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Knittel, Jeremy M.

Publications and source records attributed to Knittel, Jeremy M..

10 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS2019

Trajectory Design of the Lucy Mission to Explore the Diversity of the Jupiter Trojans

Lucy, NASA’s next Discovery-class mission, will explore the diversity of the Jupiter Trojan asteroids. The Jupiter Trojans are thought to be remnants of the early solar system that were scattered inward when the gas giants migrated to their current positions as described in the Nice model. There are two stable subpopulations, or “swarms,” captured at the Sun-Jupiter L4 and L5 regions. These objects are the most accessible samples of what the outer solar system may have originally looked like. Lucy will launch in 2021 and will visit five Trojans, including one binary system. This paper discusses the target selection process, including a description of “alternate Lucys” that were ultimately passed over in favor of the final design. The mathematics of the trajectory optimization are also discussed.

Lucy↗
NASA NTRS2019

Refining Lucy Mission Delta-V During Spacecraft Design Using Trajectory Optimization Within High-Fidelity Monte Carlo Maneuver Analysis

Recent advances linking medium-fidelity trajectory optimization and high-fidelity trajectory propagation/maneuver design software with Monte Carlo maneuver analysis and parallel processing enabled realistic statistical delta-V estimation well before launch. Completing this high-confidence, refined statistical maneuver analysis early enabled release of excess delta-V margin for increased dry mass margin for the Lucy Jupiter Trojan flyby mission. By 3.3 years before launch, 16 of 34 TCMs had 1000 re-optimized trajectory design samples, yielding tens of m/s lower 99%-probability delta-V versus targeting maneuvers to one optimal trajectory. One year later, 1000 re-optimized samples of all deterministic maneuvers and subsequent flybys further lowered estimated delta-V.

Trojan↗
NASA NTRS2019

Optimization of the Lucy Interplanetary Trajectory via Two-Point Direct Shooting

Lucy is NASA’s next Discovery-class mission and will explore the Trojan asteroids in the Sun-Jupiter L4 and L5 regions. This paper details the design of Lucy’s interplanetary trajectory using a two-point direct shooting transcription, nonlinear programming, and monotonic basin hopping. These techniques are implemented in the Evolutionary Mission Trajectory Generator (EMTG), a trajectory optimization tool developed at NASA Goddard Space Flight Center. We present applications to the baseline trajectory design, Monte Carlo analysis, and operations.

Lucy↗
NASA NTRS2017

Mission Design and Optimal Asteroid Deflection for Planetary Defense

Planetary defense is a topic of increasing interest for many reasons, which has been mentioned in "Vision and Voyages for Planetary Science in the Decade 2013-2022''. However, perhaps one of the most significant rationales for asteroid studies is the number of close approaches that have been documented recently. A space mission with a planetary defense objective aims to deflect the threatening body as far as possible from Earth. The design of a mission that optimally deflects an asteroid has different challenges: speed, precision, and system trade-off. This work addresses such issues and develops a fast transcription of the problem that can be implemented into an optimization tool, which allows for a broader trade study of different mission concepts with a medium fidelity. Such work is suitable for a mission?s preliminary study. It is shown, using the fictitious asteroid impact scenario 2017 PDC, that the complete tool is able to account for the orbit sensitivity to small perturbations and quickly optimize a deflection trajectory. The speed in which the tool operates allows for a trade study between the available hardware. As a result, key deflection dates and mission strategies are identified for the 2017 PDC.

Planetary defense↗
NASA NTRS2017

Mission Design and Optimal Asteroid Deflection for Planetary Defense

Planetary defense is a topic of increasing interest for many reasons, which has been mentioned in "Vision and Voyages for Planetary Science in the Decade 2013-2022". However, perhaps one of the most significant rationales for asteroid studies is the number of close approaches that have been documented recently. A space mission with a planetary defense objective aims to deflect the threatening body as far as possible from Earth. The design of a mission that optimally deflects an asteroid has different challenges: speed, precision, and system trade-off. This work addresses such issues and develops a fast transcription of the problem that can be implemented into an optimization tool, which allows for a broader trade study of different mission concepts with a medium fidelity. Such work is suitable for a mission's preliminary study. It is shown, using the fictitious asteroid impact scenario 2017 PDC, that the complete tool is able to account for the orbit sensitivity to small perturbations and quickly optimize a deflection trajectory. The speed in which the tool operates allows for a trade study between the available hardware. As a result, key deflection dates and mission strategies are identified for the 2017 PDC.

Trajectory optimization↗
NASA NTRS2017

Gravity-Assist Trajectories to the Ice Giants: An Automated Method to Catalog Mass-or Time-Optimal Solutions

This work presents an automated method of calculating mass (or time) optimal gravity-assist trajectories without a priori knowledge of the flyby-body combination. Since gravity assists are particularly crucial for reaching the outer Solar System, we use the Ice Giants, Uranus and Neptune, as example destinations for this work. Catalogs are also provided that list the most attractive trajectories found over launch dates ranging from 2024 to 2038. The tool developed to implement this method, called the Python EMTG Automated Trade Study Application (PEATSA), iteratively runs the Evolutionary Mission Trajectory Generator (EMTG), a NASA Goddard Space Flight Center in-house trajectory optimization tool. EMTG finds gravity-assist trajectories with impulsive maneuvers using a multiple-shooting structure along with stochastic methods (such as monotonic basin hopping) and may be run with or without an initial guess provided. PEATSA runs instances of EMTG in parallel over a grid of launch dates. After each set of runs completes, the best results within a neighborhood of launch dates are used to seed all other cases in that neighborhood---allowing the solutions across the range of launch dates to improve over each iteration. The results here are compared against trajectories found using a grid-search technique, and PEATSA is found to outperform the grid-search results for most launch years considered.

Hughes, Kyle M.↗
NASA NTRS2017

Gravity-Assist Trajectories to the Ice Giants: An Automated Method to Catalog Mass- Or Time-Optimal Solutions

This work presents an automated method of calculating mass (or time) optimal gravity-assist trajectories without a priori knowledge of the flyby-body combination. Since gravity assists are particularly crucial for reaching the outer Solar System, we use the Ice Giants, Uranus and Neptune, as example destinations for this work. Catalogs are also provided that list the most attractive trajectories found over launch dates ranging from 2024 to 2038. The tool developed to implement this method, called the Python EMTG Automated Trade Study Application (PEATSA), iteratively runs the Evolutionary Mission Trajectory Generator (EMTG), a NASA Goddard Space Flight Center in-house trajectory optimization tool. EMTG finds gravity-assist trajectories with impulsive maneuvers using a multiple-shooting structure along with stochastic methods (such as monotonic basin hopping) and may be run with or without an initial guess provided. PEATSA runs instances of EMTG in parallel over a grid of launch dates. After each set of runs completes, the best results within a neighborhood of launch dates are used to seed all other cases in that neighborhood-allowing the solutions across the range of launch dates to improve over each iteration. The results here are compared against trajectories found using a grid-search technique, and PEATSA is found to outperform the grid-search results for most launch years considered.

Hughes, Kyle M.↗
NASA NTRS2017

Validation of a Low-Thrust Mission Design Tool Using Operational Navigation Software

Design of flight trajectories for missions employing solar electric propulsion requires a suitably high-fidelity design tool. In this work, the Evolutionary Mission Trajectory Generator (EMTG) is presented as a medium-high fidelity design tool that is suitable for mission proposals. EMTG is validated against the high-heritage deep-space navigation tool MIRAGE, demonstrating both the accuracy of EMTG's model and an operational mission design and navigation procedure using both tools. The validation is performed using a benchmark mission to the Jupiter Trojans.

Englander, Jacob A.↗
NASA NTRS2017

Improved Propulsion Modeling for Low-Thrust Trajectory Optimization

Low-thrust trajectory design is tightly coupled with spacecraft systems design. In particular, the propulsion and power characteristics of a low-thrust spacecraft are major drivers in the design of the optimal trajectory. Accurate modeling of the power and propulsion behavior is essential for meaningful low-thrust trajectory optimization. In this work, we discuss new techniques to improve the accuracy of propulsion modeling in low-thrust trajectory optimization while maintaining the smooth derivatives that are necessary for a gradient-based optimizer. The resulting model is significantly more realistic than the industry standard and performs well inside an optimizer. A variety of deep-space trajectory examples are presented.

trajectory↗
NASA NTRS2017

Validation of a Low-Thrust Mission Design Tool Using Operational Navigation Software

Design of flight trajectories for missions employing solar electric propulsion requires a suitably high-fidelity design tool. In this work, the Evolutionary Mission Trajectory Generator (EMTG) is presented as a medium-high fidelity design tool that is suitable for mission proposals. EMTG is validated against the high-heritage deep-space navigation tool MIRAGE, demonstrating both the accuracy of EMTG's model and an operational mission design and navigation procedure using both tools. The validation is performed using a benchmark mission to the Jupiter Trojans.

Englander, Jacob A.↗