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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.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

ChatGPT and Other Large Language Models for Cybersecurity of Smart Grid Applications

Cybersecurity breaches targeting electrical substations constitute a significant threat to the integrity of the power grid, necessitating comprehensive defense and mitigation strategies. Any anomaly in information and communication technology (ICT) should be detected for secure communications between devices in digital substations. This paper proposes large language models (LLMs), e.g., ChatGPT, for the cybersecurity of IEC 61850-based communications. Multi-cast messages such as generic object oriented system events (GOOSE) and sampled values (SV) are used for case studies. The proposed LLM-based cybersecurity framework includes, for the first time, data pre-processing of communication systems and human-in-the-loop (HITL) training (considering the cybersecurity guidelines recommended by humans). The results show a comparative analysis of detected anomaly data carried out based on the performance evaluation metrics for different LLMs. A hardware-in-the-loop (HIL) testbed is used to generate and extract a dataset of IEC 61850 communications.

ChatGPT↗
NASA NTRS2016

Design, Development, and Testing of a UAV Hardware-in-the-Loop Testbed for Aviation and Airspace Prognostics Research

The airspace is becoming more and more complicated, and will continue to do so in the future with the integration of Unmanned Aerial Vehicles (UAVs), autonomy, spacecraft, other forms of aviation technology into the airspace. The new technology and complexity increases the importance and difficulty of safety assurance. Additionally, testing new technologies on complex aviation systems & systems of systems can be very difficult, expensive, and sometimes unsafe in real life scenarios. Prognostic methodology provides an estimate of the health and risks of a component, vehicle, or airspace and knowledge of how that will change over time. That measure is especially useful in safety determination, mission planning, and maintenance scheduling. The developed testbed will be used to validate prediction algorithms for the real-time safety monitoring of the National Airspace System (NAS) and the prediction of unsafe events. The framework injects flight related anomalies related to ground systems, routing, airport congestion, etc. to test and verify algorithms for NAS safety. In our research work, we develop a live, distributed, hardware-in-the-loop testbed for aviation and airspace prognostics along with exploring further research possibilities to verify and validate future algorithms for NAS safety. The testbed integrates virtual aircraft using the X-Plane simulator and X-PlaneConnect toolbox, UAVs using onboard sensors and cellular communications, and hardware in the loop components. In addition, the testbed includes an additional research framework to support and simplify future research activities. It enables safe, accurate, and inexpensive experimentation and research into airspace and vehicle prognosis that would not have been possible otherwise. This paper describes the design, development, and testing of this system. Software reliability, safety and latency are some of the critical design considerations in development of the testbed. Integration of HITL elements in the development phases and veri cation/ validation are key elements to this report.

HITL↗
NASA NTRS2017

A Virtual Laboratory for Aviation and Airspace Prognostics Research

Integration of Unmanned Aerial Vehicles (UAVs), autonomy, spacecraft, and other aviation technologies, in the airspace is becoming more and more complicated, and will continue to do so in the future. Inclusion of new technology and complexity into the airspace increases the importance and difficulty of safety assurance. Additionally, testing new technologies on complex aviation systems and systems of systems can be challenging, expensive, and at times unsafe when implementing real life scenarios. The application of prognostics to aviation and airspace management may produce new tools and insight into these problems. Prognostic methodology provides an estimate of the health and risks of a component, vehicle, or airspace and knowledge of how that will change over time. That measure is especially useful in safety determination, mission planning, and maintenance scheduling. In our research, we develop a live, distributed, hardware- in-the-loop Prognostics Virtual Laboratory testbed for aviation and airspace prognostics. The developed testbed will be used to validate prediction algorithms for the real-time safety monitoring of the National Airspace System (NAS) and the prediction of unsafe events. In our earlier work1 we discussed the initial Prognostics Virtual Laboratory testbed development work and related results for milestones 1 & 2. This paper describes the design, development, and testing of the integrated tested which are part of milestone 3, along with our next steps for validation of this work. Through a framework consisting of software/hardware modules and associated interface clients, the distributed testbed enables safe, accurate, and inexpensive experimentation and research into airspace and vehicle prognosis that would not have been possible otherwise. The testbed modules can be used cohesively to construct complex and relevant airspace scenarios for research. Four modules are key to this research: the virtual aircraft module which uses the X-Plane simulator and X-PlaneConnect toolbox, the live aircraft module which connects fielded aircraft using onboard cellular communications devices, the hardware in the loop (HITL) module which connects laboratory based bench-top hardware testbeds and the research module which contains diagnostics and prognostics tools for analysis of live air traffic situations and vehicle health conditions. The testbed also features other modules for data recording and playback, information visualization, and air traffic generation. Software reliability, safety, and latency are some of the critical design considerations in development of the testbed.

LVC-DE↗
NASA NTRSDate not supplied

Desert Research and Technology Studies (D-RATS) 2022 Quicklook Report

This report summarizes the Desert Research and Technology Studies (D-RATS) 2022 analog tests. BACKGROUND - Artemis Challenges – NASA’s concept of operations (ConOps) for the Artemis mission architecture brings new challenges for human exploration of the lunar surface, including: (1) Low-angle, natural lighting at lunar poles; and (2) Exploration sites that challenge communication with Earth. - International Partner Involvement – NASA is working with the Japan Aerospace Exploration Agency (JAXA) to scope mission & functional requirements for an Artemis Pressurized Rover (PR), which JAXA may provide. - Charter – HQ Exploration Systems Development Mission Directorate (ESDMD) Moon to Mars Architecture Development Office (M2MADO) Strategy and Architectures (SA) chartered the Human-in-the-Loop (HITL) test team to investigate Artemis architectural questions related to pressurized rover ConOps. - Rationale – to inform the NASA/JAXA pressurized rover study-agreement. PLAN - Objectives – Analog tests conducted in October 2022 by the D-RATS team addressed three high-level objectives: 1. Investigate pressurized rover (PR) ConOps and capabilities for Artemis exploration 2. Integrate with JAXA engineers & astronauts and incorporate JAXA PR design elements into testing. 3. Re-establish analog field-testing skills & capabilities with rovers to investigate Artemis architecture ConOps. - Secondary Objectives – Work with other groups to leverage D-RATS field test for additional objectives. 4. Work with the Public Affairs Office (PAO) to perform D-RATS public outreach activities. 5. Coordinate with the Human Physiology Performance Protection & Operations (H-3PO) team to facilitate in-field evaluation of human health and performance (HHP) objectives. 6. Share D-RATS field-site and assets with Lunar LTE Studies (Lunar LiTES) team, to aid their study of the use of 4G/LTE communication protocols and devices for astronauts and robotic nodes on the lunar surface. - Team – Fully integrated test team comprised of members from 5 NASA centers, JAXA, and the United States Geological Survey (USGS) - Location – Black Point Lava Flow, ~40 miles north of Flagstaff, AZ HIGH-LEVEL OBJECTIVES ACCOMPLISHED - Investigated Pressurized Rover ConOps & Capabilities for Artemis Exploration (Objective 1) - Completed testing with 4 crew pairs, each spending 3 days and 2 nights in the rover conducting Artemis PR dayin-the-life activities (2 JAXA astronauts, 2 JAXA engineers, 1 NASA astronaut, 3 NASA engineers). - Collected detailed objective & subjective data supporting 10 strategic questions related to Artemis PR operations. - Field geologists present in field observed rover operations & EVAs. - Science team in Houston MCC communicated directly with crew. - Demonstrated crew-led and MCC-led PR teleoperation use cases during EVAs. - Integrated with JAXA Engineers & Astronauts and Incorporated JAXA PR Design Elements into Testing (Objective 2) - NASA & JAXA engineers, flight controllers, scientists, roboticists, and astronauts directly participated in and/or observed testing both in field and in MCC-Houston. - Incorporated JAXA PR design elements into both integrated and standalone testing at JSC and in the field. - Re-established Analog Field-Testing Skills & Capabilities with Rovers to Investigate Artemis Architecture ConOps (Objective 3) - Multiple teams successfully worked to establish and manage field-test base camp, monitor and maintain the rover, and plan and execute 2 weeks of consecutive field-testing with little to no breaks between crews. TEST OUTCOMES - Results will inform Artemis architecture ConOps & capabilities related to pressurized rover operations (see sections 2 for more details) - Summary and team detailed reports will be posted on the D-RATS 2022 wiki

Analog↗
NASA NTRS2023

Desert Research and Technology Studies (D-RATS) 2022 Test Report

The primary purpose of the 2022 Desert Research and Technology Studies (D-RATS 22) analog mission field test was to provide data and recommendations regarding how pressurized rover (PR) design, cabin configuration, driving modes, timeline constraints, and mission operations can be acceptably implemented to support future Artemis missions that include a PR. The goal of these evaluations was to provide first order feedback and data on design concepts currently being traded as options for future pressurized rover flight prototypes. The Japan Aerospace Exploration Agency (JAXA) may provide a PR for future Artemis missions. One of the primary objectives of D-RATS 2022 was to share with the JAXA PR team the processes and protocols by which NASA has learned to successfully evaluate rover concepts through integrated HITL evaluations over the past 20+ years, so that JAXA could apply any applicable lessons learned to their PR design, development, testing, and evaluation.

analog↗
DOE OSTI2025

Speeding-up fuzzing through directional seeds

Abstract Fuzzing is an automated process for discovering inputs in a program that may trigger unexpected behavior. Today, fuzzing has become a standard practice for the discovery of bugs and security vulnerabilities. However, the main issue with such practices is that the exploration of the input space of programs can often be prohibitively expensive. Therefore, several alternative fuzzing strategies have been introduced during the last few years. Some fuzzing techniques rely on human expertise to provide a plausible set of initial input examples, namely, seeds. However, the process of handcrafting seeds for fuzzing purposes often becomes strenuous for humans as it requires a deeper understanding of the Program-Under-Test (PUT). Also, the use of known inputs to programs often does not trigger vulnerable program behavior or may not reach potentially vulnerable code locations. To address those issues, we propose a seed generation framework that enables Human-In-The-Loop (HITL) directed fuzzing where the human assumes a more active role in the creation of seeds that can penetrate and assess desired locations of the PUT. Our proposed framework uses Symbolic Execution (SE) to generate seeds that exercise paths to target program locations. Moreover, our framework enables the visualization of the explored execution paths in the binary of the PUT for the generated seeds. We evaluated our approach on a set of 12 carefully designed C programs with diverse characteristics that mimic real-world programs. The experimental results show the effectiveness of the proposed approach in improving the performance of standard fuzzing tools such as the American Fuzzy Lop ("Image missing" <#comment/> ). Specifically, our solution can generate seeds that substantially enhance the performance of the fuzzer, achieving speedups ranging from $$1.46\times $$ 1.46 × to $$68.53\times $$ 68.53 × for branch conditions, $$1.39\times $$ 1.39 × to $$254.62\times $$ 254.62 × for branch depths, $$14,879.59\times $$ 14 , 879.59 × to $$30,295.88\times $$ 30 , 295.88 × for branch widths over traditional seeds. Additionally, the speedup increases with the number of target function ranging from $$12,260\times $$ 12 , 260 × to $$22,856.07\times $$ 22 , 856.07 × over traditional seeds while only requiring less than 15 seconds on average for the seed generation step.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

ICAT: The Interactive Corpus Analysis Tool

The Interactive Corpus Analysis Tool (ICAT) is a Python library for creating dashboards to explore textual datasets and build simple binary classification models to help filter through them and focus on entries of interest. This tool uses a form of interactive machine learning (IML), a paradigm of “machine teaching” (Simard et al., 2017) that sits at the intersection of the fields of human computer interaction (HCI), visual analytics, and machine learning. The intent of ICAT is to allow subject matter experts (SME) with limited to no experience in machine learning to benefit from an iterative human-in-the-loop (HITL) approach to building their own model without needing to understand the details of the underlying algorithm. This interactivity is achieved by allowing the user to create features, label data points, and visually manipulate a representation of the features to manually cluster and investigate data, while a model is trained on the fly based on these actions. ICAT is built on top of the Panel (Holoviz, 2018) library, using a combination of Vega, a custom IPyWidget using D3, and ipyvuetify, and is intended to be used inside of a Jupyter environment.

Martindale, Nathan [Oak Ridge National Laboratory ↗
DOE OSTI2023

Advancements in Development and Testing of Thermal Power Dispatch Simulators

Flexible plant operations and generation (FPOG) offer nuclear power plants (NPPs) the chance to leverage alternative, non-electric revenue streams while ensuring their continued role as reliable, clean, and constant sources of baseload electrical power. The excess thermal energy generated from NPPs during periods of low electricity demand can be channeled as raw materials to numerous industrial processes via a thermal power dispatch (TPD) system. Hydrogen production via high-temperature steam electrolysis (HTSE) is an optimal use case based on technical and economic feasibility. Researchers at Idaho National Laboratory (INL) have conducted previous works that developed and implemented TPD system models within the GSE Solutions Generic Pressurized Water Reactor (GPWR) simulator to support human-in-the-loop (HITL) scenario-based evaluations. The first part of this report documents modifications made to the GPWR TPD model and HMI from the previous iteration in line with a new Sargent and Lundy (S&L) TPD design with an automatic control system. The was done in collaboration with Westinghouse using their three-loop pressurizer water reactor (W3LPWR) simulator which contains an industrial grade automatic control system for the TPD. This was installed in the Human Systems Simulation Laboratory (HSSL) at INL. The second part of the report documents findings from an all-hands-on-deck integration and verification workshop that was conducted in the HSSL over several days. The research team comprised INL human factors and TPD experts, a nuclear engineer from GSE Solutions who implemented the revised TPD model for GPWR, the human-machine interface (HMI) prototyping and human factors team from the University of Idaho, and personnel with operations experience with pressurized water reactors. The workshop provided time and expertise to conduct the final activities to bring the operations, HMI, and simulator into a functional state. The goals of the integration and verification workshop were: 1. to install the revised GPWR TPD model into the HSSL 2. verify the TPD HMI prototype was functional 3. integrate the HTSE Simulink model to GPWR. 3. Issues were identified for resolution, but overall the workshop accomplished its goal to integrated and verify the majority of the intended functional. Future work will resolve the identified issues and use the integrated simulation to support an evaluation and demonstration in the next fiscal year.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Scalability of Real-time Distribution Models

This work will focus on developing the capabilities and validating the models for a sub transmission network with multiple feeders and microgrids. To achieve this scale of Hardware-in-the-loop (HitL) simulation, it is necessary to federate and collaborate. The work aims to design the large-scale feeder models to allow federation with complementary testbeds in the future. The feeder would be designed to be reconfigurable to put the system into a variety of modes. Aggregators models will be included in each distribution network’s federate to take control actions and interact with the management systems. Lastly, the feeder model will support large scale resilience studies involving complex Distributed Energy Resources (DER) controls, microgrid studies and emulation of complex data flows in future grid architectures.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Application of Artificial Intelligence/Machine Learning to Operations Research

This report examines the transformative impact of Artificial Intelligence (AI) and Machine Learning (ML) on operations research, private industry, and government sectors, highlighting their applications in automating processes, enhancing decision-making, and optimizing complex systems. AI/ML technologies have revolutionized industries through predictive maintenance, supply chain optimization, and autonomous systems, while also advancing public safety and defense operations. However, challenges such as data integrity, model transparency, and the need for human oversight persist, particularly in high-consequence environments. The report emphasizes the critical role of explainable AI (XAI) and human-computer interaction models like Human-in-the-Loop (HITL) and Human-on-the-Loop (HOTL) in fostering trust and accountability. Balancing automation with ethical responsibility and transparency is essential for the continued successful integration of AI/ML into operational and strategic decision-making frameworks.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2005

Flight Technical Error Analysis of the SATS Higher Volume Operations Simulation and Flight Experiments

This paper provides an analysis of Flight Technical Error (FTE) from recent SATS experiments, called the Higher Volume Operations (HVO) Simulation and Flight experiments, which NASA conducted to determine pilot acceptability of the HVO concept for normal operating conditions. Reported are FTE results from simulation and flight experiment data indicating the SATS HVO concept is viable and acceptable to low-time instrument rated pilots when compared with today s system (baseline). Described is the comparative FTE analysis of lateral, vertical, and airspeed deviations from the baseline and SATS HVO experimental flight procedures. Based on FTE analysis, all evaluation subjects, low-time instrument-rated pilots, flew the HVO procedures safely and proficiently in comparison to today s system. In all cases, the results of the flight experiment validated the results of the simulation experiment and confirm the utility of the simulation platform for comparative Human in the Loop (HITL) studies of SATS HVO and Baseline operations.

Williams, Daniel M.↗
NASA NTRS2010

Modeling Pilot Behavior for Assessing Integrated Alert and Notification Systems on Flight Decks

Numerous new flight deck configurations for caution, warning, and alerts can be conceived; yet testing them with human-in-the-Ioop experiments to evaluate each one would not be practical. New sensors, instruments, and displays are being put into cockpits every day and this is particularly true as we enter the dawn of the Next Generation Air Transportation System (NextGen). By modeling pilot behavior in a computer simulation, an unlimited number of unique caution, warning, and alert configurations can be evaluated 24/7 by a computer. These computer simulations can then identify the most promising candidate formats to further evaluate in higher fidelity, but more costly, Human-in-the-Ioop (HITL) simulations. Evaluations using batch simulations with human performance models saves time, money, and enables a broader consideration of possible caution, warning, and alerting configurations for future flight decks.

Cover, Mathew↗
NASA NTRS2011

A Human-in-the-Loop Evaluation of Multi-Sector Planning in Mixed Equipage Airspace (MSP III)

A human-in-the-loop (HITL) simulation was conducted in May 2010 to determine the feasibility and value 01 conducting multi-sector planning (MSP) operations in a mixed equipage environment. Aircraft were categorized as equipped or unequipped based on the presence or absence of an air-ground data communications (Data Comm) capability for receiving auto-loadable clearances and transfer of communication messages from the air navigation service provider (ANSP). The purpose of the study was to determine the feasibility and possible benefits of introducing multi-sector planning in a mixed equipage context, or whether Data Comm equipage was required for MSP operations. Each test scenario presented one of three different equipage levels to the controllers (10%, 50% or 90% equipped aircraft), so that the operational impact of different equipage levels could be observed. Operational feasibility assessment addressed two related questions: (1) are MSP operations feasible for unequipped aircraft, and (2) are they feasible in a mixed equipage context. Similarly, two categories of potential benefits were explored: (1) system performance improvements (e.g., throughput, workload) associated with MSP at different equipage levels, and (2) the possibility of providing differential service for equipage through MSP operations. Tool requirements (for both planning and controller stations), as well as planning and coordination procedures - within facility (traffic management unit/operational area) and within sector (R-Side/D-Side) - were two other topics addressed in the study. Overall, results suggested that MSP operations were feasible in a mixed equipage environment and that the tools were effective with both equipped and unequipped aircraft. Using the MSP tools, traffic management coordinators were able to manage controller task load, effectively balancing throughput with complexity and controller task load at each of the three equipage levels tested.

Smith, Nancy↗
NASA NTRS2012

Quantifying Pilot Visual Attention in Low Visibility Terminal Operations

Quantifying pilot visual behavior allows researchers to determine not only where a pilot is looking and when, but holds implications for specific behavioral tracking when these data are coupled with flight technical performance. Remote eye tracking systems have been integrated into simulators at NASA Langley with effectively no impact on the pilot environment. This paper discusses the installation and use of a remote eye tracking system. The data collection techniques from a complex human-in-the-loop (HITL) research experiment are discussed; especially, the data reduction algorithms and logic to transform raw eye tracking data into quantified visual behavior metrics, and analysis methods to interpret visual behavior. The findings suggest superior performance for Head-Up Display (HUD) and improved attentional behavior for Head-Down Display (HDD) implementations of Synthetic Vision System (SVS) technologies for low visibility terminal area operations. Keywords: eye tracking, flight deck, NextGen, human machine interface, aviation

Ellis, Kyle K.↗
NASA NTRS2012

Comparison of Controller and Flight Deck Algorithm Performance During Interval Management with Dynamic Arrival Trees (STARS)

Managing the interval between arrival aircraft is a major part of the en route and TRACON controller s job. In an effort to reduce controller workload and low altitude vectoring, algorithms have been developed to allow pilots to take responsibility for, achieve and maintain proper spacing. Additionally, algorithms have been developed to create dynamic weather-free arrival routes in the presence of convective weather. In a recent study we examined an algorithm to handle dynamic re-routing in the presence of convective weather and two distinct spacing algorithms. The spacing algorithms originated from different core algorithms; both were enhanced with trajectory intent data for the study. These two algorithms were used simultaneously in a human-in-the-loop (HITL) simulation where pilots performed weather-impacted arrival operations into Louisville International Airport while also performing interval management (IM) on some trials. The controllers retained responsibility for separation and for managing the en route airspace and some trials managing IM. The goal was a stress test of dynamic arrival algorithms with ground and airborne spacing concepts. The flight deck spacing algorithms or controller managed spacing not only had to be robust to the dynamic nature of aircraft re-routing around weather but also had to be compatible with two alternative algorithms for achieving the spacing goal. Flight deck interval management spacing in this simulation provided a clear reduction in controller workload relative to when controllers were responsible for spacing the aircraft. At the same time, spacing was much less variable with the flight deck automated spacing. Even though the approaches taken by the two spacing algorithms to achieve the interval management goals were slightly different they seem to be simpatico in achieving the interval management goal of 130 sec by the TRACON boundary.

Battiste, Vernol↗
NASA NTRS2011

Flexible Airspace Management (FAM) Research 2010 Human-in-the-Loop Simulation

A human-in-the-Ioop (HITL) simulation was conducted to assess potential user and system benefits of Flexible Airspace Management (FAM) concept, as well as designing role definitions, procedures, and tools to support the FAM operations in the mid-term High Altitude Airspace (HAA) environment. The study evaluated the benefits and feasibility of flexible airspace reconfiguration in response to traffic overload caused by weather deviations, and compared them to those in a baseline condition without the airspace reconfiguration. The test airspace consisted of either four sectors in one Area of Specialization or seven sectors across two Areas. The test airspace was assumed to be at or above FL340 and fully equipped Vvith data communications (Data Comm). Other assumptions were consistent with those of the HAA concept. Overall, results showed that FAM operations with multiple Traffic Management Coordinators, Area Supervisors, and controllers worked remarkably well. The results showed both user and system benefits, some of which include the increased throughput, decreased flight distance, more manageable sector loads, and better utilized airspace. Also, the roles, procedures, airspace designs, and tools were all very well received. Airspace configuration options that resulted from a combination of algorithm-generated airspace configurations with manual modifications were well acceptec and posed little difficuIty and/or workload during airspace reconfiguration process. The results suggest a positive impact of FAM operations in HAA. Further investigation would be needed to evaluate if the benefits and feasibility would extend in either non-HAA or mixed equipage environment.

Lee, Paul U.↗
NASA NTRS2013

Designing Scenarios for Controller-in-the-Loop Air Traffic Simulations

Within the Human Factors Division at NASA Ames Research Center the Airspace Operations Laboratory (AOL) is developing advanced automation concepts that help to transform the National Airspace System into NextGen, the Next Generation Air Transportation System. High-fidelity human-in-the-loop (HITL) simulations are used as a means to investigate and develop roles, responsibilities, support tools, and requirements for human operators and automation. This paper describes the traffic scenario design process and strategies as used by AOL researchers. Details are presented on building scenarios for specific simulation objectives using various design strategies. A focus is set on creating scenarios based on recorded real world traffic for terminal-area simulations.

scenario design↗