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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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NASA NTRS1996

From Aeronautics to Space: Lessons in Human Automation

Civilian air flight continues on a growth curve, as more and more people utilize air travel to meet business and personal travel needs: This consumer-driven demand has resulted in the adoption of new methods to increase air system capacity and to make the air transportation system increasingly more efficient. As a consequence, civilian aviation, as an industry, has assumed a leading role in the use of automated systems, and, by implication, in the understanding of how human openers interact with these systems. Aeronautical automation systems serve a variety of roles. These include controlling aircraft and aiding, advising and monitoring numerous functions in the aircraft/airspace system. Experiences in the use of human/automation systems gathered from aviation are, in many cases, generalizable to other industries having similar requirements for human and non-human intelligent system interaction. However, the human/automation lessons learned from aviation have special relevance to the space application, where many of the same operational demands prevail. The application of aeronautical lessons of human-automated interaction to spaceflight is the subject of this paper. The discussion will address: the progress that has been made through aeronautically-based research and experience in understanding human/automation interaction, ways that this understanding can be applied to the needs of space, and the limits of our present understanding of human/automations systems. Suggestions will be offered related to human-automation research generally, and to the particular needs of the space endeavor.

Connors, Mary M.↗

NASA NTRS2021

ATTRACTOR: Autonomy Teaming and TRAjectories for Complex Trusted Operational Reliability

Autonomous systems (AS) are crucial to realizing the vision of new, complex transportation modes, such as advanced air mobility (AAM) and urban air mobility (UAM). A chief barrier to induction of AS into aviation is insufficient understanding of AS reliability in time-critical and safety-critical environments—an obstacle to certification. ATTRACTOR is aimed at building a basis for certification of classes of autonomous cyber-physical-human systems (CPHS) via establishing metrics and models of trustworthiness and trust in multi-agent team interactions, analyzable trajectories, explainability of computational algorithms (explainable artificial intelligence, or XAI), and persistent modeling and simulation, in the context of missions planning and operation. By “building a basis for certification,” we mean acquiring an understanding of when a system is trustworthy and developing computable means to estimate trustworthiness and trust in order to eventually inform functional requirements that contribute to certification. The outcomes are applicable not just to aviation but to all domains that rely on autonomous systems.

Autonomy↗

NASA NTRS1979

Space Shuttle Solid Rocket Booster decelerator subsystem - Air drop test vehicle/B-52 design

The air drop development test program for the Space Shuttle Solid Rocket Booster Recovery System required the design of a large drop test vehicle that would meet all the stringent requirements placed on it by structural loads, safety considerations, flight recovery system interfaces, and sequence. The drop test vehicle had to have the capability to test the drogue and the three main parachutes both separately and in the total flight deployment sequence and still be low-cost to fit in a low-budget development program. The design to test large ribbon parachutes to loads of 300,000 pounds required the detailed investigation and integration of several parameters such as carrier aircraft mechanical interface, drop test vehicle ground transportability, impact point ground penetration, salvageability, drop test vehicle intelligence, flight design hardware interfaces, and packaging fidelity.

Runkle, R. E.↗

NASA NTRSDate not supplied

SafeAeroBERT: Towards a Safety-Informed Aerospace-Specific Language Model

As aviation systems continue to operate with high traffic, large amounts of documents containing safety-relevant data continue to be generated via reporting systems such as the Aviation Safety Reporting System (ASRS). Advanced natural language processing techniques, specifically pre-trained language models, have shown great success in domain-specific applications; however, the text in aviation safety reports is inundated with jargon and thus not fully utilized by general pre-trained models. In this research, we work towards developing a safety-informed aerospace-specific language model by pre-training a Bidirectional Encoder Representations from Transformer (BERT) model on reports from the Aviation Safety Reporting System and the National Transportation Safety Board. The resulting model, called SafeAeroBERT, is fine-tuned for the specific task of document classification, and can be further tuned for named-entity recognition, relation detection, information retrieval, and summarization. Results from the classification task are compared between SafeAeroBERT, the base BERT, and SciBERT models and show SafeAeroBERT outperforms the general BERT and SciBERT on classifying reports about weather and procedure. SafeAeroBERT can be used on custom tasks, not limited to document classification, and is intended to aid an intelligent knowledge manager for safety report repositories.

Aviation↗

NASA NTRS1993

A fuzzy logic controller for an autonomous mobile robot

The ability of a mobile robot system to plan and move intelligently in a dynamic system is needed if robots are to be useful in areas other than controlled environments. An example of a use for this system is to control an autonomous mobile robot in a space station, or other isolated area where it is hard or impossible for human life to exist for long periods of time (e.g., Mars). The system would allow the robot to be programmed to carry out the duties normally accomplished by a human being. Some of the duties that could be accomplished include operating instruments, transporting objects, and maintenance of the environment. The main focus of our early work has been on developing a fuzzy controller that takes a path and adapts it to a given environment. The robot only uses information gathered from the sensors, but retains the ability to avoid dynamically placed obstacles near and along the path. Our fuzzy logic controller is based on the following algorithm: (1) determine the desired direction of travel; (2) determine the allowed direction of travel; and (3) combine the desired and allowed directions in order to determine a direciton that is both desired and allowed. The desired direction of travel is determined by projecting ahead to a point along the path that is closer to the goal. This gives a local direction of travel for the robot and helps to avoid obstacles.

Yen, John↗

NASA NTRS2017

Real Time Safety Monitoring: Concept for Supporting Safe Flight Operations

A number of organizations are working on processes, procedures, regulations, and technologies to maintain or improve the safety of the National Airspace System (NAS). In this paper, we describe a Real Time Safety Monitoring (RTSM) system that benefits from these efforts to define a set of safety metrics that are automatically monitored in real-time. In addition to providing information about current potentially adverse conditions to a variety of users, from those who need a broad overview of a day's flight operations to those who need to decide on a control tactic to employ in the next five minutes, the RTSM system predicts conditions within a specified prediction horizon. Its intelligent interface alerts the user, presenting the information as appropriate considering the current context and circumstances. We illustrate the system concept with five conceptual use cases, describing which safety metrics may be of the most interest to five user groups and suggesting a multi-modal display format. We posit that having access to information about adverse conditions in time to make efficient preemptive decisions without sacrificing safety will improve the already high level of safety and aid in the expansion planned for the NAS under the Next Generation Air Transportation System (NextGen).

safety↗

DOE OSTI2024

Multiparameter optical fiber sensing for energy infrastructure through nanoscale light–matter interactions: From hardware to software, science to commercial opportunities

Monitoring of energy infrastructure through robust yet economical sensing platforms is becoming an area of increased importance, with ubiquitous applications including the electrical grid, natural gas and oil transportation pipelines, H2 infrastructure (storage and transportation), carbon storage, power generation, and subsurface environments. Plasmonic and functional nanomaterial enabled fiber optic sensors show excellent promise for a wide range of sensing applications due to their versatility to be engineered for specific analytes of interest while retaining inherent advantages of the optical fiber sensor platform. Through the design of novel sensing layers, the optical transduction mechanism and wavelength dependence can also be tailored for ease of integration with low-cost interrogation systems enabling an inexpensive yet highly functional optical fiber sensing platform. In addition, recent advances in artificial intelligence and machine learning theoretical methods have been leveraged to simultaneously extract multiple parameters through multi-wavelength interrogation such that unique wavelengths can also serve as unique sensing elements, analogous to electronic nose sensor technologies. The concept of an optical fiber based “photonic nose” via multiple interrogation wavelengths and/or sensor nodes offers a compelling platform technology to realize multiparameter speciation of chemical analytes within complex gas mixtures. In this Perspective, we further generalize the notion of multiparameter sensing through the novel “photonic nervous system” concept based upon low-cost, functionalized optical fiber sensor probes monitoring a variety of distinct analyte classes (physical, chemical, electromagnetic, etc.) simultaneously to provide broad situational awareness via integrated sensors.

Su, Yang-Duan (ORCID:0000000214820902)↗

NASA NTRSDate not supplied

Data Augmentation for Intelligent Contingency Management Using Generative Adversarial Neural Networks

Artificial intelligence (AI)-based techniques for intelligent contingency management (ICM) require that intelligent agents learn various aspects of system dynamics to create and execute contingencies. For high assurance contingency management, agents achieve the most compelling results through supervised or semi-supervised machine learning, for which agents require large datasets to learn the dynamics of the system. Unfortunately, data collection in aerospace applications can be costly, due to both time and resources. Presented work describes a framework for data augmentation of ICM databases containing training data for machine learning models. This framework populates the database with the outputs of generative adversarial network (GAN) models that were trained on flight data. Methods for evaluating the suitability of these models based on the equations of motion, as well as other physical constraints, are discussed. The paper demonstrates the utility of this database for training intelligent agents on the NASA T2 generic transport aircraft model and experimental vertical takeoff and landing (VTOL) simulation model.

Generative Machine Learning↗

NASA NTRSDate not supplied

Data Augmentation for Intelligent Contingency Management Using Generative Adversarial Neural Networks

Generative Machine Learning↗

NASA NTRS2015

On-Demand Mobility (ODM) Technical Pathway: Enabling Ease of Use and Safety

On-demand mobility (ODM) through aviation refers to the ability to quickly and easily move people or equivalent cargo without delays introduced by lack of, or infrequently, scheduled service. A necessary attribute of ODM is that it be easy to use, requiring a minimum of special training, skills, or workload. Fully-autonomous vehicles would provide the ultimate in ease-of-use (EU) but are currently unproven for safety-critical applications outside of a few, situationally constrained applications (e.g. automated trains operating in segregated systems). Applied to aviation, the current and near-future state of the art of full-autonomy, may entail undesirable trade-offs such as very conservative operational margins resulting in reduced trip reliability and transportation utility. Furthermore, acceptance by potential users and regulatory authorities will be challenging without confidence in autonomous systems in developed in less critical, but still challenging applications. A question for the aviation community is how we can best develop practical ease-of-use for aircraft that are sized to carry a small number of passengers (e.g. 1-9) or equivalent cargo. Such development is unlikely to be a single event, but rather a managed, evolutionary process where responsibility and authority transitions from human to automation agents as operational experience is gained with increasingly intelligent systems. This talk presents a technology road map being developed at NASA Langley, as part of an overall strategy to foster ODM, for the development of ease-of-use for ODM aviation.

Goodrich, Ken↗

DOE OSTI2023

Exploring NaCl-PuCl 3 molten salts with machine learning interatomic potentials and graph theory

Actinide molten salts are the basis of the liquid fuels used in molten salt reactors. Due to the inherent difficulties associated with high temperature and hazardous conditions, experimental investigations of fundamental properties of these materials are usually challenging. In this work, we describe the structure and transport of NaCl-PuCl 3 mixtures using computational techniques. Three compositions were considered (16, 25, and 36 mol% PuCl 3 ) over a temperature range (730 – 1257K) using ab initio molecular dynamics, which provided the necessary data sets for training machine learned interatomic potentials. Further, molecular dynamics simulations based on these potentials were then used to determine structure and transport properties. A substantial change was noted in the structure factor when increasing the PuCl 3 content from 25 to 36 mol%. This change is linked to the aggregation of larger Pu 3+ clusters. In addition, the similarity of the atomic environments of metal cations in molten salt systems to their solid states counterparts was investigated using an unsupervised learning technique. Finally, graph theory was employed to explore the structure and size of actinide networks. Consistent with the structure factor, a dense Pu 3+ intermolecular structure is observed within the 36 mol% PuCl 3 mixture. The structure of cation-cation inter-junctions is also discussed. In all cases, the diffusion of Pu 3+ is significantly lower than that of Na + and Cl - .

36 MATERIALS SCIENCE↗

DOE OSTI2025

Roadmap on thermodynamics and thermal metamaterials

Thermal metamaterials represent a transformative paradigm in modern physics, synergizing thermodynamic principles with metamaterial engineering to master heat flow at will. As next-generation technologies demand multi-scale thermal control, this field urgently requires systematic frameworks to unify its multidisciplinary advances. Curated through a global collaboration involving over 50 specialists across 25 subdisciplines, this review primarily summarizes two decades of advancements, ranging from theoretical breakthroughs to functional implementations. The review reveals groundbreaking innovations in heat manipulation through the exploration of both classical and non-classical transport regimes, topological thermal control mechanisms, and quantum-informed phonon engineering strategies. By bridging physical insights like non-Hermitian thermal dynamics and valleytronic phonon transport with cutting-edge applications, we demonstrate paradigm-shifting capabilities: environment-adaptive thermal cloaks, AI-optimized metamaterials, and nonlinear thermal circuits enabling heat-based computation. Experimental milestones include 3D thermal null media with reconfigurable invisibility and thermal designs breaking classical conductivity limits. Here, this collaborative effort establishes an indispensable roadmap for physicists, highlighting pathways to quantum thermal management, entropy-controlled energy systems, and topological devices. As thermal metamaterials transition from laboratory marvels to technological cornerstones, this work provides the foundational lexicon and design principles for the coming era of intelligent thermal matter.

heat conduction control↗

NASA NTRS1991

Knowledge-based decision support for Space Station assembly sequence planning

A complete Personal Analysis Assistant (PAA) for Space Station Freedom (SSF) assembly sequence planning consists of three software components: the system infrastructure, intra-flight value added, and inter-flight value added. The system infrastructure is the substrate on which software elements providing inter-flight and intra-flight value-added functionality are built. It provides the capability for building representations of assembly sequence plans and specification of constraints and analysis options. Intra-flight value-added provides functionality that will, given the manifest for each flight, define cargo elements, place them in the National Space Transportation System (NSTS) cargo bay, compute performance measure values, and identify violated constraints. Inter-flight value-added provides functionality that will, given major milestone dates and capability requirements, determine the number and dates of required flights and develop a manifest for each flight. The current project is Phase 1 of a projected two phase program and delivers the system infrastructure. Intra- and inter-flight value-added were to be developed in Phase 2, which has not been funded. Based on experience derived from hundreds of projects conducted over the past seven years, ISX developed an Intelligent Systems Engineering (ISE) methodology that combines the methods of systems engineering and knowledge engineering to meet the special systems development requirements posed by intelligent systems, systems that blend artificial intelligence and other advanced technologies with more conventional computing technologies. The ISE methodology defines a phased program process that begins with an application assessment designed to provide a preliminary determination of the relative technical risks and payoffs associated with a potential application, and then moves through requirements analysis, system design, and development.

Source record↗

NASA NTRS2018

Propulsion Control Technology Development Needs to Address NASA Aeronautics Research Mission Goals for Thrusts 3a and 4

The Commercial Aero-Propulsion Control Working Group (CAPCWG), consisting of propulsion control technology leads from The Boeing Company, GE Aviation, Honeywell, Pratt & Whitney, Rolls-Royce, and NASA (National Aeronautics and Space Administration) Glenn Research Center, has been working together over the past year to identify propulsion control technology areas of common interest that we believe are critical to achieving the challenging NASA Aeronautics Research goals for Thrust 3a: Ultra-Efficient Commercial Vehicles - Subsonic Transports, and Thrust 4: Transition to Alternative Propulsion and Energy. This paper describes the various propulsion control technology development areas identified by CAPCWG as most critical for NASA to invest in. For Thrust 3a these are: i) Integrated On-Board Model Based Engine Control and Health Management; ii) Flexible and Modular Networked Control Hardware and Software Architecture; iii) Intelligent Air/Fuel Control for Low Emissions Combustion; and iv) Active Clearance Control. For Thrust 4a, the focus is on Hybrid Electric Propulsion (HEP) for single aisle commercial aircraft. The specific technology development areas include: i) Integrated Power and Propulsion System Dynamic Modeling for Control; ii) Control Architectures for HEP; iii) HEP Control Verification and Validation; and iv) Engine/Airplane Control Integration. For each of the technology areas, the discussion includes: problem to be solved and how it relates to NASA goals, and the challenges to be addressed in reducing risk.

Propulsion Control↗

DOE OSTI2022

Computational optimal transport for molecular spectra: The semi-discrete case

Comparing a discrete molecular spectrum to a continuous molecular spectrum in a quantitative manner is a challenging problem, for example, when attempting to fit a theoretical stick spectrum to a continuous spectrum. In this paper, the use of computational optimal transport is investigated for such a problem. In the optimal transport literature, the comparison of a discrete and a continuous spectrum is referred to as semi-discrete optimal transport and is a situation where a metric such as least-squares may be difficult to define except under special conditions. The merits of an optimal transport approach for this problem are investigated using the transport distance defined for the semi-discrete case. A tutorial on semi-discrete optimal transport for molecular spectra is included in this paper, and several well-chosen synthetic spectra are investigated to demonstrate the utility of computational optimal transport for the semi-discrete case. Among several types of investigations, we include calculations showing how the frequency resolution of the continuous spectrum affects the transport distance between a discrete and a continuous spectrum. We also use the transport distance to measure the distance between a continuous experimental electronic absorption spectrum of SO 2 and a theoretical stick spectrum for the same system. The comparison of the theoretical and experimental SO 2 spectra also allows us to suggest a theoretical value for the band origin that is closer to the observed band origin than previous theoretical values.

74 ATOMIC AND MOLECULAR PHYSICS↗

NASA NTRS2015

NASA Ames Sustainability Initiatives: Aeronautics, Space Exploration, and Sustainable Futures

In support of the mission-specific challenges of aeronautics and space exploration, NASA Ames produces a wealth of research and technology advancements with significant relevance to larger issues of planetary sustainability. NASA research on NexGen airspace solutions and its development of autonomous and intelligent technologies will revolutionize both the nation's air transporation systems and have applicability to the low altitude flight economy and to both air and ground transporation, more generally. NASA's understanding of the Earth as a complex of integrated systems contributes to humanity's perception of the sustainability of our home planet. Research at NASA Ames on closed environment life support systems produces directly applicable lessons on energy, water, and resource management in ground-based infrastructure. Moreover, every NASA campus is a 'city'; including an urbanscape and a workplace including scientists, human relations specialists, plumbers, engineers, facility managers, construction trades, transportation managers, software developers, leaders, financial planners, technologists, electricians, students, accountants, and even lawyers. NASA is applying the lessons of our mission-related activities to our urbanscapes and infrastructure, and also anticipates a leadership role in developing future environments for living and working in space.

Planetary futures↗

NASA NTRS1978

Laboratory and community studies of aircraft noise effects

The noise effects programs objective is to develop aircraft noise criteria and noise reduction methods for achieving greater community and passenger acceptance of air transportation systems. The approach consists of laboratory tests to subjectively evaluate the properties of aircraft-generated noise that are responsible for causing annoyance and field surveys to study the broader problems of community and passenger acceptability. The program is organized into two major thrusts: community acceptance and passenger acceptance. The community acceptance includes subjective response studies of single and multiple aircraft overflights as well as longer term community noise exposure. Emphasis is on the development of units and indices which accurately quantify annoyance. The passenger acceptance program includes studies to determine acceptably levels of interior noise and vibration for speech intelligibility and comfort of crew and passengers. Selected results from several recent studies are presented to indicate the nature, scope, and methods of the research program.

Stephens, D. G.↗

DOE OSTI2025

Artificial intelligence-based predictive modeling for imaging neutral particle analyzers on the DIII-D tokamak

The Imaging Neutral Particle Analyzer (INPA) at DIII-D is a diagnostic system used to accurately resolve the energy and spatial distributions of fast ions in fusion plasmas. A novel artificial intelligence (AI) technique named INPA-net is based on Reservoir Computing Networks and developed here to predict active and passive signals produced by charge-exchange reactions from injected and edge-cold neutrals, respectively, in magnetically confined fusion plasmas. This model is trained using a set of 21 time domain signals between 0 s to 3.35 s that includes injected beam and thermal plasma information, and 6444 real 2D experimental images of the INPA in 12 plasma discharges at DIII-D. The trained neural network is able to forecast experimental images in real-time. The model achieves an R-squared value of 0.91, which is higher than the 0.83 value achieved by a simple linear regression model. This improvement highlights the model's enhanced predictive accuracy for measured images from the validation set. This AI approach is valuable due to its rapid response times and potential for integration into real-time plasma control systems. A version of this model capable of generating syntehic images would be useful for the real-time monitoring of fast-ion transport. A comprehensive sensitivity study reveals that INPA-net maintains high performance even with variations in the input parameters, indicating the model's robustness and reliability. While developed for the INPA, the underlying architecture is adaptable and may be applied to various 2D imaging diagnostics in fusion research.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗