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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 757 records · Page 42
All sourcesNASA NTRSDOE OSTI
NASA NTRS1997

Neural Network Based Sensory Fusion for Landmark Detection

NASA is planning to send numerous unmanned planetary missions to explore the space. This requires autonomous robotic vehicles which can navigate in an unstructured, unknown, and uncertain environment. Landmark based navigation is a new area of research which differs from the traditional goal-oriented navigation, where a mobile robot starts from an initial point and reaches a destination in accordance with a pre-planned path. The landmark based navigation has the advantage of allowing the robot to find its way without communication with the mission control station and without exact knowledge of its coordinates. Current algorithms based on landmark navigation however pose several constraints. First, they require large memories to store the images. Second, the task of comparing the images using traditional methods is computationally intensive and consequently real-time implementation is difficult. The method proposed here consists of three stages, First stage utilizes a heuristic-based algorithm to identify significant objects. The second stage utilizes a neural network (NN) to efficiently classify images of the identified objects. The third stage combines distance information with the classification results of neural networks for efficient and intelligent navigation.

Kumbla, Kishan -K.↗
NASA NTRS2010

Flight Testing of the TWiLiTE Airborne Molecular Doppler Lidar

In September, 2009 the TWiLiTE (Tropospheric Wind Lidar Technology Experiment) direct detection Doppler lidar was integrated for engineering flight testing on the NASA ER-2 high altitude aircraft. The TWiI,iTE Doppler lidar measures vertical profiles of wind by transmitting a short ultraviolet (355 nm) laser pulse into the atmosphere, collecting the laser light scattered back to the lidar by air molecules and measuring the Doppler shifted frequency of that light. The magnitude of the Doppler shift is proportional to the wind speed of the air in the parcel scattering the laser light. TWiLiTE was developed with funding from the NASA Earth Science Technology Office (ESTO) Instrument Incubator Program (11P). The primary objectives of the TWiLiTE program are twofold: 1) to advance the development of key technologies and subsystems critical for a future space based Global 3-1) Wind Mission, as recommended by the National Research Council in the recent Decadal Survey for Earth Science [1] and 2) to develop, for the first time, a fully autonomous airborne Doppler lidar and to demonstrate tropospheric wind profile measurements from a high altitude downward looking, moving platform to simulate spaceborne measurements. In this paper we will briefly describe the instrument followed by a discussion of the results from the 2009 engineering test flights

Gentry, Bruce↗
NASA NTRS2018

Verification and Validation Challenges for Adaptive Flight Control of Complex Autonomous Systems

Autonomy of aerospace systems requires the ability for flight control systems to be able to adapt to complex uncertain dynamic environment. In spite of the five decades of research in adaptive control, the fact still remains that currently no adaptive control system has ever been deployed on any safety-critical or human-rated production systems such as passenger transport aircraft. The problem lies in the difficulty with the certification of adaptive control systems since existing certification methods cannot readily be used for nonlinear adaptive control systems. Research to address the notion of metrics for adaptive control began to appear in the recent years. These metrics, if accepted, could pave a path towards certification that would potentially lead to the adoption of adaptive control as a future control technology for safety-critical and human-rated production systems. Development of certifiable adaptive control systems represents a major challenge to overcome. Adaptive control systems with learning algorithms will never become part of the future unless it can be proven that they are highly safe and reliable. Rigorous methods for adaptive control software verification and validation must therefore be developed to ensure that adaptive control system software failures will not occur, to verify that the adaptive control system functions as required, to eliminate unintended functionality, and to demonstrate that certification requirements imposed by regulatory bodies such as the Federal Aviation Administration (FAA) can be satisfied. This presentation will discuss some of the technical issues with adaptive flight control and related V&V challenges.

Nguyen, Nhan T.↗
NASA NTRS2020

Robotic Specialization in Autonomous Robotic Structural Assembly

Robotic in-space assembly of large space structures is a long-term NASA goal to reduce launch costs and enable larger scale missions. Recently, researchers have proposed using discrete lattice building blocks and co-designed robots to build high-performance, scalable primary structure for various on-orbit and surface applications. These robots would locomote on the lattice and work in teams to build and reconfigure building-blocks into functional structure. However, the most reliable and efficient robotic system architecture, characterized by the number of different robotic 'species' and the allocation of functionality between species, is an open question. To address this problem, we decompose the robotic building-block assembly task into functional primitives and, in simulation, study the performance of the the variety of possible resulting architectures. For a set consisting of five process types (move self, move block, move friend, align bock, fasten block), we describe a method of feature space exploration and ranking based on energy and reliability cost functions. The solution space is enumerated, filtered for unique solutions, and evaluated against energy and reliability cost functions for various simulated build sizes. We find that a 2 species system, dividing the five mentioned process types between one unit cell transport robot and one fastening robot, results in the lowest energy cost system, at some cost to reliability. This system enables fastening functionality to occupy the build front while reducing the need for that functional mass to travel back and forth from a feed station. Because the details of a robot design affect the weighting and final allocation of functionality, a sensitivity analysis was conducted to evaluate the effect of changing mass allocations on architecture performance. Future systems with additional functionalities such as repair, inspection, and others may use this process to analyze and determine alternative robot architectures.

Bernus, Borbala↗
NASA NTRSDate not supplied

A Robust Uniform Control Approach for VTOL Aircraft

We present a uniform control approach for transitioning vertical take-off and landing aircraft. The approach combines several well-understood linear techniques, including robust servomechanism linear quadratic regulation, control allocation, and gain scheduling, to provide a practical control framework that can be used to unify the control design process in all flight regimes. The choice of command variables provides a pilot/operator with a uniform set of intuitive control inputs through all phases of flight while also being easily integrated into autonomous trajectory tracking operations. The control method is applied to the NASA LA-8 aircraft, a tandem tiltwing distributed electric propulsion research vehicle designed at NASA Langley Research Center. The trim envelope of the aircraft is explored and the aircraft control authority analyzed throughout the transition corridor. The uniform control approach is then used to develop reference command tracking controllers for both the longitudinal and lateral-directional dynamics. An example trajectory is simulated to demonstrate how the controller effectively transitions the aircraft from hover to forward flight and vice versa while tracking a desired trajectory.

VTOL↗
NASA NTRSDate not supplied

Capturing Complex Multivariate Time Series Interactions to Detect High-Risk Adverse Events During Flight

The reduction of aviation safety metrics below target thresholds continue to drive down the number of aviation fatalities and accidents. To meet future safety demands, sustained efforts by aviation agencies promoting safety assurance processes and systems have prompted ongoing research on identifying and mitigating in-flight risks. With the projected increase in passenger load factor and rollout of more autonomous systems into the national airspace, the need to detect high-risk events in-time or ahead-of-time is becoming increasingly crucial. New anomaly detection and precursor identification algorithms will need to scale to different airframes, levels of autonomy, and system complexity. While the pervasiveness of deep learning has resulted in the development of performant anomaly detection methods, these sophisticated models currently suffer from low end-user interpretability. Building off our previous work on identifying adverse events in multivariate flight data during descent, we propose a data-driven approach for detecting in-flight adverse events caused by the complex interplay of flight variables. Our approach utilizes ordinal patterns of important aircraft stability variables (e.g., airspeed and descent rate) to capture multivariate flight dynamics that can be used to predict the onset of unstable approaches, a high-risk adverse event that can occur during approach. Through the use of ordinal patterns, we aim to create more interpretable detection models of in-flight adverse events that can be translated to future autonomous systems without difficulty. Our analysis shows the presence of distinct ordinal pattern distributions that can be used to predict unstable approaches 1 minute ahead of time with an accuracy of 0.69 and a recall of 0.73 and 30 seconds ahead with an accuracy of 0.70 and a recall of 0.86.

Risk detection↗
NASA NTRSDate not supplied

Capturing Multivariate Time Series Interactions to Detect High‑Risk Instability During Approach

The reduction of aviation safety metrics below target thresholds continue to drive down the number of aviation fatalities and accidents. To meet future safety demands, sustained efforts by aviation agencies promoting safety assurance processes and systems have prompted ongoing research on identifying and mitigating in-flight risks. With the projected increase in passenger load factor and rollout of more autonomous systems into the national airspace, the need to detect high-risk events in-time or ahead-of-time is becoming increasingly crucial. New anomaly detection and precursor identification algorithms will need to scale to different airframes, levels of autonomy, and system complexity. While the pervasiveness of deep learning has resulted in the development of performant anomaly detection methods, these sophisticated models currently suffer from low end-user interpretability. Building off our previous work on identifying adverse events in multivariate flight data during descent, we propose a data-driven approach for detecting in-flight adverse events caused by the complex interplay of flight variables. Our approach utilizes ordinal patterns of important aircraft stability variables (e.g., airspeed and descent rate) to capture multivariate flight dynamics that can be used to predict the onset of unstable approaches, a high-risk adverse event that can occur during approach. Through the use of ordinal patterns, we aim to create more interpretable detection models of in-flight adverse events that can be translated to future autonomous systems without difficulty. Our analysis shows the presence of distinct ordinal pattern distributions that can be used to predict unstable approaches 1 minute ahead of time with an accuracy of 0.69 and a recall of 0.73 and 30 seconds ahead with an accuracy of 0.70 and a recall of 0.86.

Risk detection↗
NASA NTRS2011

Autonomous, In-Flight Crew Health Risk Management for Exploration-Class Missions: Leveraging the Integrated Medical Model for the Exploration Medical System Demonstration Project

The Integrated Medical Model (IMM) captures organizational knowledge across the space medicine, training, operations, engineering, and research domains. IMM uses this knowledge in the context of a mission and crew profile to forecast risks to crew health and mission success. The IMM establishes a quantified, statistical relationship among medical conditions, risk factors, available medical resources, and crew health and mission outcomes. These relationships may provide an appropriate foundation for developing an in-flight medical decision support tool that helps optimize the use of medical resources and assists in overall crew health management by an autonomous crew with extremely limited interactions with ground support personnel and no chance of resupply.

Butler, D. J.↗
NASA NTRS1999

Low Earth Orbiter: Terminal

In response to the current government budgetary environment that requires the National Aeronautics and Space Administration (NASA) to do more with less, NASA/Goddard Space Flight Center's Wallops Flight Facility has developed and implemented a class of ground stations known as a Low Earth Orbiter-Terminal (LEO-T). This development thus provides a low-cost autonomous ground tracking service for NASA's customers. More importantly, this accomplishment provides a commercial source to spacecraft customers around the world to purchase directly from the company awarded the NASA contract to build these systems. A few years ago, NASA was driven to provide more ground station capacity for spacecraft telemetry, tracking, and command (TT&C) services with a decreasing budget. NASA also made a decision to develop many smaller, cheaper satellites rather than a few large spacecraft as done in the past. In addition, university class missions were being driven to provide their own TT&C services due to the increasing load on the NASA ground-tracking network. NASA's solution for this ever increasing load was to use the existing large aperture systems to support those missions requiring that level of performance and to support the remainder of the missions with the autonomous LEO-T systems. The LEO-T antenna system is a smaller, cheaper, and fully autonomous unstaffed system that can operate without the existing NASA support infrastructure. The LEO-T provides a low-cost, reliable space communications service to the expanding number of low-earth orbiting missions around the world. The system is also fostering developments that improve cost-effectiveness of autonomous-class capabilities for NASA and commercial space use. NASA has installed three LEO-T systems. One station is at the University of Puerto Rico, the second system is installed at the Poker Flat Research Range near Fairbanks, Alaska, and the third system is installed at NASA's Wallops Flight Facility in Virginia. This paper will describe the current NASA implementation of the LEO-T network of antenna systems, the customers now being supported, and the services NASA can now offer with this new breed of autonomous ground stations. In addition, the paper will define the technical capabilities of the system and the cost effectiveness of using the systems including the capital costs of installation.

Kremer, Steven E.↗
NASA NTRS2001

Neurophysiology Summary

The terrestrial gravitational field serves as an important orientation reference for human perception and movement, being continually monitored by sensory receptors in the skin, muscles, joints, and vestibular otolith organs. Cues from these graviceptors are used by the brain to estimate spatial orientation and to control balance and movement. Changes in these cues associated with the tonic changes in gravity (gravito-inertial force),during the launch and entry phases of space flight missions result in altered perceptions, degraded motor control performance, and in some cases, "motion" sickness during, and for a period of time after, the g-transitions. In response to these transitions, however, physiological and behavioral response mechanisms are triggered to compensate for altered graviceptor cues and/or to adapt to the new sensory environment. Basic research in the neurophysiology discipline is focused on understanding the characteristic features of and the underlying mechanisms for the normal human response to tonic changes in the gravito-inertial force environment. These studies address fundamental questions regarding the role of graviceptors in orientation and movement in the terrestrial environment, as well as the capacity, specificity, and modes for neural plasticity in the sensory-motor and perceptual systems of the brain. At the 2001 workshop basic research studies were presented addressing: neuroanatomical responses to altered gravity environments, the neural mechanisms for resolving the ambiguity between tilting and translational stimuli in otolith organ sensory input, interactions between the vestibular system and the autonomic nervous system , the roles of haptic and visual cues in spatial orientation, mechanisms for training environment-appropriate sensorimotor responses triggered by environment-specific context cues, and studies of sensori-motor control of posture and locomotion in the terrestrial environment with and without recent exposure to space flight. Building on these basic research studies are more applied studies focused on the development of countermeasures to the untoward neurophysiological responses to space flight. At the 2001 workshop, applied research studies were presented addressing issues related to the use of rotational artificial gravity (centripetal acceleration) as a multisystem (bone, muscle, cardiovascular, and, perhaps, neurovestibular) countermeasure. Also presented was a clinical study reporting on a new rating system for clinical evaluation of postflight functional neurological status.

Paloski, William H.↗
DOE OSTI2026

Toward Trustworthy Autonomous Science: A Two-Year Community Roadmap

One year ago, the AISLE roadmap argued that autonomous laboratories operated as isolated islands and proposed a grassroots network organized around five critical dimensions. The field has since moved faster than that roadmap anticipated: multi-agent systems have produced experimentally validated hypotheses, self-driving laboratories have grown more interoperable and orchestrated, reasoning-trained and domain foundation models have raised the capability ceiling, and the Genesis Mission has placed autonomous experimentation at the center of U.S. federal science strategy, with industry emerging as a primary actor. Progress has met a sobering counter-current, including a corrected flagship discovery result, benchmarks showing that agents which rival experts on closed-ended questions still complete only a fraction of open-ended research, and fabricated citations surfacing at leading venues. We read this as the defining tension of the field: producing a candidate discovery is no longer the hard part, but verifying it is, and this asymmetry now limits autonomous science more than raw model capability. Accordingly, we update the roadmap around seven dimensions, revisiting the original five and elevating two former cross-cutting concerns, trust, verification, and reproducibility, and safety, security, and governance, to first-class status. We assess the original milestones (M1 through M14) as achieved, partially achieved, reframed, or open, add four new milestones (M15 through M18) for the elevated dimensions, and scope the path forward to a two-year horizon, with the first year concentrating on interfaces, protocol adoption, and the scaffolding of verification, and the second targeting federation, zero-trust coordination, and governance. Throughout, we position the grassroots network as the interoperability fabric that lets national programs, international initiatives, and commercial platforms connect rather than re-silo.

99 GENERAL AND MISCELLANEOUS↗
NASA NTRS2016

A Mission Concept to Study Multigenerational Mammalian Reproduction in Partial Gravity

A team at NASA Langley Research Center conducted a study during which a conceptual space mission was designed. In this study, rodents are used as human analogs to gather biological and systems data in a relevant environment applicable to future settlements on Mars. The mission concept uniquely addresses the combined effects of long-durations (one-year or greater), autonomous and robotic operations, and biological responses to partial gravity with an emphasis on reproduction. The objectives of this study were to 1) understand challenges associated with designing an artificial gravity habitat that supports the reproduction and maturation of a large animal colony, 2) identify mission architectures and operational concepts to transport and maintain such a facility, and 3) identify fundamental science considerations for mammalian reproduction studies to inform vehicle design. A model demonstration unit was developed to visualize and test certain design concepts that resulted from these considerations. Three versions of this demonstration unit were built over the course of the study, each taking into account lessons learned from the previous version. This paper presents the updated baseline mission and spacecraft design concepts to achieve these objectives, with a specific emphasis on updates since publication in previous works. Analyses of the integrated system trades among the elements which make up the conceptual vehicle are described to address overall feasibility and identify potential integrated design opportunities. The latest iteration of the habitat robotics design and a conceptual design example for autonomous care of crew and systems are also presented. Finally, the conclusion of this conceptual design study, necessary future analyses to enable such a facility, and comments upon other applications of a similar exploration-focused research facilities are addressed.

Rodgers, Erica M.↗
DOE OSTI2026

Large language models for transportation research: Methodologies, state of the art, and future opportunities

The rapid rise of large language models (LLMs) is transforming transportation research, with significant advancements emerging between 2023 and 2025, a period marked by the inception and swift growth of adopting and adapting LLMs for various transportation applications. Despite these significant advancements, however, a systematic review and synthesis of the existing literature remains lacking. This paper aims to fill this gap by providing a comprehensive review of the methodologies and applications of LLMs in transportation. We explore key applications, including autonomous driving, travel behavior prediction, and general transportation-related queries, alongside LLM methodologies such as zero- or few-shot learning, prompt engineering, and fine-tuning. From the review, critical research gaps are identified. From the methodological perspective, many of the research limitations can be addressed by integrating LLMs with existing tools and refining LLM architectures. From the application perspective, research opportunities for LLMs to address various transportation challenges are also explored. By synthesizing these findings, this review not only presents the state-of-the-art LLM adoption and adaptation in transportation, but also proposes future research directions as well as insights and recommendations for policymakers and practitioners, paving the way for greater LLM-driven research innovations in transportation in the future.

42 ENGINEERING↗
NASA NTRS1989

The Spartan 1 mission

The first Spartan mission is documented. The Spartan program, an outgrowth of a joint Naval Research Laboratory (NRL)/National Aeronautics and Space Administration (NASA)-Goddard Space Flight Center (GSFC) development effort, was instituted by NASA for launching autonomous, recoverable payloads from the space shuttle. These payloads have a precise pointing system and are intended to support a wide range of space-science observations and experiments. The first Spartan, carrying an NRL X-ray astronomy instrument, was launched by the orbiter Discovery (STS51G) on June 20, 1985 and recovered successfully 45 h later, on June 22. During this period, Spartan 1 conducted a preprogrammed series of observations of two X-ray sources: the Perseus cluster of galaxies and the center of our galaxy. The mission was successful from both on engineering and a scientific viewpoint. Only one problem was encountered, the attitude control system (ACS) shut down earlier than planned because of high attitude control system gas consumption. A preplanned emergency mode then placed Spartan 1 into a stable, safe condition and allowed a safe recovery. The events are described of the mission and presents X-ray maps of the two observed sources, which were produced from the flight data.

Cruddace, Raymond G.↗
NASA NTRS1990

The Spartan 1 mission

The first Spartan mission is documented. The Spartan program, an outgrowth of a joint Naval Research Laboratory (NRL)/National Aeronautics and Space Administration (NASA)-Goddard Space Flight Center (GSFC) development effort, was instituted by NASA for launching autonomous, recoverable payloads from the Space Shuttle. These payloads have a precise pointing system and are intended to support a wide range of space-science observations and experiments. The first Spartan, carrying an NRL X-ray astronomy instrument, was launched by the orbiter Discovery (STS51G) on June 20, 1985 and recovered successfully 45 h later, on June 22. During this period, Spartan 1 conducted a preprogrammed series of observations of two X-ray sources: the Perseus cluster of galaxies and the center of our galaxy. The mission was successful from both on engineering and a scientific viewpoint. Only one problem was encountered, the attitude control system (ACS) shut down earlier than planned because of high attitude control system gas consumption. A preplanned emergency mode then placed Spartan 1 into a stable, safe condition and allowed a safe recovery. The events are described of the mission and presents X-ray maps of the two observed sources, which were produced from the flight data.

Cruddace, R. G.↗
NASA NTRS1990

Results from teleoperated free-flying spacecraft simulations in the Martin Marietta space operations simulator lab

To augment the capabilities of the Space Transportation System, NASA has funded studies and developed programs aimed at developing reusable, remotely piloted spacecraft and satellite servicing systems capable of delivering, retrieving, and servicing payloads at altitudes and inclinations beyond the reach of the present Shuttle Orbiters. Since the mid 1970's, researchers at the Martin Marietta Astronautics Group Space Operations Simulation (SOS) Laboratory have been engaged in investigations of remotely piloted and supervised autonomous spacecraft operations. These investigations were based on high fidelity, real-time simulations and have covered a wide range of human factors issues related to controllability. Among these are: (1) mission conditions, including thruster plume impingements and signal time delays; (2) vehicle performance variables, including control authority, control harmony, minimum impulse, and cross coupling of accelerations; (3) maneuvering task requirements such as target distance and dynamics; (4) control parameters including various control modes and rate/displacement deadbands; and (5) display parameters involving camera placement and function, visual aids, and presentation of operational feedback from the spacecraft. This presentation includes a brief description of the capabilities of the SOS Lab to simulate real-time free-flyer operations using live video, advanced technology ground and on-orbit workstations, and sophisticated computer models of on-orbit spacecraft behavior. Sample results from human factors studies in the five categories cited above are provided.

Hartley, Craig S.↗
NASA NTRS1998

Diode laser absorption sensors for gas-dynamic and combustion flows

Recent advances in room-temperature, near-IR and visible diode laser sources for tele-communication, high-speed computer networks, and optical data storage applications are enabling a new generation of gas-dynamic and combustion-flow sensors based on laser absorption spectroscopy. In addition to conventional species concentration and density measurements, spectroscopic techniques for temperature, velocity, pressure and mass flux have been demonstrated in laboratory, industrial and technical flows. Combined with fibreoptic distribution networks and ultrasensitive detection strategies, compact and portable sensors are now appearing for a variety of applications. In many cases, the superior spectroscopic quality of the new laser sources compared with earlier cryogenic, mid-IR devices is allowing increased sensitivity of trace species measurements, high-precision spectroscopy of major gas constituents, and stable, autonomous measurement systems. The purpose of this article is to review recent progress in this field and suggest likely directions for future research and development. The various laser-source technologies are briefly reviewed as they relate to sensor applications. Basic theory for laser absorption measurements of gas-dynamic properties is reviewed and special detection strategies for the weak near-IR and visible absorption spectra are described. Typical sensor configurations are described and compared for various application scenarios, ranging from laboratory research to automated field and airborne packages. Recent applications of gas-dynamic sensors for air flows and fluxes of trace atmospheric species are presented. Applications of gas-dynamic and combustion sensors to research and development of high-speed flows aeropropulsion engines, and combustion emissions monitoring are presented in detail, along with emerging flow control systems based on these new sensors. Finally, technology in nonlinear frequency conversion, UV laser materials, room-temperature mid-IR materials and broadly tunable multisection devices is reviewed to suggest new sensor possibilities.

Non-NASA Center↗
DOE OSTI2022

ESTABLISHING ETHICAL GUIDELINES FOR APPLYING ARTIFICIAL INTELLIGENCE TO IAEA SAFEGUARDS

Drawing upon globally recognized efforts by a variety of institutions, the paper develops a practical and defensible framework for consideration and use by the International Atomic Energy Agency (IAEA) to support the adoption of credible ethical standards for autonomous and intelligent systems (AIS). The analysis is based on a future hypothetical AIS that identifies signatures of misuse, diversion, and other research and development (R&D). The hypothetical system serves as an exemplar for subject matter expert (SME) workshop participants to begin to answer ethical AIS questions around how these systems should be governed and maintained, what the internal and external considerations associated with artificial intelligence (AI) tools are, and where the boundaries between ethical and non-ethical uses are. The ethical AIS workshop explored several important topics: (a) Recommendations that can be currently implemented by the IAEA, (b) Proposed defensible criteria and metrics aligned with an ethical AI for safeguards implementation, (c) Discussion of future needs and capabilities, and (d) Derive appropriate next steps and actions to support filling current technological, operational, and cultural gaps and realizing an effective ethical AI for safeguards framework. The Establishing Ethical Guidelines for Applying AI to IAEA Safeguards project creates awareness in the community of the ethical AIS approach.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗