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At least 469 records · Page 26
All sourcesNASA NTRSDOE OSTI
NASA NTRS2021

OSIRIS-REx Extended Mission Trajectory Design & Target Search

After jettisoning its Sample Return Capsule (SRC) containing regolith samples from the near-Earth asteroid (101955) Bennu to Earth in September 2023, the Origins, Spectral Interpretation, Resource Identification, and Security–Regolith Explorer (OSIRIS-REx) spacecraft will perform a divert maneuver and safely fly by Earth at an altitude of 250 km. SRC return and the divert maneuver officially mark the completion of the spacecraft’s primary mission; however, it will continue on in heliocentric orbit with a nearly fully-functional instrument suite and enough propellant for nearly 600 m/s Delta-V. The post-Earth flyby trajectory fortuitously enables an exciting extended mission opportunity: rendezvous with the near-Earth asteroid (99942)Apophis immediately following its historic Earth close approach in April 2029. In this paper, we detail the discovery, optimization, and analysis of the Apophis rendezvous trajectory for an extended OSIRIS-REx mission. We also present the technical approach for an alternate target search and corresponding results, assessing the alternate trajectories compared to the baseline Apophis rendezvous from a trajectory design standpoint.

Brian Sutter↗
NASA NTRS2020

Solar System Escape Trajectories Using Outer Planetary Gravity Assists

A broad search of outer planet gravity assist sequences reveals flyby conditions that are naturally amenable for solar system escape. The optimal flyby conditions depend on the arrival velocity at the final body and provide the maximum possible escape speed for purely ballistic sequences. Trajectories in the 2030-2060 time frame are categorized by their encounter year with an emphasis on solar system escape speed and direction. All resulting sequences require a Jupiter gravity assist, and a considerable increase in escape speed is found in trajectories that utilize an additional Saturn, Uranus, or Neptune flyby. However, these solutions are limited by their availability and range of right ascensions. All cataloged trajectories are able to escape the solar system at least 3 au/year, and the highest energy sequences are in excess of 5.5 au/year. The search space is then used to find outer planet gravity assist trajectories to Kuiper Belt Objects (KBOs), and several cases are optimized.

Lam, Try↗
NASA NTRS2021

Expected Thrust Fraction: Resilient Trajectory Design Applied to the Earth Return Orbiter

Electric propulsion is an enabling technology for NASA’s Mars Sample Return mission that affords an order of magnitude reduction in fuel. Unfortunately, elec- tric propulsion’s low-thrust capabilities require long thrusting arcs that make space- craft susceptible to disturbances resulting in missed thrust events. One method for designing trajectories resilient to such missed thrust events is expected thrust frac- tion, which embeds their stochastic nature into a time-varying duty cycle. This paper investigates the application of expected thrust fraction to the Earth Return Orbiter’s outbound Earth-to-Mars trajectory and compares it with trajectories de- signed using traditional methods to mitigate missed thrust events. Through the use of expected thrust fraction, a trajectory with a baseline 65.4% success rate is im- proved to an 86.6% success rate at the cost of only a 12 kg reduction in delivered mass. Additionally, when expected thrust fraction is used in conjunction with a terminal coast, a 96.0% success rate is achieved, which is higher than any single mitigation technique.

Laipert, Frank↗
NASA NTRSDate not supplied

Progress on Inverse Estimation Technique of Non-Linear Pitch Damping Coefficient Curves Using Free-Flight CFD Generated Trajectories

Characterization of entry vehicle pitch damping coefficient curves is crucial to ensure appropriate re-entry and overall mission success. The pitch damping coefficient (C_(m_q )+C_(m_α ̇ )) is used to encapsulate the oscillatory growth or decay of a body during a trajectory. The inverse estimation technique utilizes an existing Free-Flight CFD (FF-CFD) dataset and wraps a reconstruction algorithm in an optimizer. The reconstruction integrates the planar equations of motion derived by Schoenenberger, Queen [1] using Python’s scipy.integrate.solve_ivp. The optimizer’s objective function is the normalized 𝐿2 residual of the angle of attack peaks between the reconstructed trajectory and the original data produced with FF-CFD. Inclusion of the peak times in this residual calculation allows for simultaneous optimization of the pitch moment coefficient, C_(m_α ). This residual equation is shown below in Eq. 1. The optimizer scipy.optimize.minimize was used with the gradient-based Powell method for the analysis presented, however the differential evolution method was investigated as means of comparison, and was found to produce marginally lower residual values with prohibitively longer run times. Further, the pitch damping curve is found by fitting a cubic interpolation function to a set of (α, (C_(m_q )+C_(m_α ̇ ))) control points, where the α points are held constant and the (C_(m_q )+C_(m_α ̇ )) values are the optimized parameters. The pitch moment curve uses a linear interpolation between the minimum and maximum α in the dataset. FF-CFD generated trajectories using the Dragonfly capsule geometry with the Genesis ballistic range model parameters were simulated and used for this analysis. These FF-CFD trajectories simulate planar motion, as restricted by the reconstructing the equations of motion, of three different cases: 1-DoF (free-to-pitch), 2-DoF (free-to-pitch and heave), and 3-DoF (free-to-pitch, heave, and decelerate). Pitch damping coefficient curves generated using this inverse estimation curve technique with FF-CFD 1-DoF Dragonfly data are found in Fig. 1. Preliminary results reconstructing ballistic range shots using these FF-CFD derived predictions of the pitch damping curve (Fig. 1) are shown in Fig. 2. It should be noted that the ballistic range shot used a Genesis model whereas the FF-CFD data used a Dragonfly geometry, however these geometries are similar.

entry↗
NASA NTRSDate not supplied

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↗
NASA NTRSDate not supplied

A New Architecture for Parallelization of Complex Spacecraft Trajectory Optimization Scans

This paper describes CopScanner, a new component of the Copernicus ecosystem for spacecraft trajectory design and optimization. CopScanner is a Python library being developed at the NASA JSC which enables easy parallelization of Copernicus scans. CopScanner is currently being developed and implemented for production of Copernicus trajectory scans for upcoming Artemis Missions (Artemis II and beyond). On the backend, CopScanner utilizes Dask, an open-source Python library for parallel computing which enables parallelization over both multi-core local machines and large-scale distributed computing clusters. CopScanner abstracts the trajectory scanning process into a DAG which is constructed using a chain of individual subscans. Each node in the DAG executes a python module, called the callable, for which there are built-in defaults, or users may specify their own. Support for custom callables makes CopScanner a versatile trajectory optimization software. All output files and associated metadata from a CopScanner scan are compressed and stored in a two-file output, collectively called the FileStore, consisting of a SQLite database and a compressed JSON MessagePack file, for which CopScanner provides a Python class for interaction.

Quentin Moore↗
NASA NTRS2023

Trajectory Design and Early Mission Operations for the Lunar IceCube Mission

The Lunar IceCube (LIC) mission, a Next Space Technologies for Exploration Partnerships (NSTEP) program selection, was launched as a rideshare onboard Artemis-I on November 16th 2022, and deployed into a high energy lunar flyby trajectory. The final destination of the mission was a polar elliptical lunar orbit from which it could conduct spectroscopy observations of the lunar surface; however, a near rectilinear halo orbit (NRHO) was planned to be used as a staging orbit that divided the lunar transfer and low-thrust spiral phases of the mission. This paper presents the process used to design the LIC transfer trajectory from the high-energy deployment state to a 9:2 synodic resonance NRHO. Additional analyses performed, to assess the critical deployment to lunar flyby phase of the trajectory and to generate recovery trajectories following a loss of contact with the spacecraft, are described as well. Lessons learned from working on the LIC mission are presented to inform the design of similar future CubeSat missions.

Robert E Pritchett↗
NASA NTRSDate not supplied

Overview of the Lunar Transit Trajectory Performed by the Power and Propulsion Element of NASA’s Gateway

NASA has committed to returning to the moon, landing the first woman and the next man on its surface. To support a sustained lunar presence, NASA is designing an orbital platform to be assembled in an orbit near the moon called the Near Rectilinear Halo Orbit (NRHO). This platform is known as the Gateway and its purpose it to support missions primarily to the lunar south pole. As NASA continues to study ways to reduce the cost of lunar exploration, a simplification implemented in 2020combinedthe first two elements of the Gateway, the Power and Propulsion Element (PPE) and NASA’s Habitation and Logistics Outpost (HALO), onto a single commercial launch vehicle (CLV). When launched together, the PPE and HALO make up the first two elements of NASA’s Gateway and exceed the performance capacity of commercially available launch vehicles to deliver directly to the moon. The delivery of the Gateway is enabled by and takes advantage of the high efficiency of the PPEs high-power Solar Electric Propulsion (SEP) system to transfer a significant starting mass from an initial Earth orbit to final insertion into the NRHO. The PPE is a 50-kW class high power solar electric propulsion stage comprised of two different types of electric thruster strings. The SEP system is operated in two different modes, a high thrust and high Isp (specific impulse), to both maximize the final delivered mass and attempt to minimize the time spent in the Van Allen Belts early in the transit trajectory. Additionally, this SEP system brings the capability to the assembled Gateway for transfer between orbits in cislunar space. This paper captures the preliminary low thrust lunar transfer reference trajectory to be flown by the PPE it delivers itself and HALO via a spiral trajectory from launch vehicle insertion to insertion into the NRHO as well as a preliminary reference round trip transfer of the Gateway from the NRHO to a Distant Retrograde Orbit (DRO) using the PPE. Once in its final NRHO, the Gateway is being designed to enable long duration human and robotic exploration of the lunar south pole as a precursor to Mars. The Gateway’s low thrust lunar transit trajectory is envisioned to prove out the application of and flight of a high-power SEP system as a demonstration of technologies applicable to the enabling of future human space exploration.

human exploration↗
NASA NTRSDate not supplied

Robust Trajectory Optimization Techniques Using a Sweeping Gradient Method and Linear Covariance Analysis

We present robust trajectory optimization techniques using a sweeping gradient method for ordinary differential equations with events (SGM) and linear covariance analysis (LinCov). SGM is a method for computing the gradient of trajectory analyses defined by performance indices over initial value problems with events with respect to static parameters. LinCov is an analytic technique for predicting stochastic behavior of dynamical systems. By combining SGM and LinCov, it is possible use efficient, off-the-shelf, gradient-based optimizers to solve robust optimal trajectory design problems. We describe the individual methods and some details on how they can be combined. Then we apply the combined techniques to a variety of orbital trajectory design problems to demonstrate its use, including minimum fuel transfer and mid-course correction burn scheduling.

Benjamin W L Margolis↗
NASA NTRSDate not supplied

Onboard Autonomous Trajectory Planning for Mars Power Descent

In recent years, there has been an increasing interest in space-qualified processors such as multi-core central processing units and graphics processing units that can withstand the adverse effects of space radiation. These processors can allow parallel programming to perform tasks that typically demand high computational power. One can study guidance schemes that can take advantage of these currently developing processors and provide more robust guidance. Software for Multi-model Autonomous Real-time Trajectories (SMART) guidance can identify robust trajectories by running an onboard Monte Carlo analysis. SMART guidance can take advantage of knowledge updates obtained from the onboard sensors, allowing it to consider the off-nominal cases that it would not typically encounter during the offline trajectory analysis. This work uses the SMART guidance for the powered divert at Mars simulation in Program to Optimize and Simulated Trajectories- II.

Pardha Sai Chadalavada↗
NASA NTRSDate not supplied

Performance Impacts to the NASA Artemis II Trajectory Correction Burn Placement

As NASA embarks to return humans to the lunar vicinity with the upcoming Artemis II mission, the selected free return trajectory taking the crew to the Moon in the Orion spacecraft is impacted by the execution of small trajectory correction burns to ensure the spacecraft stays on course for a successful return to Earth. The placement of these nominally zero translational maneuvers must account for the crew schedule, navigation tracking constraints, spacecraft venting, thermal and communication requirements, and a host of other programmatic factors. Understanding the influence the placement of these periodic burn corrections have on the integrated GN\&C performance can provide valuable insight to mission controllers and trajectory planning processes to untangle the complex trade space considered for both baseline and contingency scenarios. This sensitivity information can also be utilized to facilitate the optimized placement of these burns. This paper utilizes several techniques to systematically generate the performance impacts to the NASA Artemis II trajectory correction burn placement and demonstrate how to derive optimized locations that make the system robust to crew activity, maneuver execution errors, navigation uncertainty, orbit insertion errors, disturbance accelerations, and other system limitations.

GN&C↗
NASA NTRS2025

Robust Trajectory Optimization for NRHO Rendezvous Using SPICE Kernel Relative Motion

In this paper, robust optimization is performed on trajectory correction maneuvers during the lunar lander return phase of an Artemis mission, treating the trajectory from one hour after low lunar orbit departure to arrival in the vicinity of the lunar Gateway as a relative motion problem. To enable rapid stochastic optimization techniques requiring many candidate trajectories, SPICE kernel relative motion as implemented by the Quadratic Interpolated State Transition (QIST) system is used as the underlying dynamics propagation. The optimization is performed with a genetic optimizer using linear covariance (LinCov) software in a simplified operational context, taking into account the availability of navigation sensors with varying measurement models, ranges, and accuracies. No numerical integration is used, since the relative motion around Gateway is fully characterized with the a priori computation of the QIST coefficients. Maneuver placements are computed to optimize the minimum 3σ delta-v of the trajectory, the position dispersion at a target point, and a convex combination of these two metrics. An order of magnitude runtime improvement is provided over legacy methods with less than 10% error introduced. All QIST results are shown to be in-family with legacy methods. The tradespace for optimal delta-v design is found to range from 77.0 to 93.9 m/s, while the range of optimal dispersion is between 1.4 and 11.7 km.

Relative Motion↗
DOE OSTI2022

Trajectory design via unsupervised probabilistic learning on optimal manifolds

Abstract This article illustrates the use of unsupervised probabilistic learning techniques for the analysis of planetary reentry trajectories. A three-degree-of-freedom model was employed to generate optimal trajectories that comprise the training datasets. The algorithm first extracts the intrinsic structure in the data via a diffusion map approach. We find that data resides on manifolds of much lower dimensionality compared to the high-dimensional state space that describes each trajectory. Using the diffusion coordinates on the graph of training samples, the probabilistic framework subsequently augments the original data with samples that are statistically consistent with the original set. The augmented samples are then used to construct conditional statistics that are ultimately assembled in a path planning algorithm. In this framework, the controls are determined stage by stage during the flight to adapt to changing mission objectives in real-time.

42 ENGINEERING↗
NASA NTRS2026

A Missed Thrust Framework for Low-Thrust Spiral Trajectories to the NRHO

A framework is developed by which end-to-end optimization of many-revolution low-thrust spiral trajectories can be completed in the presence of missed thrust events. This framework is applied to the Lunar Transit trajectory by which the initial capability of NASA’s Gateway lunar space station will be delivered to a Near Rectilinear Halo Orbit. This low-thrust mission consists of three subphases, each designed according to the specific objectives and dynamical regimes encountered as the mission progresses from a medium Earth insertion orbit to cislunar space. The presented framework accounts for the unique considerations demanded by each mission phase and incorporates appropriate capabilities into a novel mission analysis tool. This methodology enables large scale and reliable analyses of missed thrust events across the end-to-end Lunar Transit to verify the robustness of flight trajectories across the full range of considered launch dates.

missed thrust↗
DOE OSTI2023

Deep generative models for vehicle speed trajectories

Generating realistic vehicle speed trajectories is a crucial component in evaluating vehicle fuel economy and in predictive control of self-driving cars. Traditional generative models rely on Markov chain methods and can produce accurate synthetic trajectories but are subject to the curse of dimensionality. They do not allow to include conditional input variables into the generation process. In this paper, we show how extensions to deep generative models allow accurate and scalable generation. Proposed architectures involve recurrent and feed-forward layers and are trained using adversarial techniques. Our models are shown to perform well on generating vehicle trajectories using a model trained on GPS data from Chicago metropolitan area.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2025

Multi-objective surrogate-assisted calibration of CPFEM models using macroscopic response and in situ EBSD measurements of grain reorientation trajectories

Crystal plasticity finite element method (CPFEM) models are widely used to simulate the deformation behaviour of polycrystalline materials, but their calibration is often limited by their high computational cost and the non-convexity of the optimisation landscape. Here, this study develops a multi-objective surrogate-assisted calibration workflow that couples a multi-objective genetic algorithm (MOGA) with an adaptively trained deep neural network (DNN) surrogate model to efficiently identify CPFEM parameters from experimental data. The workflow is demonstrated on three crystal plasticity (CP) formulations of increasing complexity — Voce hardening (VH), two-coefficient latent hardening (LH2), and six-coefficient latent hardening (LH6) — using in situ electron backscatter diffraction (EBSD) measurements of Alloy 617 under uniaxial tensile loading. The CPFEM models are calibrated against the experimentally observed stress–strain response and reorientation trajectories of eight grains, then validated against eight additional trajectories and overall texture evolution. Across the CP formulations, the macroscopic response was reproduced reliably, while differences emerged in the robustness and accuracy of the grain-scale predictions. Including grain reorientation trajectories in the multi-objective calibration improved texture evolution predictions and filtered out physically inconsistent parameter sets that can arise from calibrating against only the stress–strain data. The workflow also demonstrates good transferability of calibrated parameters from a low- to a high-fidelity microstructural model. These results provide practical guidance for integrating in situ microstructural data into CPFEM through efficient, repeatable, and physically meaningful multi-objective calibration.

Crystal plasticity finite element method↗
DOE OSTI2021

Tutorial: Langevin Dynamics methods for aerosol particle trajectory simulations and collision rate constant modeling

The Langevin Dynamics (LD) method (also known in the literature as Brownian Dynamics) is routinely used to simulate aerosol particle trajectories for transport rate constant calculations as well as to understand aerosol particle transport in internal and external fluid flows. This tutorial intends to explain the methodological details of setting up a LD simulation of a population of aerosol particles and to deduce rate constants from an ensemble of classical trajectories. We discuss the applicability and limitations of the translational Langevin equation to model the combined stochastic and deterministic motion of particles in fields of force or fluid flow. The drag force and stochastic “diffusion” force terms that appear in the Langevin equation are discussed elaborately, along with a summary of common forces relevant to aerosol systems (electrostatic, gravity, van der Waals, …); a commonly used first order and a fourth order Runge-Kutta time stepping schemes for linear stochastic ordinary differential equations are presented. A MATLAB® implementation of a LD code for simulating particle settling under gravity using the first order scheme is included for illustration. Scaling analysis of aerosol transport processes and the selection of timestep and domain size for trajectory simulations are demonstrated through two specific aerosol processes: particle diffusion charging and coagulation. Fortran® implementations of the first order and fourth order time-stepping schemes are included for simulating the 3D motion of a particle in a periodic domain. Lastly, potential applications and caveats to the usage of LD are included as a summary.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗