Results for “prototype databases” — Page 12

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 NTRS2000

Information Power Grid: Distributed High-Performance Computing and Large-Scale Data Management for Science and Engineering

We use the term "Grid" to refer to distributed, high performance computing and data handling infrastructure that incorporates geographically and organizationally dispersed, heterogeneous resources that are persistent and supported. This infrastructure includes: (1) Tools for constructing collaborative, application oriented Problem Solving Environments / Frameworks (the primary user interfaces for Grids); (2) Programming environments, tools, and services providing various approaches for building applications that use aggregated computing and storage resources, and federated data sources; (3) Comprehensive and consistent set of location independent tools and services for accessing and managing dynamic collections of widely distributed resources: heterogeneous computing systems, storage systems, real-time data sources and instruments, human collaborators, and communications systems; (4) Operational infrastructure including management tools for distributed systems and distributed resources, user services, accounting and auditing, strong and location independent user authentication and authorization, and overall system security services The vision for NASA's Information Power Grid - a computing and data Grid - is that it will provide significant new capabilities to scientists and engineers by facilitating routine construction of information based problem solving environments / frameworks. Such Grids will knit together widely distributed computing, data, instrument, and human resources into just-in-time systems that can address complex and large-scale computing and data analysis problems. Examples of these problems include: (1) Coupled, multidisciplinary simulations too large for single systems (e.g., multi-component NPSS turbomachine simulation); (2) Use of widely distributed, federated data archives (e.g., simultaneous access to metrological, topological, aircraft performance, and flight path scheduling databases supporting a National Air Space Simulation systems}; (3) Coupling large-scale computing and data systems to scientific and engineering instruments (e.g., realtime interaction with experiments through real-time data analysis and interpretation presented to the experimentalist in ways that allow direct interaction with the experiment (instead of just with instrument control); (5) Highly interactive, augmented reality and virtual reality remote collaborations (e.g., Ames / Boeing Remote Help Desk providing field maintenance use of coupled video and NDI to a remote, on-line airframe structures expert who uses this data to index into detailed design databases, and returns 3D internal aircraft geometry to the field); (5) Single computational problems too large for any single system (e.g. the rotocraft reference calculation). Grids also have the potential to provide pools of resources that could be called on in extraordinary / rapid response situations (such as disaster response) because they can provide common interfaces and access mechanisms, standardized management, and uniform user authentication and authorization, for large collections of distributed resources (whether or not they normally function in concert). IPG development and deployment is addressing requirements obtained by analyzing a number of different application areas, in particular from the NASA Aero-Space Technology Enterprise. This analysis has focussed primarily on two types of users: the scientist / design engineer whose primary interest is problem solving (e.g. determining wing aerodynamic characteristics in many different operating environments), and whose primary interface to IPG will be through various sorts of problem solving frameworks. The second type of user is the tool designer: the computational scientists who convert physics and mathematics into code that can simulate the physical world. These are the two primary users of IPG, and they have rather different requirements. The results of the analysis of the needs of these two types of users provides a broad set of requirements that gives rise to a general set of required capabilities. The IPG project is intended to address all of these requirements. In some cases the required computing technology exists, and in some cases it must be researched and developed. The project is using available technology to provide a prototype set of capabilities in a persistent distributed computing testbed. Beyond this, there are required capabilities that are not immediately available, and whose development spans the range from near-term engineering development (one to two years) to much longer term R&D (three to six years). Additional information is contained in the original.

Johnston, William E.↗

NASA NTRS2009

An Analysis of Rocket Propulsion Testing Costs

The primary mission at NASA Stennis Space Center (SSC) is rocket propulsion testing. Such testing is generally performed within two arenas: (1) Production testing for certification and acceptance, and (2) Developmental testing for prototype or experimental purposes. The customer base consists of NASA programs, DOD programs, and commercial programs. Resources in place to perform on-site testing include both civil servants and contractor personnel, hardware and software including data acquisition and control, and 6 test stands with a total of 14 test positions/cells. For several business reasons there is the need to augment understanding of the test costs for all the various types of test campaigns. Historical propulsion test data was evaluated and analyzed in many different ways with the intent to find any correlation or statistics that could help produce more reliable and accurate cost estimates and projections. The analytical efforts included timeline trends, statistical curve fitting, average cost per test, cost per test second, test cost timeline, and test cost envelopes. Further, the analytical effort includes examining the test cost from the perspective of thrust level and test article characteristics. Some of the analytical approaches did not produce evidence strong enough for further analysis. Some other analytical approaches yield promising results and are candidates for further development and focused study. Information was organized for into its elements: a Project Profile, Test Cost Timeline, and Cost Envelope. The Project Profile is a snap shot of the project life cycle on a timeline fashion, which includes various statistical analyses. The Test Cost Timeline shows the cumulative average test cost, for each project, at each month where there was test activity. The Test Cost Envelope shows a range of cost for a given number of test(s). The supporting information upon which this study was performed came from diverse sources and thus it was necessary to build several intermediate databases in order to understand, validate, and manipulate data. These intermediate databases (validated historical account of schedule, test activity, and cost) by themselves are of great value and utility. For example, for the Project Profile, we were able to merged schedule, cost, and test activity. This kind of historical account conveys important information about sequence of events, lead time, and opportunities for improvement in future propulsion test projects. The Product Requirement Document (PRD) file is a collection of data extracted from each project PRD (technical characteristics, test requirements, and projection of cost, schedule, and test activity). This information could help expedite the development of future PRD (or equivalent document) on similar projects, and could also, when compared to the actual results, help improve projections around cost and schedule. Also, this file can be sorted by the parameter of interest to perform a visual review of potential common themes or trends. The process of searching, collecting, and validating propulsion test data encountered a lot of difficulties which then led to a set of recommendations for improvement in order to facilitate future data gathering and analysis.

Ramirez-Pagan, Carmen P.↗

NASA NTRS2013

Affordable Development and Qualification Strategy for Nuclear Thermal Propulsion

Nuclear Thermal Propulsion (NTP) is a concept which uses a nuclear reactor to heat a propellant to high temperatures without combustion and can achieve significantly greater specific impulse than chemical engines. NTP has been considered many times for human and cargo missions beyond low earth orbit. A lot of development and technical maturation of NTP components took place during the Rover/NERVA program of the 60's and early 70's. Other NTP programs and studies followed attempting to further mature the NTP concept and identify a champion customer willing to devote the funds and support the development schedule to a demonstration mission. Budgetary constraints require the use of an affordable development and qualification strategy that takes into account all the previous work performed on NTP to construct an existing database, and include lessons learned and past guidelines followed. Current guidelines and standards NASA uses for human rating chemical rocket engines is referenced. The long lead items for NTP development involve the fuel elements of the reactor and ground testing the engine system, subsystem, and components. Other considerations which greatly impact the development plans includes the National Space Policy, National Environmental Policy Act, Presidential Directive/National Security Council Memorandum #25 (Scientific or Technological Experiments with Possible Large-Scale Adverse Environmental Effects and Launch of Nuclear Systems into Space), and Safeguards and Security. Ground testing will utilize non-nuclear test capabilities to help down select components and subsystems before testing in a nuclear environment to save time and cost. Existing test facilities with minor modifications will be considered to the maximum extent practical. New facilities will be designed to meet minimum requirements. Engine and test facility requirements are based on the driving mission requirements with added factors of safety for better assurance and reliability. Emphasis will be placed on small engines, since the smaller the NTP engine, the easier it is to transport, assemble/disassemble, and filter the exhaust during tests. A new ground test concept using underground bore holes (modeled after the underground nuclear test program) to filter the NTP engine exhaust is being considered. The NTP engine system design, development, test, and evaluation plan includes many engine components and subsystems, which are very similar to those used in chemical engines, and can be developed in conjunction with them Other less mature NTP engine components and subsystems (e.g., reactor) will be thoroughly analyzed and tested to acceptable levels recommended by the referenced standards and guidelines. The affordable development strategy also considers a prototype flight test, as a final step in the development process. Preliminary development schedule estimates show that an aggressive development schedule (without much margin) will be required to be flight ready for a 2033 human mission to Mars.

Gerrish, Harold P., Jr.↗

NASA NTRS2013

Affordable Development and Qualification Strategy for Nuclear Thermal Propulsion

Nuclear Thermal Propulsion (NTP) is a concept which uses a nuclear reactor to heat a propellant to high temperatures without combustion and can achieve significantly greater specific impulse than chemical engines. NTP has been considered many times for human and cargo missions beyond low earth orbit. A lot of development and technical maturation of NTP components took place during the Rover/NERVA program of the 60's and early 70's. Other NTP programs and studies followed attempting to further mature the NTP concept and identify a champion customer willing to devote the funds and support the development schedule to a demonstration mission. Budgetary constraints require the use of an affordable development and qualification strategy that takes into account all the previous work performed on NTP to construct an existing database, and include lessons learned and past guidelines followed. Current guidelines and standards NASA uses for human rating chemical rocket engines is referenced. The long lead items for NTP development involve the fuel elements of the reactor and ground testing the engine system, subsystem, and components. Other considerations which greatly impact the development plans includes the National Space Policy, National Environmental Policy Act, Presidential Directive/National Security Council Memorandum #25 (Scientific or Technological Experiments with Possible Large-Scale Adverse Environmental Effects and Launch of Nuclear Systems into Space), and Safeguards and Security. Ground testing will utilize non-nuclear test capabilities to help down select components and subsystems before testing in a nuclear environment to save time and cost. Existing test facilities with minor modifications will be considered to the maximum extent practical. New facilities will be designed to meet minimum requirements. Engine and test facility requirements are based on the driving mission requirements with added factors of safety for better assurance and reliability. Emphasis will be placed on small engines, since the smaller the NTP engine, the easier it is to transport, assemble/disassemble, and filter the exhaust during tests. A new ground test concept using underground bore holes (modeled after the underground nuclear test program) to filter the NTP engine exhaust is being considered. The NTP engine system design, development, test, and evaluation plan includes many engine components and subsystems, which are very similar to those used in chemical engines, and can be developed in conjunction with them Other less mature NTP engine components and subsystems (e.g., reactor) will be thoroughly analyzed and tested to acceptable levels recommended by the referenced standards and guidelines. The affordable development strategy also considers a prototype flight test, as a final step in the development process. Preliminary development schedule estimates show that an aggressive development schedule (without much margin) will be required to be flight ready for a 2033 human mission to Mars.

Gerrish, Harold P., Jr.↗