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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
NASA NTRS2004

A Review of the Match Technique as Applied to AASE-2/EASOE and SOLVE/THESEO 2000

We apply the GSFC trajectory model with a series of ozonesondes to derive ozone loss rates in the lower stratosphere for the AASE-2/EASOE mission (January - March 1992) and for the SOLVE/THESEO 2000 mission (January - March 2000) in an approach similar to Match. Ozone loss rates are computed by comparing the ozone concentrations provided by ozonesondes launched at the beginning and end of the trajectories connecting the launches. We investigate the sensitivity of the Match results on the various parameters used to reject potential matches in the original Match technique and conclude that only a filter based on potential vorticity changes along the calculated back trajectory seems necessary. Our study also demonstrates that calculated ozone loss rates can vary by up to a factor of two depending upon the precise trajectory paths calculated for each trajectory. As a result an additional systematic error might need to be added to the statistical uncertainties published with previous Match results. The sensitivity to the trajectory path is particularly pronounced in the month of January, the month during which the largest ozone loss rate discrepancies between photochemical models and Match are found. For most of the two study periods, our ozone loss rates agree with those previously published. Notable exceptions are found for January 1992 at 475 K and late February/early March 2000 at 450 K, both periods during which we find less loss than the previous studies. Integrated ozone loss rates in both years compare well with those found in numerous other studies and in a potential vorticity/potential temperature approach shown previously and in this paper. Finally, we suggest an alternate approach to Match using trajectory mapping that appears to more accurately reflect the true uncertainties associated with Match and reduces the dependence upon filters that may bias the results of Match through the rejection of greater than or equal to 80% of the matched sonde pairs and >99% of matched observations.

Morris, Gary A.↗
NASA NTRS1989

A predictive guidance algorithm for Mars entry

This report presents the derivation, logic, and performance of a Mars entry guidance algorithm for the Mars Rover Sample Return Mission. This algorithm guides the Mars entry vehicle along an equilibrium glide trajectory designed to satisfy a set of equality and inequality constraints at chute deploy. An equilibrium glide assumption permits analytic prediction of terminal state conditions and eliminates the need for determining numeric state sensitivities. Trajectory deviations due to dispersions or uncertainties in Martian atmosphere, vehicle aerodynamics, or entry interface conditions are accommodated simply by predicting the compensating equilibrium glide profile and achieving this profile with the available lift control. This Mars Predictive Equilibrium Glide guidance scheme was tested on a range of vehicle configurations with a variety of aerodynamic, atmosphere, and trajectory dispersions with a high degree of success.

Tigges, M. A.↗
NASA NTRS2022

Disturbances in North American Boreal Forest and Arctic Tundra: Impacts, Interactions, and Responses

Ecosystems in the North American Arctic-Boreal Zone (ABZ) experience a diverse set of disturbances associated with wildfire, permafrost dynamics, geomorphic processes, insect outbreaks and pathogens, extreme weather events, and human activity. Climate warming in the ABZ is occurring at over twice the rate of the global average, and as a result the extent, frequency, and severity of these disturbances are increasing rapidly. Disturbances in the ABZ span a wide gradient of spatiotemporal scales and have varying impacts on ecosystem properties and function. However, many ABZ disturbances are relatively understudied and have different sensitivities to climate and trajectories of recovery, resulting in considerable uncertainty in the impacts of climate warming and human land use on ABZ vegetation dynamics and in the interactions between disturbance types. Here we review the current knowledge of ABZ disturbances and their precursors, ecosystem impacts, temporal frequencies, spatial extents, and severity. We also summarize current knowledge of interactions and feedbacks among ABZ disturbances and characterize typical trajectories of vegetation loss and recovery in response to ecosystem disturbance using satellite time-series. We conclude with a summary of critical data and knowledge gaps and identify priorities for future study.

high-latitude↗
NASA NTRS2020

In-Time UAV Flight-Trajectory Estimation and Tracking Using Bayesian Filters

Rapid increase of UAV operation in the next decade in areas of on-demand delivery, medical transportation services, law enforcement, traffic surveillance and several others pose potential risks to the low altitude airspace above densely populated areas. Safety assessment of airspace demands the need for a novel UAV traffic management (UTM) framework for regulation and tracking of the vehicles. Particularly for low-altitude UAV operations, quality of GPS measurements feeding into the UAV is often compromised by loss of communication link caused by presence of trees or tall buildings in proximity to the UAV flight path. Inaccurate GPS locations may yield to unreliable monitoring and inaccurate prognosis of remaining battery life and other safety metrics which rely on future expected trajectory of the UAV. This work therefore proposes a generalized monitoring and prediction methodology for autonomous UAVs using in-time GPS measurements. Firstly, a typical 4D smooth trajectory generation technique from a series of waypoint locations with associated expected times-of-arrival based on B-spline curves is presented. Initial uncertainty in the vehicle's expected cruise velocity is quantified to compute confidence intervals along the entire flight trajectory using error interval propagation approach. Further, the generated planned trajectory is considered as the prior knowledge which is updated during its flight with incoming GPS measurements in order to estimate its current location and corresponding kinematic profiles. Estimation of position is denoted in dicrete state-space representation such that position at a future time step is derived from position and velocity at current time step and expected velocity at the future time step. A linear Bayesian filtering algorithm is employed to efficiently refine position estimation from noisy GPS measurements and update the confidence intervals. Further, a dynamic re-planning strategy is implemented to incorporate unexpected detour or delay scenarios. Finally, critical challenges related to uncertainty quantification in trajectory prognosis for autonomous vehicles are identified, and potential solutions are discussed at the end of the paper. The entire monitoring framework is demonstrated on real UAV flight experiments conducted at the NASA Langley Research Center.

Banerjee, Portia↗
NASA NTRS2021

Separation at Crossing Waypoints Under Wind Uncertainty in Urban Air Mobility

To enable high-density operations in major metropolitan areas, urban air mobility networks are anticipated to have air traffic management with higher levels of autonomy. To ensure that this type of autonomy is feasible, one of the critical steps from a safety and efficiency perspective is understanding various factors that affect the spatial separation between airborne flights and ensure that these factors can be managed. In terms of separation assurance and scheduling, an important real-world concern is that future states of aircraft cannot be perfectly predicted. The focus of this research paper is to understand how these prediction errors affect separation and scheduling services and to explore mitigation strategies to handle these errors. In this research, we have simulated these types of uncertainty by adding wind-prediction errors to trajectory predictions for separation. With these wind-prediction errors, we decompose the problem into two separate questions. First, using both simulation and analytical methods, we look at conflict-detection-only scenarios to understand how the wind errors affect required minimum temporal separation between crossing flights to ensure a specific spatial separation. Next, we study how trajectory errors effect conflict resolution, and we explore different combinations of scheduling and separation assurance to mitigate the effects of uncertainty between crossing flights. The conflict resolution algorithm aims to minimize necessary temporal separation between crossing flights under uncertainty, still ensuring safety-critical spatial separation. In summary, this research suggests that the required minimum temporal separation at a crossing waypoint is dependent on factors such as inbound crossing angle, the relative angle between wind direction and bearing of each route, wind magnitude, wind magnitude uncertainty, nominal cruise airspeed of aircraft, and look-ahead time of the conflict detection algorithm. This research also suggests that different combinations of scheduling and separation have different qualitative results. Using a combination of strategic, flow-based scheduling, tactical scheduling at crossings, speed control near crossing points, and separation management leads to a system that is insensitive to trajectory prediction errors with high throughput and flexibility for aircraft away from shared resources.

urban air mobility↗
NASA NTRS2021

Separation at Crossing Waypoints Under Wind Uncertainty in Urban Air Mobility

To enable high-density operations in major metropolitan areas, urban air mobility networks are anticipated to have air traffic management with higher levels of autonomy. To ensure that this type of autonomy is feasible, one of the critical steps from a safety and efficiency perspective is understanding various factors that affect the spatial separation between airborne flights and ensure that these factors can be managed. In terms of separation assurance and scheduling, an important real-world concern is that future states of aircraft cannot be perfectly predicted. The focus of this research paper is to understand how these prediction errors affect separation and scheduling services and to explore mitigation strategies to handle these errors. In this research, we have simulated these types of uncertainty by adding wind-prediction errors to trajectory predictions for separation. With these wind-prediction errors, we decompose the problem into two separate questions. First, using both simulation and analytical methods, we look at conflict-detection-only scenarios to understand how the wind errors affect required minimum temporal separation between crossing flights to ensure a specific spatial separation. Next, we study how trajectory errors effect conflict resolution, and we explore different combinations of scheduling and separation assurance to mitigate the effects of uncertainty between crossing flights. The conflict resolution algorithm aims to minimize necessary temporal separation between crossing flights under uncertainty, still ensuring safety-critical spatial separation. In summary, this research suggests that the required minimum temporal separation at a crossing waypoint is dependent on factors such as inbound crossing angle, the relative angle between wind direction and bearing of each route, wind magnitude, wind magnitude uncertainty, nominal cruise airspeed of aircraft, and look-ahead time of the conflict detection algorithm. This research also suggests that different combinations of scheduling and separation have different qualitative results. Using a combination of strategic, flow-based scheduling, tactical scheduling at crossings, speed control near crossing points, and separation management leads to a system that is insensitive to trajectory prediction errors with high throughput and flexibility for aircraft away from shared resources.

urban air mobility↗
DOE OSTI2025

Uncertainty quantification of a physics-informed model based on sparse identification of a Thermal Energy Distribution System

Integrated energy systems (IES)s are crucial for enhancing the economy and efficiency of power generation sources (e.g., nuclear energy) necessary to unleash American energy dominance. These systems can be integrated with thermal energy storage (TES) and intermittent renewable energies to optimize overall energy use, peak-load regulation, and demand-side responses. However, the stabilization of energy generation, transport, and utilization introduces operational complexities that exceed the challenges of managing each sub-component individually. Currently, though IESs rely on human operators for efficiency and stability, reducing human error risk and enhancing performance through automation is highly desirable. Recent advances at Idaho National Laboratory have demonstrated successful control of the Thermal Energy Distributed System (TEDS). However, the automatic control system depends on a deterministic Sparse Identification of Nonlinear Dynamics with Control (SINDyC) model, which are trained based on simulation data from physics-based simulations. Because of uncertainties in physics-based simulation, SINDyC model results in large discrepancies against experimental data and cannot be reliably used in automatic control. In this paper, we present an innovative approach to address these discrepancies by quantifying uncertainties and developing a more robust model. We first generated trajectories by using first-principles physics codes to encapsulate the experiment. Next, we trained thousands of models by randomly sampling these trajectories. We then collapsed all those models into one probabilistic SINDyC by fitting a multivariate Gaussian distribution onto the resulting coefficient’s distribution. Despite its simplicity, our approach successfully produced 95% confidence intervals that captured the experimental trajectories. It even did so with a higher probability and better U-pooling score across six of the seven relevant quantities of interest (QoIs), as compared to other classical approaches. In conclusion, ongoing research is focusing on generating new experimental trajectories to validate this approach, and on employing Bayesian calibration to refine parametric uncertainties and guide future model development efforts.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS2013

Spiraling Away from Vesta: Design of the Transfer from the Low to High Altitude Dawn Mapping Orbits

Dawn has successfully completed its orbital mission at Vesta and is currently en route to an orbital rendezvous with Ceres in 2015. The longest duration and most complex portion of the Vesta departure trajectory was the transfer from the low to high altitude science orbit. This paper describes the design of this low-thrust trajectory optimized assuming a minimum-propellant mass objective. The transfer utilized solar-electric ion propulsion applied over 139 spacecraft revolutions about Vesta. Science drivers, operational constraints, and robustness to statistical uncertainties are addressed. The 45-day transfer trajectory was successfully implemented in early 2012.

low thrust↗
NASA NTRSDate not supplied

Robust Trajectory Optimization and GN&C Performance Analysis for NRHO Rendezvous

This paper evaluates several candidate Near-Rectilinear Halo Orbits (NRHO) rendezvous trajectory designs using linear covariance (LinCov) analysis and determines the optimal locations for NRHO rendezvous translational maneuver locations. The performance of several candidate relative trajectory designs are determined as a function of relative navigation accuracy (angles only), inertial optical navigation (OpNav), range observability maneuvers, maneuver execution errors, relative maneuver targeting, and environment uncertainties. Further, the optimal locations of rendezvous maneuvers are determined for each of the candidate reference trajectories. The long-term goal of this research is to utilize LinCov and a genetic optimization algorithm (GA) to determine a complete end-to-end optimal NRHO trajectory design that is robust to navigation errors, maneuver execution errors, and environment uncertainties. This paper represents a first step toward this goal. Three candidate rendezvous trajectories with varying numbers of range-observability maneuvers are evaluated for their robustness to uncertainties, errors, and total trajectory correction delta-v performance. Some key elements of this analysis include relative navigation performance in an NRHO, relative trajectory dispersion performance, and total 3-sigma delta-v performance. This development provides the foundation to then determine an optimal and robust end-to-end NRHO rendezvous trajectory, including the determination of the optimal locations of range observability maneuvers, if needed.

Linear Covariance Analysis↗
NASA NTRS2006

Conflict Detection Using Variable Four-Dimensional Uncertainty Bounds to Control Missed Alerts

Decision-support tools for maintaining pairwise aircraft separation rely on conflict detection to alert the operator when the predicted trajectories of aircraft will result in a loss of separation. But aircraft frequently do not follow their predicted trajectories exactly. This can cause missed alerts and the failure of strategic separation procedures. We present a technique for modeling a bounded region of uncertainty around a four-dimensional predicted trajectory and an algorithm for detecting conflicts between trajectories modeled in this way that avoids missed alerts as long as the aircraft remain within the specified regions of uncertainty. In addition, we present an algorithm for detecting the intrusion of a trajectory modeled in this way into an area hazard modeled as a polygonal region. The size of the region of uncertainty can vary along the trajectory continually and independently in the along-path, cross-track, and vertical dimensions, providing an opportunity to reduce the likelihood of false alerts while protecting against typical prediction errors. The algorithm has been implemented in the Autonomous Operations Planner, a NASA Langley prototype decision support tool for airborne self-separation.

Karr, David A.↗
NASA NTRS1988

Orbit lifetime characteristics for Space Station

The factors that influence the orbital lifetime characteristics of the NASA Space Station are discussed. These include altitude, attitude, launch date, ballistic coefficient, and the presence of large articulating solar arrays. Examples from previous program systems studies are presented that illustrate how each factor affects Station orbit lifetime. The effect of atmospheric density models on orbit lifetime predictions is addressed along with the uncertainty of these predictions using current trajectory analysis of the Long Duration Exposure Facility spacecraft. Finally, nominal reboost altitude profiles and fuel requirement considerations are presented for implementing a reboost strategy based on planned Shuttle Orbiter rendezvous strategy and contingency considerations.

Deryder, L.↗
NASA NTRS1996

Flight data results of estimate fusion for spacecraft rendezvous navigation from shuttle mission STS-69

A recently developed rendezvous navigation fusion filter that optimally exploits existing distributed filters for rendezvous and GPS navigation to achieve the relative and inertial state accuracies of both in a global solution is utilized here to process actual flight data. Space Shuttle Mission STS-69 was the first mission to date which gathered data from both the rendezvous and Global Positioning System filters allowing, for the first time, a test of the fusion algorithm with real flight data. Furthermore, a precise best estimate of trajectory is available for portions of STS-69, making possible a check on the performance of the fusion filter. In order to successfully carry out this experiment with flight data, two extensions to the existing scheme were necessary: a fusion edit test based on differences between the filter state vectors, and an underweighting scheme to accommodate the suboptimal perfect target assumption made by the Shuttle rendezvous filter. With these innovations, the flight data was successfully fused from playbacks of downlinked and/or recorded measurement data through ground analysis versions of the Shuttle rendezvous filter and a GPS filter developed for another experiment. The fusion results agree with the best estimate of trajectory at approximately the levels of uncertainty expected from the fusion filter's covariance matrix.

Carpenter, J. Russell↗
NASA NTRS2010

Lidar Wind Profiler Comparison to Weather Balloon for Support of Orion Crew Exploration Vehicle Landings

A comparison study by the National Aeronautics and Space Administration Dryden Flight Research Center, Edwards, CA and the Naval Post Graduate School Center for Interdisciplinary Remotely-Piloted Aircraft Studies, Marina, CA was conducted to show the advantages of an airborne wind profiling lidar system in reducing drift uncertainty along a reentry vehicle descent trajectory. This effort was in support of the once planned Orion Crew Exploration Vehicle ground landing. A Twin Otter Doppler Wind Lidar was flown on multiple flights along the approximate ground track of an ascending weather balloons launched from the Marina Municipal Airport. The airborne lidar used was a 5-milli-Joules, 2-micron infrared laser with a 10-centimeter telescope and a two-axis scanner. Each lidar wind profile contains data for an altitude range between the surface and flight altitude of 2,700 meters, processed on board every 20 seconds. In comparison, a typical weather balloon would traverse that same altitude range with a similar data set available in approximately 15-20 minutes. These tests were conducted on November 15 & 16, 2007. Results comparing the balloon and a 10 minute multiple lidar profile averages show a best case absolute difference of 0.18 m/s (0.35 knots) in speed and 1 degree in direction during light and variable (less than 5 knots, without constant direction) wind conditions. These limited test results indicated a standard deviation wind velocity and direction differences of 0.71 m/s (1.3 knots) and 7.17 degrees for 1800Z, and 0.70 m/s (1.3 knots) and 6.79 degrees, outside of cloud layer.

Houtas, Franzeska↗
NASA NTRS2010

Lidar Wind Profiler Comparison to Weather Balloon for Support of Orion Crew Exploration Vehicle Landings

A comparison study by the National Aeronautics and Space Administration Dryden Flight Research Center (Edwards, California) and the Naval Post Graduate School Center for Interdisciplinary Remotely-Piloted Aircraft Studies (Marina, California) was conducted to show the advantages of an airborne wind profiling light detection and ranging (lidar) system in reducing drift uncertainty along a reentry vehicle descent trajectory. This effort was in support of the once planned Orion Crew Exploration Vehicle ground landing. A Twin Otter Doppler Wind Lidar was flown on multiple flights along the approximate ground track of each ascending weather balloon launched from the Marina Municipal Airport (Marina, California). The airborne lidar used was a 5-mJ, 2-micron infrared laser with a 10-cm telescope and a two-axis scanner. Each lidar wind profile contains data for an altitude range between the surface and flight altitude of 2.7 km, processed on board every 20 s. In comparison, a typical weather balloon would traverse that same altitude range with a similar data set available in approximately 15 to 20 min. These tests were conducted on November 15 and 16, 2007. Results show a best-case absolute difference of 0.18 m/s (0.35 knots) in speed and 1 degree in direct

Houtas, Franzeska F.↗
NASA NTRS2012

Development of Complexity Science and Technology Tools for NextGen Airspace Research and Applications

The objective of this research by NextGen AeroSciences, LLC is twofold: 1) to deliver an initial "toolbox" of algorithms, agent-based structures, and method descriptions for introducing trajectory agency as a methodology for simulating and analyzing airspace states, including bulk properties of large numbers of heterogeneous 4D aircraft trajectories in a test airspace -- while maintaining or increasing system safety; and 2) to use these tools in a test airspace to identify possible phase transition structure to predict when an airspace will approach the limits of its capacity. These 4D trajectories continuously replan their paths in the presence of noise and uncertainty while optimizing performance measures and performing conflict detection and resolution. In this approach, trajectories are represented as extended objects endowed with pseudopotential, maintaining time and fuel-efficient paths by bending just enough to accommodate separation while remaining inside of performance envelopes. This trajectory-centric approach differs from previous aircraft-centric distributed approaches to deconfliction. The results of this project are the following: 1) we delivered a toolbox of algorithms, agent-based structures and method descriptions as pseudocode; and 2) we corroborated the existence of phase transition structure in simulation with the addition of "early warning" detected prior to "full" airspace. This research suggests that airspace "fullness" can be anticipated and remedied before the airspace becomes unsafe.

Holmes, Bruce J.↗
NASA NTRS2025

Mission-Maps For Outbound Cislunar Transfer Trajectories

This study quantifies the robustness and sensitivity of an outbound cislunar trajectory for a lunar lander in the form of mission-maps, or topological maps that allows either a computer program or mission designer to intuitively optimize the placement of critical outbound correction burns from the derived sensitivity data. The non-linear multi-body dynamics are applied to generate an outbound cislunar reference profile used by a linear covariance analysis (LinCov) tool to compute the expected Δv and trajectory dispersions due to the initial state uncertainty, sensor errors, maneuver execution errors, and disturbance accelerations along the outbound cislunar profile. The rapid performance analysis capabilities of LinCov are complimented with parallel processing techniques to evaluate hundreds and thousands of different translational burn locations, placements, and targeting constraints to identify the combination that minimizes the total Δv usage (nominal plus 3σ Δv) and trajectory dispersions at lunar orbit insertion. This study utilizes a generalized reference targeting algorithm to quickly assess the integrated closed-loop GN&C system performance due to different targeting configurations and constraints. The resulting mission maps provide an intuitive insight to ascertain each trajectory correction maneuver’s (TCM) sensitivity to different burn times along an outbound cislunar trajectory and quickly identify desirable engineering tradeoffs when performing analysis on the number and placement of these burns that nominally zero. Multiple mission maps are generated for a variety of different performance parameters that allow engineers to visually identify optimal solutions for trajectory correction maneuver placements, the number of correction burns, and the targeting constraints for each burn.

GN&C↗
NASA NTRSDate not supplied

Trajectory Planning for Mission Survivability of Autonomous Vehicles in Moderately to Extremely Uncertain Environments

Trajectory planning is a particularly challenging task for autonomous vehicles when the uncertainties in their operating environment cannot be characterized statistically. In this paper, we propose a receding horizon control strategy with novel trajectory planning policies that enable dynamic updating of the planned trajectories of autonomous vehicles operating in environments where potential conflicts are, from a statistical perspective, either partially known or completely unknown. The proposed policies utilize two metrics: (1) the number of feasible trajectories; and (2) the robustness of the feasible trajectories. We measure the effectiveness of the suggested policies in terms of mission survivability, which is defined as the probability that the primary mission is accomplished or, if that is not possible, the vehicle lands safely at an alternative site. We show that a linear combination of both metrics is an effective objective function when there is a mix of partially known and unknown uncertainties. When the operating environment is dominated by unknown disturbances, maximizing the number of feasible trajectories results in the highest mission survivability. These findings have significant implications for achieving safe aviation. autonomy.

Aviation autonomy↗