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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 289 records · Page 16

Feedback laws for fuel minimization for transport aircraft

The Theoretical Mechanics Branch has as one of its long-range goals to work toward solving real-time trajectory optimization problems on board an aircraft. This is a generic problem that has application to all aspects of aviation from general aviation through commercial to military. Overall interest is in the generic problem, but specific problems to achieve concrete results are examined. The problem is to develop control laws that generate approximately optimal trajectories with respect to some criteria such as minimum time, minimum fuel, or some combination of the two. These laws must be simple enough to be implemented on a computer that is flown on board an aircraft, which implies a major simplification from the two point boundary value problem generated by a standard trajectory optimization problem. In addition, the control laws allow for changes in end conditions during the flight, and changes in weather along a planned flight path. Therefore, a feedback control law that generates commands based on the current state rather than a precomputed open-loop control law is desired. This requirement, along with the need for order reduction, argues for the application of singular perturbation techniques.

Price, D. B.↗

Optimal collision avoidance guidance for formation-flying applications

Several proposed space science missions require deployment of a number of spacecraft to form a single functional unit or a formation flying spacecraft. There are many applications of a formation flying spacecraft; variable baseline optical space interferometry is one of them.

collision avoidance path-planning formation-flying↗

NASA Tech Briefs, September 2006

Topics covered include: Improving Thermomechanical Properties of SiC/SiC Composites; Aerogel/Particle Composites for Thermoelectric Devices; Patches for Repairing Ceramics and Ceramic- Matrix Composites; Lower-Conductivity Ceramic Materials for Thermal-Barrier Coatings; An Alternative for Emergency Preemption of Traffic Lights; Vehicle Transponder for Preemption of Traffic Lights; Automated Announcements of Approaching Emergency Vehicles; Intersection Monitor for Traffic-Light-Preemption System; Full-Duplex Digital Communication on a Single Laser Beam; Stabilizing Microwave Frequency of a Photonic Oscillator; Microwave Oscillators Based on Nonlinear WGM Resonators; Pointing Reference Scheme for Free-Space Optical Communications Systems; High-Level Performance Modeling of SAR Systems; Spectral Analysis Tool 6.2 for Windows; Multi-Platform Avionics Simulator; Silicon-Based Optical Modulator with Ferroelectric Layer; Multiplexing Transducers Based on Tunnel-Diode Oscillators; Scheduling with Automated Resolution of Conflicts; Symbolic Constraint Maintenance Grid; Discerning Trends in Performance Across Multiple Events; Magnetic Field Solver; Computing for Aiming a Spaceborne Bistatic- Radar Transmitter; 4-Vinyl-1,3-Dioxolane-2-One as an Additive for Li-Ion Cells; Probabilistic Prediction of Lifetimes of Ceramic Parts; STRANAL-PMC Version 2.0; Micromechanics and Piezo Enhancements of HyperSizer; Single-Phase Rare-Earth Oxide/Aluminum Oxide Glasses; Tilt/Tip/Piston Manipulator with Base-Mounted Actuators; Measurement of Model Noise in a Hard-Wall Wind Tunnel; Loci-STREAM Version 0.9; The Synergistic Engineering Environment; Reconfigurable Software for Controlling Formation Flying; More About the Tetrahedral Unstructured Software System; Computing Flows Using Chimera and Unstructured Grids; Avoiding Obstructions in Aiming a High-Gain Antenna; Analyzing Aeroelastic Stability of a Tilt-Rotor Aircraft; Tracking Positions and Attitudes of Mars Rovers; Stochastic Evolutionary Algorithms for Planning Robot Paths; Compressible Flow Toolbox; Rapid Aeroelastic Analysis of Blade Flutter in Turbomachines; General Flow-Solver Code for Turbomachinery Applications; Code for Multiblock CFD and Heat-Transfer Computations; Rotating-Pump Design Code; Covering a Crucible with Metal Containing Channels; Repairing Fractured Bones by Use of Bioabsorbable Composites; Kalman Filter for Calibrating a Telescope Focal Plane; Electronic Absolute Cartesian Autocollimator; Fiber-Optic Gratings for Lidar Measurements of Water Vapor; Simulating Responses of Gravitational-Wave Instrumentation; SOFTC: A Software Correlator for VLBI; Progress in Computational Simulation of Earthquakes; Database of Properties of Meteors; Computing Spacecraft Solar-Cell Damage by Charged Particles; Thermal Model of a Current-Carrying Wire in a Vacuum; Program for Analyzing Flows in a Complex Network; Program Predicts Performance of Optical Parametric Oscillators; Processing TES Level-1B Data; Automated Camera Calibration; Tracking the Martian CO2 Polar Ice Caps in Infrared Images; Processing TES Level-2 Data; SmaggIce Version 1.8; Solving the Swath Segment Selection Problem; The Spatial Standard Observer; Less-Complex Method of Classifying MPSK; Improvement in Recursive Hierarchical Segmentation of Data; Using Heaps in Recursive Hierarchical Segmentation of Data; Tool for Statistical Analysis and Display of Landing Sites; Automated Assignment of Proposals to Reviewers; Array-Pattern-Match Compiler for Opportunistic Data Analysis; Pre-Processor for Compression of Multispectral Image Data; Compressing Image Data While Limiting the Effects of Data Losses; Flight Operations Analysis Tool; Improvement in Visual Target Tracking for a Mobile Robot; Software for Simulating Air Traffic; Automated Vectorization of Decision-Based Algorithms; Grayscale Optical Correlator Workbench; "One-Stop Shopping" for Ocean Remote-Sensing and Model Data; State Analysis Database Tool; Generating CAHV and CAHVOmages with Shadows in ROAMS; Improving UDP/IP Transmission Without Increasing Congestion; FORTRAN Versions of Reformulated HFGMC Codes; Program for Editing Spacecraft Command Sequences; Flight-Tested Prototype of BEAM Software; Mission Scenario Development Workbench; Marsviewer; Tool for Analysis and Reduction of Scientific Data; ASPEN Version 3.0; Secure Display of Space-Exploration Images; Digital Front End for Wide-Band VLBI Science Receiver; Multifunctional Tanks for Spacecraft; Lightweight, Segmented, Mostly Silicon Telescope Mirror; Assistant for Analyzing Tropical-Rain-Mapping Radar Data; and Anion-Intercalating Cathodes for High-Energy- Density Cells.

Source record↗

Stereo Vision Based Terrain Mapping for Off-Road Autonomous Navigation

Successful off-road autonomous navigation by an unmanned ground vehicle (UGV) requires reliable perception and representation of natural terrain. While perception algorithms are used to detect driving hazards, terrain mapping algorithms are used to represent the detected hazards in a world model a UGV can use to plan safe paths. There are two primary ways to detect driving hazards with perception sensors mounted to a UGV: binary obstacle detection and traversability cost analysis. Binary obstacle detectors label terrain as either traversable or non-traversable, whereas, traversability cost analysis assigns a cost to driving over a discrete patch of terrain. In uncluttered environments where the non-obstacle terrain is equally traversable, binary obstacle detection is sufficient. However, in cluttered environments, some form of traversability cost analysis is necessary. The Jet Propulsion Laboratory (JPL) has explored both approaches using stereo vision systems. A set of binary detectors has been implemented that detect positive obstacles, negative obstacles, tree trunks, tree lines, excessive slope, low overhangs, and water bodies. A compact terrain map is built from each frame of stereo images. The mapping algorithm labels cells that contain obstacles as no-go regions, and encodes terrain elevation, terrain classification, terrain roughness, traversability cost, and a confidence value. The single frame maps are merged into a world map where temporal filtering is applied. In previous papers, we have described our perception algorithms that perform binary obstacle detection. In this paper, we summarize the terrain mapping capabilities that JPL has implemented during several UGV programs over the last decade and discuss some challenges to building terrain maps with stereo range data.

passive perception↗

Wide-Field InfraRed Survey Telescope (WFIRST) Slitless Spectrometer: Design, Prototype, and Results

The slitless spectrometer plays an important role in the Wide-Field InfraRed Survey Telescope (WFIRST) mission for the survey of emission-line galaxies. This will be an unprecedented very wide field, HST quality 3D survey of emission line galaxies. The concept of the compound grism as a slitless spectrometer has been presented previously. The presentation briefly discusses the challenges and solutions of the optical design, and recent specification updates, as well as a brief comparison between the prototype and the latest design. However, the emphasis of this paper is the progress of the grism prototype: the fabrication and test of the complicated diffractive optical elements and powered prism, as well as grism assembly alignment and testing. Especially how to use different tools and methods, such as IR phase shift and wavelength shift interferometry, to complete the element and assembly tests. The paper also presents very encouraging results from recent element tests to assembly tests. Finally we briefly touch the path forward plan to test the spectral characteristic, such as spectral resolution and response.

Grism↗

Testing Enabling Technologies for Safe UAS Urban Operations

A set of more than 100 flight operations were conducted at NASA Langley Research Center using small UAS (sUAS) to demonstrate, test, and evaluate a set of technologies and an overarching air-ground system concept aimed at enabling safety. The research vehicle was tracked continuously during nominal traversal of planned flight paths while autonomously operating over moderately populated land. For selected flights, off-nominal risks were introduced, including vehicle-to-vehicle (V2V) encounters. Three contingency maneuvers were demonstrated that provide safe responses. These maneuvers made use of an integrated air/ground platform and two on-board autonomous capabilities. Flight data was monitored and recorded with multiple ground systems and was forwarded in real time to a UAS traffic management (UTM) server for airspace coordination and supervision.

Moore, Andrew J.↗

NASA’s Space Launch System: New Launch Capability for Artemis Lunar and Deep Space Science Missions

With stacking and integration of the initial Block 1 Space Launch System (SLS) expected to begin in 2020, NASA’s powerful new launch vehicle is ready to take center stage in the agency’s Artemis program to return astronauts to the Moon. Combining the highest launch thrust and largest payload capacity ever developed, SLS also enables a new generation of high-C3 science missions to destinations such as the gas and ice giants, the Kuiper Belt, and even beyond the solar system. Block 1 is only the beginning, as the vehicle has a planned evolution path to progressively more powerful variants. In addition to these block upgrades providing increased lift capability, the vehicle can be configured to fly in crew configuration with the Orion spacecraft or in cargo configuration with payload fairings for launching science mission or large infrastructure, providing a flexible launch option. For Artemis I, the first SLS flight, the Block 1 vehicle in the crew configuration will send an uncrewed Orion spacecraft to lunar orbit for a thorough systems checkout before the crewed Artemis II flight. The Block 1 vehicle uses a proven propulsion system consisting of solid rocket boosters and RS-25 engines to lift more than 27 metric tons [t] to trans-lunar injection (TLI). In its cargo configuration, Block 1 can be fitted with a 5 m payload fairing. The second variant, Block 1B, uses a more powerful upper stage to increase payload mass to TLI to 38-42 t, depending on crew or cargo configuration. In the crew configuration, a co-manifested payload of up to 10 t can ride along in the Universal Stage Adapter (USA), which has as much volume for payloads as a 5 m-class payload fairing. The Block 2 evolved variant will lift 43-46 t to TLI, depending on crew or cargo configuration. The Block 1B and Block 2 vehicles can be outfitted with an 8.4 m-diameter payload fairing, available in 19.1 m and 27.4 m lengths, providing unprecedented volume for payloads. Larger-diameter 10 m fairings may also be an option in the future on the Block 2 vehicle. The unrivalled mass, volume and high-energy launches of SLS can provide significant mission flexibility for payloads and/or additional upper stages to open trade space for a new generation of exploration missions. SLS was designed to meet requirements for launching large-volume infrastructure as outlined in numerous studies of missions to cislunar space or Mars. Mission concept studies from the science community also point toward new possibilities enabled by SLS. Probes with more robust science packages can be sent to the gas giants. Dual spacecraft can be manifested for missions to Uranus and Neptune. Additional third or fourth payload stages can be encapsulated in the payload fairings to achieve missions to the Kuiper Belt or beyond. In addition, the large volume can be used to design and deploy wide-aperture mirrors on future space telescopes and to enable nuclear-thermal propulsion missions. At AIAA Ascend, the SLS Program will provide technical information on vehicle capabilities as well as descriptions of ongoing discussions with mission planners for utilizing the vehicle for an array of deep space missions.

Stephen Creech↗

NASA's Space Launch System Begins Integration, Stacking in Preparation for Artemis I Launch

The Artemis era of human lunar exploration is nearing take-off as NASA’s new super heavy-lift launch vehicle, the Space Launch System (SLS), begins stack-ing and integration operations in mid-2020 at Kennedy Space Center (KSC) in Florida. With a planned upgrade path to progressively more powerful vehicles and availability in crew and cargo configurations, SLS provides a unique and flexible launch solution to send crew, large-scale infrastructure and robotic probes to deep space. The SLS Block 1 vehicle, the initial variant to fly, is optimized for lunar missions with a proven propulsion system consisting of four liquid hydrogen (LH2)/liquid oxygen (LOX)-fed RS-25 engines and twin five-segment solid rocket boosters (SRBs). The Block 1 vehicle can also be outfitted with an industry-standard 5 m-class payload fairing (the “cargo” configuration) and will launch at least 27 metric tons (t) of mass to trans-lunar injection (TLI). SLS is the backbone of NASA’s Artemis program, which will return the agency’s human spaceflight program to the Moon for the first time since 1972. For the Artemis I mission, SLS will send an uncrewed Orion spacecraft to TLI, where it will enter a distant retrograde lunar orbit and fly 38,000 nmi past the Moon – farther than any spacecraft built for humans has ever traveled. The SLS Block 1 vehicle for Artemis I completed manufacturing in 2019. Several elements, including the upper stage, have been delivered to the Exploration Ground Systems (EGS) program at KSC and are being prepped for integration and stack-ing. The five-segment solid rocket boosters – the largest and most powerful ever built for flight – are also complete. The booster motor segments for the Artemis I flight are scheduled to ship from prime contractor Northrop Grumman’s Utah facilities and begin stacking and integration at KSC in June 2020. The SLS core stage is the largest rocket stage NASA has ever built in terms of volume and height, and includes the avionics and the tanks that feed cryogenic propellant to the four RS-25s (formerly Space Shuttle Main Engines [SSMEs]). They have been modified with an updated controller and nozzle insulation to protect them from the hotter launch environment. The SLS core stage is currently being test-ed at NASA’s Stennis Space Center (SSC) in a series of “green run” tests to verify it meets design and performance requirements. Following the green run test series, which is scheduled to culminate with a full-duration hot-fire of the four RS-25 engines, the core stage will ship to KSC and be stacked between the sol-id rocket boosters in the Vehicle Assembly Building (VAB). Integration of the vehicle will continue with the upper stage, known as the Interim Cryogenic Propulsion Stage (ICPS) and the Launch Vehicle Stage Adapter (LVSA) on the core stage. Another adapter, the Orion Stage Adapter (OSA), connects SLS to Orion and provides housing for 13 6U CubeSat payloads manifested on Artemis I. The CubeSats will be released in deep space after Orion separates from the vehicle, and the flight marks the first ride share opportunity for independent small-sats to deep space. The second major SLS variant to come online, Block 1B, replaces the single-engine ICPS with a four-engine LH2/LOX Exploration Upper Stage (EUS). This more powerful upper stage, along with other vehicle up-grades, will enable the Block 1B vehicle to launch 38-42 t to TLI, depending on crew or cargo configuration. The final evolution of the vehicle, Block 2, will onramp evolved solid rocket boosters to increase mass to TLI to 43-46 t, de-pending on crew or cargo configuration. The Block 1B/Block 2 vehicles can be outfitted with an 8.4 m-diameter payload fairing in 19.1 m or 27.4 m lengths, to provide unprecedented volume for payloads. With the initial Block 1 vehicle completely manufactured and the core stage in final testing before shipping to KSC, the SLS Program and its industry partners have made significant progress manufacturing subsequent vehicles. For the second Block 1 vehicle, the solid rocket motor segments are complete, as are the RS-25 engines with controllers. All five major components of the Artemis II core stage – the forward skirt, LOX and LH2 tanks, intertank and engine section – are manufactured and technicians are installing subsystems at NASA’s rocket factory, Michoud Assembly Facility. The RL-10 engine for the Artemis II ICPS is complete and panels have been machined for its LH2 tank. In addition, panels are machined for the vehicle’s two adapters, with welding scheduled to begin in summer 2020. Flight hard-ware is also in production for the third SLS vehicle, with several booster motor segments cast. The pace of development on the EUS has increased, with the goal to complete Critical Design Review (CDR) in December 2020. Several EUS test rings have been machined at Michoud. The EUS is designed to exe-cute a variety of missions – human spaceflight, deployment of deep-space infra-structure, or high-C3 missions to the outer solar system – with crew and cargo configurations available beginning in the mid-2020s. The near-term goal for the nation’s powerful new space exploration asset, however, is to launch the Arte-mis program, and send the first woman and the next man to the lunar surface. At the Astrodynamics Specialist Conference, the SLS program will update the community on the progress of the initial Block 1 vehicle in final green run test-ing, integration and stacking. In addition, this paper will provide an update to the community on the manufacturing status of subsequent Block 1 and Block 1B vehicles.

Steve Creech↗

Lunar Excavator Mission Operations using Dynamic Movement Primitives

To support sustainable infrastructure on the Moon, NASA must leverage robots to extract lunar resources for in-situ processing and construction. As part of this effort, NASA is launching the in-situ resource utilization (ISRU) Pilot Excavator later this decade to validate a robotic regolith excavator based on the Regolith Advanced Surface Systems Operations Robot (RASSOR). RASSOR is designed to extract and transport regolith to meet the needs of ISRU architectures. During its mission, Pilot Excavator will be tasked with driving in test patterns to demonstrate the operational concept. One of these tests is a circular trajectory around the lander while avoiding miscellaneous surface hazards such as lunar rocks. To this end, we utilize dynamic movement primitives to represent navigation sequences as primitive trajectories. Here, we introduce a novel obstacle avoidance parameter, which is configured to avoid rocks throughout testing exercises. We demonstrate the effectiveness our method in a newly developed simulation tool called the Simulated Excavation Environment for Lunar Operations (SEELO) using models based on the NASA RASSOR 2.0 excavator. After making key changes to the obstacle avoidance formulation, our results show that the robot is able to safety and robustly navigate the lunar surface with densely populated rock obstacles while retaining the desired circle pattern behavior.

Space Robotics and Automation↗

Adaptive Optimization for System Performance and Combined Bernstein Polynomial, Optimal Reciprocal Collision Avoidance, Differential Dynamic Programming for Trajectory Replanning and Collision Avoidance for UAM Vehicles

The emerging urban air mobility (UAM) sector in aerospace is driving development of unconventional multi-modal vehicle configurations and autonomous flight. The combination of multi-modal vehicle dynamics, complex environment, requirements to deal with flight contingencies in an efficient and safe manner, as well as necessity for precise trajectory following and performance, are the driving influence behind adaptive optimization for system performance. We are interested in trajectory optimization algorithm that would system parameter estimation and identifying the optimal switching time between modes of hybrid dynamical systems. This presentation discusses a parameterized optimal control trajectory optimization algorithm that is an extended and generalized version of Differential Dynamic Programming (DDP), titled Parameterized Differential Dynamic Programming (PDDP). DDP is an efficient trajectory optimization algorithm relying on second order approximations of a system’s dynamics and cost function and has recently been applied to optimize systems with time invariant parameters. Experiments are presented applying PDDP to solve model predictive control (MPC) and moving horizon estimation (MHE) tasks simultaneously. In particular, PDDP is used to determine the optimal transition point between flight regimes of a complex urban air mobility (UAM) class vehicle exhibiting multiple phases of flight and to identify and compensate for actuation faults.

optimization↗

Designing a Flight Test of a Flight Path Management System for Advanced Air Mobility Research

The National Aeronautics and Space Administration (NASA) has completed a flight test to evaluate the performance of an onboard prototype automation system operating in future high density urban airspace. The test was part of a research investigation of the Urban Air Mobility (UAM) concept, with a focus on a future environment having hundreds of simultaneous operations over a metropolitan area. The complexity of this future UAM airspace may require automation capable of replanning an aircraft’s path in the presence of traffic and other changing constraints. A live-virtual-constructive (LVC) approach was used to conduct the test. Prototype automation technology was integrated into one of the two live aircraft, which were combined with virtual traffic to create a mixed reality environment at the target airspace density. In-flight evaluation enabled verification of the automation’s functions and discovery of any unexpected behaviors resulting from its operation in an actual flight environment. The in-flight evaluation also provided data for validation of air traffic simulations. This paper discusses the design, methodology, and challenges overcome to conduct a successful flight test. Remaining challenges, future work, and recommendations to improve the flight test capability are also discussed.

Advanced Air Mobility↗

Pathfinding for Airspace with Autonomous Vehicles (PAAV) Overview for RTCA SC-228

The Pathfinding for Airspace with Autonomous Vehicles (PAAV) sub-project started in 2021 under NASA’s Air Traffic Management – eXploration (ATM-X) project. ATM-X as a project is conducting research to support the growth of traditional aviation and new entrants. This presentation discusses the background of the PAAV project as well as it’s current areas of focus around uncrewed aircraft system (UAS) operations. The areas include the development of a flight test ecosystem, detect and avoid, traffic pattern integration, aircraft-to-aircraft communications, and contingency management. The aim of these research areas is to help inform the development of performance standards and FAA-approved procedures for integrating UAS into the national airspace system (NAS). The presentation seeks to describe the PAAV research objectives in sufficient detail to allow the committee to provide feedback on the sub-project's approach and main areas of interest.

uncrewed aircraft systems↗

A High-Performance Computing Predictive GNSS Performance Monitor for Autonomous Air Vehicles in Urban Environments

This report offers analysis and design insights for leveraging High-Performance Computing (HPC) to predict line-of-sight (LOS) Global Navigation Satellite System (GNSS) availability in a city. This work is motivated by the emerging fields of Advanced and Urban Air Mobility (AAM/UAM), where regulatory authorities are seeking city-scale, meter-resolution risk forecasting in order to safely integrate new flight missions with existing urban life and infrastructure. This work addresses the technical challenge of efficiently computing urban GNSS satellite visibility to predict GNSS performance metrics under these requirements. We present a new HPC-optimized shadow casting algorithm variant as a ray-based approach to forecasting satellite visibility. We apply this algorithm variant in a software-defined prognostic service which generates a GNSS navigation risk-correlated map as a path planning-style potential field. We detail dominant computational burdens, viable simplifying assumptions, and different algorithmic implementations, intending to demonstrate a baseline of computation time needed by each stage in such a service. We conclude by analyzing the prototype service’s prediction accuracy compared to receiver data from Corpus Christi, Texas. This informs design trade-offs along the dimensions of hardware, computation time, and tolerable forecasting error (including proportions of false positives and false negatives).

GNSS↗