide this same anomaly-detection capability for a complicated cryogenic fluid system, software engineers, physicists, interns and KATE experts are working to upgrade the software capabilities and graphical user interface. Much progress was made during this effort to improve KATE. A display of the entire cryogenic system's graph, with nodes for components and edges for their connections, was added to the KATE software. A searching functionality was added to the new graph display, so that users could easily center their screen on specific components. The GUI was also modified so that it displayed information relevant to the new project goals. In addition, work began on adding new pneumatic and electronic subsystems into the KATE knowledge base, so that it could provide health and status monitoring for those systems. Finally, many fixes for bugs, memory leaks, and memory errors were implemented and the system was moved into a state in which it could be presented to stakeholders. Overall, the KATE system was improved and necessary additional features were added so that a presentation of the program and its functionality in the next few months would be a success.

Schrading, J. Nicolas

Software Users Manual (SUM): Extended Testability Analysis (ETA) Tool

This software user manual describes the implementation and use the Extended Testability Analysis (ETA) Tool. The ETA Tool is a software program that augments the analysis and reporting capabilities of a commercial-off-the-shelf (COTS) testability analysis software package called the Testability Engineering And Maintenance System (TEAMS) Designer. An initial diagnostic assessment is performed by the TEAMS Designer software using a qualitative, directed-graph model of the system being analyzed. The ETA Tool utilizes system design information captured within the diagnostic model and testability analysis output from the TEAMS Designer software to create a series of six reports for various system engineering needs. The ETA Tool allows the user to perform additional studies on the testability analysis results by determining the detection sensitivity to the loss of certain sensors or tests. The ETA Tool was developed to support design and development of the NASA Ares I Crew Launch Vehicle. The diagnostic analysis provided by the ETA Tool was proven to be valuable system engineering output that provided consistency in the verification of system engineering requirements. This software user manual provides a description of each output report generated by the ETA Tool. The manual also describes the example diagnostic model and supporting documentation - also provided with the ETA Tool software release package - that were used to generate the reports presented in the manual

Maul, William A.

Analyzing EOSDIS Dataset Research Outputs using Knowledge Graphs and Large Language Models

Datasets, unlike publications, can be updated over time, with each new version receiving a DOI but not always being linked to previous ones. This complicates tracking citations across a dataset’s lifecycle. We address this by integrating dataset versions and citations into a knowledge graph (KG), which helps trace dataset citations and analyze dataset usage in applied research. To categorize publications from various journals, we fine-tuned NASA IMPACT INDUS Large Language Model (LLM) on a labeled publication set, assigning publications to one of twenty applied research areas. By linking datasets to these research areas, we improved dataset searchability and discovery through these domains.

open-source

Stirling Engine Dynamic System Modeling

The Thermo-Mechanical systems branch at the Glenn Research Center focuses a large amount time on Stirling engines. These engines will be used on missions where solar power is inefficient, especially in deep space. I work with Tim Regan and Ed Lewandowski who are currently developing and validating a mathematical model for the Stirling engines. This model incorporates all aspects of the system including, mechanical, electrical and thermodynamic components. Modeling is done through Simplorer, a program capable of running simulations of the model. Once created and then proven to be accurate, a model is used for developing new ideas for engine design. My largest specific project involves varying key parameters in the model and quantifying the results. This can all be done relatively trouble-free with the help of Simplorer. Once the model is complete, Simplorer will do all the necessary calculations. The more complicated part of this project is determining which parameters to vary. Finding key parameters depends on the potential for a value to be independently altered in the design. For example, a change in one dimension may lead to a proportional change to the rest of the model, and no real progress is made. Also, the ability for a changed value to have a substantial impact on the outputs of the system is important. Results will be condensed into graphs and tables with the purpose of better communication and understanding of the data. With the changing of these parameters, a more optimal design can be created without having to purchase or build any models. Also, hours and hours of results can be simulated in minutes. In the long run, using mathematical models can save time and money. Along with this project, I have many other smaller assignments throughout the summer. My main goal is to assist in the processes of model development, validation and testing.

Nakis, Christopher G.

Enhancing Dataset Discovery and Usage Tracking in Earth Sciences: Integrating Knowledge Graphs and Large Language Models

NASA's Data Active Archive Centers (DAACs) have played a crucial role in supporting a wide range of applied research in Earth and Environmental sciences. To date, over 20,000 publications have been collected, citing more than 3,000 NASA Earth science datasets. We present an innovative approach that links datasets and collected publications through a knowledge graph (KG). This KG enables the tracking of dataset citations throughout the dataset's lifecycle, revealing patterns of dataset usage across various applied research areas. We fine-tuned the pre-trained NASA IMPACT INDUS-Base Retriever Large Language Model (LLM) using a set of labeled publication abstracts. Our results indicate that 87% of the publications were classified into one of twenty applied research areas, while the remaining 13% were categorized into non-applied research areas. The classified publications linked to datasets are used to discover datasets by users interested in specific applied research and by dataset providers to determine dataset usage for applications.

open-source

Multidisciplinary Model Transformation Through Simplified Intermediate Representations

There has long been a challenge of making engineering tools from multiple disciplines interoperate. This problem extends to system modeling practices. This challenge has been confronted with a wide variety of techniques. These techniques include attempting to interface tools together into combined suites, attempting to find underlying commonalities in mathematics, supporting connections through semantic encoding, various graph mappings and transformations, and code wrappers. All of these approaches have strengths and weaknesses. These are measured in multiple areas: relative freedom of action of individual domain engineers in developing their own tools, speed of execution, ease of creation, traceability, fidelity of information transfer, and degree of alignment between the concepts of different domains. This paper presents an approach to this interoperation problem currently being used in the World-Wide Web. The approach is to develop easy-to-parse formats that allow flexibility to both the file author and file interpreter. Many of the formats that are currently deployed sacrifice runtime performance for the ability of third parties to easily understand what to do with the data. XML became popular earlier as a de-facto standard format for many web applications, but is now being replaced by JSON to enhance human readability and provide a simpler data model. This is the basis for work in this paper. Our approach, which provides the key to interoperation, is a simplified “shrapnel” intermediate collection of objects and relationships that is the result of a breakdown of the system model into minimal pieces. It is then reassembled on the destination side, forming a two-step transformation. Previous efforts with single-step transformations have proven too difficult to create efficiently. In contrast, the use of this approach leads to an almost automatic procedure for transformation development. The Europa project is a large engineering project that must coordinate the efforts of many different teams with different specialties. The traditional form of exchanging engineering information has been documentation. The vision of model-based systems engineering is to make this information exchange much more digital. This paper presents the application of our simplified format to connecting two different engineering tools to the system model, with a focus on a dynamic mission simulation encoded in Modelica.

Cole, Bjorn

Discovering Research Areas in Dataset Applications Through Knowledge Graphs and Large Language Models

Scientific datasets are increasingly cited in peer-reviewed journal publications, facilitating easy access to research utilizing those datasets. Datasets undergo a life cycle where older versions of datasets are replaced by newer versions often due to improvements in data resolution, algorithms, and other factors. Unlike peer reviewed documents registered with a single Digital Unique Identifier (DOI), datasets can be updated over time and the newer version of the datasets are registered with a new DOI which is not necessarily linked to the previous version of the dataset. It is challenging when publications citing a dataset need to be traced over the entire life cycle of that dataset. We provide an innovative approach to link the dataset versions and publications using a knowledge graph (KG). KG can help to trace the dataset cited in publications over the entire dataset life cycle and shed light into dataset usage in various applied research areas. We fine-tuned the pretrained NASA IMPACTINDUS Large Language Model (LLM) on a set of labeled publications abstracts. Our results showed that 87% of the publications were classified into one of twenty applied research areas, while the remaining 13% were classified into non-applied research areas. By linking datasets to applied research areas through the KG and employing Global Change Master Directory(GCMD), a well-established controlled vocabulary of scientific keywords describing Earth science datasets, we contribute to a transparent and advanced search and discovery mechanism for datasets across the Earth data ecosystem. The integrated KG and LLM approach is now incorporated and operational in dataset publication management at one of NASA’s Earth science data archival centers.

data provenance

Organization of P, S, and Fe Inclusions in a Freshwater Magnetococcus

Magnetotactic bacteria are a heterogeneous group of motile, mainly aquatic procaryotes that align and swim along geomagnetic field lines. They are of interest to astrobiologists because of the magnetite crystals found in the Mars meteorite ALH84001 which share many characteristics with the magnetite produced intracellularly by magnetotactic bacteria. These bacteria are diverse morphologically, physiologically and phylogenetically, sharing a few key characteristics: 1) the presence of intracellular membrane-bound magnetic crystals (magnetosomes), usually but not always arranged in chains; 2) motility by means of flagella; and 3) microaerophillic or anaerobic physiology. The bilophotrichous (having two flagella bundles) magnetotactic cocci (MC) are ubiquitous in aquatic habitats but have proven extremely difficult to cultivate. Because only several marine strains have been isolated and grown in axenic culture, little is known about the physiology and the biogeochemical roles of the MC. We studied the composition and distribution of intracellular structures in an uncultured MC, designated ARB-1. To do this, a combination of light microscopy, environmental scanning electron microscopy (ESEM), transmission electron microscopy (TEM) and energy dispersive X-ray spectroscopy (EDS) were used. Cells of ARB-1 were separated from sediments collected from Baldwin Lake (Los Angeles Arboretum, Arcadia, CA). They are large spherical to oblate spheroidal Gram-negative cells, ranging from 1 to 4 micrometers along the maximum dimension, which is perpendicular to the direction of swimming. Cells have two large phosphorus-containing inclusions that comprise a large percentage of the cell volume. Many smaller sulfur inclusions are located at the convex end of the cell. Most of the cellular Fe is present in the magnetosomes. These may be arranged as a clump at the concave end of the cell, near the two flagella bundles, or as chains, or as both a clump and chains. The magnetosomes were identified as magnetite (Fe3O4) by selected area electron diffraction (SAED) and high resolution TEM. We saw a trend between cell size and organization of the magnetosomes. Smaller, more spherical cells were more likely to have chains than were larger, more oblate cells. This may indicate different populations of cells, or it may be attributed to variations in cell growth cycle. The size distribution (length) of magnetosomes in chains was similar to that of magnetosomes in clusters, except that there was a larger size range for clustered magnetosomes. Magnetosomes from ARB-1 cells average 82 nm in length. If plotted on a graph of length as a function of aspect ratio, they fall within the single domain region of the plot. If compared with the size distributions of magnetite from ALH84001 and magnetosomes from the cultured magnetotactic vibrio MV-1, the magnetites produced by ARB-1 cells are, on average, larger and have a wider range of aspect ratio. ARB-1 cells have a specific organization of the P, S, and Fe inclusions. The P inclusions always occupy the majority of the cell volume and separate the S inclusions from the disorganized clumps of magnetosomes and the flagella bundles. The P inclusions may contain polyphosphate, which could play several roles in motility, adaptation to stress, growth and division, buoyancy, and energy. The S inclusions might be a way to store S, a potential energy source, when the cells move from sulfide to oxygen zones. The consistency of P, S, and Fe organization in ARB-1 cells suggests that these inclusions have some specific and interactive functions.

Cox, Lea

Environmental Stress Testing of the Single Sample Cylinder: A Proven Consensus Standard for Internal Gas Analysis (IGA) or Residual Gas Analysis (RGA)

In August 2008, Schuessler Consulting was contracted by NASA GSFC in support of the NASA Electronic Parts and Packaging (NEPP) program to perform two separate studies on moisture laden air in a stainless steel cylinder that had been designed to become a consensus standard for Test Method 1018. This Test Method was originally released for hybrids under Mil. Std. 883 but was quickly utilized on other microelectronic devices under the auspice of Mil. Std. 750. The cylinder had subsequently been fabricated for the 750 community. It was back-filled with moist air and subsequently analyzed over a period of time under a previous NASA contract. It had been shown that moisture in the 4000 - 5000 ppm range could be analyzed rather precisely with a mass spectrometer, commonly referred to as a Residual Gas Analyzer (RGA). The scope of this study was to ascertain if the composition and precision varied as a function of thermal shock at sub-zero temperatures and whether there was consensus when the standard was submitted to other RGA units. It was demonstrated and published that the consensus standard would yield precise RGA data for moisture within +/- 1% when optimized for a given RGA unit. It has been subsequently shown in this study at Oneida Research Services, that sub-zero storage did not affect that precision when a well-defined protocol for the analysis was followed. The consensus standard was taken to a second facility for analysis where it was found that moisture adsorption on the transfer lines caused precision to drop to +/- 12%. The Single Sample Cylinder (SSC) is a one liter stainless steel cylinder with associated sampling valves and has considerable weight and volume. But this considerable size allows for approximately 300 gas samples of the same composition to be delivered to any RGA unit. Lastly, a smaller cylinder, approximately 75 cc, of a second consensus standard was fabricated and tested with a different mix of fixed gases where moisture was kept in the 100 ppm range. This second standard has the potential of providing 30 gaseous samples and can be readily shipped to any analytical facility that desires to generate comparison RGA data. A series of comparison residual gas analyses was performed at the Honeywell Federal Manufacturing & Technologies facility in the National Nuclear Facility Administration s plant in Kansas City to complete this project. It was shown that improvements in the precision of a given RGA unit can be done by controlling the cycle time for each analysis and increasing analysis temperatures to minimize moisture adsorption. It was also found that a "one time event" in the subzero storage of the large SSC did not effect the units ability to continuously supply precise samples of the same chemistry, however the "event" caused a permanent +8% shift in the reported value of the moisture content. Lastly, a set of SSC RGA results was plotted on a common graph with DSCC "correlation study" RGA data. The result demonstrates the ability of the SSC to remove many of the individual variances that single, individual samples introduce. The consensus standards are now in storage at Oneida Research Services, one of the DSCC certified houses that does RGA to Military Standards, where they await future studies. The analytical data and the operational parameters of the instruments used are provided in the following discussion. Limitations and suggested means for improvement of both precision and accuracy are provided.

Schuessler, Philipp WH