Results for “TRAJECTORIES” — Page 45

NASA NTRS1997

Mars Free Return Trajectories

For human missions to Mars, the top priority is a safe return of the crew to Earth. In the case of an emergency, trajectories that naturally return to the Earth with no intervention are preferred. In this paper we use automated design software to compute all possible Mars Free Return trajectories form 1995 to 2020, given constraints on the total time of flight and on the launch energy. The resulting data file contains all of the previouslknown types of returns.

Mars↗

NASA NTRS1994

(abstract) Optimal Low Thrust Trajectories Using Differential Inclusion Concepts

Low thrust propulsion systems typically have their greatest benefit for high energy missions or missions with large post-launch maneuver requirements. Missions which have been examined include main belt asteroid rendezvous, comet rendezvous, outer planet and Mercury orbiters, Pluto flyby, and solar probe missions. Low thrust mission design software used to determine these trajectories is based on two distinct formulations of the optimal control problem: the indirect and direct methods. The traditional approach (indirect) is to use the calculus of variations to obtain first order necessary conditions on the states and costates. In contrast, direct methods are conceptually different in that no explicit integration takes place. A direct method based on differential inclusion concepts has been developed and successfully used to compute low thrust trajectories. This new approach removes explicit control dependence from the problem thereby reducing the dimension of the parameter space for the nonlinear programming problem. Also when compared to other direct methods, fewer nonlinear constraints are required to represent the dynamics of the problem.

low↗

NASA NTRS2020

Estimating Wildfire-Generated Ozone Over North America Using Ozonesonde Profiles and a Differential Back Trajectory Technique

An objective method, employing HYSPLIT back-trajectories and Moderate Resolution Imaging Spectroradiometer (MODIS) fire observations, is developed to estimate ozone enhancement in air transported from regions of active forest fires at 18 ozone sounding sites located across North America. The Differential Back Trajectory (DBT) method compares mean differences between ozone concentrations associated with fire-affected and fire-unaffected parcels. It is applied to more than 1100 ozonesonde profiles collected from these sites during the summer months June to August, 2006, 2008, 2010 and 2011. Layers of high ozone associated with low humidity were first removed from the ozonesonde profiles to minimize the potential effects of stratospheric intrusions on the calculations. No significant influence on average ozone levels by North American fires was found for stations located at Arctic latitudes. The ozone enhancement for stations nearer large fires, such as Trinidad Head and Bratt’s Lake, was up to 324.8% of the TTOC (Total Tropospheric Ozone Column). Fire ozone accounted for up to 8.3% of TTOC at downwind sites such as Yarmouth, Sable Island, Narragansett, and Walsingham. The results are consistent with other studies that have reported an increase in ozone production with the age of the smoke plume.

Moderate Resolution Imaging Spectroradiometer (MOD↗

NASA NTRSDate not supplied

Integrated Crewed Mars Mission Analysis, Part II: The Trajectory Strikes Back

Crewed missions to Mars present a challenging problem involving strong interactions between a variety of spacecraft systems. Design and architecture decisions made by one system can have powerful implications for another. Siloed subsystem development and optimization efforts are unlikely to generate optimal results for the integrated system and may lead to counterproductive investments at the mission and system level. Mismatched assumptions between different subsystems can also negatively impact the final result. Integrated systems analysis, trade studies, and sensitivity analysis are a critical element of successful Mars mission design. Previous work examined the linkages between Environmental Control and Life Support System (ECLSS) loop closure, food water content, spares Probability of Sufficiency (POS), and other factors by performing an integrated mass and cost assessment of a variety of Mars habitat and transportation system designs. This paper expands upon that work by evaluating the impact of mission duration, trajectory, and propulsion technology alongside key habitat variables. Transportation system and trajectory design decisions have enormous impacts on overall system mass, and the impacts of those decisions are themselves sensitive to the mass of the habitat that is being transported. This paper examines a variety of mission cases and evaluates total departure mass for each case. An estimate of relative costs for specific cases is also provided. The results are discussed, with an emphasis on the sensitivity of mass, cost, and other figures of merit to key parameters. Interactions and dependencies between various decisions, particularly those that relate to technology investments, are also highlighted. Overall, the various elements, systems, and subsystems required to support human spaceflight should not be optimized and evaluated in isolation, but instead should be analyzed as part of an integrated system. This paper demonstrates how integrated analysis can improve system understanding and lead to more optimal and effective crewed exploration systems.

Human Spaceflight↗

NASA NTRSDate not supplied

Integrated Crewed Mars Mission Analysis, Part II: The Trajectory Strikes Back

Crewed missions to Mars present a challenging problem involving strong interactions between a variety of spacecraft systems. Design and architecture decisions made by one system can have powerful implications for another. Siloed subsystem development and optimization efforts are unlikely to generate optimal results for the integrated system and may lead to counterproductive investments at the mission and system level. Mismatched assumptions between different subsystems can also negatively impact the final result. Integrated systems analysis, trade studies, and sensitivity analysis are a critical element of successful Mars mission design. Previous work examined the linkages between Environmental Control and Life Support System (ECLSS) loop closure, food water content, spares Probability of Sufficiency (POS), and other factors by performing an integrated mass and cost assessment of a variety of Mars habitat and transportation system designs. This paper expands upon that work by evaluating the impact of mission duration, trajectory, and propulsion technology alongside key habitat variables. Transportation system and trajectory design decisions have enormous impacts on overall system mass, and the impacts of those decisions are themselves sensitive to the mass of the habitat that is being transported. This paper examines a variety of mission cases and evaluates total departure mass for each case. An estimate of relative costs for specific cases is also provided. The results are discussed, with an emphasis on the sensitivity of mass, cost, and other figures of merit to key parameters. Interactions and dependencies between various decisions, particularly those that relate to technology investments, are also highlighted. Overall, the various elements, systems, and subsystems required to support human spaceflight should not be optimized and evaluated in isolation, but instead should be analyzed as part of an integrated system. This paper demonstrates how integrated analysis can improve system understanding and lead to more optimal and effective crewed exploration systems.

Human Spaceflight↗

NASA NTRSDate not supplied

Improving Multi-Model Trajectory Simulation Estimators using Model Selection and Tuning

Multi-model Monte Carlo methods have been demonstrated to be an efficient and accurate alternative to standard Monte Carlo (MC) in the model-based propagation of uncertainty in entry, descent, and landing (EDL) applications. These multi-model MC methods fuse predictions from low-fidelity models with the high-fidelity EDL model of interest to produce unbiased statistics with a fraction of the computational cost. The accuracy and efficiency of the multi-model MC methods are dependent upon the magnitude of correlations of the low-fidelity models with the high-fidelity model, but also upon the correlation amongst the low-fidelity models, and their relative computational cost. Because of this layer of complexity, the question of how to optimally select the set of low-fidelity models has remained open. In this work, methods for optimal model construction and tuning are investigated as a means to increase the speed and precision of trajectory simulation for EDL. Specifically, the focus is on the inclusion of low-fidelity model tuning within the sample allocation optimization that accompanies multi-model MC methods. Preliminary results indicate that low-fidelity model tuning can significantly improve efficiency and precision of trajectory simulations and provide an increased edge to multi-model MC methods when compared to standard MC. The challenges and potential benefits to exploring a fully iterative and comprehensive optimization strategy in future work are highlighted.

uncertainty quantification↗

NASA NTRSDate not supplied

Fast Earth-Mars Roundtrip Trajectories to Reduce Health and Safety Risks for Crewed Missions

The extended mission duration of a crewed Mars mission compounds integrated risks to crew health and safety. Shortening mission duration would therefore have a direct impact on reducing many human health and performance risk factors. This paper describes trajectory feasibility analyses performed to examine trajectory options for a fast crewed mission to Mars. Studies were conducted to examine options with short overall mission durations (≤ 400-day roundtrip) and options that focus on minimizing astronaut time in deep space, while allowing for longer Mars surface stays. Trade studies were performed to determine ∆v requirements for a range of launch dates, Mars orbit periods, Mars stay times, and Earth-to-Mars flight time maxima. The implications of a Venus gravity assist are also described. The analyses presented here build on and specifically aim to optimize and address key concerns of assumptions made in previously published studies of fast crewed Mars missions.

Mars↗

NASA NTRSDate not supplied

Application of Tisserand's Criterion and the Lidov-Kozai Effect to STORM's Trajectory Design

The Solar-Terrestrial Observer for the Response of the Magnetosphere (STORM) concept recently completed its Phase A design funded by NASA's Heliophysics Medium-class Explorers program. The mission design required a lunar gravity assist to insert the single spacecraft into a 30-Earth-radii circular geocentric science orbit inclined 90 degrees to the ecliptic. STORM's trajectory design leveraged several interesting gravitational effects from third bodies. This paper describes our application of Tisserand's criterion for finding feasible transfers and lunar gravity assist trajectories, and the Lidov-Kozai effect to design a maneuver-free science orbit optimization and decommissioning strategy.

tisserand criterion↗

NASA NTRSDate not supplied

Markov Decision Process based Trajectory Planning for UAVs under Uncertain Wind Conditions

In this paper we propose a Markov Decision Process (MDP) algorithm for path-planning of Unmanned Aviation Vehicles (UAVs) under varying wind conditions. Solutions to path-planning for UAVs are becoming increasingly necessary as autonomous UAVs continue to enter commercial and government spaces. Path-planning is inherently challenging, as UAVs needs to account for dynamically changing flying conditions such as weather, obstacle or no-fly zones, degraded vehicle health and off-nominal battery power consumption. Machine learning methods such as Markov Decision Process (MDPs) have the potential to revolutionize how vehicles navigate in such uncertain environments. Previous papers have demonstrated the use of MDPs to optimize UAV path-planning for energy consumption under time-varying wind distribution. In this study, UAV trajectories from a pre-determined waypoint to target cell, will be computed on a 7X7 grid environment by optimizing parameters for mission assurance and safety limits in addition to the energy consumption, and operation time. The UAV navigates the grid by taking actions to move in either of the eight cardinal and intercardinal directions, under constant thrust profile. The next state of the UAV is calculated by considering its action, transition probability, obstacle cells and the wind speed magnitude and direction. Both constant and stochastic wind will be considered in this paper, the parameters being extracted from real wind measurements in proximity to an experimental UAV flight. One of the studies to be demonstrated in this paper is that as the unmanned airspace gets more complex with multiple vehicles and environmental uncertainties, trade-offs between energy consumption, operation time, risk tolerance, and mission assurance needs to be made. Further, MDPs are capable of fast computation of UAV trajectories under varying wind, hence making them suitable for in-flight path planners.

decision-making↗

NASA NTRSDate not supplied

Robust Trajectory Design for Rendezvous in a Near Rectilinear Halo Orbit

Future NASA Artemis missions will require complex docking plans between the Orion capsule and Lunar Gateway that meet predetermined safety constraints while minimizing fuel usage and state uncertainty at rendezvous. In this paper, linear covariance analysis is applied to a first order relative form of Near-Rectilinear Halo Orbit dynamics to determine the nominal trajectories and state dispersions associated with various maneuver profiles in the Sun-referenced Local Vertical Local Horizontal reference frame of the lunar Gateway. These maneuver profiles are optimized using a particle swarm optimizer and direct search algorithm to find trajectories that satisfy approach corridor, free drift, velocity magnitude, under-burn, and maneuver transfer time safety constraints to 3-sigma certainty.

Linear Covariance Analysis↗

NASA NTRSDate not supplied

A New Eclipse Algorithm for use in Spacecraft Trajectory Optimization

This paper presents a new eclipse algorithm, which determines if a spacecraft is in sunlight or shadow, that is simple to define, fast to compute, smooth and continuous in all regions external to the eclipsing body, and suitable for use in a spacecraft trajectory optimization problem. Details of the design evolution are presented, including the specifics of the algorithm's implementation in the trajectory design of NASA's Artemis I mission to a lunar DRO. Some alternate uses and discussion of future work is also presented.

Orion↗

NASA NTRSDate not supplied

Trajectory Generation with Load Constraints for Robotic Manipulators

Future large spacecraft will utilize robotic manipulators for in-space servicing, assembly, and manufacturing. Due to launch mass constraints, such manipulators will be designed to be as lightweight as possible. Trajectory generation algorithms will need to factor in load constraints to avoid overexerting and damaging manipulators. This paper investigates an approach that combines optimal Rapidly-exploring Random Trees, spline interpolation, and Model Predictive Control to generate a manipulator trajectory which respects load constraints.

Manipulators↗

NASA NTRSDate not supplied

Machine Learning Approach for Aircraft Performance Model Parameter Estimation for Trajectory Prediction Applications

Inaccurate prediction of aircraft trajectory by ground-based decision support tools (DST) is a major concern in air traffic management (ATM). Aircraft trajectory prediction tools rely on a simplified point-mass aircraft performance model (APM) to make their predictions. Even though the performance coefficients and weight of an aircraft are a vital part of the APM’s predictions and accuracy, these coefficients are proprietary in nature and therefore, unavailable to DSTs. Current ATM research focuses on improving the estimate of some APM parameters by freezing all other coefficients. This simplified approach introduces unwanted sources of bias and negatively impacts the accuracy of the performance model. In this paper, we apply machine learning (ML) techniques for the simultaneous prediction of three key APM parameters (two drag coefficients and the initial aircraft weight). To accomplish this, we employ an ordinary differential equation (ODE) fitting approach to generate optimized APM parameter labels customized to each individual flight record. Subsequently, we train ML models to capture the relationship between the historical data and the optimized APM parameters. Two different ML model solutions are applied and APM coefficients are predicted for unseen flights. The results indicate that the ML models are able to capture the relationship between APM parameters and flight-related features with good accuracy.

trajectory prediction, machine learning, aircraft ↗

NASA NTRSDate not supplied

Initial Study of Tailored Trajectory Management for Multi-Vehicle Uncrewed Regional Air Cargo Operations

The primary contribution of this paper is an evaluation of the potential value of a tailored trajectory management (TTM) capability for uncrewed aircraft (UA) operators that is proactive in detecting conflicts and developing trajectory-based solutions for UA prior to air traffic control (ATC) performing conflict resolution. The experiment matrix is composed of one baseline simulation that models current air traffic operations without such a capability and four test simulations with different configurations of such a capability. In each simulation, five UA operations into Fort Worth Alliance airport were modeled in the presence of recorded tracks for about 4700 flights on January 18, 2022. The analysis focused on the extent to which such a capability was able to preclude an event that could spike UA operator workload. More specifically, in this study, the emulated UA operator TTM capability for multi-vehicle regional air cargo operations was able to reduce the number of instances of concurrent UA conflicts in the modeled ATC conflict resolution timeframe of 8 minutes or less from three to as low as one.

uncrewed aircraft, regional air cargo, tailored tr↗

NASA NTRS2024

Computing Proximity to Threat Along Uncertain Trajectory to Support Urban Air Mobility

Many airspace threats affect the selection of a flight route, such as terrain, physical obstacles, adverse weather, and special-use airspace, among others. Threat avoidance during Urban Air Mobility (UAM) and Low Altitude Mobility (LAM) flights is especially challenging due to their lower cruising altitudes. These operations may be exposed to buildings, towers, trees, terrain undulations, etc., along much of their flight route. Moreover, these low-altitude flights in urban environments are expected to encounter very busy airspace, increasing the workload associated with threat avoidance. The Proximity to Threat (PtT) function aims to support onboard or remote pilots by computing the risk from geospatial threats in the airspace along an aircraft’s flight path. The threats are both static entities and dynamic airspace restrictions that have been modeled and stored in geo-referenced mapping databases. The flight path may be specified by waypoints, airways, or similar discrete route elements or by a time series of closely spaced position and altitude points. Flight path uncertainty can also be taken into account by assuming both the position and altitude to be sampled from two normal distributions, each being specified by a mean and variance. PtT uses this additional information to verify that the flight path remains clear of threats along a wider path or if a position is reached earlier or later than anticipated, assuring the pilot or operator that there will be an available safety margin even if the aircraft deviates due to one or more occurrences of unexpected wind gusts, mechanical failures, airspeed changes, collision avoidance maneuvers, etc. The client can specify an uncertainty confidence level to bound the set of trajectories evaluated for threats so that the confidence level corresponds to the client’s risk tolerance under the expected conditions. PtT can be used as a pre-flight planning tool to determine a safe route through known threats and in-flight to avoid emerging or changing threats. In this report, we present the PtT function, discuss how the trajectory uncertainty is incorporated into the PtT function, and describe the use of this PtT function in a representative scenario.

urban air mobility↗

NASA NTRS2024

A Trajectory-Tracking Algorithm for the LSMS Family of Cable-Driven Cranes

The Lightweight Surface Manipulation System, or LSMS, is a family of scalable long-reach cable-actuated manipulators. The design of the LSMS has a high payload ratio for efficient operations on planetary surfaces like the Moon or Mars. The LSMS has nonlinear, coupled, and hybrid dynamics. The engineering decisions that led to these challenging dynamics make this structure light and efficient. This paper proposes a novel trajectory tracking algorithm for these cranes that facilitates precise autonomous and teleoperated operations. This algorithm enables these robots to follow complex trajectories that avoid obstacles and pickup regolith in a construction site.

trajectory tracking↗

NASA NTRSDate not supplied

FATE: The drifting Fish Aggregating Device (dFAD) TrajEctory Modeling Tool for Marine Protected Area Management

Drifting fish aggregating devices (dFADs) routinely enter marine protected areas (MPAs) and may undermine MPA protections by drifting out of the MPA with the aggregated fish biomass, or grounding and damaging sensitive coral reef habitats. MPA managers must decide whether to deploy resources in response to dFAD intrusions. To address this issue, we propose to quantify dFAD activity in relation to ocean currents, fish biomass, and animal telemetry at Palmyra Atoll, part of the Pacific Remote Islands Marine National Monument in the central Pacific Ocean. Specifically, we propose to develop the dFAD TrajEctory Tool (FATE). FATE is an innovative decision support tool that will use NASA observations and numerical models to predict future dFAD trajectories and inform TNC and USFWS whether they should deploy tactical resources (boats, personnel) to monitor, intercept, or retrieve dFADs that have entered the Refuge. The objectives are to use NASA observational constraints on ocean winds and currents to assist with the ecological management of the Palmyra Atoll NWR and MPA. Specifically, we will deliver an operational software tool that quantifies the grounding risk associated with each tracked dFAD and decision support for grounding risk mitigation via intercept at sea. This project addresses Element 3.3: Protected area management of the 2022 Ecological Conservation Solicitation by developing a tool needed by MPA managers to make tactical and strategic decisions focused on improving the effectiveness of MPAs. By quantifying the riskof dFADs, this project will help monitor and better inform the deployment of tactical (ships/personnel) and strategic (legislative) resources to better manage MPAs. This project is a collaboration between The Nature Conservancy, who operate long-term projects within the Palmyra MPA, and the U.S. Fish and Wildlife Service, who have the authority to make decisions related to its management. We expect that the results of our proposal will benefit marine resources within the Palmyra MPA and could be transferred to other remote MPAs within the US and other island nations within the Pacific Ocean.

TrajEctory↗

NASA NTRS2024

A Trajectory Tracking Algorithm for the LSMS Family of Cable-Driven Crane

The Lightweight Surface Manipulation System, or LSMS, is a family of scalable long-reach cable-actuated manipulators. The design of the LSMS has a high payload ratio for efficient operations on planetary surfaces like the Moon or Mars. The LSMS has nonlinear, coupled, and hybrid dynamics. The engineering decisions that led to these challenging dynamics make this structure light and efficient. This paper proposes a novel trajectory tracking algorithm for these cranes that facilitates precise autonomous and teleoperated operations. This algorithm enables these robots to follow complex trajectories that avoid obstacles and pickup regolith in a construction site.

lunar operations↗