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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 523 records · Page 29
All sourcesNASA NTRSDOE OSTI
NASA NTRS1993

Remote driving with reduced bandwidth communication

Oak Ridge National Laboratory has developed a real-time video transmission system for low bandwidth remote operations. The system supports both continuous transmission of video for remote driving and progressive transmission of still images. Inherent in the system design is a spatiotemporal limitation to the effects of channel errors. The average data rate of the system is 64,000 bits/s, a compression of approximately 1000:1 for the black and white National Television Standard Code video. The image quality of the transmissions is maintained at a level that supports teleoperation of a high mobility multipurpose wheeled vehicle at speeds up to 15 mph on a moguled dirt track. Video compression is achieved by using Laplacian image pyramids and a combination of classical techniques. Certain subbands of the image pyramid are transmitted by using interframe differencing with a periodic refresh to aid in bandwidth reduction. Images are also foveated to concentrate image detail in a steerable region. The system supports dynamic video quality adjustments between frame rate, image detail, and foveation rate. A typical configuration for the system used during driving has a frame rate of 4 Hz, a compression per frame of 125:1, and a resulting latency of less than 1s.

Depiero, Frederick W.↗
NASA NTRS2007

Entry Attitude Controller for the Mars Science Laboratory

This paper describes the preliminary concept for the RCS 3-axis attitude controller for the exo-atmospheric and guided entry phases of the Mars Science Laboratory Entry, Descend and Landing. The entry controller is formulated as three independent channels in the control frame, which is nominally aligned with the stability frame. Each channel has a feedfoward and a feedback. The feedforward path enables fast response to large bank commands. The feedback path stabilizes the vehicle angle of attack and sideslip around its trim position, and tracks bank commands. The feedback path has a PD/D structure with deadbands that minimizes fuel usage. The performance of this design is demonstrated via simulation.

Mars↗
NASA NTRS2009

Spacecraft Internal Acoustic Environment Modeling

Acoustic modeling can be used to identify key noise sources, determine/analyze sub-allocated requirements, keep track of the accumulation of minor noise sources, and to predict vehicle noise levels at various stages in vehicle development, first with estimates of noise sources, later with experimental data. In FY09, the physical mockup developed in FY08, with interior geometric shape similar to Orion CM (Crew Module) IML (Interior Mode Line), was used to validate SEA (Statistical Energy Analysis) acoustic model development with realistic ventilation fan sources. The sound power levels of these sources were unknown a priori, as opposed to previous studies that RSS (Reference Sound Source) with known sound power level was used. The modeling results were evaluated based on comparisons to measurements of sound pressure levels over a wide frequency range, including the frequency range where SEA gives good results. Sound intensity measurement was performed over a rectangular-shaped grid system enclosing the ventilation fan source. Sound intensities were measured at the top, front, back, right, and left surfaces of the and system. Sound intensity at the bottom surface was not measured, but sound blocking material was placed tinder the bottom surface to reflect most of the incident sound energy back to the remaining measured surfaces. Integrating measured sound intensities over measured surfaces renders estimated sound power of the source. The reverberation time T6o of the mockup interior had been modified to match reverberation levels of ISS US Lab interior for speech frequency bands, i.e., 0.5k, 1k, 2k, 4 kHz, by attaching appropriately sized Thinsulate sound absorption material to the interior wall of the mockup. Sound absorption of Thinsulate was modeled in three methods: Sabine equation with measured mockup interior reverberation time T60, layup model based on past impedance tube testing, and layup model plus air absorption correction. The evaluation/validation was carried out by acquiring octave band microphone data simultaneously at ten fixed locations throughout the mockup. SPLs (Sound Pressure Levels) predicted by our SEA model match well with measurements for our CM mockup, with a more complicated shape. Additionally in FY09, background NC noise (Noise Criterion) simulation and MRT (Modified Rhyme Test) were developed and performed in the mockup to determine the maximum noise level in CM habitable volume for fair crew voice communications. Numerous demonstrations of simulated noise environment in the mockup and associated SIL (Speech Interference Level) via MRT were performed for various communities, including members from NASA and Orion prime-/sub-contractors. Also, a new HSIR (Human-Systems Integration Requirement) for limiting pre- and post-landing SIL was proposed.

Chu, SShao-sheng R.↗
NASA NTRS2007

System for Thermal Imaging of Hot Moving Objects

The High Altitude/Re-Entry Vehicle Infrared Imaging (HARVII) system is a portable instrumentation system for tracking and thermal imaging of a possibly distant and moving object. The HARVII is designed specifically for measuring the changing temperature distribution on a space shuttle as it reenters the atmosphere. The HARVII system or other systems based on the design of the HARVII system could also be used for such purposes as determining temperature distributions in fires, on volcanoes, and on surfaces of hot models in wind tunnels. In yet another potential application, the HARVII or a similar system would be used to infer atmospheric pollution levels from images of the Sun acquired at multiple wavelengths over regions of interest. The HARVII system includes the Ratio Intensity Thermography System (RITS) and a tracking subsystem that keeps the RITS aimed at the moving object of interest. The subsystem of primary interest here is the RITS (see figure), which acquires and digitizes images of the same scene at different wavelengths in rapid succession. Assuming that the time interval between successive measurements is short enough that temperatures do not change appreciably, the digitized image data at the different wavelengths are processed to extract temperatures according to the principle of ratio-intensity thermography: The temperature at a given location in a scene is inferred from the ratios between or among intensities of infrared radiation from that location at two or more wavelengths. This principle, based on the Stefan-Boltzmann equation for the intensity of electromagnetic radiation as a function of wavelength and temperature, is valid as long as the observed body is a gray or black body and there is minimal atmospheric absorption of radiation.

Weinstein, Leonard↗
NASA NTRS2010

Spacecraft Internal Acoustic Environment Modeling

Acoustic modeling can be used to identify key noise sources, determine/analyze sub-allocated requirements, keep track of the accumulation of minor noise sources, and to predict vehicle noise levels at various stages in vehicle development, first with estimates of noise sources, later with experimental data. This paper describes the implementation of acoustic modeling for design purposes by incrementally increasing model fidelity and validating the accuracy of the model while predicting the noise of sources under various conditions. During FY 07, a simple-geometry Statistical Energy Analysis (SEA) model was developed and validated using a physical mockup and acoustic measurements. A process for modeling the effects of absorptive wall treatments and the resulting reverberation environment were developed. During FY 08, a model with more complex and representative geometry of the Orion Crew Module (CM) interior was built, and noise predictions based on input noise sources were made. A corresponding physical mockup was also built. Measurements were made inside this mockup, and comparisons were made with the model and showed excellent agreement. During FY 09, the fidelity of the mockup and corresponding model were increased incrementally by including a simple ventilation system. The airborne noise contribution of the fans was measured using a sound intensity technique, since the sound power levels were not known beforehand. This is opposed to earlier studies where Reference Sound Sources (RSS) with known sound power level were used. Comparisons of the modeling result with the measurements in the mockup showed excellent results. During FY 10, the fidelity of the mockup and the model were further increased by including an ECLSS (Environmental Control and Life Support System) wall, associated closeout panels, and the gap between ECLSS wall and mockup wall. The effect of sealing the gap and adding sound absorptive treatment to ECLSS wall were also modeled and validated.

Chu, Shao-Sheng R.↗
NASA NTRS2008

Attitude Controller for the Atmospheric Entry of the Mars Science Laboratory

This paper describes the attitude controller for the atmospheric entry of the Mars Science Laboratory (MSL). The controller will command 8 RCS thrusters to control the 3- axis attitude of the entry capsule. The Entry Controller is formulated as three independent channels in the control frame, which is nominally aligned with the stability frame. Each channel has a feedfoward and a feedback path. The feedforward path enables fast response to large bank commands. The feedback path stabilizes the vehicle angle of attack and sideslip around its trim position, and tracks bank commands. The feedback path has a PD/D control structure with deadbands that minimizes fuel usage. The performance of this design is demonstrated via computer simulations.

attitude controller↗
NASA NTRS2012

NASA's Marshall Space Flight Center Recent Studies and Technology Developments in the Area of SSA/Orbital Debris

NASA/MSFC has been investigating the various aspects of the growing orbital debris problem since early 2009. Data shows that debris ranging in size from 5 mm to 10 cm presents the greatest threat to operational spacecraft today. Therefore, MSFC has focused its efforts on small orbital debris. Using off-the-shelf analysis packages, like the ESA MASTER software, analysts at MSFC have begun to characterize the small debris environment in LEO to support several spacecraft concept studies and hardware test programs addressing the characterization, mitigation, and ultimate removal, if necessary, of small debris. The Small Orbital Debris Active Removal (SODAR) architectural study investigated the overall effectiveness of removing small orbital debris from LEO using a low power, space-based laser. The Small Orbital Debris Detection, Acquisition, and Tracking (SODDAT) conceptual technology demonstration spacecraft was developed to address the challenges of in-situ small orbital debris environment classification including debris observability and instrument requirements for small debris observation. Work is underway at MSFC in the areas of hardware and testing. By combining off the shelf digital video technology, telescope lenses, and advanced video image FPGA processing, MSFC is building a breadboard of a space based, passive orbital tracking camera that can detect and track faint objects (including small debris, satellites, rocket bodies, and NEOs) at ranges of tens to hundreds of kilometers and speeds in excess of 15 km/sec,. MSFC is also sponsoring the development of a one-of-a-kind Dynamic Star Field Simulator with a high resolution large monochrome display and a custom collimator capable of projecting realistic star images with simple orbital debris spots (down to star magnitude 11-12) into a passive orbital detection and tracking system with simulated real-time angular motions of the vehicle mounted sensor. The dynamic star field simulator can be expanded for multiple sensors (including advanced star trackers), real-time vehicle pointing inputs, and more complex orbital debris images. This system is also adaptable to other sensor optics, missions, and installed sensor testing.

Wiegmann, Bruce M.↗
NASA NTRS2021

Fluid Servicing Road Area SWMUs 037 and 102 Interim Groundwater Monitoring Report Kennedy Space Center, Florida

This Interim Groundwater Monitoring (IGWM) Report presents the findings of the IGWM activities conducted during the 2021 reporting period at the Fluid Servicing Road Area (FSRA) of Kennedy Space Center (KSC), Florida. The IGWM program was implemented at sites where active remediation was not occurring to monitor and track plume footprints and concentrations. FSRA is located east of the Vehicle Assembly Building and includes Components Cleaning Facility (CCF) also known as Solid Waste Management Unit (SWMU) 030; Converter Compressor Building (CCB) also known as SWMU 089; Area South of K7-516 (516S) also known as SWMU 100; Propellants Support Building Area (PSBA) also known as SWMU 102; and Former Drum Storage Area (FDSA) also known as SWMU 037.

Carol Cady↗
DOE OSTI2025

Synopsis of NREL's Automated Mobility District (AMD) Research Program and Associated Publications

An automated mobility district (AMD) envisions a system of integrated mobility options that serves major activity centers such as campuses, central business districts, and large medical facilities. The National Renewable Energy Laboratory (NREL) has been investigating the implementation prospects for fully automated passenger transport systems that are deployed to operate within dense urban settings. This document provides a synopsis of findings revealed over the last three phases of work, which have yielded insights into the creation and management of AMDs anticipated to use automated vehicle (AV) technology over the next decade. Phase I and Phase II tracked the deployment and lessons learned from 10 early-stage demonstrations of automated shuttle deployments, and their associated insights into the challenges for automated driving systems to achieve safe operations within district-scale deployments. Phase III began in-depth investigations of critical subsystem components, as automation, electrification, and on-demand service continue to converge within initial AMD operations. These directed studies focus on elements of electrification, curbfront/station management, the role of infrastructure sensing, and overall integration of AMD safety management in central, simultaneous coordination of multiple AMD fleets. Future research in AMDs includes systems engineering methodology (more frequently referred to as "digital twins") for planning, design, testing, and ongoing operation of AMDs; location (or co-location) of management functions; and human supervision and passenger communications for safety and security in unattended vehicles. The synopsis references the foundational research products (papers and presentations) that have been published through conference proceedings, journal articles, and NREL reports.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2023

Lithium-Ion Battery Technologies for Electric Vehicles: Progress and challenges

Electric Vehicle (EV) sales and adoption have seen a significant growth in recent years, thanks to advancements and cost reduction in lithium-ion battery technology, attractive performance of EVs, governments' incentives, and the push to reduce greenhouse gases and pollutants. In this article, we will explore the progress in lithium-ion batteries and their future potential in terms of energy density, life, safety, and extreme fast charge. Here we will also discuss material sourcing, supply chain, and end-of-life-cycle management as they have become important considerations in the ecosystem of batteries for the sustained growth and adoption of EVs. With significant government and private sector investments in research and development, processing, and manufacturing and advances in anodes (lithium and silicon), cathodes (high nickel), designs, supply chain development, and the circularity of lithium-ion batteries, lithium-based batteries are on track to make EVs mainstream, addressing climate concerns of fossil-fueled vehicles.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
NASA NTRS2001

X-38 Application of Dynamic Inversion Flight Control

This paper summarizes the application of a nonlinear dynamic inversion (DI) flight control system (FCS) to an autonomous flight test vehicle in NASA's X-38 Project, a predecessor to the International Space Station (ISS) Crew Return Vehicle (CRV). Honeywell's Multi-Application Control-H (MACH) is a parameterized FCS design architecture including both model-based DI rate-compensation and classical P+I command-tracking. MACH was adopted by X-38 in order to shorten the design cycle time for different vehicle shapes and flight envelopes and evolving aerodynamic databases. Specific design issues and analysis results are presented for the application of MACH to the 3rd free flight (FF3) of X-38 Vehicle 132 (V132). This B-52 drop test, occurring on March 30, 2000, represents the first flight test of MACH and one of the first few known applications of DI in the primary FCS of an autonomous flight test vehicle.

Wacker, Roger↗
NASA NTRS2008

Attitude and Translation Control of a Solar Sail Vehicle

A report discusses the ability to control the attitude and translation degrees-of-freedom of a solar sail vehicle by changing its center of gravity. A movement of the spacecraft s center of mass causes solar-pressure force to apply a torque to the vehicle. At the compact core of the solar-sail vehicle lies the spacecraft bus which is a large fraction of the total vehicle mass. In this concept, the bus is attached to the spacecraft by two single degree-of-freedom linear tracks. This allows relative movement of the bus in the sail plane. At the null position, the resulting solar pressure applies no torque to the vehicle. But any deviation of the bus from the null creates an offset between the spacecraft center of mass and center of solar radiation pressure, resulting in a solar-pressure torque on the vehicle which changes the vehicle attitude. Two of the three vehicle degrees of freedom can be actively controlled in this manner. The third, the roll about the sunline, requires a low-authority vane/propulsive subsystem. Translation control of the vehicle is achieved by directing the solar-pressure-induced force in the proper inertial direction. This requires attitude control. Attitude and translation degrees-of-freedom are therefore coupled. A guidance law is proposed, which allows the vehicle to stationkeep at an appropriate point on the inertially-rotating Sun-Earth line. Power requirements for moving the bus are minimal. Extensive software simulations have been performed to demonstrate the feasibility of this concept.

Singh, Gurkirpal↗
NASA NTRS1961

Considerations Affecting Satellite and Space Probe Research with Emphasis on the "Scout" as a Launch Vehicle

This report reviews a number of the factors which influence space flight experiments. Included are discussions of payload considerations, payload design and packaging, environmental tests, launch facilities, tracking and telemetry requirements, data acquisition, processing and analysis procedures, communication of information, and project management. Particular emphasis is placed on the "Scout" as a launching vehicle. The document includes a description of the geometry of the "Scout" as well as its flight capabilities and limitations. Although oriented toward the "Scout" vehicle and its payload capabilities, the information presented is sufficiently general to be equally applicable to most space vehicle systems.

Posner, Jack↗
NASA NTRS1982

Advanced Multipurpose Rendezvous Tracking System Study

Rendezvous and docking (R&D) sensors needed to support Earth orbital operations of vehicles were investigated to determine the form they should take. An R&D sensor must enable an interceptor vehicle to determine both the relative position and the relative attitude of a target vehicle. Relative position determination is fairly straightforward and places few constraints on the sensor. Relative attitude determination, however, is more difficult. The attitude is calculated based on relative position measurements of several reflectors placed in a known arrangement on the target vehicle. The constraints imposed on the sensor by the attitude determination method are severe. Narrow beamwidth, wide field of view (fov), high range accuracy, and fast random scan capability are all required to determine attitude by this method. A consideration of these constraints as well as others imposed by expected operating conditions and the available technology led to the conclusion that the sensor should be a cw optical radar employing a semiconductor laser transmitter and an image dissector receiver.

Laurie, R. J.↗
NASA NTRSDate not supplied

James Webb Space Telescope Navigation Optimization Challenges

The James Webb Space Telescope (JWST) is a NASA flagship mission launched on December 25, 2021. The early orbit phase was highlighted by three midcourse correction burns that were performed to maneuver the vehicle into a libration orbit at the second Sun-Earth-Moon (SEM) libration point (L2). During the coast to L2, the vehicle’s primary observatory and sunshield were deployed. Once the tennis-court-sized sunshield was unfurled and tensioned into place, the large area exposed to solar radiation pressure (SRP) dictated that the SRP force model would need to account for the vehicle’s geometry, reflective properties, and orientation relative to the Sun. Following the insertion of JWST into its L2 libration orbit on January 24, 2022, the commissioning phase for the vehicle’s observatory commenced along with the first cycle of routine station-keeping maneuvers. The NASA Goddard Space Flight Center’s Flight Dynamics Facility (FDF) provides navigation services for the JWST mission. The FDF serves as the prime or backup navigation operations center for more than 30 active missions spanning a wide array of flight regimes performing orbit determination, maneuver planning, trajectory optimization, and tracking data evaluation. Definitive orbit determination for JWST is performed by the FDF using an Extended Kalman Filter (EKF) to estimate the vehicle’s trajectory and reflective properties using Deep Space Network (DSN) TRK-2-34 tracking data and spacecraft attitude telemetry. For the purposes of orbit prediction and station-keeping maneuver targeting, the sensitivity of the SRP force to the vehicle’s orientation requires that predictive attitude information must be incorporated to generate accurate orbit predictions and maneuver plans. Predictive attitude plans are provided to the FDF by the JWST Spacecraft Operations Center (SOC). Short-term (28 day) orbit predictions are propagated using a Short Range Attitude Plan (SRAP) to model the vehicle’s future attitude states for up to a week. SRAP attitude data is highly reliable, as it reflects finalized planned attitude states that the vehicle will be commanded to attain during the ensuing week. A Long Range Attitude Plan (LRAP) can be implemented to model predicted attitude states beyond one week, but these predictions are tentative and subject to revision due to changes in science operations plans. Instead, a conservative approach of applying a Sun-Pointing Neutral (SPN) attitude configuration is utilized for long-term (2 year) orbit predictions where reliable planned attitude data is not available. SPN attitude mode aligns the net SRP force along the JWST-to-Sun vector where it becomes independent of the vehicle’s angle of rotation about this vector, defined as the Sun yaw. Given the dynamic instability of the libration orbit, station-keeping thrust must be applied in either the sunward or anti-sunward direction to balance the resulting orbit. The attitude constraints of the vehicle also impose limits on the available pointing directions for station-keeping thrusters. The thrusters cannot be aligned with the optimal pointing direction for sunward maneuvers, rendering sunward maneuvers to be significantly less fuel efficient than anti-sunward maneuvers. Consequently, station-keeping maneuvers must be targeted to balance the orbit while ensuring that the next maneuver will also be performed in the anti-sunward direction to optimize propellant usage. When targeting a station-keeping maneuver, the attitude and SRP modeling configuration which is applied to the predicted post-maneuver trajectory will dictate the direction of the subsequent station-keeping maneuver, assuming nominal propulsion system performance. If the predicted post-maneuver attitude states result in an SRP model which under-predicts the cumulative SRP impact on the post-maneuver orbit, a targeted anti-sunward maneuver will be larger than necessary and the next maneuver will need to be executed sunward in order to compensate. In contrast, an anti-sunward maneuver which is targeted using an SRP model which over-predicts the cumulative SRP impact will achieve station-keeping while ensuring that the next maneuver will likewise be performed anti-sunward. For this reason, station-keeping maneuvers are targeted while applying the SPN attitude mode, as this mode entails the largest possible SRP area cross-section and therefore a larger modeled cumulative SRP impact. This paper documents the NASA Goddard Space Flight Center’s FDF support for JWST on-orbit operations and the analysis projects undertaken utilizing the experiences and data accumulated throughout the first full year of routine science operations. The results of these analysis efforts have been used to implement improvements to orbit prediction accuracy and maneuver efficiency which have the potential to prolong the lifespan of JWST to continue to conduct ground-breaking infrared astronomy for decades to come.

Flight Dynamics↗
DOE OSTI2021

Optimizing Vehicle Fleet and Assignment for Concentrating Solar Power Plant Heliostat Washing

Concentrating solar power central-receiver plants use thousands of sun-tracking mirrors, i.e., heliostats, to reflect sunlight to a central receiver, which collects and uses the heat to generate electricity. Over time, soiling reduces the reflectivity of the heliostats and, therefore, the efficiency of the system. Current industry practice sends vehicles to wash heliostats in an ad hoc fashion. We present a mixed-integer nonlinear program that determines wash vehicle fleet size, mix, and assignment of wash crews to heliostats to minimize the sum of (i) the revenues lost due to heliostat soiling, (ii) the costs of hiring wash crews and operating the vehicles, and (iii) the costs of purchasing wash vehicles. We establish conditions for convexity of the objective function, and then propose a decomposition method that enables near-optimal solutions to the wash vehicle fleet sizing and assignment problem on the order of a couple of minutes. Furthermore, these solutions yield hundreds of thousands of dollars in savings per year over current industry practices.

14 SOLAR ENERGY↗
NASA NTRS1999

Reusable Launch Vehicle Control in Multiple Time Scale Sliding Modes

A reusable launch vehicle control problem during ascent is addressed via multiple-time scaled continuous sliding mode control. The proposed sliding mode controller utilizes a two-loop structure and provides robust, de-coupled tracking of both orientation angle command profiles and angular rate command profiles in the presence of bounded external disturbances and plant uncertainties. Sliding mode control causes the angular rate and orientation angle tracking error dynamics to be constrained to linear, de-coupled, homogeneous, and vector valued differential equations with desired eigenvalues placement. The dual-time scale sliding mode controller was designed for the X-33 technology demonstration sub-orbital launch vehicle in the launch mode. 6DOF simulation results show that the designed controller provides robust, accurate, de-coupled tracking of the orientation angle command profiles in presence of external disturbances and vehicle inertia uncertainties. It creates possibility to operate the X-33 vehicle in an aircraft-like mode with reduced pre-launch adjustment of the control system.

Shtessel, Yuri↗