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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 451 records · Page 25
All sourcesNASA NTRSDOE OSTI
NASA NTRS1993

Integrated control of hypersonic vehicles - A necessity not just a possibility

The unique problems to be encountered in the design of systems for the precise control of hypersonic vehicles are to be reviewed and discussed. These problems pose significant research challenges if successful guidance and control systems are to be developed for this new class of vehicle. These challenges will be shown to arise due to the stringent mission requirements on the vehicle, and the highly integrated configuration designs being considered. In this paper, the mission requirements and operational goals of these vehicles will be first reviewed, and the trajectory performance issues highlighted. Then the presence of critical coupling between several vehicular subsystems will be clearly exposed, and the dynamic interactions between these subsystems will be presented. The results to be discussed are based on the analysis of a generic hypersonic vehicle, with characteristics similar to the X-30. It is an unstable, highly-coupled, aeropropulsive/aeroelastic system, with large variations in its attitude-dynamic characteristics over its extensive flight envelope. The genesis of these interactions is explored, the magnitudes quantified, and their significance in the context of control-system design presented. Finally, some candidate designs for the highly-integrated control systems will be presented.

Schmidt, David K.↗
NASA NTRS2013

Launch Vehicle Abort Analysis for Failures Leading to Loss of Control

Launch vehicle ascent is a time of high risk for an onboard crew. There is a large fraction of possible failures for which time is of the essence and a successful abort is possible if the detection and action happens quickly enough. This paper focuses on abort determination based on data already available from the Guidance, Navigation, and Control system. This work is the result of failure analysis efforts performed during the Ares I launch vehicle development program. The two primary areas of focus are the derivation of abort triggers to ensure that abort occurs as quickly as possible when needed, but that false aborts are avoided, and evaluation of success in aborting off the failing launch vehicle.

Hanson, John M.↗
NASA NTRS2010

Flash LIDAR Emulator for HIL Simulation

NASA's Autonomous Landing and Hazard Avoidance Technology (ALHAT) project is building a system for detecting hazards and automatically landing controlled vehicles safely anywhere on the Moon. The Flash Light Detection And Ranging (LIDAR) sensor is used to create on-the-fly a 3D map of the unknown terrain for hazard detection. As part of the ALHAT project, a hardware-in-the-loop (HIL) simulation testbed was developed to test the data processing, guidance, and navigation algorithms in real-time to prove their feasibility for flight. Replacing the Flash LIDAR camera with an emulator in the testbed provided a cheaper, safer, more feasible way to test the algorithms in a controlled environment. This emulator must have the same hardware interfaces as the LIDAR camera, have the same performance characteristics, and produce images similar in quality to the camera. This presentation describes the issues involved and the techniques used to create a real-time flash LIDAR emulator to support HIL simulation.

Brewster, Paul F.↗
NASA NTRS2014

Misconceptions of Electric Propulsion Aircraft and Their Emergent Aviation Markets

Over the past several years there have been aircraft conceptual design and system studies that have reached conflicting conclusions relating to the feasibility of full and hybrid electric aircraft. Some studies and propulsion discipline experts have claimed that battery technologies will need to improve by 10 to 20 times before electric aircraft can effectively compete with reciprocating or turbine engines. However, such studies have approached comparative assessments without understanding the compelling differences that electric propulsion offers, how these technologies will fundamentally alter the way propulsion integration is approached, or how these new technologies can not only compete but far exceed existing propulsion solutions in many ways at battery specific energy densities of only 400 watt hours per kilogram. Electric propulsion characteristics offer the opportunity to achieve 4 to 8 time improvements in energy costs with dramatically lower total operating costs, while dramatically improving efficiency, community noise, propulsion system reliability and safety through redundancy, as well as life cycle Green House Gas emissions. Integration of electric propulsion will involve far greater degrees of distribution than existing propulsion solutions due to their compact and scale-free nature to achieve multi-disciplinary coupling and synergistic integration with the aerodynamics, highlift system, acoustics, vehicle control, balance, and aeroelasticity. Appropriate metrics of comparison and differences in analysis/design tools are discussed while comparing electric propulsion to other disruptive technologies. For several initial applications, battery energy density is already sufficient for competitive products, and for many additional markets energy densities will likely be adequate within the next 7 years for vibrant introduction. Market evolution and early adopter markets are discussed, along with the investment areas that will fill technology gaps and create opportunities for the effective, near-term electric aircraft products. Without understanding both the context of how electric propulsion will integrate into the vehicle system, and evolve into the market place it is likely that electric propulsion will continue to be misunderstood.

Moore, Mark D.↗
DOE OSTI2020

Advancing Fusion with Machine Learning Research Needs Workshop Report

Abstract Machine learning and artificial intelligence (ML/AI) methods have been used successfully in recent years to solve problems in many areas, including image recognition, unsupervised and supervised classification, game-playing, system identification and prediction, and autonomous vehicle control. Data-driven machine learning methods have also been applied to fusion energy research for over 2 decades, including significant advances in the areas of disruption prediction, surrogate model generation, and experimental planning. The advent of powerful and dedicated computers specialized for large-scale parallel computation, as well as advances in statistical inference algorithms, have greatly enhanced the capabilities of these computational approaches to extract scientific knowledge and bridge gaps between theoretical models and practical implementations. Large-scale commercial success of various ML/AI applications in recent years, including robotics, industrial processes, online image recognition, financial system prediction, and autonomous vehicles, have further demonstrated the potential for data-driven methods to produce dramatic transformations in many fields. These advances, along with the urgency of need to bridge key gaps in knowledge for design and operation of reactors such as ITER, have driven planned expansion of efforts in ML/AI within the US government and around the world. The Department of Energy (DOE) Office of Science programs in Fusion Energy Sciences (FES) and Advanced Scientific Computing Research (ASCR) have organized several activities to identify best strategies and approaches for applying ML/AI methods to fusion energy research. This paper describes the results of a joint FES/ASCR DOE-sponsored Research Needs Workshop on Advancing Fusion with Machine Learning, held April 30–May 2, 2019, in Gaithersburg, MD (full report available at https://science.osti.gov/-/media/fes/pdf/workshop-reports/FES_ASCR_Machine_Learning_Report.pdf ). The workshop drew on broad representation from both FES and ASCR scientific communities, and identified seven Priority Research Opportunities (PRO’s) with high potential for advancing fusion energy. In addition to the PRO topics themselves, the workshop identified research guidelines to maximize the effectiveness of ML/AI methods in fusion energy science, which include focusing on uncertainty quantification, methods for quantifying regions of validity of models and algorithms, and applying highly integrated teams of ML/AI mathematicians, computer scientists, and fusion energy scientists with domain expertise in the relevant areas.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS2021

Simulation and Modeling Concepts for Secure Airspace Operations

This paper examines cyber security vulnerabilities of Urban Air Mobility operations. With the expected advent of new entrants including Unmanned Aerial Systems, Commercial Launch Vehicles and Urban Air Mobility aircraft, the future United States National Airspace System will have to evolve to include their operations along with the current commercial, general aviation and military operations. The National Aeronautics and Space Administration and the Federal Aviation Administration are working together to provide a vision for aviation operations in the future—2045 and beyond. Their National Airspace System Horizons initiative seeks to provide stakeholders a list of operational scenarios and technologies, concepts and strategies needed for supporting that vision. They have identified cybersecurity as one of the seven strategic interest areas for realizing this vision. Consequently, NASA is studying cyber resiliency for secure airspace operations. While there are many pathways to attack a cyber physical system such as Urban Air Mobility, their effect is expressed in modification or corruption of data/information used for controlling vehicles and making operational decisions. The paper describes cybersecurity technologies of Encryption, Blockchain, Virtual Information Fabric Infrastructure, Trusted Platform Module and Anomaly Detection for protecting the data, and the cyber resiliency of the current and future air traffic management system.

Urban Air Mobility↗
NASA NTRS2021

Simulation and Modeling Concepts for Secure Airspace Operations

This paper examines cyber security vulnerabilities of Urban Air Mobility operations. With the expected advent of new entrants including Unmanned Aerial Systems, Commercial Launch Vehicles and Urban Air Mobility aircraft, the future United States National Airspace System will have to evolve to include their operations along with the current commercial, general aviation and military operations. The National Aeronautics and Space Administration and the Federal Aviation Administration are working together to provide a vision for aviation operations in the future—2045 and beyond. Their National Airspace System Horizons initiative seeks to provide stakeholders a list of operational scenarios and technologies, concepts and strategies needed for supporting that vision. They have identified cybersecurity as one of the seven strategic interest areas for realizing this vision. Consequently, NASA is studying cyber resiliency for secure airspace operations. While there are many pathways to attack a cyber physical system such as Urban Air Mobility, their effect is expressed in modification or corruption of data/information used for controlling vehicles and making operational decisions. The paper describes cybersecurity technologies of Encryption, Blockchain, Virtual Information Fabric Infrastructure, Trusted Platform Module and Anomaly Detection for protecting the data, and the cyber resiliency of the current and future air traffic management system.

Urban Air Mobility↗
NASA NTRS1986

Independent Orbiter Assessment (IOA): Analysis of the rudder/speed brake subsystem

The results of the Independent Orbiter Assessment (IOA) of the Failure Modes and Effects Analysis (FMEA) and Critical Items List (CIL) are presented. The IOA approach features a top-down analysis of the hardware to determine failure modes, criticality, and potential critical items. To preserve independence, this analysis was accomplished without reliance upon the results contained within the NASA FMEA/CIL documentation. The independent analysis results for the Orbiter Rudder/Speedbrake Actuation Mechanism is documented. The function of the Rudder/Speedbrake (RSB) is to provide directional control and to provide a means of energy control during entry. The system consists of two panels on a vertical hinge mounted on the aft part of the vertical stabilizer. These two panels move together to form a rudder but split apart to make a speedbrake. The Rudder/Speedbrake Actuation Mechanism consists of the following elements: (1) Power Drive Unit (PDU) which is composed of hydraulic valve module and a hydraulic motor-powered gearbox which contains differentials and mixer gears to provide PDU torque output; (2) four geared rotary actuators which apply the PDU generated torque to the rudder/speedbrake panels; and (3) ten torque shafts which join the PDU to the rotary actuators and interconnect the four rotary actuators. Each level of hardware was evaluated and analyzed for possible failures and causes. Criticality was assigned based upon the severity of the effect for each failure mode. Critical RSB failures which result in potential loss of vehicle control were mainly due to loss of hydraulic fluid, fluid contaminators, and mechanical failures in gears and shafts.

Wilson, R. E.↗
NASA NTRSDate not supplied

Simulation and Modeling Concepts for Secure Airspace Operations

With the expected advent of new entrants including Unmanned Aerial Systems, Commercial Launch Vehicles and Urban Air Mobility aircraft, the future United States National Airspace System will have to evolve to include their operations along with the current commercial, general aviation and military operations. The National Aeronautics and Space Administration and the Federal Aviation Administration are working together to provide a vision for aviation operations in the future—2045 and beyond. Their National Airspace System Horizons initiative seeks to provide stakeholders a list of operational scenarios and technologies, concepts and strategies needed for supporting that vision. They have identified cybersecurity as one of the seven strategic interest areas for realizing this vision. Consequently, NASA is studying cyber resiliency for secure airspace operations. This paper examines cyber security vulnerabilities of Urban Air Mobility operations. While there are many pathways to attack a cyber physical system such as Urban Air Mobility, their effect is expressed in modification or corruption of data/information used for controlling vehicles and making operational decisions. The paper describes cybersecurity technologies of Encryption, Blockchain, Virtual Information Fabric Infrastructure, Trusted Platform Module and Anomaly Detection for protecting the data, thus, improving the cyber resiliency of the current and future air traffic management system.

Cybersecurity↗
DOE OSTI2022

Important powertrain dynamics for developing models for control of connected and automated electrified vehicles

Connected and Automated Vehicles (CAV) technology presents significant opportunities for energy saving in the transportation sector. CAV technology forecasts vehicle and powertrain power needs under various terrain, ambient, and traffic conditions. Integration of the CAV technology in Hybrid Electric Vehicles (HEVs) provides the opportunity for optimal vehicle operation. Indeed, Hybrid Electric Vehicle powertrains present high degrees of flexibility and possibility for choosing optimum powertrain modes based on the predicted traction power needs. In modeling complex CAV powertrain dynamics, the modeler needs to consider short-time scale powertrain dynamics, such as engine transients, and hysteresis of mode-switching for a multi-mode HEV. Therefore, the powertrain dynamics essential for developing powertrain controllers for a class of connected HEVs is presented. To this end, control-oriented powertrain dynamic models for a test vehicle consisting of full electric, hybrid, and conventional engine operating modes are developed. The resulting powertrain model can forecast vehicle traction torque and energy consumption for the specified prediction horizon of the test vehicle. The model considers different operating modes and associated energy penalty terms for mode switching. Thus, the vehicle controller can determine the optimum powertrain mode, torque, and speed for forecasted vehicle operation via utilizing connectivity data. The powertrain model is validated against the experimental data and shows prediction error of less than 5% for predicting vehicle energy consumption. The model is used to create energy penalty maps that can be used for CAV control, for example fuel penalty map for engine torque changes (10–40 Nm) at each engine speed. The results of model-based optimization show optimum switching delays ranging from 0.4 to 1.4 s to avoid hysteresis in mode switching.

Engineering↗
NASA NTRS2011

Autonomous Landing and Ingress of Micro-Air-Vehicles in Urban Environments Based on Monocular Vision

Unmanned micro air vehicles (MAVs) will play an important role in future reconnaissance and search and rescue applications. In order to conduct persistent surveillance and to conserve energy, MAVs need the ability to land, and they need the ability to enter (ingress) buildings and other structures to conduct reconnaissance. To be safe and practical under a wide range of environmental conditions, landing and ingress maneuvers must be autonomous, using real-time, onboard sensor feedback. To address these key behaviors, we present a novel method for vision-based autonomous MAV landing and ingress using a single camera for two urban scenarios: landing on an elevated surface, representative of a rooftop, and ingress through a rectangular opening, representative of a door or window. Real-world scenarios will not include special navigation markers, so we rely on tracking arbitrary scene features; however, we do currently exploit planarity of the scene. Our vision system uses a planar homography decomposition to detect navigation targets and to produce approach waypoints as inputs to the vehicle control algorithm. Scene perception, planning, and control run onboard in real-time; at present we obtain aircraft position knowledge from an external motion capture system, but we expect to replace this in the near future with a fully self-contained, onboard, vision-aided state estimation algorithm. We demonstrate autonomous vision-based landing and ingress target detection with two different quadrotor MAV platforms. To our knowledge, this is the first demonstration of onboard, vision-based autonomous landing and ingress algorithms that do not use special purpose scene markers to identify the destination.

micro air vehicles (MAVs)↗
NASA NTRS1982

An advanced tracker design for pointing and control of space vehicles using the charge injection device

The use of charge transfer devices (CTD) in pointing and control of space vehicles is examined, with emphasis on the use of charge injection devices (CID). The selection of CTD type and CID operation, including CID signal and noise analysis and signal improvement, are discussed. Star tracking operational advantages of the CTD are pointed out, and the tracking optical concept is discussed and graphically depicted. The position interpolation procedure and the effects of rate of stellar motion on position interpolation are considered, and error analysis is examined. Finally, the breadboard and test program are discussed in detail, coarse and fine acquisition, test for star, track pattern, test procedure and results. An overall accuracy performance of approximately 0.02 pixels or approximately 0.8 arcsec for the test equipment and tracker was obtained.

Jones, C.↗
NASA NTRS1992

Air-breathing hypersonic vehicle guidance and control studies: An integrated trajectory/control analysis methodology, phase 2

An integrated trajectory/control analysis algorithm has been used to generate trajectories and desired control strategies for two different hypersonic air-breathing vehicle models and orbit targets. Both models used cubic spline curve fit tabulated winged-cone accelerator vehicle representations. Near-fuel-optimal, horizontal takeoff trajectories, imposing a dynamic pressure limit of 1000 psf, were developed. The first model analysis case involved a polar orbit and included the dynamic effects of using elevons to maintain longitudinal trim. Analysis results indicated problems with the adequacy of the propulsion model and highlighted dynamic pressure/altitude instabilities when using vehicle angle of attack as a control variable. Also, the magnitude of computed elevon deflections to maintain trim suggested a need for alternative pitch moment management strategies. The second analysis case was reformulated to use vehicle pitch attitude relative to the local vertical as the control variable. A new, more realistic, air-breathing propulsion model was incorporated. Pitch trim calculations were dropped and an equatorial orbit was specified. Changes in flight characteristics due to the new propulsion model have been identified. Flight regimes demanding rapid attitude changes have been noted. Also, some issues that would affect design of closed-loop controllers were ascertained.

Hattis, Philip D.↗
DOE OSTI2024

A comprehensive guide to CAN IDS data and introduction of the ROAD dataset

Although ubiquitous in modern vehicles, Controller Area Networks (CANs) lack basic security properties and are easily exploitable. A rapidly growing field of CAN security research has emerged that seeks to detect intrusions or anomalies on CANs. Producing vehicular CAN data with a variety of intrusions is a difficult task for most researchers as it requires expensive assets and deep expertise. To illuminate this task, we introduce the first comprehensive guide to the existing open CAN intrusion detection system (IDS) datasets. We categorize attacks on CANs including fabrication (adding frames, e.g., flooding or targeting and ID), suspension (removing an ID’s frames), and masquerade attacks (spoofed frames sent in lieu of suspended ones). We provide a quality analysis of each dataset; an enumeration of each datasets’ attacks, benefits, and drawbacks; categorization as real vs. simulated CAN data and real vs. simulated attacks; whether the data is raw CAN data or signal-translated; number of vehicles/CANs; quantity in terms of time; and finally a suggested use case of each dataset. State-of-the-art public CAN IDS datasets are limited to real fabrication (simple message injection) attacks and simulated attacks often in synthetic data, lacking fidelity. In general, the physical effects of attacks on the vehicle are not verified in the available datasets. Only one dataset provides signal-translated data but is missing a corresponding “raw” binary version. This issue pigeon-holes CAN IDS research into testing on limited and often inappropriate data (usually with attacks that are too easily detectable to truly test the method). The scarcity of appropriate data has stymied comparability and reproducibility of results for researchers. As our primary contribution, we present the Real ORNL Automotive Dynamometer (ROAD) CAN IDS dataset, consisting of over 3.5 hours of one vehicle’s CAN data. ROAD contains ambient data recorded during a diverse set of activities, and attacks of increasing stealth with multiple variants and instances of real (i.e. non-simulated) fuzzing, fabrication, unique advanced attacks, and simulated masquerade attacks. To facilitate a benchmark for CAN IDS methods that require signal-translated inputs, we also provide the signal time series format for many of the CAN captures. Our contributions aim to facilitate appropriate benchmarking and needed comparability in the CAN IDS research field.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Next-Generation Energy Technologies for Connected and Automated On-Road Vehicles (NEXTCAR) - Predictive Data-Driven Vehicle Dynamics and Powertrain Control: from ECU to the Cloud (Final Scientific/Technical Report)

This project developed and demonstrated a predictive, data-driven vehicle control system designed to improve energy efficiency and driving performance. The team created intelligent self-driving car technology that optimizes fuel and electricity use by proactively planning vehicle actions. By combining Level 4 autonomous driving capabilities with vehicle-to-everything (V2X) connectivity, the system enables vehicles to adjust speed and change lanes in response to traffic signals, surrounding vehicles, and road conditions, reducing unnecessary stops and delays. In testing, the system improved vehicle fuel economy by more than 30% and reduced travel time by approximately 10%, compared to a conventional adaptive cruise control baseline. These results demonstrate the technical effectiveness of using predictive, V2X-enabled strategies, such as traffic light timing and surrounding traffic awareness, to inform real-time vehicle powertrain control and driving behavior. Additionally, a supporting cloud platform was developed to provide dispatch and route recommendations as well as to log vehicle data, demonstrating the economic feasibility of this approach at the fleet level. By optimizing dispatching and routing operations, this technology enables electric fleet operators to use their vehicles more efficiently and reduce reliance on diesel backups, lowering both operating costs and energy consumption. Overall, this project’s technology advances the future of clean, energy-efficient transportation, enabling vehicles and fleets to reduce energy waste, cut costs, and lower emissions through intelligent automation and connectivity.

33 ADVANCED PROPULSION SYSTEMS↗
NASA NTRS1974

Human vs autonomous control of planetary roving vehicles

Supervisory or semiautonomous control has some compelling advantages over step-by-step human command and verification for the operation of roving vehicles on remote planetary surfaces. There are also disadvantages in relation to the complex system that must be mobilized and the chain of events that must be enacted to conduct a mission. Which of the two control methods is better on technical grounds may not be the deciding factor in its acceptance or rejection. Some of the issues that affect changes in spacecraft design and operation are summarized. To accelerate the movement toward more autonomous machines, it will be necessary to understand and to address the problems that such autonomy will create for other elements of the control system and for the control process.

Whitney, W. M.↗