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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 37 records · Page 2
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NASA NTRS2016

Differential Evolution Optimization for Targeting Spacecraft Maneuver Plans

Previous analysis identified specific orbital parameters as being safer for conjunction avoidance for the TDRS fleet. With TDRS-9 being considered an at-risk spacecraft, a potential conjunction concern was raised should TDRS-9 fail while at a longitude of 12W. This document summarizes the analysis performed to identify if these specific orbital parameters could be targeted using the remaining drift-termination maneuvers for the relocation of TDRS-9 from 41W longitude to 12W longitude.

Manuever↗
NASA NTRSDate not supplied

Flight Performance Maneuver Planning for NASA’s X-57 “Maxwell” Flight Demonstrator – Part 2: Power-On Effects

Distributed Electric Propulsion technology as envisioned for NASA’s X-57 “Maxwell” flight demonstrator concept was designed to increase high-speed cruise efficiency compared to a combustion-powered general aviation baseline. A portion of this increased efficiency was due to beneficial aero-propulsive interaction inherent to the distributed propulsion architecture. The measure of the increase in efficiency between a conventional and distributed propulsion wing was to be determined by comparing flight test data from the electrically powered, conventional wing X-57 Mod II configuration to data obtained from the electrically powered, distributed propulsion wing X-57 Mod III/IV configuration. Flight test maneuvers that accommodate errors in instrumentation and the flight test environment were previously developed to establish the power-off drag characteristics for all X-57 configurations. In this paper, test points and maneuvers are evaluated to establish the installed and gross thrust that build upon the power-off drag estimates. Analysis of the proposed power-on maneuvers shows that the selected test points and measurement techniques could generate installed thrust estimates within 3-7% (at the 50% confidence level) of the actual values if each maneuver is conducted over a time period of 40 seconds.

Nicholas K Borer↗
NASA NTRS2019

Flight Performance Maneuver Planning for NASA’s X-57 “Maxwell” Flight Demonstrator – Part 1: Power-Off Glides

Distributed Electric Propulsion technology is expected to yield up to a fivefold increase in high-speed cruise efficiency for NASA’s X-57 “Maxwell” flight demonstrator when compared to a combustion-powered general aviation baseline. A portion of this increased efficiency is due to beneficial aero-propulsive interaction inherent to the distributed propulsion architecture. The measure of the relative increase in efficiency between a conventional and distributed propulsion wing will be extracted from comparisons between flight test data from the electrically powered X-57 Mod II configuration with a conventional wing, and from the electrically powered X-57 Mod III/IV configuration with a distributed propulsion wing. Flight test maneuvers that accommodate errors in instrumentation and the flight test environment are developed to establish the power-off drag characteristics for all X-57 configurations. Analysis of these maneuvers with typical errors, including pilot-in-the-loop simulation data that incorporates simulated atmospheric turbulence effects, shows that the proposed power-off flight maneuvers can generate accurate power-off drag predictions for the X-57. These predictions show that the power-off differences in aerodynamic performance between the conventional and distributed propulsion configurations can be accurately measured from flight test data in the presence of typical data error sources.

Borer, Nicholas K.↗
NASA NTRS2003

On-board autonomous attitude maneuver planning for planetary spacecraft using genetic algorithms

A key enabling technology that leads to greater spacecraft autonomy is the capability to autonomously and optimally slew the spacecraft from and to different attitudes while operating under a number of celestial and dynamic constraints. The task of finding an attitude trajectory that meets all the constraints is a formidable one, in particular for orbiting or fly-by spacecraft where the constraints and initial and final conditions are of time-varying nature. This paper presents an approach for attitude path planning that makes full use of a priori constraint knowledge and is computationally tractable enough to be executed on-board a spacecraft. The approach is based on incorporating the constraints into a cost function and using a Genetic Algorithm to iteratively search for and optimize the solution. This results in a directed random search that explores a large part of the solution space while maintaining the knowledge of good solutions from iteration to iteration. A solution obtained this way may be used 'as is' or as an initial solution to initialize additional deterministic optimization algorithms. A number of example simulations are presented including the case examples of a generic Europa Orbiter spacecraft in cruise as well as in orbit around Europa. The search times are typically on the order of minutes, thus demonstrating the viability of the presented approach. The results are applicable to all future deep space missions where greater spacecraft autonomy is required. In addition, onboard autonomous attitude planning greatly facilitates navigation and science observation planning, benefiting thus all missions to planet Earth as well.

genetic algorithm↗
NASA NTRS2004

Spacecraft Attitude Maneuver Planning Using Genetic Algorithms

A key enabling technology that leads to greater spacecraft autonomy is the capability to autonomously and optimally slew the spacecraft from and to different attitudes while operating under a number of celestial and dynamic constraints. The task of finding an attitude trajectory that meets all the constraints is a formidable one, in particular for orbiting or fly-by spacecraft where the constraints and initial and final conditions are of time-varying nature. This approach for attitude path planning makes full use of a priori constraint knowledge and is computationally tractable enough to be executed onboard a spacecraft. The approach is based on incorporating the constraints into a cost function and using a Genetic Algorithm to iteratively search for and optimize the solution. This results in a directed random search that explores a large part of the solution space while maintaining the knowledge of good solutions from iteration to iteration. A solution obtained this way may be used as is or as an initial solution to initialize additional deterministic optimization algorithms. A number of representative case examples for time-fixed and time-varying conditions yielded search times that are typically on the order of minutes, thus demonstrating the viability of this method. This approach is applicable to all deep space and planet Earth missions requiring greater spacecraft autonomy, and greatly facilitates navigation and science observation planning.

Kornfeld, Richard P.↗
NASA NTRS2017

Orbit Determination Strategy and Simulation Performance for OSIRIS-REx Proximity Operations

The Origins Spectral Interpretation Resource Identification Security Regolith Explorer (OSIRISREx)is a NASA New Frontiers mission to the near-earth asteroid Bennu that will rendez vousin 2018, create a comprehensive and detailed set of observations over several years, collect a regolith sample, and return the sample to Earth in 2023. The Orbit Determination (OD) team isa sub-section of the Flight Dynamics System responsible for generating precise reconstructions and predictions of the spacecraft trajectory. The OD team processes radiometric data, LIDAR, as well as center-finding and landmark-based Optical Navigation images throughout the proximity operations phase to estimate and predict the spacecraft location within several meters. Stringent knowledge requirements stress the OD teams concept of operations and procedures to produce verified and consistent high quality solutions for observation planning, maneuver planning, and onboard sequencing. This paper will provide insight into the OD concept of operations and summarize the OD performance expected during the approach and early proximity operation phases,based on our pre-encounter knowledge of Bennu. Strategies and methods used to compare and evaluate predicted and reconstructed solutions are detailed. The use of high fidelity operational tests during early 2017 will stress the teams concept of operations and ability to produce precise OD solutions with minimal turn-around delay.

Leonard, Jason M.↗
NASA NTRS2018

Realistic Covariance Generation for the GPM Spacecraft

A covariance realism process for NASA's Global Precipitation Measurement (GPM) spacecraft is detailed. The GPM spacecraft is in a low earth orbit, and performs collision avoidance maneuvers few times a year. Currently GPM is below the International Space Station (ISS). So, in addition to cataloged debris objects, GPM must contend with smallsat/cubesat objects that are deployed from the ISS. Both operational scenarios require complete knowledge of the expected GPM prediction errors as a function of time. In this study, we present a method for generating realistic predicted covariance that uses linear propagation of the covariance with the addition of process noise. Further analyses are presented for the process noise ''tuning'' that generates an inflation factor based on the observed error statistics of the predictive satellite trajectories when compared to the definitive ones. Different tuning strategies are considered and compared via a Goodness-of-Fit testing for the Gaussian properties of the scaled covariance. SpaceNav's realistic covariance generation approach takes into account the contribution of predicted maneuver errors in the increased propagation uncertainty. Corresponding maneuver uncertainty is injected into the state uncertainty, and is used within the collision avoidance process to determine the collision risk for close approach events that follow a maneuver. This is a critical step in the maneuver planning process that provides the satellite operator with an accurate quantification of the collision probability for planned maneuvers. Using this information, an informed decision can be made to proceed with a maneuver if the collision risk is acceptable. This approach is validated by Monte-Carlo simulations and results are presented.

spacecraft uncertainty propagation↗
NASA NTRS1999

Autonomous Formation Flying from Ground to Flight

The cost of on-orbit operations remains a significant and increasingly visible concern in the support of satellite missions. Headway has been made in automating some ground operations; however, increased mission complexity and more precise orbital constraints have compelled continuing human involvement in mission design and maneuver planning operations. AI Solutions, Inc. in cooperation with the National Aeronautics and Space Administration's (NASA) Goddard Space Flight Center (GSFC) has tackled these more complex problems through the development of AutoCon as a tool for an automated solution. NASA is using AutoCon to automate the maneuver planning for the Earth Orbiter-1 (EO-1) mission. AutoCon was developed originally as a ground system tool. The EO-1 mission will be using a scaled version of AutoCon on-board the EO-1 satellite to command orbit adjustment maneuvers. The flight version of AutoCon plans maneuvers based on formation flying algorithms developed by GSFC, JPL, and other industry partners. In its fully autonomous mode, an AutoCon planned maneuver will be executed on-board the satellite without intervention from the ground. This paper describes how AutoCon automates maneuver planning for the formation flying constraints of the EO-1 mission. AutoCon was modified in a number of ways to automate the maneuver planning on-board the satellite. This paper describes how the interface and functionality of AutoCon were modified to support the on-board system. A significant component of this modification was the implementation of a data smoother, based on a Kalman filter, that ensures that the spacecraft states estimated by an on-board GPS receiver are as accurate as possible for maneuver planning. This paper also presents the methodology use to scale the AutoCon functionality to fit and execute on the flight hardware. This paper also presents the modes built that allow the incremental phasing in of autonomy. New technologies for autonomous operations are usually received with significant, and probably appropriate trepidation. A number of safeguards have been designed in both AutoCon and the interfacing systems to alleviate the potential of mission-impacting anomalies from the on-board autonomous system. This paper describes the error checking, input data integrity validation and limits set on maneuvers in AutoCon and the on-board system.

Chapman, Keith B.↗
NASA NTRS1999

Autonomous Formation Flying from the Ground to Flight

The cost of on-orbit operations remains a significant and increasingly visible concern in the support of satellite missions. Headway has been made in automating some ground operations; however, increased mission complexity and more precise orbital constraints have compelled continuing human involvement in mission design and maneuver planning operations. AI Solutions, Inc. in cooperation with the National Aeronautics and Space Administration's (NASA) Goddard Space Flight Center (GSFC) has tackled these more complex problems through the development of AutoCon(TM) as a tool for an automated solution. NASA is using AutoCon(TM) to automate the maneuver planning for the Earth Orbiter-1 (EO-1) mission. AutoCon(TM) was developed originally as a ground system tool. The EO-1 mission will be using a scaled version of AutoCon(TM) on-board the EO-1 satellite to command orbit adjustment maneuvers. The flight version of AutoCon(TM) plans maneuvers based on formation flying algorithms developed by GSFC, JPL, and other industry partners. In its fully autonomous mode, an AutoCon(TM) planned maneuver will be executed on-board the satellite without intervention from the ground. This paper describes how AutoCon(TM) automates maneuver planning for the formation flying constraints of the EO-1 mission. AutoCon(TM) was modified in a number of ways to automate the maneuver planning on-board the satellite. This paper describes how the interface and functionality of AutoCon(TM) were modified to support the on-board system. A significant component of this modification was the implementation of a data smoother, based on a Kalman filter, that ensures that the spacecraft states estimated by an on-board GPS receiver are as accurate as possible for maneuver planning. This paper also presents the methodology used to scale the AutoCon(TM) functionality to fit and execute on the flight hardware. This paper also presents the modes built into the system that allow the incremental phasing in of autonomy. New technologies for autonomous operations are usually received with significant, and probably appropriate, trepidation. A number of safeguards have been designed in both AutoCon(TM) and the interfacing systems to alleviate the potential of mission-impacting anomalies from the on-board autonomous system. This paper describes the error checking, input data integrity validation, and limits set on maneuvers in AutoCon(TM) and the on-board system.

Chapman, Keith B.↗
NASA NTRS2002

An Overview of Trajectory Design Operations for the Microwave Anisotropy Probe (MAP) Mission

The main science objective of the Microwave Anisotropy Probe (MAP) mission is to produce an accurate full-sky map of the cosmic microwave background temperature fluctuations - anisotropy. MAP will collect these measurements from a lissajous orbit about the Sun-Earth/Moon L2 Lagrange Point. The NASA Goddard Space Flight Center (GSFC) Flight Dynamics Analysis Branch provided mission analysis, maneuver planning and maneuver calibration for the MAP spacecraft. This paper will provide an overview of the MAP trajectory design, a summary of the maneuvers executed. Differences from the pre-launch nominal plan will also be discussed. During the MAP phasing loops, MAP performed three calibration maneuvers in order to characterize the performance of the primary sets of thrusters - +X, +Z, and -Z. The calibration maneuvers were designed to minimize their impact on the trajectory. Four maneuvers were performed to set up the gravity assist of the Moon - required to propel MAP out to its orbit about L2. These maneuvers were performed at the three phasing loop perigees and at 18 hours after the final perigee. It became necessary to alter some of the perigee maneuvers in order to shape the gravity assist. This shaping was done to help meet some mission goals. In particular, the gravity assist was changed slightly in order to remove lunar shadows in both the cruise out to L2 and in the first revolution about L2. This amounted to a change in the phasing loop AV of less than 1 m/s. After the gravity assist, two mid-course correction (MCC) maneuvers were performed in order to fine-tune the trajectory. MCC1 was used to clean up and errors which resulted from the gravity assist. MCC2 was performed in order to mitigate a large stationkeeping maneuver following a crucial instrument calibration period during the cruise phase. MAP executed it's first stationkeeping maneuver in January 16th and is ready for a second calibration period during late Winter / early Spring. Further information concerning subsequent stationkeeping maneuver will be added as they become available.

Cuevas, Osvaldo O.↗