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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 127 records · Page 7
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NASA NTRS2021

Navigation Prediction Performance During OSIRIS-REx Proximity Operations at (101955) Bennu

The OSIRIS-REx (Origins, Spectral Interpretation, Resource Identification and Security–Regolith Explorer) Orbit Determination team performed covariance analyses prior to the commencement of proximity operations (ProxOps) at (101955) Bennu to determine the expected predicted trajectory performance in order to meet trajectory knowledge requirements throughout each phase of the mission. One of the primary requirements placed on the predicted trajectory performance was based on the performance during orbital phases leading up to the maneuver to initiate the Touch-and-Go (TAG) trajectory descent. Throughout ProxOps the nominal force models being used to predict the spacecraft trajectory were updated in an effort to improve the prediction performance. The most significant models that contributed to prediction performance were of solar radiation pressure, thermal reradiation of the spacecraft, predicted attitude errors, and desaturation maneuvers. Efforts were made throughout all of ProxOps to monitor, trend, predict, and update spacecraft modeling to improve the prediction performance. These efforts were vital to reduce the spacecraft knowledge errors necessary to achieve a TAG target smaller than pre-launch analysis allowed due to the rough terrain of Bennu. Increased precision in predicted trajectory errors allowed for refined uncertainties to be used for future phase planning throughout the mission. The navigation team successfully predicted the spacecraft trajectory throughout all of ProxOps achieving predicted trajectories errors less than originally analyzed.

Jason M. Leonard↗
NASA NTRS2017

Preliminary Investigation of Impact of Technological Impairment on Trajectory-Based Operations

The Next Generation Air Transportation System (NextGen) incorporates collaborative air traffic management and Trajectory-Based Operations (TBO) in order to significantly increase the capacity, efficiency, and predictability of operations in the National Airspace System (NAS), without decreasing safety. This is enabled by airspace users and service providers sharing knowledge about operations that allows prediction of the complete 4D flight trajectory with as little uncertainty as possible. Additionally, new software and hardware technology is critical to reaching NextGen goals, especially with regard to TBO. What if the technologies that are critical for TBO were to be impaired or fail completely? Should there be a malfunction of a piece of the technology, it must be ensured that the whole system does not break down completely or suffer severe impairment. Instead, operations need to be maintained proportionally to the problem and safety needs to be ensured (graceful degradation). This paper proposes a systematic framework to investigate the vulnerability of TBO to technology disruption, and determine the impact of technological impairment on TBO. Two representative technologies are chosen for detailed investigation and the impact of their impairment on the degradation of TBO is illustrated using a weather-related scenario. XXXX There are several possible directions of future work. We believe it is desirable to develop methods to quantitatively assess the impact of technological disruption on TBO and to have the simulation tools to validate the impact. The availability of prognostics and health management methods could be leveraged to predict technological failure/disruption, thus predicting how TBO will be a ected, and possibly pro-actively mitigating the impact. It is important to develop large-scale scenarios where the e ect of technological impairment is prominent, and identify methods to quantitatively assess the extent of TBO degradation. An important goal of such an investigation is the development of failure-resistant resilient trajectory-based oper- ations. Resilience14, 15 is the property of a system to \bounce back" and resume at least a signi cant portion of its functionalities after degradation due to technological impairment(s). A systems resilience includes properties such as \bu ering capacity" (quantifying disruptions the system can absorb or adapt to without a fundamental breakdown in performance or in the systems structure), \ exibility" (ability to restructure itself in response to external changes or pressures), "margin" (how closely the system is currently operating rela- tive to one or another kind of performance boundary), \tolerance" (whether the system gracefully degrades as stress/pressure increase, or collapses quickly when pressure exceeds adaptive capacity), etc. Future work needs to focus on quantifying and improving the resilience of TBO, and identifying resilient design solutions for aviation.

TBO↗
NASA NTRS1993

Onboard Signal Processing: Wave of the Future for Planetary Radio Science?

Future spacecraft-based radio observations of planetary surfaces, rings, and atmospheres could significantly benefit from recent technological advances in real-time digital signal processing (DSP) hardware. Traditionally, the radio observations have been carried out in a 'down link' configuration in which about 20-W spacecraft transmitted RF power illuminates the target of interest and the perturbed signal is collected at an Earth receiving station. The down link configuration was dictated by the large throughput of received data, corresponding to a relatively large recording band width (about 50 kHz) needed to capture the coherent and scattered signal components in the presence of trajectory, ephemeris, and measurement uncertainties. An alternative 'up link' configuration in which powerful Earth-based radio transmitters (20-200 kW) are used to illuminate the target and data are recorded on board a spacecraft could enhance the measurements' signal-to-noise ratio by a factor of about 1000, allowing a quantum leap in scientific capabilities. Various aspects of alternative signal processing technologies are discussed.

Marouf, E. A.↗
NASA NTRS2005

Aerocapture Performance Analysis of A Venus Exploration Mission

A performance analysis of a Discovery Class Venus Exploration Mission in which aerocapture is used to capture a spacecraft into a 300km polar orbit for a two year science mission has been conducted to quantify its performance. A preliminary performance assessment determined that a high heritage 70 sphere-cone rigid aeroshell with a 0.25 lift to drag ratio has adequate control authority to provide an entry flight path angle corridor large enough for the mission s aerocapture maneuver. A 114 kilograms per square meter ballistic coefficient reference vehicle was developed from the science requirements and the preliminary assessment s heating indicators and deceleration loads. Performance analyses were conducted for the reference vehicle and for sensitivity studies on vehicle ballistic coefficient and maximum bank rate. The performance analyses used a high fidelity flight simulation within a Monte Carlo executive to define the aerocapture heating environment and deceleration loads and to determine mission success statistics. The simulation utilized the Program to Optimize Simulated Trajectories (POST) that was modified to include Venus specific atmospheric and planet models, aerodynamic characteristics, and interplanetary trajectory models. In addition to Venus specific models, an autonomous guidance system, HYPAS, and a pseudo flight controller were incorporated in the simulation. The Monte Carlo analyses incorporated a reference set of approach trajectory delivery errors, aerodynamic uncertainties, and atmospheric density variations. The reference performance analysis determined the reference vehicle achieves 100% successful capture and has a 99.87% probability of attaining the science orbit with a 90 meters per second delta V budget for post aerocapture orbital adjustments. A ballistic coefficient trade study conducted with reference uncertainties determined that the 0.25 L/D vehicle can achieve 100% successful capture with a ballistic coefficient of 228 kilograms per square meter and that the increased ballistic coefficient increases post aerocapture V budget to 134 meters per second for a 99.87% probability of attaining the science orbit. A trade study on vehicle bank rate determined that the 0.25 L/D vehicle can achieve 100% successful capture when the maximum bank rate is decreased from 30 deg/s to 20 deg/s. The decreased bank rate increases post aerocapture delta V budget to 102 meters per second for a 99.87% probability of attaining the science orbit.

Starr, Brett R.↗
NASA NTRS2010

Predictability of Top of Descent Location for Operational Idle-Thrust Descents

To enable arriving aircraft to fly optimized descents computed by the flight management system (FMS) in congested airspace, ground automation must accurately predict descent trajectories. To support development of the trajectory predictor and its uncertainty models, commercial flights executed idle-thrust descents at a specified descent speed, and the recorded data included the specified descent speed profile, aircraft weight, and the winds entered into the FMS as well as the radar data. The FMS computed the intended descent path assuming idle thrust after top of descent (TOD), and the controllers and pilots then endeavored to allow the FMS to fly the descent to the meter fix with minimal human intervention. The horizontal flight path, cruise and meter fix altitudes, and actual TOD location were extracted from the radar data. Using approximately 70 descents each in Boeing 757 and Airbus 319/320 aircraft, multiple regression estimated TOD location as a linear function of the available predictive factors. The cruise and meter fix altitudes, descent speed, and wind clearly improve goodness of fit. The aircraft weight improves fit for the Airbus descents but not for the B757. Except for a few statistical outliers, the residuals have absolute value less than 5 nmi. Thus, these predictive factors adequately explain the TOD location, which indicates the data do not include excessive noise.

Stell, Laurel L.↗
NASA NTRS2017

Entry, Descent, and Landing technological barriers and crewed MARSvehicle performance analysis

Mars has been explored historically only by robotic crafts, but a crewed mission encompasses several new engineering challenges – high ballistic coefficient entry, hypersonic decelerators, guided entry for reaching intended destinations within acceptable margins for error in the landing ellipse, and payload mass are all critical factors for evaluation. A comprehensive EDL parametric analysis has been conducted in support of a high mass landing architecture by evaluating three types of vehicles −70° Sphere Cone, Ellipsled and SpaceX hybrid architecture called Red Dragon as potential candidate options for crewed entry vehicles. Aerocapture at the Martian orbit of about 400 km and subsequent Entry-from-orbit scenarios were investigated at velocities of 6.75 km/s and 4 km/s respectively. A study on aerocapture corridor over a range of entry velocities (6–9 km/s) suggests that a hypersonic L/D of 0.3 is sufficient for a Martian aerocapture. Parametric studies conducted by varying aeroshell diameters from 10 m to 15 m for several entry masses up to 150 mt are summarized and results reveal that vehicles with entry masses in the range of about 40–80 mt are capable of delivering cargo with a mass on the order of 5–20 mt. For vehicles with an entry mass of 20 mt to 80 mt, probabilistic Monte Carlo analysis of 5000 cases for each vehicle were run to determine the final landing ellipse and to quantify the statistical uncertainties associated with the trajectory and attitude conditions during atmospheric entry. Strategies and current technological challenges for a human rated Entry, Descent, and Landing to the Martian surface are presented in this study.

Prabhakar Subrahmanyam↗
NASA NTRS2019

InSight orbit determination

The InSight mission relied on accurate deep-space navigation for a successful Mars landing on November 26, 2018. In this paper, we discuss the role of the cruise Orbit Determination team, whose responsibilities included determining the spacecraft state, predicting the future trajectory, and quantifying the uncertainty associated with those estimates. In particular, we will focus on spacecraft dynamic modeling, small forces due to attitude control, radiometric tracking data, filter strategies, uncertainty quantification, and responses to unexpected flight situations. We will also provide analysis of reconstructed maneuvers, small forces, and delivery accuracy at Mars arrival.

Seubert, Jill↗
NASA NTRS2017

JUNO navigation for Jupiter orbit insertion

Juno arrived at Jupiter on 05 July 2016 UTC, achieving orbit with the execution of the Jupiter Orbit Insertion (JOI) maneuver. Thanks to a dynamically wellbehaved spacecraft, the delivery of Juno to JOI was done largely with only a maneuver to setup and Earth gravity assist (EGA), an EGA, an EGA clean-up maneuver, and a JOI targeting maneuver. During the last several weeks of the approach to JOI, the dominant uncertainties in the predicted trajectory were from the Jupiter barycenter ephemeris. In this paper, we discuss the maneuver and orbit determination (OD) strategy for successfully arriving at JOI, the the challenges of calculating a correction to the Jupiter barycenter ephemeris using only radiometric data types, and how the ephemeris estimates during approach to JOI compare to a post-JOI trajectory reconstruction.

Takahashi, Yu↗
NASA NTRS2024

Iterated Sigma-Point Kalman Filtering for Trajectory Reconstruction

Two second-order Kalman filtering methods are added to the New Statistical Trajec-tory Estimation Program (NewSTEP). The two filters are of the class of Sigma-Point Kalman Filters, namely the Unscented Kalman Filter and the Divided Difference Filter. Both filters are implemented with an iterative measurement update step. Results from simulation test case and a flight data test case are provided to show the filter performance. The results indicate that the new second-order filters pro-duce trajectory estimates with reduced uncertainties when compared to the existing first-order filtering method.

Sophia Vedvik↗
NASA NTRS2022

Mangroves Cover Change Trajectories 1984-2020: The Gradual Decrease of Mangroves in Colombia

Awareness of the significant benefits of mangroves to human lives and their role in regulating environmental processes has increased during the recent decades. Yet there remains significant uncertainty about the mangrove change trajectories and the drivers of change at national scales. In Colombia, the absence of historical satellite imagery and persistent cloud cover have impeded the accurate mapping of mangrove extent and change over time. We create a temporally consistent Landsat-derived dataset using the LandTrendr algorithm to track the historical land cover and mangrove conversion from 1984-2020 across Colombia. Over this period, mangrove extent decreased by ~48.000ha (14% of total mangrove area). We find a gradual reduction of mangrove extent along the Pacific coast since 2004, whereas, in the Caribbean, mangrove cover declined around during 1984-1988 and also after 2012. Our time-series analysis matches with drivers of mangrove change at three local sites. For instance, hydroclimatic events, dredging activities, and high sediment loads transported by the rivers have collectively improved mangrove recovery in some sites. In contrast, human activities pressure linked to agricultural expansion and road construction have degraded mangroves. The transition from dense mangrove to other vegetation types is the most significant conversion affecting mangrove cover in Colombia, impacting an area of 38,469 ± 2,829 ha. We anticipate increased mangrove loss, especially along the Pacific coast, resulting from intensified human activity. Prioritization of conservation areas is needed to support local institutions, maintain currently protected areas, and develop strategies (e.g. payment for ecosystem services) to preserve one of the most pristine mangrove regions in the Western Hemisphere.

Landsat↗
NASA NTRSDate not supplied

Copernicus-LinCov (COPCOV) Software Integration in Support of Robust Trajectory Optimization

Robust trajectory optimization is the process of optimizing a trajectory while accounting for system uncertainty due to a variety of potential error sources. This work highlights the development and features of a novel tool known as CopCov to support robust trajectory optimization efforts. CopCov acts as an interface between Copernicus, a generalized trajectory design and optimization tool, and LinCov, a linear covariance analysis tool. By having a direct interface between these two software packages, Copernicus can receive covariance information from LinCov through a direct feedback loop, thus enabling optimization of a trajectory that is robust to trajectory dispersions and navigation errors. This paper details the architecture of CopCov and its flexibility to operate under varying configurations, including with both tools running locally or alternatively with the tools communicating via a remote connection. Additionally, the CopCov tool is demonstrated on a simple Hohmann transfer reference trajectory with varying numbers of Trajectory Correction Maneuvers (TCMs) and varying problem formulations. This example scenario is used to highlight how the inclusion of the CopCov interface affects burn placement of both major burns and minor burns (i.e., TCMs) in the optimized solution. Results are compared against analytical solutions and against a Genetic Algorithm (GA) optimizer for independent verification and validation.

Copernicus↗
NASA NTRS2000

Chance Encounter with a Stratospheric Kerosene Rocket Plume From Russia Over California

A high-altitude aircraft flight on April 18, 1997 detected an enormous aerosol cloud at 20 km altitude near California (37 N). Not visually observed, the cloud had high concentrations of soot and sulfate aerosol, and was over 180 km in horizontal extent. The cloud was probably a large hydrocarbon fueled vehicle, most likely from rocket motors burning liquid oxygen and kerosene. One of two Russian Soyuz rockets could have produced the cloud: a launch from the Baikonur Cosmodrome, Kazakhstan on April 6; or from Plesetsk, Russia on April 9. Parcel trajectories and long-lived trace gas concentrations suggest the Baikonur launch as the cloud source. Cloud trajectories do not trace the Soyuz plume from Asia to North America, illustrating the uncertainties of point-to-point trajectories. This cloud encounter is the only stratospheric measurement of a hydrocarbon fuel powered rocket.

Newman, P. A.↗
NASA NTRS1975

Dispersion analysis techniques within the space vehicle dynamics simulation program

The Space Vehicle Dynamics Simulation (SVDS) program was evaluated as a dispersion analysis tool. The Linear Error Analysis (LEA) post processor was examined in detail and simulation techniques relative to conducting a dispersion analysis using the SVDS were considered. The LEA processor is a tool for correlating trajectory dispersion data developed by simulating 3 sigma uncertainties as single error source cases. The processor combines trajectory and performance deviations by a root-sum-square (RSS process) and develops a covariance matrix for the deviations. Results are used in dispersion analyses for the baseline reference and orbiter flight test missions. As a part of this study, LEA results were verified as follows: (A) Hand calculating the RSS data and the elements of the covariance matrix for comparison with the LEA processor computed data. (B) Comparing results with previous error analyses. The LEA comparisons and verification are made at main engine cutoff (MECO).

Snow, L. S.↗
NASA NTRS2012

An Efficient Deterministic Approach to Model-based Prediction Uncertainty Estimation

Prognostics deals with the prediction of the end of life (EOL) of a system. EOL is a random variable, due to the presence of process noise and uncertainty in the future inputs to the system. Prognostics algorithm must account for this inherent uncertainty. In addition, these algorithms never know exactly the state of the system at the desired time of prediction, or the exact model describing the future evolution of the system, accumulating additional uncertainty into the predicted EOL. Prediction algorithms that do not account for these sources of uncertainty are misrepresenting the EOL and can lead to poor decisions based on their results. In this paper, we explore the impact of uncertainty in the prediction problem. We develop a general model-based prediction algorithm that incorporates these sources of uncertainty, and propose a novel approach to efficiently handle uncertainty in the future input trajectories of a system by using the unscented transformation. Using this approach, we are not only able to reduce the computational load but also estimate the bounds of uncertainty in a deterministic manner, which can be useful to consider during decision-making. Using a lithium-ion battery as a case study, we perform several simulation-based experiments to explore these issues, and validate the overall approach using experimental data from a battery testbed.

Daigle, Matthew J.↗
NASA NTRS2007

Preliminary Performance Analyses of the Constellation Program ARES 1 Crew Launch Vehicle

By the time NASA's Exploration Systems Architecture Study (ESAS) report had been released to the public in December 2005, engineers at NASA's Marshall Space Flight Center had already initiated the first of a series of detailed design analysis cycles (DACs) for the Constellation Program Crew Launch Vehicle (CLV), which has been given the name Ares I. As a major component of the Constellation Architecture, the CLV's initial role will be to deliver crew and cargo aboard the newly conceived Crew Exploration Vehicle (CEV) to a staging orbit for eventual rendezvous with the International Space Station (ISS). However, the long-term goal and design focus of the CLV will be to provide launch services for a crewed CEV in support of lunar exploration missions. Key to the success of the CLV design effort and an integral part of each DAC is a detailed performance analysis tailored to assess nominal and dispersed performance of the vehicle, to determine performance sensitivities, and to generate design-driving dispersed trajectories. Results of these analyses provide valuable design information to the program for the current design as well as provide feedback to engineers on how to adjust the current design in order to maintain program goals. This paper presents a condensed subset of the CLV performance analyses performed during the CLV DAC-1 cycle. Deterministic studies include development of the CLV DAC-1 reference trajectories, identification of vehicle stage impact footprints, an assessment of launch window impacts to payload performance, and the computation of select CLV payload partials. Dispersion studies include definition of input uncertainties, Monte Carlo analysis of trajectory performance parameters based on input dispersions, assessment of CLV flight performance reserve (FPR), assessment of orbital insertion accuracy, and an assessment of bending load indicators due to dispersions in vehicle angle of attack and side slip angle. A short discussion of the various customers for the dispersion results, along with results and ramifications of each study, are also provided.

Phillips, Mark↗
DOE OSTI2025

Back trajectories for TBS flights (c1-level)

The ARMTRAJ VAP provides four trajectory datasets initialized at ARM deployment coordinates and configured using ARM datasets. The four trajectory datasets support aerosol, cloud, and planetary boundary layer research. Trajectory calculations use the HYSPLIT model informed by the ERA5 reanalysis dataset at its highest spatial resolution (~31 km). For each sample in each of the four datasets, HYSPLIT will also be run at multiple starting locations surrounding ARM deployments, enabling an ensemble of runs from which the mean and variability (estimated uncertainty) of each sample's trajectory coordinates, thermodynamic properties, or other fields will be reported.

54 ENVIRONMENTAL SCIENCES↗
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 there are moderate to extreme uncertainties in their operating environment, i.e., where the trajectories of hazards are partially known to completely unknown. 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. 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↗