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Results for “optimization, trajectory design”

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 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
NASA NTRS2007

Solar Sail Spaceflight Simulation

The Solar Sail Spaceflight Simulation Software (S5) toolkit provides solar-sail designers with an integrated environment for designing optimal solar-sail trajectories, and then studying the attitude dynamics/control, navigation, and trajectory control/correction of sails during realistic mission simulations. Unique features include a high-fidelity solar radiation pressure model suitable for arbitrarily-shaped solar sails, a solar-sail trajectory optimizer, capability to develop solar-sail navigation filter simulations, solar-sail attitude control models, and solar-sail high-fidelity force models.

Lisano, Michael↗
NASA NTRS2015

Near-Earth Asteroids 2006 RH120 AND 2009 BD: Proxies for Maximally Accessible Objects?

NASA's Near-Earth Object Human Space Flight Accessible Targets Study (NHATS) has identified over 1,400 of the approximately 12,800 currently known near-Earth asteroids (NEAs) as more astrodynamically accessible, round-trip, than Mars. Hundreds of those approximately 1,400 NEAs can be visited round-trip for less change-in-velocity than the lunar surface, and dozens can be visited round-trip for less change-in-velocity than low lunar orbit. How accessible might the millions of undiscovered NEAs be? We probe that question by investigating the hypothesis that NEAs 2006 RH120 and 2009 BD are proxies for the most accessible NEAs we would expect to find, and describing possible future NEA population model studies.

Trajectory Optimization↗
NASA NTRS2016

Low-Thrust Transfers from Distant Retrograde Orbits to L2 Halo Orbits in the Earth-Moon System

Enable future missions Any mission to a DRO or halo orbit could benefit from the capability to transfer between these orbits Chemical propulsion could be used for these transfers, but at high propellant cost Fill gaps in knowledge A variety of transfers using SEP or solar sails have been studied for the Earth-Moon system Most results in literature study a single transfer This is a step toward understanding the wide array of types of transfers available in an N-body force model.

optimization↗
NASA NTRS2016

General Mission Analysis Tool (GMAT)

This is a software tutorial and presentation demonstrating the application of the General Mission Analysis Tool (GMAT) to the critical design phase of NASA missions. The demonstration discusses GMAT basics, then presents a detailed example of GMAT application to the Transiting Exoplanet Survey Satellite (TESS) mission. Other examples include OSIRIS-Rex. This talk is a combination of existing presentations; a GMAT basics and overview, and technical presentations from the TESS and OSIRIS-REx projects on their application of GMAT to critical mission design. The GMAT basics slides are taken from the open source training material. The OSIRIS-REx slides are from a previous conference presentation. The TESS slides are a streamlined version of the CDR package provided by the project with SBU and ITAR data removed by the TESS project.

optimization↗
NASA NTRS2017

Lucy: Navigating a Jupiter Trojan Tour

In January 2017, NASA selected the Lucy mission to explore six Jupiter Trojan asteroids. These six bodies, remnants of the primordial material that formed the outer planets, were captured in the Sun-Jupiter L4 and L5 Lagrangian regions early in the solar system formation. These particular bodies were chosen because of their diverse spectral properties and the chance to observe up close for the first time two orbiting approximately equal mass binaries, Patroclus and Menoetius. KinetX, Inc. is the primary navigation supplier for the Lucy mission. This paper describes preliminary navigation analyses of the approach phase for each Trojan encounter.

trajectory design↗
NASA NTRSDate not supplied

Titan Sample Return Mission using V-Infinity Leveraging

The unique environment of the Saturnian moon Titan provides a particular incentive for a sample return mission in the mid twenty-first century. The thick atmosphere and low gravity provide both useful benefits and harrowing challenges that make optimizing the return trajectory, whether for time of flight or ΔV, especially important for such a long-term mission in order to maximize return. V-infinity leveraging provides a unique capability for finding epoch independent, reduced ΔV return trajectories which can be reliably converged from theoretical results. This paper will demonstrate the ability to use this technique to enable Titan sample missions and examine it relative to other options.

Titan↗
NASA NTRSDate not supplied

Titan Sample Return Mission Using V-Infinity Leveraging

The unique environment of the Saturnian moon Titan provides a particular incentive for a sample return mission in the mid twenty-first century. The thick atmosphere and low gravity provide both useful benefits and harrowing challenges that make optimizing the return trajectory, whether for time of flight or ΔV, especially important for such a long-term mission in order to maximize return. V-infinity leveraging provides a unique capability for finding epoch independent, reduced ΔV return trajectories which can be reliably converged from theoretical results. This paper will demonstrate the ability to use this technique to enable Titan sample missions and examine it relative to other options.

Titan↗
NASA NTRS1973

Low-thrust trajectory analysis for the geosynchronous mission

Methodology employed in development of a computer program designed to analyze optimal low-thrust trajectories is described, and application of the program to a Solar Electric Propulsion Stage (SEPS) geosynchronous mission is discussed. To avoid the zero inclination and eccentricity singularities which plague many small-force perturbation techniques, a special set of state variables (equinoctial) is used. Adjoint equations are derived for the minimum time problem and are also free from the singularities. Solutions to the state and adjoint equations are obtained by both orbit averaging and precision numerical integration; an evaluation of these approaches is made.

Jasper, T. P.↗
NASA NTRS2017

Automation of POST Cases via External Optimizer and "Artificial p2" Calculation

During early conceptual design of complex systems, speed and accuracy are often at odds with one another. While many characteristics of the design are fluctuating rapidly during this phase there is nonetheless a need to acquire accurate data from which to down-select designs as these decisions will have a large impact upon program life-cycle cost. Therefore enabling the conceptual designer to produce accurate data in a timely manner is tantamount to program viability. For conceptual design of launch vehicles, trajectory analysis and optimization is a large hurdle. Tools such as the industry standard Program to Optimize Simulated Trajectories (POST) have traditionally required an expert in the loop for setting up inputs, running the program, and analyzing the output. The solution space for trajectory analysis is in general non-linear and multi-modal requiring an experienced analyst to weed out sub-optimal designs in pursuit of the global optimum. While an experienced analyst presented with a vehicle similar to one which they have already worked on can likely produce optimal performance figures in a timely manner, as soon as the "experienced" or "similar" adjectives are invalid the process can become lengthy. In addition, an experienced analyst working on a similar vehicle may go into the analysis with preconceived ideas about what the vehicle's trajectory should look like which can result in sub-optimal performance being recorded. Thus, in any case but the ideal either time or accuracy can be sacrificed. In the authors' previous work a tool called multiPOST was created which captures the heuristics of a human analyst over the process of executing trajectory analysis with POST. However without the instincts of a human in the loop, this method relied upon Monte Carlo simulation to find successful trajectories. Overall the method has mixed results, and in the context of optimizing multiple vehicles it is inefficient in comparison to the method presented POST's internal optimizer functions like any other gradient-based optimizer. It has a specified variable to optimize whose value is represented as optval, a set of dependent constraints to meet with associated forms and tolerances whose value is represented as p2, and a set of independent variables known as the u-vector to modify in pursuit of optimality. Each of these quantities are calculated or manipulated at a certain phase within the trajectory. The optimizer is further constrained by the requirement that the input u-vector must result in a trajectory which proceeds through each of the prescribed events in the input file. For example, if the input u-vector causes the vehicle to crash before it can achieve the orbital parameters required for a parking orbit, then the run will fail without engaging the optimizer, and a p2 value of exactly zero is returned. This poses a problem, as this "non-connecting" region of the u-vector space is far larger than the "connecting" region which returns a non-zero value of p2 and can be worked on by the internal optimizer. Finding this connecting region and more specifically the global optimum within this region has traditionally required the use of an expert analyst.

Dees, Patrick D.↗
NASA NTRS1997

Lunar Prospector Mission Design

The National Aeronautics and Space Administration (NASA) has selected Lunar Prospector as one of the discovery missions to conduct solar system exploration science investigations. The mission is NASA's first lunar voyage to investigate key science objectives since Apollo and will be launched in September 1997. In keeping with discovery program requirements to reduce total mission cost and utilize new technology, Lunar Prospector's mission design and control will focus on the use of innovative and proven trajectory analysis programs. As part of this effort, the Ames Research Center and the Goddard Space Flight Center have become partners in the Lunar Prospector trajectory team to provide the trajectory analysis and orbit determination support. The mission design of Lunar Prospector is characterized by a direct minimum energy transfer trajectory to the moon with an injection into a circular 100 km altitude polar mapping orbit. The mission design will incorporate the optimization of the reference trajectory for a new launch vehicle. An extended mission includes a periselene altitude approaching 10 km. As part of the navigation, a new lunar potential model will be used that incorporates data from the recent Clementine mission. This paper provides understanding of the design of the Lunar Prospector mission and the optimization process of the nominal trajectory, orbit determination, launch windows, and lunar orbit targets, and discusses the feasibility of meeting the mission goals.

Folta, David↗
NASA NTRS2017

Evolution of Trajectory Design Requirement of NASA's Planned Europa Clipper Mission

Europa is one of the most scientifically intriguing targets in planetary science due to its potential suitability for extant life. As such, NASA has funded the California Institute of Technology Jet Propulsion Laboratory and the Johns Hopkins University Applied Physics Laboratory to jointly develop the planned Europa Clipper mission—a multiple Europa flyby mission architecture aimed to thoroughly investigate the habitability of Europa and provide reconnaissance data to determine a landing site that maximizes the probability of both a safe landing and high scientific value for a potential future Europa lander. The trajectory design—a major enabling component for this Europa Clipper mission concept—was developed to maximize science from a set of eight model payload instruments determined by a NASA-appointed Europa Science Definition Team (SDT) between 2011-2015. On May 26, 2015, NASA officially selected 10 instruments from 6 different U.S. research facilities and universities. With the selection of instruments have come the development of new science measurement requirements, as well as a rich set of requirements stemming from project policies, planetary protection, and the evolved capability and characteristics of the flight system and mission operations system. This paper will focus on the evolution of requirements levied on the trajectory design, discuss strategies and solutions to the multidimensional optimization problem of designing high fidelity end-to-end trajectories that maximize Europa science while mitigating mission risk, complexity and cost, and last, verification of candidate trajectories to meet the requirements on the trajectory design.

Buffington, Brent↗
NASA NTRS2016

Trajectory Design Enhancements to Mitigate Risk for the Transiting Exoplanet Survey Satellite (TESS)

The Transiting Exoplanet Survey Satellite (TESS) will employ a highly eccentric Earth orbit, in 2:1 lunar resonance, which will be reached with a lunar flyby preceded by 3.5 phasing loops. The TESS mission has limited propellant and several constraints on the science orbit and on the phasing loops. Based on analysis and simulation, we have designed the phasing loops to reduce delta-V (DV) and to mitigate risk due to maneuver execution errors. We have automated the trajectory design process and use distributed processing to generate and optimal nominal trajectories; to check constraint satisfaction; and finally to model the effects of maneuver errors to identify trajectories that best meet the mission requirements.

satellite↗
NASA NTRS2015

Multi-Objective Hybrid Optimal Control for Interplanetary Mission Planning

Preliminary design of low-thrust interplanetary missions is a highly complex process. The mission designer must choose discrete parameters such as the number of flybys, the bodies at which those flybys are performed, and in some cases the final destination. Because low-thrust trajectory design is tightly coupled with systems design, power and propulsion characteristics must be chosen as well. In addition, a time-history of control variables must be chosen which defines the trajectory. There are often many thousands, if not millions, of possible trajectories to be evaluated. The customer who commissions a trajectory design is not usually interested in a point solution, but rather the exploration of the trade space of trajectories between several different objective functions. This can be very expensive process in terms of the number of human analyst hours required. An automated approach is therefore very desirable. This work presents such an approach by posing the mission design problem as a multi-objective hybrid optimal control problem. The methods is demonstrated on hypothetical mission to the main asteroid belt and to Deimos.

Trajectory Design↗
NASA NTRS1981

Piloted simulation of an on-board trajectory optimization algorithm

This paper will describe a real time piloted simulation of algorithms designed for on-board computation of time-optimal intercept trajectories for an F-8 aircraft. The algorithms, which were derived using singular perturbation theory, generate commands that are displayed to the pilot on flight director needles on the 8-ball. By flying the airplane so as to zero the horizontal and vertical needles, the pilot flies an approximation to a time-optimal intercept trajectory. The various display and computation modes that are available will be described and results will be presented illustrating the performance of the algorithms with a pilot in the loop.

Price, D. B.↗
NASA NTRS2015

Multi-Objective Hybrid Optimal Control for Multiple-Flyby Low-Thrust Mission Design

Preliminary design of low-thrust interplanetary missions is a highly complex process. The mission designer must choose discrete parameters such as the number of flybys, the bodies at which those flybys are performed, and in some cases the final destination. In addition, a time-history of control variables must be chosen that defines the trajectory. There are often many thousands, if not millions, of possible trajectories to be evaluated. The customer who commissions a trajectory design is not usually interested in a point solution, but rather the exploration of the trade space of trajectories between several different objective functions. This can be a very expensive process in terms of the number of human analyst hours required. An automated approach is therefore very desirable. This work presents such an approach by posing the mission design problem as a multi-objective hybrid optimal control problem. The method is demonstrated on a hypothetical mission to the main asteroid belt.

Optimization↗