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At least 19 records

DINGO: Digital assistant to grid operators for resilience management of power distribution system

With increasing adverse weather events and disasters, enabling resiliency of the power distribution system (PDS) is becoming increasingly important. Here in this work, resiliency is defined as the systems ability to keep supplying critical loads even with multiple contingencies. Resiliency may depend on: (a) advanced tools to assist operators in situational awareness and decision making with the increasing volume of data generated by the PDS, (b) visualization and ease of interaction with system resources and information, especially during extreme events and resulting human operator stress, and (c) flexible resources and autonomous control. Operators and support engineers need to interact with the system for key information and take action under stress, given the requirement for decisions in a short time. Integrated technological solutions are prevailing steps to support the most appropriate decision during critical times to serve essential loads. In order to meet the required goals, a Real-time Resiliency Monitoring and Operational Decision Support (RT-RMOD) tool have been developed. It supports various functionalities, including real-time monitoring, resilience assessment, and proactive decision support. However, this work makes advanced feature additions to the tool by developing data-enabled resilience management algorithms for (i) outage detection and localization, (ii) Resiliency-metric driven restoration and reconfiguration, and (iii) NLP based digital assistant for operators called DINGO (DIgital assistaNt to Grid Operators) to interact with Advanced Distribution Management System (ADMS) and RT-RMOD. The developed algorithm was validated for multiple cases of weather events using a real-world, off-grid microgrid system modeled in a real-time simulator, sensor data, and software tools.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Digital Assistance for System Requirement Discovery and Analysis using Machine Learning Natural Language Processing Algorithm

NASA’s Air Traffic Management-Exploration (ATM-X) Urban Air Mobility (UAM) Airspace Subproject is conducting research that evolves UAM airspace towards a highly automated and operationally flexible system of the future (see https://www.nasa.gov/uam-overview/ for more information). The complexity of UAM airspace, and its evolution through a series of transformative epochs, requires a planning tool to effectively organize, integrate, and communicate the research that will guide the evolution of UAM operations in the National Airspace System (NAS). The planning tool, called the UAM airspace research roadmap (or just roadmap), is being developed as a new system engineering methodology leveraging model based system engineering (MBSE) and machine learning natural language processing (ML NLP, or just NLP) capabilities. This presentation gives an overview of the NLP application within this system engineering methodology and will describe how it is being used to meet the ATM-X UAM Airspace Subproject’s overarching research goals.

ATM↗

Doppler detection of decompression bubbles with computer assisted digitization of ultrasonic signals

The use of an inexpensive, commercially available audio digitizer in conjunction with a PC to digitize Doppler bubble signals for visual and electronic evaluation is reported. This device can be operated simultaneously with Doppler audio monitoring. Precordial and arterial Doppler recordings of gas bubbles were obtained from anesthetized dogs after intravascular infusion or following decompression. Additional evaluations were conducted on Doppler bubble recordings obtained from human decompression studies. The device can be used in real-time or for later signal analysis. Accompanying menu-driven software provides for numerous signal modification options and visual displays. This device can provide a simultaneous visual display of Doppler signals normally available only for audio evaluation.

Butler, B. D.↗

GraphAide: Advanced Graph-Assisted Query and Reasoning System

Curating knowledge from multiple siloed sources that contain both structured and unstructured data is a major challenge in many real-world applications. Pattern matching and querying represent fundamental tasks in modern data analytics that leverage this curated knowledge. The development of such applications necessitates overcoming several research challenges, including data extraction, named entity recognition, data modeling, and designing query interfaces. Moreover, the explainability of these functionalities is critical for their broader adoption. The emergence of Large Language Models (LLMs) has accelerated the development lifecycle of new capabilities. Nonetheless, there is an ongoing need for domain-specific tools tailored to user activities. The creation of digital assistants has gained considerable traction in recent years, with LLMs offering a promising avenue to develop such assistants utilizing domain-specific knowledge and assumptions. In this context, we introduce an advanced query and reasoning system, GraphAide, which constructs a knowledge graph (KG) from diverse sources and allows to query and reason over the resulting KG. GraphAide harnesses both the KG and LLMs to rapidly develop domain-specific digital assistants. It integrates design patterns from retrieval augmented generation (RAG) and the semantic web to create an agentic LLM application. GraphAide underscores the potential for streamlined and efficient development of specialized digital assistants, thereby enhancing their applicability across various domains.

Purohit, Sumit [BATTELLE (PACIFIC NW LAB)] (ORCID:↗

Inspecta Annual Technical Report

Sandia National Laboratories (SNL) is designing and developing an Artificial Intelligence (AI)-enabled smart digital assistant (SDA), Inspecta (International Nuclear Safeguards Personal Examination and Containment Tracking Assistant). The goal is to provide inspectors an in-field digital assistant that can perform tasks identified as tedious, challenging, or prone to human error. During 2021, we defined the requirements for Inspecta based on reviews of International Atomic Energy Agency (IAEA) publications and interviews with former IAEA inspectors. We then mapped the requirements to current commercial or open-source technical capabilities to provide a development path for an initial Inspecta prototype while highlighting potential research and development tasks. We selected a highimpact inspection task that could be performed by an early Inspecta prototype and are developing the initial architecture, including hardware platform. This paper describes the methodology for selecting an initial task scenario, the first set of Inspecta skills needed to assist with that task scenario and finally the design and development of Inspecta’s architecture and platform.

42 ENGINEERING↗

Technical Assistance for Digital Assurance: DistribuTECH Workshop

Idaho National Laboratory, the Department of Energy’s Grid Deployment Office, and other national laboratories are collaborating to ensure the U.S. energy infrastructure is reliable, resilient, and secure. This involves strategically leveraging digital technologies to modernize the grid, enhance its resilience against all hazards and disruptions, and fortify national energy security across a diverse energy portfolio. In this workshop you will learn about Idaho National Lab’s Technical Assistance programs, where organizations will be matched with a national laboratory subject matter expert to focus on their key topical area. The technical assistance offered through this track is designed to be responsive to a rapidly changing regulatory landscape and cutting-edge technologies that enhance grid reliability and efficiency. Users will be guided through a tailored analysis and mitigation program to determine their current security posture and given assistance in evaluating supply chain and protection choices against potential consequences.

Digital assurance↗

Portable Wireless LAN Device and Two-way Radio Threat Assessment for Aircraft Navigation Radios

Measurement processes, data and analysis are provided to address the concern for Wireless Local Area Network devices and two-way radios to cause electromagnetic interference to aircraft navigation radio systems. A radiated emission measurement process is developed and spurious radiated emissions from various devices are characterized using reverberation chambers. Spurious radiated emissions in aircraft radio frequency bands from several wireless network devices are compared with baseline emissions from standard computer laptops and personal digital assistants. In addition, spurious radiated emission data in aircraft radio frequency bands from seven pairs of two-way radios are provided, A description of the measurement process, device modes of operation and the measurement results are reported. Aircraft interference path loss measurements were conducted on four Boeing 747 and Boeing 737 aircraft for several aircraft radio systems. The measurement approach is described and the path loss results are compared with existing data from reference documents, standards, and NASA partnerships. In-band on-channel interference thresholds are compiled from an existing reference document. Using these data, a risk assessment is provided for interference from wireless network devices and two-way radios to aircraft systems, including Localizer, Glideslope, Very High Frequency Omnidirectional Range, Microwave Landing System and Global Positioning System. The report compares the interference risks associated with emissions from wireless network devices and two-way radios against standard laptops and personal digital assistants. Existing receiver interference threshold references are identified as to require more data for better interference risk assessments.

Nguyen, Truong X.↗

Inspecta Technical Report

Sandia National Laboratories (SNL) has developed Inspecta (International Nuclear Safeguards Personal Examination and Containment Tracking Assistant), an AI-powered smart digital assistant (SDA) equipped with robotic capabilities. This innovative tool aims to enhance the effectiveness, efficiency, and safety of international nuclear safeguards inspections. Inspecta is designed to assist inspectors on-site by supporting or automating tasks that are often mundane, hazardous, or prone to errors. In 2021, the development team established the specifications for Inspecta by thoroughly analyzing International Atomic Energy Agency (IAEA) documents and consulting with former IAEA inspectors and subject matter experts. This process involved aligning in-field inspection tasks with existing commercial and open-source technologies, thereby creating a roadmap for the initial prototype of Inspecta and identifying areas requiring further research and development. From 2022 to 2025, the focus shifted to integrating a critical inspection activity—the examination of seals—into an early version of Inspecta. This phase has involved the development of both software and hardware capabilities essential for this task. This report outlines the advancements in Inspecta’s functionalities, particularly those that support the seal examination process.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

Inspecta Technical Report

Sandia National Laboratories (SNL) is in the process of creating Inspecta (International Nuclear Safeguards Personal Examination and Containment Tracking Assistant), an Artificial Intelligence (AI)-powered smart digital assistant (SDA) with robotic capabilities, aimed at enhancing the effectiveness, efficiency, and safety of international nuclear safeguards inspections. This innovative tool is designed to assist inspectors on-site by supporting or automating tasks that are typically mundane, hazardous, or susceptible to errors. In 2021, the development team established the specifications for Inspecta by analyzing International Atomic Energy Agency (IAEA) documents and consulting with former IAEA inspectors and subject matter experts. This process involved aligning in-field inspection tasks with existing commercial or open-source technologies to outline a roadmap for the initial prototype of Inspecta, while also identifying areas needing further research and development. From 2022 – 2024, the focus has shifted to integrating a critical inspection activity, the examination of seals, into an early version of Inspecta. This has involved developing both the software and hardware capabilities necessary for this task. This report outlines the ongoing advancements in Inspecta's functionalities, specifically those supporting the seal examination process.

97 MATHEMATICS AND COMPUTING↗

Remote Arrhythmia Monitoring System Developed

Telemedicine is taking a step forward with the efforts of team members from the NASA Glenn Research Center, the MetroHealth campus of Case Western University, and the University of Akron. The Arrhythmia Monitoring System is a completed, working test bed developed at Glenn that collects real-time electrocardiogram (ECG) signals from a mobile or homebound patient, combines these signals with global positioning system (GPS) location data, and transmits them to a remote station for display and monitoring. Approximately 300,000 Americans die every year from sudden heart attacks, which are arrhythmia cases. However, not all patients identified at risk for arrhythmias can be monitored continuously because of technological and economical limitations. Such patients, who are at moderate risk of arrhythmias, would benefit from technology that would permit long-term continuous monitoring of electrical cardiac rhythms outside the hospital environment. Embedded Web Technology developed at Glenn to remotely command and collect data from embedded systems using Web technology is the catalyst for this new telemetry system (ref. 1). In the end-to-end system architecture, ECG signals are collected from a patient using an event recorder and are transmitted to a handheld personal digital assistant (PDA) using Bluetooth, a short-range wireless technology. The PDA concurrently tracks the patient's location via a connection to a GPS receiver. A long distance link is established via a standard Internet connection over a 2.5-generation Global System for Mobile Communications/General Packet Radio Service (GSM/GPRS)1 cellular, wireless infrastructure. Then, the digital signal is transmitted to a call center for monitoring by medical professionals.

York, David W.↗

Emerging materials intelligence ecosystems propelled by machine learning

We report that the age of cognitive computing and artificial intelligence (AI) is just dawning. Inspired by its successes and promises, several AI ecosystems are blossoming, many of them within the domain of materials science and engineering. These materials intelligence ecosystems are being shaped by several independent developments. Machine learning (ML) algorithms and extant materials data are utilized to create surrogate models of materials properties and performance predictions. Materials data repositories, which fuel such surrogate model development, are mushrooming. Automated data and knowledge capture from the literature (to populate data repositories) using natural language processing approaches is being explored. The design of materials that meet target property requirements and of synthesis steps to create target materials appear to be within reach, either by closed-loop active-learning strategies or by inverting the prediction pipeline using advanced generative algorithms. AI and ML concepts are also transforming the computational and physical laboratory infrastructural landscapes used to create materials data in the first place. Surrogate models that can outstrip physics-based simulations (on which they are trained) by several orders of magnitude in speed while preserving accuracy are being actively developed. Automation, autonomy and guided high-throughput techniques are imparting enormous efficiencies and eliminating redundancies in materials synthesis and characterization. The integration of the various parts of the burgeoning ML landscape may lead to materials-savvy digital assistants and to a human-machine partnership that could enable dramatic efficiencies, accelerated discoveries and increased productivity. Here, we review these emergent materials intelligence ecosystems and discuss the imminent challenges and opportunities. The materials research landscape is being transformed by the infusion of approaches based on machine learning. This Review discusses the emerging materials intelligence ecosystems and the potential of human-machine partnerships for fast and efficient virtual materials screening, development and discovery.

36 MATERIALS SCIENCE↗

Preliminary Design and Evaluation of Portable Electronic Flight Progress Strips

There has been growing interest in using electronic alternatives to the paper Flight Progress Strip (FPS) for air traffic control. However, most research has been centered on radar-based control environments, and has not considered the unique operational needs of the airport air traffic control tower. Based on an analysis of the human factors issues for control tower Decision Support Tool (DST) interfaces, a requirement has been identified for an interaction mechanism which replicates the advantages of the paper FPS (e.g., head-up operation, portability) but also enables input and output with DSTs. An approach has been developed which uses a Portable Electronic FPS that has attributes of both a paper strip and an electronic strip. The prototype flight strip system uses Personal Digital Assistants (PDAs) to replace individual paper strips in addition to a central management interface which is displayed on a desktop computer. Each PDA is connected to the management interface via a wireless local area network. The Portable Electronic FPSs replicate the core functionality of paper flight strips and have additional features which provide a heads-up interface to a DST. A departure DST is used as a motivating example. The central management interface is used for aircraft scheduling and sequencing and provides an overview of airport departure operations. This paper will present the design of the Portable Electronic FPS system as well as preliminary evaluation results.

Doble, Nathan A.↗

Portable Wireless Device Threat Assessment for Aircraft Navigation Radios

This paper addresses the concern for Wireless Local Area Network devices and two-way radios to cause electromagnetic interference to aircraft navigation radio systems. Spurious radiated emissions from various IEEE 802.11a, 802.11b, and Bluetooth devices are characterized using reverberation chambers. The results are compared with baseline emissions from standard laptop computer and personal digital assistants (PDAs) that are currently allowed for use on aircraft. The results indicate that the WLAN devices tested are not more of a threat to aircraft navigation radios than standard laptop computers and PDAs in most aircraft bands. In addition, spurious radiated emission data from seven pairs of two-way radios are provided. These two-way radios emit at much higher levels in the bands considered. A description of the measurement process, device modes of operation and the measurement results are reported.

Nguyen, Truong X.↗

Third Generation Wireless Phone Threat Assessment for Aircraft Communication and Navigation Radios

Radiated emissions in aircraft communication and navigation bands are measured from third generation (3G) wireless mobile phones. The two wireless technologies considered are the latest available to general consumers in the US. The measurements are conducted using reverberation chambers. The results are compared against baseline emissions from laptop computers and personal digital assistant devices that are currently allowed to operate on aircraft. Using existing interference path loss data and receivers interference threshold, a risk assessment is performed for several aircraft communication and navigation radio systems. In addition, cumulative interference effects of multiple similar devices are conservatively estimated or bounded. The effects are computed by summing the interference power from individual devices that is scaled according to the interference path loss at its location.

Nguyen, Truong X.↗

An XML Representation for Crew Procedures

NASA ensures safe operation of complex systems through the use of formally-documented procedures, which encode the operational knowledge of the system as derived from system experts. Crew members use procedure documentation on the ground for training purposes and on-board space shuttle and space station to guide their activities. Investigators at JSC are developing a new representation for procedures that is content-based (as opposed to display-based). Instead of specifying how a procedure should look on the printed page, the content-based representation will identify the components of a procedure and (more importantly) how the components are related (e.g., how the activities within a procedure are sequenced; what resources need to be available for each activity). This approach will allow different sets of rules to be created for displaying procedures on a computer screen, on a hand-held personal digital assistant (PDA), verbally, or on a printed page, and will also allow intelligent reasoning processes to automatically interpret and use procedure definitions. During his NASA fellowship, Dr. Simpson examined how various industries represent procedures (also called business processes or workflows), in areas such as manufacturing, accounting, shipping, or customer service. A useful method for designing and evaluating workflow representation languages is by determining their ability to encode various workflow patterns, which depict abstract relationships between the components of a procedure removed from the context of a specific procedure or industry. Investigators have used this type of analysis to evaluate how well-suited existing workflow representation languages are for various industries based on the workflow patterns that commonly arise across industry-specific procedures. Based on this type of analysis, it is already clear that existing workflow representations capture discrete flow of control (i.e., when one activity should start and stop based on when other activities start and stop), but do not capture the flow of data, materials, resources or priorities. Existing workflow representation languages are also limited to representing sequences of discrete activities, and cannot encode procedures involving continuous flow of information or materials between activities.

Simpson, Richard C.↗

Wireless Phone Threat Assessment for Aircraft Communication and Navigation Radios

Emissions in aircraft communication and navigation bands are measured for the latest generation of wireless phones. The two wireless technologies considered, GSM/GPRS and CDMA2000, are the latest available to general consumers in the U.S. A base-station simulator is used to control the phones. The measurements are conducted using reverberation chambers, and the results are compared against FCC and aircraft installed equipment emission limits. The results are also compared against baseline emissions from laptop computers and personal digital assistant devices that are currently allowed to operate on aircraft.

Nguyens, T. X.↗