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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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At least 361 records · Page 20
All sourcesNASA NTRSDOE OSTI
NASA NTRS2019

Evaluation of Technology Concepts for Traffic Data Management and Relevant Audio for Datalink in Commercial Airline Flight Decks

Datalink is currently operational for departure clearances and in oceanic environments and is currently being tested in high altitude domestic enroute airspace. Interaction with even simple datalink clearances may create more workload for flight crews than the voice system they replace if not carefully designed. Datalink may also introduce additional complexity for flight crews with hundreds of uplink messages now defined for use. Finally, flight crews may lose airspace awareness and operationally relevant information that they normally pickup from Air Traffic Control (ATC) voice communications with other aircraft (i.e., “party-line” transmissions). Once again, automation may be poised to increase workload on the flight deck for incremental benefit. Datalink implementation to support future air traffic management concepts needs to be carefully considered, understanding human communication norms and especially, the change from voice- to text-based communications modality and its effect on pilot workload and situation awareness. Increasingly autonomous systems, where autonomy is designed to support human-autonomy teaming, may be suited to solve these issues. NASA is conducting research and development of increasingly autonomous systems, utilizing machine-learning algorithms seamlessly integrated with humans whereby task performance of the combined system is significantly greater than the individual components. Increasingly autonomous systems offer the potential for significantly improved levels of performance and safety that are superior to either human or automation alone. Two increasingly autonomous systems concepts - a traffic data manager and a conversational co-pilot - were developed to intelligently address the datalink issues in a complex, future state environment with significant levels of traffic. The system was tested for suitability of datalink usage for terminal airspace. The traffic data manager allowed for automated declutter of the Automatic Dependent Surveillance-Broadcast (ADS-B) display. The system determined relevant traffic for display based on machine learning algorithms trained by experienced human pilot behaviors. The conversational co-pilot provided relevant audio air traffic control messages based on context and proximity to ownship. Both systems made use of the connected aircraft concepts to provide intelligent context to determine relevancy above and beyond proximity to ownship. A human-in-the-loop test was conducted in NASA Langley Research Center’s Integration Flight Deck B-737-800 simulator to evaluate the traffic data manager and the conversational co-pilot. Twelve airline crews flew various normal and non-normal procedures and their actions and performance were recorded in response to the procedural events. This paper details the flight crew performance and evaluation during the events.

Etherington, Timothy↗
NASA NTRSDate not supplied

TPSAS-NF1676L-14273-DND

ATOL is a World-unique lab facility that supports investigations / proof-of-concept studies to explore NextGen operations, procedures, and technologies. ATOL was originally created to fill a research gap at LaRC between low fidelity desk-top simulations and the high fidelity Cockpit Motion Facility for human-in-the-loop studies. Development began more than 10 years ago to study new ATM concept feasibility and distributed ATM flight deck capabilities in the en-route domain. First formal experiment in 2001. Capability was created as research requirements/goals dictated. Development philosophy is to develop models to the level of fidelity needed for studies. Simulation has numerous models/capabilities at varying levels of fidelity.

Tod Lewis↗
NASA NTRSDate not supplied

Automatic Dependent Surveillance-Broadcast (ADS-B) In-Trail Procedures (ITP)

Aircraft in oceanic and remote non-radar airspace frequently fly for extended periods of time in the same direction, at the same time, along similar flight paths as other aircraft. Since there is no radar surveillance, controllers use procedural separation to ensure that aircraft remain separated. Procedural separation distances are typically larger than radar separation distances and as a result aircraft operating in oceanic airspace are sometimes held at non-optimal flight levels due to conflicting traffic at intervening flight levels. Automatic Dependent Surveillance-Broadcast (ADS-B) In-Trail Procedures (ITP) were developed to enable flight level change maneuvers that would otherwise not be possible with current procedural separation standards. Aircraft operators choosing to equip with an ADS-B transceiver and an appropriate onboard decision support system would be able to take advantage of these procedures when operating in proximity to aircraft equipped with a suitable ADS-B transmitter (“ADS-B Out”). The ability to perform in-trail maneuvers to achieve more time at optimum altitudes could result in more efficient and predictable flight profiles thereby saving fuel and in some cases allowing operators to make beneficial operational decisions. NASA first began developing ADS-B ITP in 2003 as a result of a desire to develop methodologies, concepts, and procedures to reduce separation requirements for future air transportation systems using airborne ADS-B. The objectives were to provide insight into the details necessary to reduce separation requirements for the future and to develop applications that could provide incentives for operators to voluntarily equip with transformational technologies. From 2003 to 2008, NASA conducted research that supported the development of ITP including batch simulations, human-in-the-loop experiments and avionics and separation standards development. This research showed enough maturity and benefit that in 2008, the FAA Surveillance and Broadcast Services (SBS) program adopted ADS-B ITP as one of their three key, near-term applications to make use of ADS-B-In. The FAA developed an agreement with NASA to transition the technology and established an FAA project for the purpose of performing an operational trial of ADS-B ITP in revenue service in the summer of 2011. The objectives of the project are to a) validate the operational performance and economic benefits of ITP; and b) develop and validate ADS-B ITP Minimum Operational Performance Specifications (MOPS) material. As a part of this project, the FAA established agreements with United Airlines and Honeywell. The agreements include the work necessary for the development, certification and installation of onboard systems for twelve United Airlines 747-400s. ITP system development is nearly complete and certification activities are underway. The FAA project has also been working with Oakland Oceanic Control Center (ZOA) and the FAA’s Oceanic and Offshore Operations Office to develop controller procedures and safety analyses that are required to support the flight trial. The FAA has also been working on the development of an ITP Operational Specification that should be approved this April. The presentation will cover some of the key aspects of the development, challenges, and integration required to successfully transition ADS-B ITP from a concept in 2003 to flight trials in revenue service in 2011.

Kenneth M Jones↗
NASA NTRS2020

Hybrid Electric MC-12 Ground Testing Plan Chapter

In the commercial aviation world, hybrid/electric propulsion is a promising technology for fuel, emissions, and noise reduction in support of the challenging goals established by 2050 EU Flightpath/SRIA, NASA ARMD Strategic Implementation Plan, and the US Air Force ATTAM programs. Ongoing results indicate operational benefits are possible in those three technical areas. Considering military applications, hybrid/electric propulsion may yield further significant improvements by enabling new, unorthodox mission capabilities. Potential benefits are expected in the areas of vehicle signature reduction (lower noise, lower exhaust signature), usage in enhanced flight environments, minimized human-in-the-loop workload by offering a platform compatible with future goals of autonomous operations facilitation, maintenance cost reductions, and performance burst/dash energy. Additional synergies are likely when used in conjunction with energy weapons. Some potential areas of mutual interest could include, dusty operations capability, remote supply capability, extended surveillance, dispatch able power, fuel-flexible vehicles, and autonomous rescue equipment. Many of the key technologies that have been demonstrated in ground operation must now be qualified for altitude conditions. We expect to have many flight qualified powertrain systems over the next decade for military planners to choose from for new future battlefield capability. This requires new flight-weight and flight-efficient powertrain components, fault tolerant power management, and electromagnetic interference mitigation technologies. Moreover, initial studies indicate some combination of ambient and cryogenic thermal management and relatively high bus voltages when compared to state of practice will be required to achieve a net system benefit. Developing all these powertrain technologies within a realistic aircraft architectural geometry and under realistic operational conditions requires a unique electric aircraft test bed. The MC-12 surveillance aircraft is an ideal military aircraft for demonstrating some of the benefits of incorporating hybrid electric propulsion. This report details an approach for full-scale ground-based altitude testing the hybrid electric MC-12 powertrain through a full flight profile.

military electric aircraft propulsion↗
NASA NTRS2020

Air Traffic Management TestBed Data Exchange Model

The Air Traffic Management (ATM) TestBed is a Platform as a Service that is being developed by the National Aeronautics and Space Administration (NASA) to help design, configure, integrate, run, and monitor air traffic simulations. The platform is designed to provide cloud services including back-end, big-data analytics tools, on-demand computing resource management, data storage, and communication middleware. The ATM TestBed reduces the time to test concepts and technologies, supports interactions among various methods such as human-in-the-loop and automation-in-the-loop simulations, and enables collaborative simulations by sharing technologies and tools in the ATM community. In order to allow easier access to simulation components, TestBed provides a messaging support layer for connectivity using a consistent set of input/output interfaces. In addition, a standard data format is introduced to facilitate communication between the components. The data exchange model, supported in the messaging support layer, standardizes the format of the information to be exchanged among the components. This document describes the messaging data model currently developed in TestBed and provides data dictionaries for references to component developers as well as simulation engineers.

air traffic simulation↗
NASA NTRSDate not supplied

An Examination of Two Non-Cooperative Detect and Avoid Well Clear Definitions

NASA’s Unmanned Aircraft Systems Integration into the National Airspace System (UAS in the NAS) project examines the technical barriers associated with the operation of UAS in civil airspace. The present study explored the differential effects of two candidate non-cooperative Detect-and-Avoid Well Clear (DWC)definitions on pilot and system performance in a human-in-the-loop simulation. Active-duty UAS pilots were recruited to maintain DWC against representative Class 4 encounter types with a low size, weight, and power (SWaP) radar declaration range of 3.5 nautical miles (nmi). Objective performance indicated that pilots could consistently maintain DWC against non-cooperative intruders with either DWC candidate, with negligible differences in response times and separation performance against caution and warning-level threats. While losses of DWC were avoided at rates comparable to Phase 1 findings, pilots uploaded their responses to caution-level alerts over 5 seconds faster in the current setup relative to Phase 1. Encounters with faster closure rates were susceptible to shortened caution-level alert durations, especially when employing the DWC criterion with the additional ‘Tau’ (temporal) component. Consequently, caution-level threats frequently elevated to warning-level status (nearly twice as often with theTau candidate). The variable caution alert durations appeared to impact pilots’ coordination with air traffic control (ATC), as ATC approval rates were lower with the ‘Tau’and ‘Disc’ candidates relative to Phase 1 research. Ultimately, the increased alerting time enabled by the Disc candidate deemed it more suitable for any reductions to the assumed radar declaration range requirement, which was re-evaluated in a follow-on study. Findings from this study will inform Phase 2 Minimum Operational Performance Standards (MOPS)development for UAS with alternative surveillance equipment and performance capabilities.

Kevin J Monk↗
NASA NTRSDate not supplied

Demonstrating Early-Adopter Benefits of Submitting Multiple Trajectory Options for Airlines

A workshop at NASA Ames Research Center was held with airline industry stakeholders to demonstrate the impact of using Trajectory Options Sets (TOSs) during a Collaborative Trajectory Options Program (CTOP) for severe weather operations. The demonstration was conducted using apart-task Human-in-the-Loop (HITL) simulation of the Integrated Demand Management (IDM) concept, which is an air traffic management method that uses CTOP to deliver preconditioned traffic to the Time-Based Flow Management (TBFM) region. The demonstration addressed the following research objectives: first, determine who receives a greater benefit, TOS-participating or TOS-excluded airlines? Second, determine which method of trajectory selection yields a better solution, human/manual selection or automation? Finally, obtain feedback from stakeholders on their impression of the concept and recommendations for future work. The results showed that TOS-participating airlines received greater benefit in terms of total ground delay, ground delay savings, number of reroute options, and additional flight time, compared to TOS-excluded airlines. However, this result was dependent on the situational context, such as the number and location of flights. We found that all airlines benefitted when just a subset of airlines submitted TOS, but the greatest benefit went to the TOS-participating airlines. These benefits to the TOS-participating airlines were diminished as the number of TOS-participants in the system increased. Therefore, there was an “early-adopter” effect that suggested airlines could benefit by becoming the first to equip TOS without causing unfair disadvantages to those who do not equip TOS. In addition, we found that manual selection of trajectory options performed similarly to CTOP, but the CTOP solution was more efficient in terms of number of reroutes, additional flight time, and average ground delay for rerouted flights. Feedback from the stakeholders was solicited, and their overall impressions of the demonstrations were positive. They remarked that CTOP could do a better job than current day solutions, and they thought airlines could benefit from continuing to develop TOS capabilities.

Integrated Demand Management↗
NASA NTRSDate not supplied

Demonstrating the Early Adopter Benefits of Submitting Multiple Trajectory Options for Airlines

Integrated Demand Management (IDM), is a NASA developed Traffic Flow Management (TFM) concept that uses Collaborative Trajectory Options Program (CTOP) to precondition traffic flows into the Time Based Flow Management (TBFM) region, helping traffic planners manage imbalances between demand and capacity in the National Airspace (NAS). A workshop held at NASA was conducted to demonstrate how individual airlines can be impacted by using Trajectory Options Sets (TOS) during IDM operations. A primary concern that was specifically addressed in a part-task Human-in-the-Loop simulation was who received the greater benefit, TOS participating or non-TOS participating airlines? The results showed that TOS participating airlines received greater benefit in terms of ground delay, number of reroute options, and additional flight time, than non-TOS participating airlines. However, this result was dependent on the number and location of flights. Therefore, it was advantageous for airlines to equip TOS. In addition, we found that non-TOS participating airlines also benefitted from other airlines participating in TOS, because the total system-wide ground delay was reduced as more TOS were introduced into the system. The evidence suggests that the benefits were distributed fairly, and there were no unfair disadvantages for airlines who did not equip TOS.

Integrated Demand Management↗
NASA NTRS2020

Tactical Separation and Safety Alerting System for Terminal Airspace

Provision of tactical alerts to aid air traffic controllers in providing separation assurance in terminal airspace is hindered by the complexity of the airspace, its operations, and flight procedures. A prototype automation system is studied that provides controllers with both separation and safety alerts based on or derived from the separation standard for terminal airspace. The system models flight trajectories heuristically, with use of merged intent information from readily available sources: area navigation departure procedures, flight-plan routes, and arrival nominal interior routes used in terminal automation systems. Flight vertical intent is modeled according to standard procedural restrictions except when superseded by controller-issued altitude clearances. Importantly, flight trajectories are modeled for all aircraft, including those conducting visual approaches. New safety-alert thresholds for aircraft conducting visual approaches are studied. Performance of the system is evaluated through fast-time playback of recorded air traffic data from high-fidelity Human-In-The-Loop simulations and real-world operations in two Terminal Radar Approach Control facilities. The prototype system is found to produce a false-alert rate of 8% for separation alerts. The number and validity of safety alerts are studied by comparing with the current Conflict Alert system, showing that the false alerts of Conflict Alert are at 85% and they are avoided in the prototype system.

Air Traffic Management↗
NASA NTRSDate not supplied

An Evaluation of UAS Pilot Workload and Acceptability Ratings with Four Simulated Radar Declaration Ranges

Currently, minimum operational performance standards (MOPS) are being developed for a broader range of unmanned aircraft system (UAS) platforms, including smaller UAS that will feature onboard sensors that are low in size, weight, and power, otherwise known as low SWaP. The low SWaP sensors used to detect non-cooperative traffic will have limited declaration ranges compared to those designed for medium-to-large UAS. A human-in-the-loop (HITL) study was conducted examining four possible radar declaration ranges (i.e., 1.5 NM, 2 NM, 2.5 NM, and 3 NM) for a potential low SWaP sensor with a detect and avoid (DAA) system encountering various non-cooperative encounters in Oakland Center airspace. Participants had lower workload, particularly workload associated with temporal demand and effort, in scenarios that featured larger declaration ranges. Furthermore, participants reported better ability to remain DAA well clear within the larger declaration range conditions, specifically with the 2.5 NM and 3 NM conditions.

UAS↗
NASA NTRSDate not supplied

M:N Operations NASA/Uber Collaboration

In this presentation, current approaches to enable multiple-operator, multiple vehicle (M:N) operations are reviewed together with recent collaborative efforts between NASA and Uber. Topics include a review of human-automation teaming (HAT) concepts, including plays and working agreements, and a particular task-allocation method called Automation Level-based Task Allocation (ALTA). Following introductory material on HAT, an overview of a recent (July 2020) cognitive walkthrough study of M:N operations in the context of a food delivery via small-Unmanned Aircraft Systems application is provided. Initial results from this cognitive walkthrough detailing operator feedback on displays, operator and supervisor roles and responsibilities, and the overall concept of operation are reviewed. The presentation concludes with a description of a future, human-in-the-loop simulation experiment of M:N operations in a high-fidelity environment, which will examine the effects of high workload and assistive automation/tools on operator performance.

human-automation teaming↗
NASA NTRS2001

Monte-carlo maneuver analysis for the microwave anisotropy probe

The results of this trajectory replication are presented, followed by the results of monte-carlo maneuver simulations. The results are subject to two important assumptions: that linearization is valid (as the software used for the monte-carlo simulation, LAMBIC, is based on a linearization of the trajectory about the nominal) and that the planned human-in-the-loop lunar targeting may be approximated by targeting to a fixed aimpoint.

monte-carlo↗
NASA NTRS2018

Do You See What I See? Interactive Visualization of Mission Design and Navigation

Mission Design and Navigation (MDNav) is an intensive process requiring advanced computational resources, expert human intuition, and many successive human-in-the-loop iterations to converge on acceptable trajectory designs or navigation solutions. The current bottleneck in MDNav is not the underlying computational algorithms but the human cognitive capacity to prune through a multitude of simulated results to select high-value candidates. One approach to alleviate this burden is through the judicious application of visualizations that allow humans to interactively filter data in multiple dimensions to reveal salient patterns and highlight divergences. When designed efficiently, such interactive visualizations should aid human operators to get familiar with data faster, visually observe correlations, and communicate findings more effortlessly. In this work, we present three visualization case studies that have the potential to increase human operator efficiency in MDNav. While identifying the most critical “pain points” that operators face, and also working on potential solutions, we followed a human-centered design approach. We started with a series of interviews with potential users, and then rapidly created prototypes for alternative solutions, validated outcomes with feedback from users through out development of these proof of concept visualizations. With this survey of our current efforts, we demonstrate the transformative capability of interactive data visualizations for improving mission development and operations, enabling operators to grow intuition, and communicating key concepts across diverse mission teams.

Arora, Nitin↗
DOE OSTI2025

Interactive Rotated Object Detection for Novel Class Detection in Remotely Sensed Imagery

In this paper we propose IRTR-DETR an Interactive and Real-Time Rotated DEtection TRansformer that extends IRTDETR to predict rotated bounding boxes. IRTR-DETR maintains the Human-In-The-Loop (HIL) workflow of IRTDETR but introduces rotation-aware heads for improved detection of objects with arbitrary orientations. Similarly to IRTDETR IRTR-DETR can be trained with a small labeled sample set in an interactive setting but we show that it can also be pretrained on related but not identical data--such as a building damage dataset--before being applied to tasks like identifying buildings under construction. We demonstrate the efficacy of our approach on the publicly available Tiny-DOTA and xBD dataset as well as two study-cases on proprietary datasets of greenhouses and houses under construction ("waffle homes"). Detecting greenhouses is highly relevant in the context of damage assessment while "waffle homes" aid understanding typical floorplans and building codes in different areas both thereby supporting population modeling emergency response and policy planning. Our method outperforms the state of the art in interactive rotated object detection on the Tiny-DOTA dataset by 5.7 percent and improves upon the non interactive RTDETR by 7.85 to 19.39 percent (depending on the number of provided samples) while maintaining its real-time efficiency.

Burges, Marvin [ORNL] (ORCID:0000000312690769)↗
DOE OSTI2025

HEPTAPOD: Orchestrating High Energy Physics Workflows Towards Autonomous Agency

Many workflows in high-energy-physics (HEP) stand to benefit from recent advances in transformer-based large language models (LLMs). While early applications of LLMs focused on text generation and code completion, modern LLMs now support orchestrated agency: the coordinated execution of complex, multi-step tasks through tool use, structured context, and iterative reasoning. We introduce the HEP Toolkit for Agentic Planning, Orchestration, and Deployment (HEPTAPOD), an orchestration framework designed to bring this emerging paradigm to HEP pipelines. The framework enables LLMs to interface with domain-specific tools, construct and manage simulation workflows, and assist in common utility and data analysis tasks through schema-validated operations and run-card-driven configuration. To demonstrate these capabilities, we consider a representative Beyond the Standard Model (BSM) Monte Carlo validation pipeline that spans model generation, event simulation, and downstream analysis within a unified, reproducible workflow. HEPTAPOD provides a structured and auditable layer between human researchers, LLMs, and computational infrastructure, establishing a foundation for transparent, human-in-the-loop systems.

Menzo, Tony [Alabama U.; Fermilab] (ORCID:00000002↗
DOE OSTI2025

Explainable AI for Multivariate Time Series Pattern Exploration: Latent Space Visual Analytics With Temporal Fusion Transformer and Variational Autoencoders in Power Grid Event Diagnosis

Detecting and analyzing complex patterns in multivariate time-series data is crucial for decision-making in urban and environmental system operations. However, challenges arise from the high dimensionality, intricate complexity, and interconnected nature of complex patterns, which hinder the understanding of their underlying physical processes. Existing AI methods often face limitations in interpretability, computational efficiency, and scalability, reducing their applicability in real-world scenarios. This paper proposes a novel visual analytics framework that integrates two generative AI models, Temporal Fusion Transformer (TFT) and Variational Autoencoders (VAEs), to reduce complex patterns into lower-dimensional latent spaces and visualize them in 2D using dimensionality reduction techniques such as PCA, t-SNE, and UMAP with DBSCAN. These visualizations, presented through coordinated and interactive views and tailored glyphs, enable intuitive exploration of complex multivariate temporal patterns, identifying patterns’ similarities and uncover their potential correlations for a better interpretability of the AI outputs. The framework is demonstrated through a case study on power grid signal data, where it identifies multi-label grid event signatures, including faults and anomalies with diverse root causes. Additionally, novel metrics and visualizations are introduced to validate the models and assess the performance, efficiency, and consistency of latent maps generated by VAE, which have been utilized in prior studies for latent space cartography and used as a benchmark in this study, and the emerging TFT architecture under various configurations. These analyses provide actionable insights for model parameter tuning and reliability improvements. Comparative results highlight that TFT achieves shorter run times and superior scalability to diverse time-series data shapes compared to VAE. This work advances fault diagnosis in multivariate time series, fostering explainable AI to support critical system operations.

Explainable AI↗
NASA NTRS2014

Air Traffic Controller Performance and Acceptability of Multiple UAS in a Simulated NAS Environment

Previously, we showed that air traffic controllers (ATCos) rated UAS pilot verbal response latencies as acceptable when a 1.5 s delay was added to the UAS pilot responses, but a 5 s delay was rated as mostly unacceptable. In the present study we determined whether a 1.5 s added delay in the UAS pilots' verbal communications would affect ATCos interactions with UAS and other conventional aircraft when the number and speed of the UAS were manipulated. Eight radar-certified ATCos participated in this simulation. The ATCos managed a medium altitude sector containing arrival aircraft, en route aircraft, and one to four UAS. The UAS were conducting a surveillance mission and flew at either a "slow" or "fast" speed. We measured both UAS and conventional pilots' verbal communication latencies, and obtained ATCos' acceptability ratings for these latencies. Although the UAS pilot response latencies were longer than those of conventional pilots, the ATCos rated UAS pilot verbal communication latencies to be as acceptable as those of conventional pilots. Because the overall traffic load within the sector was held constant, ATCos only performed slightly worse when multiple UAS were in their sector compared to when only one UAS was in the sector. Implications of these findings for UAS integration in the NAS are discussed.

measured response↗