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NASA NTRS1999

ACTS 118x Final Report High-Speed TCP Interoperability Testing

With the recent explosion of the Internet and the enormous business opportunities available to communication system providers, great interest has developed in improving the efficiency of data transfer using the Transmission Control Protocol (TCP) of the Internet Protocol (IP) suite. The satellite system providers are interested in solving TCP efficiency problems associated with long delays and error-prone links. Similarly, the terrestrial community is interested in solving TCP problems over high-bandwidth links. Whereas the wireless community is interested in improving TCP performance over bandwidth constrained, error-prone links. NASA realized that solutions had already been proposed for most of the problems associated with efficient data transfer over large bandwidth-delay links (which include satellite links). The solutions are detailed in various Internet Engineering Task Force (IETF) Request for Comments (RFCs). Unfortunately, most of these solutions had not been tested at high-speed (155+ Mbps). Therefore, the NASA's ACTS experiments program initiated a series of TCP experiments to demonstrate scalability of TCP/IP and determine how far the protocol can be optimized over a 622 Mbps satellite link. These experiments were known as the 118i and 118j experiments. During the 118i and 118j experiments, NASA worked closely with SUN Microsystems and FORE Systems to improve the operating system, TCP stacks. and network interface cards and drivers. We were able to obtain instantaneous data throughput rates of greater than 520 Mbps and average throughput rates of 470 Mbps using TCP over Asynchronous Transfer Mode (ATM) over a 622 Mbps Synchronous Optical Network (SONET) OC12 link. Following the success of these experiments and the successful government/industry collaboration, a new series of experiments. the 118x experiments. were developed.

Ivancic, William D.↗

NASA NTRSDate not supplied

Expanding Biological Repository Data Available for Sharing and Knowledge Discovery

Biology has developed next-generation data science and alternative analytical approaches with methodologies which require principal investigator (PI) experimental assay data be re-used. This new approach involves mining multiple datasets at once from various hierarchical organizations of biological complexity, while concurrently evaluating how experimental factors affect endpoints of standard assays. The purpose of the NASA Ames Life Sciences Data Archive (ALSDA) is to collect, curate, and make findable, accessible, interoperable, and reusable (FAIR) all non-human space-relevant biological data. These data include mission metadata, subject metadata, assay metadata (parameters), raw and processed assay data, assay imagery, and subject-experienced telemetry (radiation, temperature, humidity, acoustics, vibrations). ALSDA has transformed to bring current biological repository data and all future collected data into this new scientific data mining reality. It has integrated into the ‘NASA Open Science’ group of projects to facilitate a suite of new tools and workflows to improve data accessibility and reusability by implementing data management plans, automating data submission agreements, and adopting the single-point-of-entry data submission portal, originally developed by NASA GeneLab. These systems required ALSDA to develop science assay configurations for the submission portal, capturing essential assay parameters according to established norms in each sub-field within biology. The submission portal expedites data collection by enhancing ease of PI data submission, providing a user interface and specificity for which data is to be submitted. ALSDA datasets are curated to maintain rich metadata, accuracy of datasets, data transparency, provenance, and additionally ensure data are machine-readable (e.g., R and Python languages). ALSDA integration with GeneLab and its analysis portals enable higher-order physiological-level datasets be mined in conjunction with -omics datasets. As ALSDA physiological-level datasets are published (micro-computed tomography, histology, intraocular pressure, hormonal assays, immunostaining, ultrasonography), the merging of hierarchical organizations of biological complexity from spaceflight will enable new knowledge discovery approaches.

Ryan T Scott↗

DOE OSTI2021

A KBase Case Study on Genome-wide Transcriptomics and Plant Primary Metabolism in Sorghum

A better understanding of the genetic and metabolic mechanisms that confer stress resistance and tolerance in plants is key to engineering new crops through advanced breeding technologies. This requires a systems biology approach that builds on a genome-wide understanding of the regulation of gene expression, plant metabolism, physiology and growth. In this study, we examine the response to drought stress in Sorghum, as we leverage the tools for transcriptomics and plant metabolic modeling we have implemented at the U.S. Department of Energy Systems Biology Knowledgebase (KBase). KBase enables researchers worldwide to collaborate and advance research by allowing them to upload private or public data into the KBase Narrative Interface, empowering them to analyze this data using a rich, extensible array of computational and data-analytics tools, and allows them to securely share scientific workflows and conclusions. We demonstrate how to use the current RNA-seq tools in KBase, applicable to both plants and microbes, to assemble and quantify long transcripts and identify differentially expressed genes effectively. More specifically, we demonstrate the utility of the platform by identifying key genes that are differentially expressed during drought-stress in Sorghum bicolor, which is an important sustainable production crop plant. We then show how to use KBase tools to predict the membership of genes in metabolic pathways and examine expression data in the context of metabolic subsystems. We demonstrate the power of the platform by making the data analysis and interpretation available to the biologists in the reproducible, re-usable, point-and-click format of a KBase Narrative thus promoting FAIR (Findable, Accessible, Interoperable and Reusable) guiding principles for scientific data management and stewardship.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS2002

MDP: Reliable File Transfer for Space Missions

This paper presents work being done at NASA/GSFC by the Operating Missions as Nodes on the Internet (OMNI) project to demonstrate the application of the Multicast Dissemination Protocol (MDP) to space missions to reliably transfer files. This work builds on previous work by the OMNI project to apply Internet communication technologies to space communication. The goal of this effort is to provide an inexpensive, reliable, standard, and interoperable mechanism for transferring files in the space communication environment. Limited bandwidth, noise, delay, intermittent connectivity, link asymmetry, and one-way links are all possible issues for space missions. Although these are link-layer issues, they can have a profound effect on the performance of transport and application level protocols. MDP, a UDP-based reliable file transfer protocol, was designed for multicast environments which have to address these same issues, and it has done so successfully. Developed by the Naval Research Lab in the mid 1990's, MDP is now in daily use by both the US Post Office and the DoD. This paper describes the use of MDP to provide automated end-to-end data flow for space missions. It examines the results of a parametric study of MDP in a simulated space link environment and discusses the results in terms of their implications for space missions. Lessons learned are addressed, which suggest minor enhancements to the MDP user interface to add specific features for space mission requirements, such as dynamic control of data rate, and a checkpoint/resume capability. These are features that are provided for in the protocol, but are not implemented in the sample MDP application that was provided. A brief look is also taken at the status of standardization. A version of MDP known as NORM (Neck Oriented Reliable Multicast) is in the process of becoming an IETF standard.

Rash, James↗

NASA NTRSDate not supplied

Expanding Repository Data Available For Sharing and Knowledge Discovery

Some of the hardest space biology and space health challenges require data-intensive, bioinformatic, meta-analytical, and computer-assisted research approaches. These challenges include examining interdisciplinary space life science research across experiments and across interacting spaceflight hazards (radiation, altered gravity, confinement, hostile-closed environments, distance-duration from Earth). The approaches to confront these challenges involve mining multiple datasets simultaneously from various hierarchical organizations of biological complexity, all while concurrently evaluating how experimental design factors affect endpoints of standard assays. To enable this field, it is essential that principal investigators (PIs) submit data in a structure so it can be maximally re-used. The purpose of the NASA Ames Life Sciences Data Archive (ALSDA) is to collect, curate, and make publicly available all non-human space-relevant biological data. ALSDA must also ensure data are open-access, and maximally findable, accessible, interoperable, and reusable (FAIR). The scope of ALSDA data collected and submitted by PIs include subject and study design metadata, assay metadata parameters, raw and processed assay data, assay imagery/video, and subject-experienced mission data telemetry (radiation, temperature, humidity, acoustics, vibrations, etc.). ALSDA recently integrated into a collaborative group of Open Science projects to facilitate a suite of new tools and workflows that will improve data submission, accessibility, and reusability by implementing digital data submission agreements, and adopting the data management system originally developed by NASA GeneLab. ALSDA intends to bring current biological repository data and all future collected data into this new scientific data reuse reality. This new suite of tools will enable ALSDA to deploy a science curation system using scientific assay configurations for the data submission portal. It will capture essential assay parameters according to established standards in each sub-field within biology. The submission portal expedites data collection by enhancing ease of PI data submission, providing a user interface and specificity for which data is to be submitted. Data submissions can be brought into cutting-edge informatic analysis portals to enable mining of physiological, behavioral, biochemical, and imaging datasets in conjunction with ‘omics-level datasets. As ALSDA datasets are submitted, curated, and published (e.g., micro-computed tomography, histology, pulse oximetry, serum metabolites, magnetic resonance imaging, intraocular pressure, novel object recognition, etc.), the merging together of spaceflight data along this multi-hierarchical complexity of biology will enable informatics and data-intensive approaches resulting in knowledge discoveries across missions, space hazards, and biological disciplines.

Biology↗

NASA NTRSDate not supplied

Expanding Repository Data Available For Sharing And Knowledge Discovery

life science↗

DOE OSTI2024

OpenFacadeControl: enabling integration of automated facades with other building systems

Automated facades are, for the most part, still considered as separate from other building systems throughout the design, installation, commissioning, operation, and maintenance cycle. This takes place despite the fact that their energy and comfort performance are deeply interlinked with the operation of lighting and HVAC systems. Over the last two decades, research has shown that there are significant advantages from operating facades as an integrated system with the rest of the building. Nevertheless, significant barriers prevent this type of integration becoming more common. One of them is the lack of a platform that is inexpensive to implement and that easily allows the practical implementation of integrated control algorithms across fenestration and other building systems, using a variety of communications protocols. This is particularly challenging when automated facades are installed in existing buildings, where interaction with legacy building systems that were installed over the past lifetime of the building can require a high degree of interoperability. OpenFacadeControl (OFC) is an open-source controls framework aimed at unified control of facades and other building systems, including the sharing of third-party sensor information. Through leveraging the Volttron controls platform, it allows the integration of systems and sensors that are manufactured by different companies and that use different communications protocols into an ensemble that functions as a single system. OFC is designed to enable integrated control algorithms of varying degrees of complexity, ranging from simple, heuristic controls to more sophisticated approaches like model-predictive control. Use of a research version to test advanced lighting and shading strategies in a full-scale experimental testbed has demonstrated the ease of deploying advanced control solutions using OpenFacadeControl. This paper presents the structure of OpenFacadeControl and a demonstration case showing the use of OFC in laboratory tests of advanced lighting and fenestration controls that coordinated motorized shades communicating via the BACnet building communications standard and lights communicating via internet-protocol-based application programming interface (API), based on the readings of a shared light level sensor communicating via a different API.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

NASA NTRS2002

MDP: Reliable File Transfer for Space Missions

This paper presents work being done at NASA/GSFC (Goddard Space Flight Center) by the Operating Missions as Nodes on the Internet (OMNI) project to demonstrate the application of the Multicast Dissemination Protocol (MDP) to space missions to reliably transfer files. This work builds on previous work by the OMNI project to apply Internet communication technologies to space communication. The goal of this effort is to provide an inexpensive, reliable, standard, and interoperable mechanism for transferring files in the space communication environment. Limited bandwidth, noise, delay, intermittent connectivity, link asymmetry, and one-way links are all possible issues for space missions. Although these are link-layer issues, they can have a profound effect on the performance of transport and application level protocols. MDP, a UDP (User Datagram Protocol)-based reliable file transfer protocol, was designed for multicast environments which have to address these same issues, and it has done so successfully. Developed by the Naval Research Lab in the mid 1990s, MDP is now in daily use by both the US Post Office and the DoD (Department of Defense). This paper describes the use of MDP to provide automated end-to-end data flow for space missions. It examines the results of a parametric study of MDP in a simulated space link environment and discusses the results in terms of their implications for space missions. Lessons learned are addressed, which suggest minor enhancements to the MDP user interface to add specific features for space mission requirements, such as dynamic control of data rate, and a checkpoint/resume capability. These are features that are provided for in the protocol, but are not implemented in the sample MDP application that was provided. A brief look is also taken at the status of standardization. A version of MDP known as NORM (Nack Oriented Reliable Multicast) is in the process of becoming an IETF (Internet Engineering Task Force) standard.

Rash, James↗

NASA NTRSDate not supplied

Enabling Space Biological Knowledge Discovery Through Image and Video Data Sharing

Increased biomedical risks and challenges associated with deep space missions and experiments (cis-Lunar, Mars transit/surface) require new knowledge discovery and development of novel ecosystems. Supporting distant and long-duration missions and experiments requires biological data (from yeast, microbes, fruit flies, C. elegans, plants, crops, rodents, humans) be findable, accessible, interoperable, reusable (FAIR), and maximally open-access. As data-intensive, bioinformatic, meta-analytical, and computer-assisted approaches continue to be a centerpiece of modern research, the NASA Biological and Physical Sciences division is expanding its Open Science capabilities beyond NASA GeneLab. The NASA Ames Life Sciences Data Archive (ALSDA) is a repository which is responsible for collecting and access to space biological imagery and video, alongside tabular and environmental data. In this presentation, we will discuss strategies dealing with archiving, curating, and accessibility of images from very distinct imaging modalities (e.g., micro-computed tomography, magnetic resonance imaging, photographic images of plants, fluorescence microscopy, behavioral videos, etc.). There are two main challenges: 1. Open-source data storage and 2. Metadata related to the imagery-video. Both have been solved by leveraging two existing open-source systems. For data storage, ALSDA is utilizing components through the Open Microscopy Environment (OME), which can read most imaging proprietary formats and display on a web interface complex multidimensional images (Z stack, multi-channel, temporal, spectral). Most technical metadata from imaging modalities are captured seamlessly. For metadata capturing experimental details, ALSDA (like GeneLab) uses the ISA-Tab specification which relies on the ISA data model to order and classify metadata. The ISA data model uses a tree structure with three files to capture the metadata: The top layer is the Investigations file, the second layer is the Study file(s), and the last layer is the Assay file(s). We believe such an approach may be useful for other types of image research data from other investigators in the AGU community.

imaging↗

NASA NTRS2006

Mission Control Technologies: A New Way of Designing and Evolving Mission Systems

Current mission operations systems are built as a collection of monolithic software applications. Each application serves the needs of a specific user base associated with a discipline or functional role. Built to accomplish specific tasks, each application embodies specialized functional knowledge and has its own data storage, data models, programmatic interfaces, user interfaces, and customized business logic. In effect, each application creates its own walled-off environment. While individual applications are sometimes reused across multiple missions, it is expensive and time consuming to maintain these systems, and both costly and risky to upgrade them in the light of new requirements or modify them for new purposes. It is even more expensive to achieve new integrated activities across a set of monolithic applications. These problems impact the lifecycle cost (especially design, development, testing, training, maintenance, and integration) of each new mission operations system. They also inhibit system innovation and evolution. This in turn hinders NASA's ability to adopt new operations paradigms, including increasingly automated space systems, such as autonomous rovers, autonomous onboard crew systems, and integrated control of human and robotic missions. Hence, in order to achieve NASA's vision affordably and reliably, we need to consider and mature new ways to build mission control systems that overcome the problems inherent in systems of monolithic applications. The keys to the solution are modularity and interoperability. Modularity will increase extensibility (evolution), reusability, and maintainability. Interoperability will enable composition of larger systems out of smaller parts, and enable the construction of new integrated activities that tie together, at a deep level, the capabilities of many of the components. Modularity and interoperability together contribute to flexibility. The Mission Control Technologies (MCT) Project, a collaboration of multiple NASA Centers, led by NASA Ames Research Center, is building a framework to enable software to be assembled from flexible collections of components and services.

Trimble, Jay↗

NASA NTRS2015

Unified User Interface to Support Effective and Intuitive Data Discovery, Dissemination, and Analysis at NASA GES DISC

Goddard Earth Sciences Data and Information Services Center (GES DISC) has been providing access to scientific data sets since 1990s. Beginning as one of the first Earth Observing System Data and Information System (EOSDIS) archive centers, GES DISC has evolved to offer a wide range of science-enabling services. With a growing understanding of needs and goals of its science users, GES DISC continues to improve and expand on its broad set of data discovery and access tools, sub-setting services, and visualization tools. Nonetheless, the multitude of the available tools, a partial overlap of functionality, and independent and uncoupled interfaces employed by these tools often leave the end users confused as of what tools or services are the most appropriate for a task at hand. As a result, some the services remain underutilized or largely unknown to the users, significantly reducing the availability of the data and leading to a great loss of scientific productivity. In order to improve the accessibility of GES DISC tools and services, we have designed and implemented UUI, the Unified User Interface. UUI seeks to provide a simple, unified, and intuitive one-stop shop experience for the key services available at GES DISC, including sub-setting (Simple Subset Wizard), granule file search (Mirador), plotting (Giovanni), and other services. In this poster, we will discuss the main lessons, obstacles, and insights encountered while designing the UUI experience. We will also present the architecture and technology behind UUI, including NodeJS, Angular, and Mongo DB, as well as speculate on the future of the tool at GES DISC as well as in a broader context of the Space Science Informatics.

web portal↗

DOE OSTI2013

National Geothermal Data System: Transforming the Discovery, Access, and Analytics of Data for Geothermal Exploration

Compendium of Papers from the 38th Workshop on Geothermal Reservoir Engineering Stanford University, Stanford, California February 11-13, 2013 The National Geothermal Data System (NGDS) is a distributed, interoperable network of data collected from state geological surveys across all fifty states and the nation’s leading academic geothermal centers. The system serves as a platform for sharing consistent, reliable, geothermal-relevant technical data with users of all types, while supplying tools relevant for their work. As aggregated data supports new scientific findings, this content-rich linked data ultimately broadens the pool of knowledge available to promote discovery and development of commercial-scale geothermal energy production. Most of the up-front risks associated with geothermal development stem from exploration and characterization of subsurface resources. Wider access to distributed data will, therefore, result in lower costs for geothermal development. NGDS is on track to become fully operational by 2014 and will provide a platform for custom applications for accessing geothermal relevant data in the U.S. and abroad. It is being built on the U.S. Geoscience Information Network (USGIN) data integration framework to promote interoperability across the Earth sciences community. The basic structure of the NGDS employs state-of-the art informatics to advance geothermal knowledge. The following four papers comprising this Open-File Report are a compendium of presentations, from the 38th Annual Workshop on Geothermal Reservoir Engineering, taking place February 11-13, 2013 at Stanford University, Stanford, California. “NGDS Geothermal Data Domain: Assessment of Geothermal Community Data Needs,” outlines the efforts of a set of nationwide data providers to supply data for the NGDS. In particular, data acquisition, delivery, and methodology are discussed. The paper addresses the various types of data and metadata required and why simple links to existing data are insufficient for promoting geothermal exploration. Authors of this paper are Arlene Anderson, US DOE Geothermal Technologies Office, David Blackwell, Southern Methodist University (SMU), Cathy Chickering (SMU), Toni Boyd, Oregon Institute of Technology’s GeoHeat Center, Roland Horne, Stanford University, Matthew MacKenzie, Uberity, Joe Moore, University of Utah, Duane Nickull, Uberity, Stephen Richard, Arizona Geological Survey, and Lisa Shevenell, University of Nevada, Reno. “NGDS User Centered Design: Meeting the Needs of the Geothermal Community,” discusses the user- centered design approach taken in the development of a user interface solution for the NGDS. The development process is research based, highly collaborative, and incorporates state-of-the-art practices to ensure a quality user interface for the widest and greatest utility. Authors of this paper are Harold Blackman, Boise State University, Suzanne Boyd, Anthro-Tech, Kim Patten, Arizona Geological Survey, and Sam Zheng, Siemens Corporate Research. “Fueling Innovation and Adoption by Sharing Data on the DOE Geothermal Data Repository Node on the National Geothermal Data System,” describes the motivation behind the development of the Geothermal Data Repository (GDR) and its role in the NGDS. This includes the benefits of using the GDR to share geothermal data of all types and DOE’s data submission process. Authors of this paper are Jon Weers, National Renewable Energy Laboratory and Arlene Anderson, US DOE Geothermal Technologies Office. Finally, “Developing the NGDS Adoption of CKAN for Domestic & International Data Deployment,” provides an overview of the “Node-In-A-Box” software package designed to provide data consumers with a highly functional interface to access the system, and to ease the burden on data providers who wish to publish data in the system. It is important to note that this software package constitutes a reference implementation and that the NGDS architecture is based on open standards, which means other server software can make resources available, and other client applications can utilize NGDS data. Authors of this paper are Ryan Clark, Arizona Geological Survey (AZGS), Christoph Kuhmuench, Siemens Corporate Research, and Stephen Richard, AZGS.

15 GEOTHERMAL ENERGY↗

DOE OSTI2024

DOE BSSD Performance Management Metrics Report Q1

Microbes play key roles in our biosphere, from driving global nutrient cycling to impacting plant, animal and human health and disease. Complex data from microbial genomes, proteins, and metabolites provide a window into these tiny engines that drive life on our planet. Yet these data are dispersed among researchers’ laboratories and various repositories, making it difficult to access. This calls for new ways of managing data, improving data interoperability, advancing community standards, and creating an infrastructure where data are shared efficiently. We have built the National Microbiome Data Collaborative (NMDC) to advance how scientists create, use, and reuse data to redefine the way we understand and harness the power of microbes. The vision of the National Microbiome Data Collaborative (NMDC) is to drive a microbiome data sharing network connecting data, people, and ideas to advance microbiome innovation and discovery. The NMDC was launched in 2019 and brought together DOE National Laboratories to collaborate across resources, capabilities, and expertise. The NMDC team was strategically assembled to include software developers, microbial researchers, metadata experts, and multi-omics specialists. The diversity of the NMDC team reflects the inherently interdisciplinary nature of microbiome science, and we leverage the strengths of the DOE National Laboratory system. Towards BER’s goal of advancing an iterative systems biology approach to the understanding of microbial genomes, the NMDC serves as a foundation for infrastructure, data standards, and community building. Together with the flagship DOE User Facilities, the Joint Genome Institute (JGI) and the Environmental Molecular Sciences Laboratory (EMSL), we are developing core capabilities in metadata standards for environmental descriptors and sample handling and processing; standardized bioinformatic workflows; an interface for data search and access; and robust community engagement activities. The NMDC production platform supports long-term data infrastructure and community building for BER’s bioenergy and environmental research goals. Our approach leverages lessons learned and an ambitious framework for collaborative, interdisciplinary data infrastructure to support microbiome research. The NMDC supports data, information, and knowledge access through three defined software tools – the Submission Portal, NMDC EDGE, and the Data Portal – driven by community needs. Herein, we describe the value proposition for the microbiome research community, our overarching strategy, and challenges and opportunities for developing the NMDC as both an infrastructure and community engagement program.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2025

ChargeX OCPI Recommendations

The Open Charge Point Interface (OCPI) is an open protocol that enables electric vehicle (EV) charging systems to work together across networks. It supports communication and data sharing between Charge Point Operators (CPOs), who manage charging stations, and e-Mobility Service Providers (eMSPs), who provide charging services to EV drivers. OCPI facilitates functions like user authorization, remote charge point control, charging session data exchange, and billing through Charge Detail Records (CDRs). This allows EV roaming, so drivers can charge at different networks without multiple accounts. As the EV market grows due to increased adoption and technological advancements, OCPI faces higher demands. This has revealed issues with CDR format consistency, timestamp standardization across regions, transmission of EV-side error codes for troubleshooting, and support for new use cases. These challenges can affect operations and user experience, particularly as the industry starts considering Vehicle-to-Grid (V2G) systems, where EVs supply energy to the grid, and Vehicle-to-Everything (V2X) technologies for broader energy interactions. Using feedback from the ChargeX Diagnostics taskforce discussions, industry 1-on-1 meetings, technical standards, and OCPI’s evolution through versions (e.g., OCPI 2.1.1, 2.2, and 2.2.1), this report identifies these issues and suggests practical recommendations. These aim to improve interoperability, streamline operations, and prepare OCPI for future trends in the EV charging ecosystem.

32 - ENERGY CONSERVATION, CONSUMPTION, AND UTILIZA↗

DOE OSTI2026

Enabling the Broader Use of MOOSE for Nuclear Energy and Other Simulation

This Final Scientific and Technical Report summarizes work performed under the Phase IIA SBIR project “Enabling the Broader Use of MOOSE for Nuclear Energy and Other Simulation” (DE-SC0020906) from August 2023 through August 2025. The objective of the Phase IIA effort was to mature and harden capabilities developed during Phase II, with the goal of enabling practical interoperability between Coreform’s isogeometric analysis (IGA) technologies and the Multiphysics Object-Oriented Simulation Environment (MOOSE), while improving robustness, performance, and scalability for complex, nuclear-relevant geometries. Over the course of Phase IIA, the project established and validated an extraction-based interoperability pathway between Coreform tools and MOOSE. A combined mesh and matrix format was defined collaboratively with MOOSE developers and integrated into the solver, enabling standard MOOSE workflows to operate on data exported from Coreform’s IGA and Flex Representation Method (FRM) pipelines. Early demonstrations validated architectural compatibility using linear solid mechanics problems, while later efforts focused on benchmark testing and external use. By the end of the project period, engineers at BWXT were able to independently set up and execute a simulation using the Coreform–MOOSE workflow and provide direct feedback that informed further refinement. In parallel, substantial effort was devoted to improving the robustness of trimmed U-spline construction for complex CAD geometries. A growing test suite of nuclear-relevant models was compiled through collaboration with multiple stakeholders and used to drive extensive bug fixing and reliability improvements. These efforts resulted in improved robustness and performance, including the addition of fallback capabilities that enhance reliability when the underlying commercial CAD kernel fails. Performance-oriented work progressed later in the project, with the development and demonstration of methods to decompose complex geometries into structured subregions and updated data representations to support more efficient solver processing. Additionally, extensive enhancements to threadsafe parallel data structures and trimming operations established a foundation for scalable processing of large assemblies. Collaboration with Sandia National Laboratories on the SGM geometric modeling kernel advanced to a functioning interface test case, positioning the workflow for future kernel integration. Overall, the Phase IIA effort successfully transitioned the project from architectural proof-of-concept to externally exercised, solver-integrated capability, while clarifying remaining technical challenges related to standardization, performance optimization, and kernel integration.

42 ENGINEERING↗

NASA NTRSDate not supplied

Developing Concepts of Operations Using Multi-Step Tool Techniques With Large Language Models

The National Aeronautics and Space Administration (NASA) Air Mobility Pathfinders (AMP) project is developing and evaluating concepts of operations (ConOps) for safe, secure, and scalable Urban Air Mobility (UAM) operations. The AMP project’s Operational Concepts, Architecture, and Requirements Integration (OCARI) Team is using a Model Based System Engineering (MBSE) approach for integration, interoperability, and traceability of Advanced Air Mobility (AAM) ecosystems centered around urban air taxi services. The team’s goal is to define structures and behaviors needed for system feasibility, readiness, and interoperability, establish a UAM knowledge base, and trace and validate assumptions and requirements relevant to AAM. NASA Langley Research Center (LaRC) is spearheading an innovative digital engineering approach to integrate, communicate, and facilitate the research of multi-modal transportation systems. The Knowledge-based Digital Platform (KbDP) is a concept being developed that ties the workflows of Project Managers (PM), Principal Investigators (PI), and System Engineers together across organizational boundaries. It does so through the management of an information database defined by mathematical, data science, and system engineering principles. Machine Learning (ML) algorithms play a key role in this concept by extracting meaningful knowledge from relational and graph databases, document repositories, and system artifacts, which the human user leverages to greatly improve the efficiency and effectiveness of their research. Recent advancements in the field of Large Language Models (LLMs), specifically models trained for tool use, such as Command-R , now allow for the reliable implementation of single-step and multi-step tool-centric systems. These techniques provide the LLM with a set of tools, in our case Python functions, that can be called on to answer a much wider range of questions compared to LLMs implemented using a traditional single-source or Retrieval Augmented Generation (RAG) approach. Through this method, the LLM can pull information from multiple data sources, such as relational or graph databases, document repositories, application programming interfaces (APIs), and SysML artifacts depending on the user’s question. The LLM can also output the information in a variety of different formats, using output generation tools, such as CSV, UML, or SysML artifacts. Additionally, tools can be assigned roles and can work together to provide answers to queries in an “agent” like approach, similar to that implemented by Microsoft’s AutoGen framework where different agents can converse with each other to accomplish tasks. Previously, our team developed a chatbot system with “agent like” functionality in the form of different “modes” the user could select from a user interface (UI), this architecture can be seen on the left in figure 1. Three different modes were implemented, the first mode allowed the LLM to utilize the structures and algorithms within a graph database to trace UAM requirements. The second mode gave the LLM access to a vector search capable of providing relevant information from thousands of document pages related to UAM ConOps and requirements. The third mode served as a general assistant where users could enter open-ended questions and custom prompts to utilize the LLM for different use-cases. This system improved the process surrounding generating and analyzing information related to UAM requirements, however, the implementation provided a clunky user experience. Users were required to know what mode to select within the UI in advance before entering their question to the selected tool. Moreover, the different tools were isolated from each other, they lacked bidirectional links that would allow for tools to collaborate to generate better responses. Our team is working on a new architecture, seen on the right in the below figure, with the goal to address many of the UX shortcomings of our original system while improving the accuracy and depth of responses from the LLM. This new system will automatically select the appropriate tool to use based off the user’s question. Each tool will be capable of calling on any of the other tools available to the LLM, resulting in a collaborative pipeline where tools can pass data between other tools until enough data is received to generate an answer to the user’s question. Using a locally deployed, open-source, LLM, the NASA OCARI team, in collaboration with Collins Aerospace, will implement a prototype application that will bridge knowledge across multiple sources to assist System Engineers (SEs) with requirements discovery and tracing, research question and use case identification, and assumption validation. Such a system will also allow SEs to more easily, and intuitively, explore the AAM ecosystem, ultimately improving the efficiency and effectiveness of the SE's research and decision-making processes surrounding ConOps development and validation. In this session, our team will provide a video demonstration of our new prototype architecture in action. We will also present an overview of our prototype system architecture and talk about its advantages over traditional LLM deployments along with how those advantages can provide additional value to the field of System Engineering.

systems engineering↗

NASA NTRSDate not supplied

Lunar Search & Rescue Applications of Lunar GNSS

Accurate lunar navigation and timing knowledge provides for the development of safety-critical services in the cislunar and lunar surface domain. Currently under development, the Goddard Space Flight Center’s (GSFC) Search and Rescue Mission Office is investigating and integrating search and rescue (SAR) capability into planned and future lunar communication and navigation interfaces. Lunar Search and Rescue (LunaSAR) development has a stated end-goal for assured, reliable, and timely indication of distress events for a wide variety of lunar surface users, including government-sponsored, commercial, and international users. LunaSAR performance requirements are modelled after the current terrestrial Cospas-Sarsat distress notification system, leveraging an internationally robust global navigation satellite system (GNSS) ecosystem as a core element of survivor locating capability. This presentation will discuss NASA’s work to develop user-focused distress messaging capabilities including infusion of example sensor data for triggering of automated distress alerts coupled with location-tagging. Additionally, the presentation will examine overall message structures, rotating fields for use in bi-directional distress messaging, and specific use cases based on NASA’s lunar exploration and lunar communication relay architectures. Modelling and simulation of LunaSAR use by individual lunar explorers will be discussed, based on notional industry and government design reference missions and mission considerations. Results from GSFC-funded Internal Research and Development (IRAD) efforts will be detailed, including successful distress message formulation simulating the ingestion of example legacy space suit telemetry fields. Hardware-in-the-loop testing using high-reliability software defined radio (SDR) modules serve as an example of IRAD successes and the framework for technical requirements. Architectural development and technical evolution from 2020 to 2021 included alignment of LunaSAR distress waveforms with ongoing NASA LunaNet interoperability development, as well as engagement with NASA Lunar Spectrum authorities for allocation of UHF-band distress frequencies on the lunar surface. S-Band and UHF-band transmission characteristics will be detailed, along with band-specific applications of each emission type. Additionally, examples of ingestion and formatting of GNSS signals (using historical terrestrial National Marine Electronics Association-formatted GNSS data) will be detailed, underscoring lunar user needs for a common lunar GNSS receiver output message framework. Maturity and ability to support evolving lunar exploration goals has been demonstrated and will be detailed, with maturity gaps such as position, navigation, and timing (PNT) and lunar reference frames identified within the context of distress message generation. Provision of LunaSAR services for lunar surface users represents a new era of ensured safety for lunar explorers and builds off of forty years of the Cospas-Sarsat program, underscoring the importance of lunar GNSS for safety-critical applications and growing interest in safe, reliable lunar surface operations. Enabled by new GNSS systems being developed by government and industry partners, NASA will continue to evolve and integrate lunar GNSS types into distress message generation, with a focus on compact and efficient message transmission over various lunar communication links. When fielded, LunaSAR will be the first dedicated search and rescue notification system employed on another celestial body. Robust lunar navigation and timing services form the core of LunaSAR capabilities, allowing for system syncing with time-dominant sensors, and high-accuracy location of those in distress while engaged in lunar surface activities.

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NASA NTRS2014

Using Social Media and Mobile Devices to Discover and Share Disaster Data Products Derived From Satellites

Data products derived from Earth observing satellites are difficult to find and share without specialized software and often times a highly paid and specialized staff. For our research effort, we endeavored to prototype a distributed architecture that depends on a standardized communication protocol and applications program interface (API) that makes it easy for anyone to discover and access disaster related data. Providers can easily supply the public with their disaster related products by building an adapter for our API. Users can use the API to browse and find products that relate to the disaster at hand, without a centralized catalogue, for example floods, and then are able to share that data via social media. Furthermore, a longerterm goal for this architecture is to enable other users who see the shared disaster product to be able to generate the same product for other areas of interest via simple point and click actions on the API on their mobile device. Furthermore, the user will be able to edit the data with on the ground local observations and return the updated information to the original repository of this information if configured for this function. This architecture leverages SensorWeb functionality [1] presented at previous IGARSS conferences. The architecture is divided into two pieces, the frontend, which is the GeoSocial API, and the backend, which is a standardized disaster node that knows how to talk to other disaster nodes, and also can communicate with the GeoSocial API. The GeoSocial API, along with the disaster node basic functionality enables crowdsourcing and thus can leverage insitu observations by people external to a group to perform tasks such as improving water reference maps, which are maps of existing water before floods. This can lower the cost of generating precision water maps. Keywords-Data Discovery, Disaster Decision Support, Disaster Management, Interoperability, CEOS WGISS Disaster Architecture

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