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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
NASA NTRS2015

Taxi Time Prediction at Charlotte Airport Using Fast-Time Simulation and Machine Learning Techniques

Accurate taxi time prediction can be used for more efficient runway scheduling to increase runway throughput and reduce taxi times and fuel consumptions on the airport surface. This paper describes two different approaches to predicting taxi times, which are a data-driven analytical method using machine learning techniques and a fast-time simulation-based approach. These two taxi time prediction methods are applied to realistic flight data at Charlotte Douglas International Airport (CLT) and assessed with actual taxi time data from the human-in-the-loop simulation for CLT airport operations using various performance measurement metrics. Based on the preliminary results, we discuss how the taxi time prediction accuracy can be affected by the operational complexity at this airport and how we can improve the fast-time simulation model for implementing it with an airport scheduling algorithm in real-time operational environment.

Lee, Hanbong↗
NASA NTRS2018

From Formal Requirements to Highly Assured Software for Unmanned Aircraft Systems

Operational requirements of safety-critical systems are often written in restricted specification logics. These restricted logics are amenable to automated analysis techniques such as model-checking, but are not rich enough to express complex requirements of unmanned systems. This short paper advocates for the use of expressive logics, such as higher-order logic, to specify the complex operational requirements and safety properties of unmanned systems. These rich logics are less amenable to automation and, hence, require the use of interactive theorem proving techniques. However, these logics support the formal verification of complex requirements such as those involving the physical environment. Moreover, these logics enable validation techniques that increase con dence in the correctness of numerically intensive software. These features result in highly-assured software that may be easier to certify. The feasibility of this approach is illustrated with examples drawn for NASA's unmanned aircraft systems.

Munoz, Cesar↗
NASA NTRS2002

Airborne Use of Traffic Intent Information in a Distributed Air-Ground Traffic Management Concept: Experiment Design and Preliminary Results

This paper presents initial findings of a research study designed to provide insight into the issue of intent information exchange in constrained en-route air-traffic operations and its effect on pilot decision making and flight performance. The piloted simulation was conducted in the Air Traffic Operations Laboratory at the NASA Langley Research Center. Two operational modes for autonomous operations were compared under conditions of low and high operational complexity. The tactical mode was characterized primarily by the use of state information for conflict detection and resolution and an open-loop means for the pilot to meet operational constraints. The strategic mode involved the combined use of state and intent information, provided the pilot an additional level of alerting, and allowed a closed-loop approach to meeting operational constraints. Operational constraints included separation assurance, schedule adherence, airspace hazard avoidance, flight efficiency, and passenger comfort. Potential operational benefits of both modes are illustrated through several scenario case studies. Subjective pilot ratings and comments comparing the tactical and strategic modes are presented.

Wing, David J.↗
NASA NTRS2001

Airborne Use of Traffic Intent Information in a Distributed Air-Ground Traffic Management Concept: Experiment Design and Preliminary Results

This paper presents initial findings of a research study designed to provide insight into the issue of intent information exchange in constrained en-route air-traffic operations and its effect on pilot decision making and flight performance. The piloted simulation was conducted in the Air Traffic Operations Laboratory at the NASA Langley Research Center. Two operational modes for autonomous operations were compared under conditions of low and high operational complexity. The tactical mode was characterized primarily by the use of state information for conflict detection and resolution and an open-loop means for the pilot to meet operational constraints. The strategic mode involved the combined use of state and intent information, provided the pilot an additional level of alerting, and allowed a closed-loop approach to meeting operational constraints. Operational constraints included separation assurance, schedule adherence, airspace hazard avoidance, flight efficiency, and passenger comfort. Potential operational benefits of both modes are illustrated through several scenario case studies. Subjective pilot ratings and comments comparing the tactical and strategic modes are presented.

Wing, David J.↗
DOE OSTI2026

Operating advanced scientific instruments with AI agents that learn on the job

Advanced scientific user facilities, such as next generation X-ray light sources and self-driving laboratories, are revolutionizing scientific discovery by automating routine tasks and enabling rapid experimentation and characterizations. However, these facilities must continuously evolve to support new experimental workflows, adapt to diverse user projects, and meet growing demands for more intricate instruments and experiments. This continuous development introduces significant operational complexity, necessitating a focus on usability, reproducibility, and intuitive human-instrument interaction. In this work, we explore the integration of agentic AI, powered by Large Language Models (LLMs), as a transformative tool to achieve this goal. We present our approach to developing a human-in-the-loop pipeline for operating advanced instruments including an X-ray nanoprobe beamline and an autonomous robotic station dedicated to the design and characterization of materials. Specifically, we evaluate the potential of various LLMs as trainable scientific assistants for orchestrating complex, multi-task workflows, which also include multimodal data, optimizing their performance through optional human input and iterative learning. We demonstrate the ability of AI agents to bridge the gap between advanced automation and user-friendly operation, paving the way for more adaptable and intelligent scientific facilities.

Large Language Models↗
NASA NTRS2011

Achieving the Proper Balance Between Crew and Public Safety

A paramount objective of all human-rated launch and reentry vehicle developers is to ensure that the risks to both the crew onboard and the public are minimized within reasonable cost, schedule, and technical constraints. Past experience has shown that proper attention to range safety requirements necessary to ensure public safety must be given early in the design phase to avoid additional operational complexities or threats to the safety of people onboard, and the design engineers must give these requirements the same consideration as crew safety requirements. For human spaceflight, the primary purpose and operational concept for any flight safety system is to protect the public while maximizing the likelihood of crew survival. This paper will outline the policy considerations, technical issues, and operational impacts regarding launch and reentry vehicle failure scenarios where crew and public safety are intertwined and thus addressed optimally in an integrated manner. An overview of existing range and crew safety policy requirements will be presented. Application of these requirements and lessons learned from both the Space Shuttle and Constellation Programs will also be discussed. Using these past programs as examples, the paper will detail operational, design, and analysis approaches to mitigate and balance the risks to people onboard and in the public. Manned vehicle perspectives from the Federal Aviation Administration (FAA) and Air Force organizations that oversee public safety will be summarized as well. Finally, the paper will emphasize the need to factor policy, operational, and analysis considerations into the early design trades of new vehicles to help ensure that both crew and public safety are maximized to the greatest extent possible.

Gowan, John↗
NASA NTRSDate not supplied

Trajectory Operations of the Artemis I Mission

This paper describes the operational design and execution of the Artemis I trajectory. It was an operationally complex trajectory with powered lunar flybys and insertion into a Distant Retrograde Orbit (DRO). A joint team of trajectory analysts at the NASA Johnson Space Center (JSC) were responsible for the design and operation of nominal and off-nominal in-space trajectories. A process was developed to convert optimized reference trajectories into Orion burn plans that could be uplinked to the vehicle. During the mission, the joint flight controller and engineering team continuously evaluated upcoming translational burns using actual vehicle conditions, monitored the trajectory for opportunities to re-optimize the trajectory in order to reduce propellant usage, and prepared for potential off-nominal scenarios. Overall Orion in-space trajectory performance is compared tomission designs to demonstrate the success of the design and operations work-flows.

Artemis I↗
NASA NTRSDate not supplied

Planning for Compilation of a Quantum Algorithm for Graph Coloring

Recently, the problem of compiling general quantum algorithms for implementation on near-term quantum processors has been introduced to the AI community. Previous work demonstrated that temporal planning is an attractive approach for part of this compilation task, specifically, the routing of circuits that implement the Quantum Alternating Operator Ansatz (QAOA) applied to theMaxCut problem on a quantum processor architecture. In this paper, we extend the earlier work to route circuits that implement QAOAfor Graph Coloring problems. QAOA for coloring requires execution of more, and more complex, operations on the chip, which makes routing a more challenging problem. We evaluate the approach on state-of-the-art hardware architectures from leading quantum computing companies. Additionally, we investigate applying the planning approach to qubit initialization as well as routing. Our empirical evaluation shows that temporal planning compares well to reasonable analytic upper bounds [20], and that solving qubit initialization with a classical planner generally helps temporal planners in finding shorter-makespan compilations for QAOA for Graph Coloring.These advances suggest that temporal planning can be an effective approach for more complex quantum computing algorithms and architectures.

Minh Do↗
NASA NTRSDate not supplied

TPSAS-NF1676L-29995-DND

Humans operating complex, socio-technical systems strive to develop a system understanding deeper than the interface and procedures support. System indications may not support a clear understanding of system state; indications can be fragmented, and the operator is responsible for integrating data. System designers make inappropriately generous assumptions about the average operator’s ability to make sense of the system.

Randy Mumaw↗
NASA NTRS2016

Taxi-Out Time Prediction for Departures at Charlotte Airport Using Machine Learning Techniques

Predicting the taxi-out times of departures accurately is important for improving airport efficiency and takeoff time predictability. In this paper, we attempt to apply machine learning techniques to actual traffic data at Charlotte Douglas International Airport for taxi-out time prediction. To find the key factors affecting aircraft taxi times, surface surveillance data is first analyzed. From this data analysis, several variables, including terminal concourse, spot, runway, departure fix and weight class, are selected for taxi time prediction. Then, various machine learning methods such as linear regression, support vector machines, k-nearest neighbors, random forest, and neural networks model are applied to actual flight data. Different traffic flow and weather conditions at Charlotte airport are also taken into account for more accurate prediction. The taxi-out time prediction results show that linear regression and random forest techniques can provide the most accurate prediction in terms of root-mean-square errors. We also discuss the operational complexity and uncertainties that make it difficult to predict the taxi times accurately.

Safe and efficient surface operations↗
NASA NTRS2001

General Aviation Aircraft Reliability Study

This reliability study was performed in order to provide the aviation community with an estimate of Complex General Aviation (GA) Aircraft System reliability. To successfully improve the safety and reliability for the next generation of GA aircraft, a study of current GA aircraft attributes was prudent. This was accomplished by benchmarking the reliability of operational Complex GA Aircraft Systems. Specifically, Complex GA Aircraft System reliability was estimated using data obtained from the logbooks of a random sample of the Complex GA Aircraft population.

Pettit, Duane↗
NASA NTRS2006

The Cassini-Huygens Mission Overview

The Cassini-Huygens Program is an international science mission to the Saturnian system. Three space agencies and seventeen nations contributed to building the Cassini spacecraft and Huygens probe. The Cassini orbiter is managed and operated by NASA's Jet Propulsion Laboratory. The Huygens probe was built and operated by the European Space Agency. The mission design for Cassini-Huygens calls for a four-year orbital survey of Saturn, its rings, magnetosphere, and satellites, and the descent into Titan's atmosphere of the Huygens probe. The Cassini orbiter tour consists of 76 orbits around Saturn with 45 close Titan flybys and 8 targeted icy satellite flybys. The Cassini orbiter spacecraft carries twelve scientific instruments that are performing a wide range of observations on a multitude of designated targets. The Huygens probe carried six additional instruments that provided in-situ sampling of the atmosphere and surface of Titan. The multi-national nature of this mission poses significant challenges in the area of flight operations. This paper will provide an overview of the mission, spacecraft, organization and flight operations environment used for the Cassini-Huygens Mission. It will address the operational complexities of the spacecraft and the science instruments and the approach used by Cassini-Huygens to address these issues.

mission operations↗
NASA NTRS2011

Benefits of Operational Consideration into the Guidance, Navigation, and Control Design of Spacecraft

The following paper points out historical examples where operational consideration into the GN&C design could have helped avoid operational complexity, reduce costs, ensure the ability for a GN&C system to be able to adapt to failures, and in some cases might have helped save mission objectives. A costly repeat of mistakes could befall a program if previous operational lessons, especially from operators of vehicles with similar GN&C systems, are not considered during the GN&C design phase of spacecraft. The information gained from operational consideration during the design can lead to improvements of the design, allow less ground support during operations, and prevent repetition of previous mistakes. However, this benefit can only occur if spacecraft operators adequately capture lessons learned that would improve future designs for operations and those who are designing spacecraft incorporate inputs from those that have previously operated similar GN&C systems.

Morris, Mark C.↗
NASA NTRS2017

Simulation Based Studies of Low Latency Teleoperations for NASA Exploration Missions

Human exploration of Mars will involve both crewed and robotic systems. Many mission concepts involve the deployment and assembly of mission support assets prior to crew arrival on the surface. Some of these deployment and assembly activities will be performed autonomously while others will be performed using teleoperations. However, significant communications latencies between the Earth and Mars make teleoperations challenging. Alternatively, low latency teleoperations are possible from locations in Mars orbit like Mars' moons Phobos and Deimos. To explore these latency opportunities, NASA is conducting a series of studies to investigate the effects of latency on telerobotic deployment and assembly activities. These studies are being conducted in laboratory environments at NASA's Johnson Space Center (JSC), the Human Exploration Research Analog (HERA) at JSC and the NASA Extreme Environment Mission Operations (NEEMO) underwater habitat off the coast of Florida. The studies involve two human-in-the-loop interactive simulations developed by the NASA Exploration Systems Simulations (NExSyS) team at JSC. The first simulation investigates manipulation related activities while the second simulation investigates mobility related activities. The first simulation provides a simple real-time operator interface with displays and controls for a simulated 6 degree of freedom end effector. The initial version of the simulation uses a simple control mode to decouple the robotic kinematic constraints and a communications delay to model latency effects. This provides the basis for early testing with more detailed manipulation simulations planned for the future. Subjects are tested using five operating latencies that represent teleoperation conditions from local surface operations to orbital operations at Phobos, Deimos and ultimately high Martian orbit. Subject performance is measured and correlated with three distance-to-target zones of interest. Each zone represents a target distance ranging from beyond 10m in Zone 1, through 1 cm to contact in Zone 5 with a step size factor of 10. Collected data consists of both objective simulation data (time, distance, hand controller inputs, velocity) and subjective questionnaire data. The second simulation provides a simple real-time operator interface with displays and control of a simulated surface rover. The rover traverses a synthetic Mars-like terrain and must be maneuvered to avoid obstacles while progressing to its destination. Like the manipulator simulation, subjects are tested using five operating latencies that represent teleoperation conditions from local surface operations to orbital operations at Phobos, Deimos and ultimately high Martian orbit. The rover is also operated at three different traverse speeds to assess the correlation between latency and speed. Collected data consisted of both objective simulation data (time, distance, hand controller inputs, braking) and subjective questionnaire data. These studies are exploring relationships between task complexity, operating speeds, operator efficiencies, and communications latencies for low latency teleoperations in support of human planetary exploration. This paper presents early results from these studies along with the current observations and conclusions. These and planned future studies will help to inform NASA on the potential for low latency teleoperations to support human exploration of Mars and inform the design of robotic systems and exploration missions.

Gernhardt, Michael L.↗
DOE OSTI2025

Unified Universal Control and Coordination of Inverter-Based Resources, and Validation for a PV + Battery Hybrid Plant

As renewable energy deployment grows, hybrid power plants (HPPs) combining photovoltaic (PV) and battery systems must evolve to offer both energy and grid stability services. These systems typically include a mix of grid-following (GFL) and grid-forming (GFM) inverters, presenting unique coordination and control challenges. This Department of Energy–funded project developed and validated a Unified Universal Control and Coordination (UUCC) framework for such PV + battery hybrid plants, enabling seamless and stable operation, including ultrafast black start, autonomous synchronization, and robust frequency and voltage regulation, under different grid conditions. The project significantly advanced the understanding of inverter-based resource (IBR) control by developing and validating three complementary system-level approaches for hybrid GFL/GFM operation: 1. A combined Virtual Resistance (VR)-based GFL and Virtual Oscillator Control (VOC)-based GFM method, where each inverter type is governed by a specialized control strategy. Together, these achieve stable, fast-response coordination, eliminating inrush current and enabling smooth black start and grid synchronization across a wide range of grid strengths. 2. A Deadbeat-based UUCC strategy, which uses discrete-time, switching-cycle-level control for both GFL and GFM inverters. This approach replaces traditional PI/PLL control with a control parameter-free, high-bandwidth framework that supports stable LVRT and instantaneous synchronization under all conditions. 3. A benchmark comparison with Siemens’ commercial GFM microgrid controller, which provided a fast baseline platform. The commercial approach decoupled v & f control was implemented on a commercial microgrid controller.The baseline commercial benchmark helped highlight superior transient response and black start performance offered by the deadbeat and VOC approaches. These technical contributions offer substantial improvements over conventional inverter control schemes, which often rely on slow phase-locked loop (PLL)-based synchronization, require careful control parameters tuning, and prone to unstable in weak grids with GFL inverters and in stiff grid with GFM inverters therefore challenging for hybrid GFL+GFM under all grid conditions. The deadbeat-based UUCC framework enables simpler, faster, and more robust operation of hybrid IBR systems using wide-bandgap (WBG) devices such as SiC power semiconductors. The rapid expansion of hybrid distributed energy resources (DERs), including residential and commercial PV-BESS installations such as Tesla Powerwall, PV with vehicle-to-grid (V2G) capability, and other integrated configurations, presents complex operational challenges for medium-voltage radial distribution feeders. These networks are subject to frequent disturbances such as faults, switching operations, rapid reclosing sequences, and feeder reconfigurations, all of which introduce dynamic stress on IBRs. In addition, planned feeder segmentation and deliberate islanding for resilience will require DERs that can autonomously perform blackstart, establish voltage and frequency references, and resynchronize with the main grid. The advanced deadbeat-based UUCC control and blackstart functionalities developed in this project directly address these requirements, enabling decentralized and autonomous operation of inverter-dominated DERs in distribution systems under a wide range of fault and reconfiguration scenarios. From a public benefit perspective, these innovations enable more reliable and cost-effective integration of renewable energy into distribution networks. The ability to autonomously black start and stabilize grids under varying grid conditions support accelerates recovery from outages and support decentralized resilient energy systems. By reducing system complexity and improving performance, this project lays critical groundwork for future inverter-dominated power grids that are clean, reliable, and accessible to all.

14 SOLAR ENERGY↗
NASA NTRS2020

Characterization of How CO2 Level May Impact Crew Performance Related to the HSIA Risk

Safety and mission critical anomalies are inevitable on NASA exploration missions. Delays and interruptions in communication with Earth-experts drives the requirement that crew resolve these anomalies on their own. The Human Factors and Behavioral Performance (HFBP) element of the NASA Human Research Program (HRP) recently stood-up the Human-System Integration Architecture (HSIA) risk. The specific risk statement is: “Given decreasing real-time ground support for execution of complex operations during future exploration missions, there is a possibility of adverse performance outcomes including that crew are unable to adequately respond to unanticipated critical malfunctions or detect safety critical procedural errors.” Reliable, on-board capabilities will need to support the crew - not only to resolve anomalies, but also to promote situation awareness (SA) and to reduce workload. Unfortunately, the present level of technological advancement limits the range of achievable intelligent support (Wu & Vera, 2019). The Human Capabilities Assessment for Autonomous Missions (HCAAM) projects were devised to identify how technology may benefit crew situation awareness and enhance crew trust in the intelligent systems. A suite of time-critical and complex exploration tasks have been identified (Holden et al., 2019) that may advance human-integration Concept of Operations (ConOps) development. This ConOps (a future HFBP directed task) along with standards and guidelines (Holden et al., 2019) may be used as the foundation for human-system requirements for a self-reliant crew. Spaceflight CO2 levels are elevated relative to terrestrial levels. Above 2.5 mmHg there is an increase in the incidence of crew headaches (Law et al., 2014) and Mission Control reports of mood and performance changes in the crew. The concern is that elevated CO2 effects may exacerbate the HSIA risk. Unfortunately, effects of higher concentrations of CO2 on performance decrements are not well established. The main goal of the current report is to identify how elevated CO2 impacts the HSIA risk. The approach taken is to trace the relationship between cognitive and motor abilities required for anomaly response with critical mission tasks and the level of technological advancement to support anomaly resolution to identify how elevated CO2 may impact the HSIA risk. The conclusion is that elevated CO2 could exacerbate the HSIA risk. Several research gaps are identified.

cognition↗
NASA NTRSDate not supplied

Assessment of the State of Communication Delay Research in Preparation for Missions Beyond Low Earth Orbit

NASA’s mission-operations paradigm, established during Project Mercury and minimally evolving through the Apollo Program, Space Shuttle Program, and ISS missions, has primarily depended on real-time support from a ground team of experts. This ground team has served as the safety net for crewed spaceflight missions over the past 60 years, managing the combined state of the mission, vehicle, and crew. However, this operational paradigm, which has seen little change in its Human-Systems Integration Architecture (HSIA), will face challenges during long-duration exploration missions beyond low Earth orbit. Lunar missions may experience one-way communication latencies ranging from 3 to 14 seconds, while Mars missions will encounter up to a 44-minute round-trip latency at a maximum distance from Earth. Communication delays negatively impact the behavioral health and performance of individuals and crews operating across the multi-team space-to-ground system. Previous research indicates that increased isolation and the challenges posed by delayed communication lead to heightened stress, frustration, adverse behavioral symptoms, and reduced individual performance. NASA has investigated the nature and effectiveness of managing this shift in complex operations since early 2000, but additional research is necessary to assess the issues associated with communication latencies and identify effective countermeasures. This work aimed to examine the evidence from 20 years of research on comm delays. We systematically reviewed the past 20 years of communication delay literature, focusing on how this research aligns with relevant, high-priority needs in the HSIA, Team, and BMed Risks. This type of panoramic review has not been done since 2013; a current, aggregated picture of what has been studied and how is needed to inform additional studies and mitigation development. Additional perspectives were gained from interviews with the research participants, operations experts, and communication delay researchers. Results from this effort will help characterize the risk posed by communication latency for upcoming Artemis missions and point toward potential mitigations. The final results will be presented. For the literature review, we formed a search term seed set drawing from languages used in two papers representative of the previous state of knowledge and supplemented it with additional search terms. We conducted literature searches on Google Scholar, PubMed, and Web of Science and searched NASA project archives for output from NASA-sponsored research. This search yielded 150 papers, of which 48 were relevant. SME interviews provided perspective on key communication delay issues and concerns and what is being worked on to mitigate those issues. Preliminary results of the literature review have been presented. Final results to be presented include the results of the literature review and findings from the interviews.

literature review↗