Search NASA⌕ Search

SEARCH · Search NASA

Results for “knowledge-based”

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.

519 records · Page 29

Market Survey 2020: Commercial Clinical Decision Support Systems and Wellness Tools

For long-duration, deep space exploration missions, current methods for managing and supporting crew health and medical conditions will be unsuitable. Communication and data transmission lags will necessitate the use of a sophisticated clinical decision support system (CDSS) that will tailor diagnosis and treatment guidance that is context-sensitive for anticipated astronaut health, wellness, and medical conditions. A variety of clinical decision support (CDS) and wellness tools (WT) are currently available in the commercial market and a broad-brush survey of this market can provide an initial impression of the current state of the art which, in turn, can inform the roadmap of NASA deep space CDSS development and associated requirements. Such a survey was undertaken during the first six months of 2020 using directed convenience sampling to obtain information provided by vendors on their websites; both commercially available CDS and WT (such as those used to track and monitor nutrition, exercise, and sleep) were included. Areas assessed were item type (e.g., software/application, device); primary purpose of the item (e.g., diagnostic support, nutrition tracking); additional purposes (if any); reported features, capabilities, and functionality; setting of use (e.g., inpatient, outpatient); intended user (e.g., clinician, patient); location and sources of data/information used or produced by the item; integration with patient electronic health record (EHR); compliance with interoperability ontologies and standards (e.g., Health Level 7 [HL7], Systematized Nomenclature of Medicine – Clinical Terminology [SNOMED-CT]); and whether the item is knowledge-based (derived from research findings) or non-knowledge-based (derived through artificial intelligence, machine learning, advanced probability and statistics), among others. Ninety-seven (97) vendor websites describing 196 CDS and 73 WT (269 total) were reviewed and coded. The primary purpose of the majority of CDS reviewed is diagnosis or diagnosis/treatment/drug decision support—targeted for clinician use— and the primary purpose of the majority of WT reviewed is the monitoring of different health metrics, most often through the use of a biosensor device (e.g., blood pressure)—targeted for patient use. Very few CDS or WT appear to comply with major international interoperability standards or can be integrated with a patient’s EHR data. None consider contextual factors, such as conditions of the physical environment (e.g., CO2 levels). The majority of CDS and WT reviewed are non-knowledge, cloud- or web-based applications or software. Forty-three (43) major findings were identified and the implications those findings have for NASA will be discussed. Example major findings include: CDS-WT capabilities range from diagnosis to treatment applications, CDS-WT may be wearable or non-wearable and are technologically advanced and only a few CDS-WT tools referenced compliance to ensure interoperability, among other findings. Recommendations will also be offered that will help to address ExMC Gap, Medical-701: Enhance medical capabilities within an exploration medical system.

market survey↗

Operations Automation Using the Link Monitor and Control Operator Assistant

The Link Monitor & Control Operator Assistant (LMC OA) is a knowledge-based prototype system which uses Artificial Intelligence (AI) techniques to provide semi-automated monitor and control functions to support operations of the Deep Space Network (DSN) 70-Meter antenna at the Goldstone Deep Space Communications Camplex (DSCC).

Goldstone↗

Design Exploration of a Transonic Cruise Slotted Airfoil

A knowledge-based aerodynamic design method, CDISC, has been leveraged for the computational design exploration of the cruise slotted airfoil as a drag-saving technology for single aisle, transonic transport aircraft. Aerodynamic predictions were generated using the NASA USM3D Reynolds-averaged Navier-Stokes flow solver, and laminar flow assessments were conducted using the NASA BLSTA3D boundary layer profile solver paired with the LASTRAC stability analysis and transition prediction software. The CDISC design method was used to parametrically vary several slotted-airfoil design variables to understand their impact on aerodynamic performance. In addition to establishing best practices for slotted airfoil design, it was observed that the historically noted skin-friction penalty for cruise slotted airfoils was attributed to the low-Reynolds-number boundary layer of the flap. At cruise, this skin-friction penalty negated any potential decrease in pressure drag enabled by the cruise slotted airfoil architecture. This observation led to the development of an Aft-Laminar Multi-element Airfoil concept that uses airfoil shaping to promote natural laminar flow on the flap. At cruise conditions, the concept is predicted to offer a 2.7% reduction in sectional drag relative to a fully turbulent supercritical airfoil. Off-design analyses showed that laminar flow could be maintained with near-cruise variations in angle of attack and Mach number, resulting in sustained aerodynamic efficiency improvements and a delay in the drag rise Mach number. A low-speed, high-lift analysis at takeoff conditions predicted a maximum lift coefficient of 2.4 could be achieved by use of a variable-camber leading edge on the main element and simple deflection of the flap. These computationally-predicted benefits have motivated future research toward an aft-laminar cruise slotted wing design as an incremental step toward the application of natural laminar flow technology on transonic commercial transports.

Brett R Hiller↗

New developments in space radiation research at NASA: Annotating data using a novel radiation biology ontology

Like many interdisciplinary sciences, data producers and consumers in the field of radiation biology often use a wide variety of terminology to describe their experiments and data. Furthermore, space systems and technologies are rapidly evolving, and a shared understanding and common terminology for these is also lacking. The efficiency of research organizations can be enhanced by standardizing metadata through the use of knowledge resources like ontologies. Employing a sophisticated model such as a formal ontology to standardize metadata enables automated data acquisition processes and supports more complete, accurate meta-analysis through more efficient and complete data discovery and retrieval, particularly when using multiple data sources. Thus, we developed the Radiation Biology Ontology (RBO) in order to improved radiation biology metadata uniformity and transparency. We used open-source software (the Ontology Development Kit, Protégé and WebProtégé) and worked within the OBO Foundry framework, which includes a set of ontology development principles and practices for ontology consistency, uniformity, and accountability. The RBO has now been incorporated into two radiation research data repositories, NASA’s GeneLab omics database (https://genelab.nasa.gov), and the European Commission STORE database (https://www.storedb.org/). Continuous build integration tools allowed our international RBO collaboration to be more efficient and focus its efforts on semantic model design. Currently, the RBO contains over 300 annotated classes and individuals specific to the study of radiation on biological systems, as well as imports of many additional classes from other OBO Foundry ontologies that relate to and/or provide context for these RBO entities. We publish the RBO through the OBO Foundry, so that it is available for browsing, download, and querying through NCBI Bioportal web site and application programming interface. The NASA Ames Life Science Data Archive (ALSDA) is also in the process of adopting use of the RBO, taking NASA one step closer to a knowledge-based system for space biology data. It is our hope that the global communities of radiation research Investigators, data curators and data analysts can similarly leverage the RBO and will contribute to its further development.

radiation↗

Fault Detection and Diagnosis in Spacecraft Electrical Power Systems

The ability to accurately identify and isolate failures in the electrical power system (EPS) is critical to ensure the reliability of spacecraft. This paper proposes a novel solution to the problem of fault detection and diagnosis in direct current (DC) electric power systems for spacecraft. Autonomous operation becomes essential during deep space missions that lack the ability to monitor and control the spacecraft from ground locations. The current state of EPS fault supervision is insufficient to guarantee highly reliable operation. To solve this issue, a combination of model-based and knowledge-based techniques are used in a hierarchical framework to improve the diagnostic performance of the system. Noise, disturbances, and modeling errors are considered in the design of the fault detection system. Practical considerations related to spacecraft flight hardware and software are accounted for in the system design for flight applications. To assess the functionality of the design, a wide array of failures are simulated in a series of experiments. The experiments showed that the technique improved the capability of the autonomous system by increasing the number of fault types diagnosed. The significance of this study is to provide a framework capable of advanced diagnostics of an EPS with little to no interaction from human operators.

Autonomous Power Systems↗

Increasing the Uptake of Ecological Model Results in Policy Decisions to Improve Biodiversity Outcomes

Models help decision-makers anticipate the consequences of policies for ecosystems and people; for instance, improving our ability to represent interactions between human activities and ecological systems is essential to identify pathways to meet the 2030 Sustainable Development Goals. However, use of modeling outputs in decision-making remains uncommon. We share insights from a multidisciplinary National Socio-Environmental Synthesis Center working group on technical, communication, and process-related factors that facilitate or hamper uptake of model results. We emphasize that it is not simply technical model improvements, but active and iterative stakeholder involvement that can lead to more impactful outcomes. In particular, trust- and relationship-building with decision-makers are key for knowledge-based decision making. In this respect, nurturing knowledge exchange on the interpersonal (e.g., through participatory processes), and institutional level (e.g., through science-policy interfaces across scales), represent promising approaches. To this end, we offer a generalized approach for linking modeling and decision-making.

Biodiversity-ecosystem function relationships↗

Benefits of Ka-band GaN MMIC High Power Amplifiers With Wide Bandwidth and High Spectral/Power Added Efficiencies for Cognitive Radio Platforms

A cognitive radio on a future NASA near-Earth spacecraft will be capable of sensing its environment and dynamically adapting its operating parameters to provide the desired SATCOM service to the mission. A key component that can enable this type of operation is a high-power amplifier (HPA) that resides on the radio platform. In this paper, we present the RF performance characteristics of a Ka-band gallium nitride (GaN) monolithic microwave integrated circuit (MMIC) based HPA for cognitive radio platforms. These characteristics include the output power, gain, power added efficiency (PAE), RMS error vector magnitude (EVM), spectral efficiency, 3rd-order intermodulation distortion (IMD) products, spectrum, spectral regrowth, noise figure (NF), and phase noise. The data presented indicates that the HPA meets NTIA, military, and commercial spectral mask requirements. In addition, we discuss the benefits offered by the above performance characteristics toward the design and implementation of a cognitive radio platform. Furthermore, as examples, we discuss three potential use cases that apply artificial intelligence (AI) and machine learning (ML) techniques and exploit the performance characteristics discussed above to provide a knowledge-based cognitive radio platform design for SATCOM. Thus, cognitive radios with performance flexibility can enable roaming and provide seamless interoperability autonomously in the future between NASA, commercial, and other space networks owned by U.S. government agencies.

Gallium nitride↗

Benefits of Ka-band GaN MMIC High Power Amplifiers With Wide Bandwidth and High Spectral/Power Added Efficiencies for Cognitive Radio Platforms

A cognitive radio on a future NASA near-Earth spacecraft will be capable of sensing its environment and dynamically adapting its operating parameters to provide the desired SATCOM service to the mission. A key component that can enable this type of operation is a high-power amplifier (HPA) that resides on the radio platform. In this report, we present the RF performance characteristics of a Ka-band gallium nitride (GaN) monolithic microwave integrated circuit (MMIC) based HPA for cognitive radio platforms. These characteristics include the output power, gain, power added efficiency (PAE), RMS error vector magnitude (EVM), spectral efficiency, 3rdorder intermodulation distortion (IMD) products, spectrum, spectral regrowth, noise figure (NF), phase noise, and group delay. The data presented indicates that the HPA meets NTIA, military, and commercial spectral mask requirements. In addition, we discuss the benefits offered by the above performance characteristics toward the design and implementation of a cognitive radio platform. Furthermore, as examples, we discuss three potential use cases that apply artificial intelligence (AI) and machine learning (ML) techniques and exploit the performance characteristics discussed above to provide a knowledge-based cognitive radio platform design for SATCOM. Thus, cognitive radios with performance flexibility can enable roaming and provide seamless interoperability autonomously in the future between NASA, commercial, and other space networks owned by U.S. government agencies.

Gallium nitride↗

Transonic Cruise Slotted Wing Design for Commercial Transport Aircraft using CDISC

A knowledge-based aerodynamic design method, CDISC, has been extended to enable the computational design of transonic cruise slotted wings for commercial transport aircraft. The cruise slotted wing is a multielement wing concept with a forward main element and an aft flap element, separated to form an intermediate slot. This slot favorably redirects airflow from the main element lower surface toward the low-momentum, upper-surface boundary layer of the flap. Relative to the supercritical wing, the cruise slotted wing enables greater aft loading that helps to reduce shock strength and transonic pressure drag. The cruise slotted wing may be considered a passive drag reduction technology with potential fuel-burn savings and increased vehicle range for next-generation aircraft. The current paper seeks to quantify the drag-saving benefits of cruise slotted wing technology in application to single-aisle commercial transport aircraft. A series of multielement design constraints were developed within CDISC for the design of a partial-span, cruise slotted wing for a Mach-0.8 variant of the Common Research Model. To mitigate the skin-friction drag penalty associated with cruise slotted wings, the design features a flap with natural laminar flow over approximately 75% of the flap surface area. Cruise drag estimates from the NASA USM3D-ME flow solver between a supercritical wing and the partial-span, cruise slotted wing design were within one drag count. Near-cruise, off-design analyses showed limited laminar-flow sensitivity to angle of attack and a more gradual drag rise compared to a supercritical wing. Based on this observed benefit, future work is motivated to design a cruise slotted wing with laminar flow on both wing elements to achieve a significant reduction in cruise drag while delaying drag divergence.

CDISC↗

Transonic Cruise Slotted Wing Design for Commercial Transport Aircraft using CDISC

A knowledge-based aerodynamic design method, CDISC, has been extended to enable the computational design of transonic cruise slotted wings for commercial transport aircraft. The cruise slotted wing is a multielement wing concept with a forward main element and an aft flap element, separated to form an intermediate slot. This slot favorably redirects airflow from the main element lower surface toward the low-momentum, upper-surface boundary layer of the flap. Relative to the supercritical wing, the cruise slotted wing enables greater aft loading that helps to reduce shock strength and transonic pressure drag. The cruise slotted wing may be considered a passive drag-reduction technology with potential fuel burn savings and increased vehicle range for next-generation aircraft. The current paper seeks to quantify the drag-saving benefits of cruise slotted wing technology in application to single-aisle commercial transport aircraft. A series of multielement design constraints were developed within CDISC for the design of a partial-span, cruise slotted wing for a Mach-0.8 variant of the Common Research Model. To mitigate the skin-friction drag penalty associated with cruise slotted wings, the design features a flap with natural laminar flow over approximately 75% of the flap surface area. Cruise drag estimates from the NASA USM3D flow solver between a supercritical wing and the partial-span, cruise slotted wing design were within one drag count. Near-cruise, off-design analyses showed limited laminar flow sensitivity to angle of attack and a more gradual drag rise compared to a supercritical wing. Based on this demonstrated benefit, future work is motivated to design a cruise slotted wing with natural laminar flow on both wing elements to achieve a significant reduction in cruise drag while providing delayed drag divergence.

CDISC↗

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↗

Cruise Slotted Wing Design with Natural Laminar Flow for Transonic Commercial Transport Aircraft

The present computational study investigates the aerodynamic design and analysis of cruise slotted wings with natural laminar flow for transonic transport aircraft. The cruise slotted wing is a multielement wing concept that features an intermediate slot to achieve greater aft loading relative to supercritical wings for the potential benefit of reduced shock strength and pressure drag. Transonic near-cruise, off-design assessments have also shown improved drag rise characteristics due to the ability of the slot to mitigate boundary layer separation on the aft flap component. However, due to the decreased Reynolds number of the flap, the cruise slotted wing has historically incurred a skin-friction drag penalty relative to a conventional supercritical wing. To offset this penalty, a cruise slotted wing with the forward main element and aft flap element shaped to achieve natural laminar flow is desired. Toward this effort, a knowledge-based aerodynamic design method, CDISC, has been leveraged to design a partial-span cruise slotted wing with natural laminar flow for a Mach-0.8 variant of the Common Research Model. Drag comparisons will be provided at cruise and near-cruise, off-design conditions relative to both fully turbulent and natural laminar flow conventional wing designs. It is anticipated that pairing natural laminar flow technology with the cruise slotted wing architecture will allow for cruise drag performance similar to conventional laminar flow wings with improved drag rise characteristics and more limited laminar-flow sensitivity at off-design conditions. Preliminary results for a cruise slotted wing with laminar flow on the outboard wing section only have shown a 10-ct cruise drag reduction relative to a conventional supercritical wing, but a 8-ct penalty relative to the conventional NLF wing. The final paper will include results for a cruise slotted wing design with laminar flow on both the inboard and outboard wing sections.

CFD↗

Cruise Slotted Wing Design with Natural Laminar Flow for Transonic Commercial Transport Aircraft

The present computational study investigates the aerodynamic design and analysis of cruise slotted wings with natural laminar flow for transonic transport aircraft. The cruise slotted wing is a multielement wing concept that features an intermediate slot to achieve greater aft loading relative to supercritical wings for the potential benefit of reduced shock strength and pressure drag. Transonic near-cruise, off-design assessments have also shown improved drag rise characteristics due to the ability of the slot to mitigate boundary layer separation on the aft flap component. However, due to the decreased Reynolds number of the flap, the cruise slotted wing has historically incurred a skin-friction drag penalty relative to a conventional supercritical wing. To offset this penalty, a cruise slotted wing with the forward main element and aft flap element shaped to achieve natural laminar flow is desired. Toward this effort, a knowledge-based aerodynamic design method, CDISC, has been leveraged to design a partial-span cruise slotted wing with natural laminar flow for a Mach-0.8 variant of the Common Research Model. Drag comparisons will be provided at cruise and near-cruise, off-design conditions relative to both fully turbulent and natural laminar flow conventional wing designs. It is anticipated that pairing natural laminar flow technology with the cruise slotted wing architecture will allow for cruise drag performance similar to conventional laminar flow wings with improved drag rise characteristics and more limited laminar-flow sensitivity at off-design conditions. Preliminary results for a cruise slotted wing with laminar flow on the outboard wing section only have shown a 10-ct cruise drag reduction relative to a conventional supercritical wing, but a 8-ct penalty relative to the conventional NLF wing. The final paper will include results for a cruise slotted wing design with laminar flow on both the inboard and outboard wing sections.

Natural Laminar Flow↗

Irrelevance Reasoning in Knowledge Based Systems

This dissertation considers the problem of reasoning about irrelevance of knowledge in a principled and efficient manner. Specifically, it is concerned with two key problems: (1) developing algorithms for automatically deciding what parts of a knowledge base are irrelevant to a query and (2) the utility of relevance reasoning. The dissertation describes a novel tool, the query-tree, for reasoning about irrelevance. Based on the query-tree, we develop several algorithms for deciding what formulas are irrelevant to a query. Our general framework sheds new light on the problem of detecting independence of queries from updates. We present new results that significantly extend previous work in this area. The framework also provides a setting in which to investigate the connection between the notion of irrelevance and the creation of abstractions. We propose a new approach to research on reasoning with abstractions, in which we investigate the properties of an abstraction by considering the irrelevance claims on which it is based. We demonstrate the potential of the approach for the cases of abstraction of predicates and projection of predicate arguments. Finally, we describe an application of relevance reasoning to the domain of modeling physical devices.

INFERENCE↗