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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 NTRS2003

Revolutionary Propulsion Systems for 21st Century Aviation

The air transportation for the new millennium will require revolutionary solutions to meeting public demand for improving safety, reliability, environmental compatibility, and affordability. NASA's vision for 21st Century Aircraft is to develop propulsion systems that are intelligent, virtually inaudible (outside the airport boundaries), and have near zero harmful emissions (CO2 and Knox). This vision includes intelligent engines that will be capable of adapting to changing internal and external conditions to optimally accomplish the mission with minimal human intervention. The distributed vectored propulsion will replace two to four wing mounted or fuselage mounted engines by a large number of small, mini, or micro engines, and the electric drive propulsion based on fuel cell power will generate electric power, which in turn will drive propulsors to produce the desired thrust. Such a system will completely eliminate the harmful emissions. This paper reviews future propulsion and power concepts that are currently under development at NASA Glenn Research Center.

Sehra, Arun K.↗

NASA NTRS2012

EVA Radio DRATS 2011 Report

In the Fall of 2011, National Aeronautics and Space Administration (NASA) Glenn Research Center (GRC) participated in the Desert Research and Technology Studies (DRATS) field experiments held near Flagstaff, Arizona. The objective of the DRATS outing is to provide analog mission testing of candidate technologies for space exploration, especially those technologies applicable to human exploration of extra- terrestrial rocky bodies. These activities are performed at locations with similarities to extra-terrestrial conditions. This report describes the Extravehicular Activity (EVA) Dual-Band Radio Communication System which was demonstrated during the 2011 outing. The EVA radio system is designed to transport both voice and telemetry data through a mobile ad hoc wireless network and employs a dual-band radio configuration. Some key characteristics of this system include: 1. Dual-band radio configuration. 2. Intelligent switching between two different capability wireless networks. 3. Self-healing network. 4. Simultaneous data and voice communication.

Swank, Aaron J.↗

NASA NTRS2017

Exploring Concepts of Operations for On-Demand Passenger Air Transportation

In recent years, a surge of interest in "flying cars" for city commutes has led to rapid development of new technologies to help make them and similar on-demand mobility platforms a reality. To this end, this paper provides analyses of the stakeholders involved, their proposed operational concepts, and the hazards and regulations that must be addressed. Three system architectures emerged from the analyses, ranging from conventional air taxi to revolutionary fully autonomous aircraft operations, each with vehicle safety functions allocated differently between humans and machines. Advancements for enabling technologies such as distributed electric propulsion and artificial intelligence have had major investments and initial experimental success, but may be some years away from being deployed for on-demand passenger air transportation at scale.

Nneji, Victoria Chibuogu↗

NASA NTRS1990

Investigation of Air Transportation Technology at Princeton University, 1989-1990

The Air Transportation Technology Program at Princeton University proceeded along six avenues during the past year: microburst hazards to aircraft; machine-intelligent, fault tolerant flight control; computer aided heuristics for piloted flight; stochastic robustness for flight control systems; neural networks for flight control; and computer aided control system design. These topics are briefly discussed, and an annotated bibliography of publications that appeared between January 1989 and June 1990 is given.

Stengel, Robert F.↗

NASA NTRS2005

A Framework for Integration of IVHM Technologies for Intelligent Integration for Vehicle Management

As a part of the overall goal of developing Integrated Vehicle Health Management (IVHM) systems for aerospace vehicles, the NASA Faculty Fellowship Program (NFFP) at Marshall Space Flight Center has performed a pilot study on IVHM principals which integrates researched IVHM technologies in support of Integrated Intelligent Vehicle Management (IIVM). IVHM is the process of assessing, preserving, and restoring system functionality across flight and ground systems (NASA NGLT 2004). The framework presented in this paper integrates advanced computational techniques with sensor and communication technologies for spacecraft that can generate responses through detection, diagnosis, reasoning, and adapt to system faults in support of IIVM. These real-time responses allow the IIVM to modify the effected vehicle subsystem(s) prior to a catastrophic event. Furthermore, the objective of this pilot program is to develop and integrate technologies which can provide a continuous, intelligent, and adaptive health state of a vehicle and use this information to improve safety and reduce costs of operations. Recent investments in avionics, health management, and controls have been directed towards IIVM. As this concept has matured, it has become clear the IIVM requires the same sensors and processing capabilities as the real-time avionics functions to support diagnosis of subsystem problems. New sensors have been proposed, in addition, to augment the avionics sensors to support better system monitoring and diagnostics. As the designs have been considered, a synergy has been realized where the real-time avionics can utilize sensors proposed for diagnostics and prognostics to make better real-time decisions in response to detected failures. IIVM provides for a single system allowing modularity of functions and hardware across the vehicle. The framework that supports IIVM consists of 11 major on-board functions necessary to fully manage a space vehicle maintaining crew safety and mission objectives: Guidance and Navigation; Communications and Tracking; Vehicle Monitoring; Information Transport and Integration; Vehicle Diagnostics; Vehicle Prognostics; Vehicle mission Planning; Automated Repair and Replacement; Vehicle Control; Human Computer Interface; and Onboard Verification and Validation. Furthermore, the presented framework provides complete vehicle management which not only allows for increased crew safety and mission success through new intelligence capabilities, but also yields a mechanism for more efficient vehicle operations. The representative IVHM technologies for IIVH includes: 1) robust controllers for use in re-usable launch vehicles, 2) scaleable/flexible computer platform using heterogeneous communication, 3) coupled electromagnetic oscillators for enhanced communications, 4) Linux-based real-time systems, 5) genetic algorithms, 6) Bayesian Networks, 7) evolutionary algorithms, 8) dynamic systems control modeling, and 9) advanced sensing capabilities. This paper presents IVHM technologies developed under NASA's NFFP pilot project. The integration of these IVHM technologies forms the framework for IIVM.

Paris, Deidre E.↗

NASA NTRS1996

Energy Beam Highways Through the Skies

The emergence of Energy Beam Flight Transportation Systems could dramatically change the way we travel in the 21st Century. A framework for formulating 'Highways of Light' and the top level architectures that invoke radically new Space Power Grid infrastructure, are introduced. Basically, such flight systems, hereafter called Lightcraft, would employ off-board energy beam sources (either laser or microwave) to energize on-board dependent 'motors' -- instead of the traditional autonomous 'engines' with their on-board energy sources (e.g., chemical fuels). Extreme reductions in vehicle dry mass appear feasible with the use of off-board power and a high degree of on-board artificial intelligence. Such vehicles may no longer need airports for refueling (since they require no propellant), and could possibly pick up travelers at their homes -- before motoring over to one of many local boost stations, for the flight out. With off-board power, hyper-energetic acceleration performance and boost-glide trajectories become feasible. Hypersonic MS airbreathing propulsion can enable boosts up to twice escape velocity, which will cut trip times to the moon down to 5.5 hours. The predominant technological, environmental and social factors that will result from such transportation systems will be stressed. This presentation first introduces the remote source siting options for the space power system infrastructure, and then provides three representative laser/microwave Lightcraft options (derived from historical Case Studies): i.e., 'Acorn', 'Toy Top', and 'Disc.' Next the gamut of combined-cycle engine options developed for these Lightcraft are examined -- to illuminate the 'emerging technologies' that must be harnessed to produce flight hardware. Needed proof-of concept experiments are identified, along with the Macro-Level Issues that can springboard these revolutionary concepts into hardware reality.

Myrabo, Leik N.↗

NASA NTRS2001

1999 Bioastronomy Meeting

The 6th Bioastronomy Conference, Bioastronomy '99: A New Era in Bioastronomy, was held at the Hapuna Prince Beach hotel on the Big Island of Hawaii from August 2-6, 1999. The series of previous Bioastronomy meetings have played an important role in integrating the broader interests and techniques of both astronomy and biology to understand the origin and evolution of living systems in the universe, and to generating a context for exploration in our solar system and in extrasolar planetary systems. The scope of these interdisciplinary fields is captured in the topics discussed at the meeting: organic molecules in interstellar and interplanetary space; origin and evolution of planetary systems; comets, asteroids, and other small bodies and their role in the origin and evolution of life; Earth as a living planet; extreme environments on Earth; origin of life; transport of life between planets; evolution of life and intelligence; detection and characterization of extrasolar planets; search for extraterrestrial technology and life; future missions; and public acceptance and support of scientific studies of life in the universe.

Meech, Karen J.↗

NASA NTRS2000

"1999 Bioastronomy Meeting"

Meech, Karen J.↗

NASA NTRS2006

Intelligent Chemical Sensor Systems for In-space Safety Applications

Future in-space and lunar operations will require significantly improved monitoring and Integrated System Health Management (ISHM) throughout the mission. In particular, the monitoring of chemical species is an important component of an overall monitoring system for space vehicles and operations. For example, in leak monitoring of propulsion systems during launch, inspace, and on lunar surfaces, detection of low concentrations of hydrogen and other fuels is important to avoid explosive conditions that could harm personnel and damage the vehicle. Dependable vehicle operation also depends on the timely and accurate measurement of these leaks. Thus, the development of a sensor array to determine the concentration of fuels such as hydrogen, hydrocarbons, or hydrazine as well as oxygen is necessary. Work has been on-going to develop an integrated smart leak detection system based on miniaturized sensors to detect hydrogen, hydrocarbons, or hydrazine, and oxygen. The approach is to implement Microelectromechanical Systems (MEMS) based sensors incorporated with signal conditioning electronics, power, data storage, and telemetry enabling intelligent systems. The final sensor system will be self-contained with a surface area comparable to a postage stamp. This paper discusses the development of this "Lick and Stick" leak detection system and it s application to In-Space Transportation and other Exploration applications.

Hunter, G. W.↗

DOE OSTI2021

Building Intelligent Cyberinfrastructure to Learn Iteratively from both Observations and Models for Understanding Watershed Dynamics

Focal Area(s): Predictive modeling through the use of AI techniques and AI-derived model components; the use of AI and other tools to design a prediction system comprising of a hierarchy of models (e.g., AI-driven model/component/parameterization selection). Science Challenge: Watershed processes, such as the fate and transport of sediment, carbon and nutrients across landscapes and their fluxes to water bodies (e.g., streams, rivers and lakes), have important implications for global and regional carbon and nutrient dynamics, biogeochemical functioning of terrestrial ecosystems, and soil functions. The magnitude of lateral surface/subsurface transport and fluxes of sediment, carbon and nutrients are key factors controlling the vulnerability of watersheds to climate extremes such as droughts, wildfires, and floods. Recent field observations and other scientific evidence suggest that the magnitudes of lateral transport and fluxes of sediment, carbon and nutrients are governed primarily by the spatial and vertical heterogeneity of landscape and soil properties and by pedogenic processes. However, the current generation of land surface and watershed models do not mechanistically couple the terrestrial and hydrologic systems, nor do they represent sufficiently the spatial and vertical heterogeneity of land surface and subsurface properties. On the other hand, increasing complexity of coupled watershed and land surface models requires more data to parameterize, calibrate and validate. Remote sensing (RS) provides a means to acquire spatial data and characterize their heterogeneity at the watershed scale, overcoming a major limitation associated with conventional point measurements. To improve the representation of land-surface and surface/subsurface process coupling and sub-grid heterogeneity in watershed models, it is essential to build our predictive understanding by learning from both the multi-scale multi-process modeling and diverse multi-scale data while leveraging powerful artificial intelligence (AI) techniques.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2001

Secure Large-Scale Airport Simulations Using Distributed Computational Resources

To fully conduct research that will support the far-term concepts, technologies and methods required to improve the safety of Air Transportation a simulation environment of the requisite degree of fidelity must first be in place. The Virtual National Airspace Simulation (VNAS) will provide the underlying infrastructure necessary for such a simulation system. Aerospace-specific knowledge management services such as intelligent data-integration middleware will support the management of information associated with this complex and critically important operational environment. This simulation environment, in conjunction with a distributed network of supercomputers, and high-speed network connections to aircraft, and to Federal Aviation Administration (FAA), airline and other data-sources will provide the capability to continuously monitor and measure operational performance against expected performance. The VNAS will also provide the tools to use this performance baseline to obtain a perspective of what is happening today and of the potential impact of proposed changes before they are introduced into the system.

McDermott, William J.↗

NASA NTRS2004

A Probabilistic Assessment of NASA Ultra-Efficient Engine Technologies for a Large Subsonic Transport

NASA's Ultra Efficient Engine Technology (UEET) program features advanced aeropropulsion technologies that include highly loaded turbomachinery, an advanced low-NOx combustor, high-temperature materials, intelligent propulsion controls, aspirated seal technology, and an advanced computational fluid dynamics (CFD) design tool to help reduce airplane drag. A probabilistic system assessment is performed to evaluate the impact of these technologies on aircraft fuel burn and NOx reductions. A 300-passenger aircraft, with two 396-kN thrust (85,000-pound) engines is chosen for the study. The results show that a large subsonic aircraft equipped with the UEET technologies has a very high probability of meeting the UEET Program goals for fuel-burn (or equivalent CO2) reduction (15% from the baseline) and LTO (landing and takeoff) NOx reductions (70% relative to the 1996 International Civil Aviation Organization rule). These results are used to provide guidance for developing a robust UEET technology portfolio, and to prioritize the most promising technologies required to achieve UEET program goals for the fuel-burn and NOx reductions.

Tong, Michael T.↗

NASA NTRS1980

Upgrading the free flying rendezvous and docking simulator and the orbital servicer system

Recommendations are made for upgrading two teleoperator/robotics test and simulation systems based upon a review of latest technology advances in the involved disciplines. A second generation Free Flying Mobility Unit is recommended which adds a sixth degree of freedom and incorporates other improvements which greatly expand the center's capability to perform evaluation tests and demonstrations of advanced systems concepts for rendezvous and docking in support of the Teleoperator Maneuvering System (TMS) Program. The Orbital Servicer System provides the capability for testing and demonstrating concepts for on orbit servicing of compatibly designed satellites/payloads. The TMS is to be the transporting vehicle for the servicer. The manipulator arm of the Orbital service System is presently computer controlled in the trajectory portion of the module transfer operation. The ultimate objective is to fully automte its operation requiring additional capabilities in sensors, artificial intelligence, image analysis, communications, computer programming, pattern recognition, kinematics, and manipulator design. It is recommended that the Electronics and Control Laboratory move to acquire the basic competencies in robotics necessary to achieve full automation.

Eastman, R. M.↗

DOE OSTI2025

Beyond the four core effects: revisiting thermoelectrics with a high-entropy design

Low-exergy waste heat, which constitutes the majority of industrial-scale thermal losses, remains largely unrecoverable with conventional technologies. Thermoelectrics offer a solid-state solution for converting this hard-to-access energy into electricity, making them attractive for decentralized power generation and sensor applications. High-entropy materials (HEMs) have gained traction as a strategy for better-performing thermoelectrics, but the mechanisms driving their benefits require further exploration. This article highlights key insights for heat and electronic transport in HEMs. For heat transport, we argue that reduced, and often ultralow, lattice thermal conductivity in HEMs—with respect to ordered counterparts—can be taken for granted, emerging naturally as a fifth core effect of high-entropy systems. While band convergence is often considered beneficial for electronic transport, its impact depends strongly on the electronic structure. We summarize the scenarios where it can be detrimental to thermoelectric performance. These insights motivate strategies that align seamlessly with advancements in artificial intelligence and data-driven approaches, helping accelerate the discovery of next-generation thermoelectric materials.

Oses, Corey [Johns Hopkins Univ., Baltimore, MD (U↗

NASA NTRS1990

Automatic Speech Recognition in Air Traffic Control: a Human Factors Perspective

The introduction of Automatic Speech Recognition (ASR) technology into the Air Traffic Control (ATC) system has the potential to improve overall safety and efficiency. However, because ASR technology is inherently a part of the man-machine interface between the user and the system, the human factors issues involved must be addressed. Here, some of the human factors problems are identified and related methods of investigation are presented. Research at M.I.T.'s Flight Transportation Laboratory is being conducted from a human factors perspective, focusing on intelligent parser design, presentation of feedback, error correction strategy design, and optimal choice of input modalities.

Karlsson, Joakim↗

DOE OSTI2024

Analysis of Automated Transit Network Systems with Battery-Electric Vehicles in Automated Mobility Districts: Preprint

The paper provides an overview of the insights and findings of the National Renewable Energy Laboratory's (NREL) ongoing research on the implementation of automated mobility districts (AMDs). AMD is a term coined by NREL to describe a geographically defined district or major activity center located in a dense urban setting with mobility applications provided by automated/autonomous vehicle (AV) systems spanning internal circulation and first-mile/last-mile connections to regional transportation hubs. Research over the past five years has focused on understanding the evolution of AMDs, beginning with demonstrations of automated shuttles prior to the pandemic, to more integrated on-demand mobility systems currently in initial stages of deployment. Initial insights and findings from earlier studies include the need for designation of a "jurisdiction having authority," a clear vision of a complete system to provide end-to-end mobility services, and the requisite intelligent infrastructure to complement AV technology. NREL's most recent Phase III research investigates station boarding/alighting (curb) issues, the full electrification of fleets, and the need for a systems engineering methodology (SEM) to properly analyze the complexities resulting from the convergence of automation, on-demand mobility, and electrification of the transit systems within the AMD. The paper reviews the findings of AMD research conducted during Phase I, II, and III, with special emphasis on Phase III results with respect to a descriptive example of the proposed SEM when a "digital twin" analytical model is used to simulate the transport fleet's battery-electric vehicle miles of travel and associated duty cycles through a rigorous analytical assessment with a comprehensive modeling process.

ADVANCED PROPULSION SYSTEMS↗

NASA NTRS2005

IVHM Framework for Intelligent Integration for Vehicle Health Management

Integrated Vehicle Health Management (IVHM) systems for aerospace vehicles, is the process of assessing, preserving, and restoring system functionality across flight and techniques with sensor and communication technologies for spacecraft that can generate responses through detection, diagnosis, reasoning, and adapt to system faults in support of Integrated Intelligent Vehicle Management (IIVM). These real-time responses allow the IIVM to modify the affected vehicle subsystem(s) prior to a catastrophic event. Furthermore, this framework integrates technologies which can provide a continuous, intelligent, and adaptive health state of a vehicle and use this information to improve safety and reduce costs of operations. Recent investments in avionics, health management, and controls have been directed towards IIVM. As this concept has matured, it has become clear that IIVM requires the same sensors and processing capabilities as the real-time avionics functions to support diagnosis of subsystem problems. New sensors have been proposed, in addition to augment the avionics sensors to support better system monitoring and diagnostics. As the designs have been considered, a synergy has been realized where the real-time avionics can utilize sensors proposed for diagnostics and prognostics to make better real-time decisions in response to detected failures. IIVM provides for a single system allowing modularity of functions and hardware across the vehicle. The framework that supports IIVM consists of 11 major on-board functions necessary to fully manage a space vehicle maintaining crew safety and mission objectives. These systems include the following: Guidance and Navigation; Communications and Tracking; Vehicle Monitoring; Information Transport and Integration; Vehicle Diagnostics; Vehicle Prognostics; Vehicle Mission Planning, Automated Repair and Replacement; Vehicle Control; Human Computer Interface; and Onboard Verification and Validation. Furthermore, the presented framework provides complete vehicle management which not only allows for increased crew safety and mission success through new intelligence capabilities, but also yields a mechanism for more efficient vehicle operations.

Paris, Deidre↗

NASA NTRS2017

Semi-Supervised Learning of Lift Optimization of Multi-Element Three-Segment Variable Camber Airfoil

This chapter describes a new intelligent platform for learning optimal designs of morphing wings based on Variable Camber Continuous Trailing Edge Flaps (VCCTEF) in conjunction with a leading edge flap called the Variable Camber Krueger (VCK). The new platform consists of a Computational Fluid Dynamics (CFD) methodology coupled with a semi-supervised learning methodology. The CFD component of the intelligent platform comprises of a full Navier-Stokes solution capability (NASA OVERFLOW solver with Spalart-Allmaras turbulence model) that computes flow over a tri-element inboard NASA Generic Transport Model (GTM) wing section. Various VCCTEF/VCK settings and configurations were considered to explore optimal design for high-lift flight during take-off and landing. To determine globally optimal design of such a system, an extremely large set of CFD simulations is needed. This is not feasible to achieve in practice. To alleviate this problem, a recourse was taken to a semi-supervised learning (SSL) methodology, which is based on manifold regularization techniques. A reasonable space of CFD solutions was populated and then the SSL methodology was used to fit this manifold in its entirety, including the gaps in the manifold where there were no CFD solutions available. The SSL methodology in conjunction with an elastodynamic solver (FiDDLE) was demonstrated in an earlier study involving structural health monitoring. These CFD-SSL methodologies define the new intelligent platform that forms the basis for our search for optimal design of wings. Although the present platform can be used in various other design and operational problems in engineering, this chapter focuses on the high-lift study of the VCK-VCCTEF system. Top few candidate design configurations were identified by solving the CFD problem in a small subset of the design space. The SSL component was trained on the design space, and was then used in a predictive mode to populate a selected set of test points outside of the given design space. The new design test space thus populated was evaluated by using the CFD component by determining the error between the SSL predictions and the true (CFD) solutions, which was found to be small. This demonstrates the proposed CFD-SSL methodologies for isolating the best design of the VCK-VCCTEF system, and it holds promise for quantitatively identifying best designs of flight systems, in general.

Intelligent Systems↗