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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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45 records · Page 3
All sourcesNASA NTRSDOE OSTI
NASA NTRS1989

Atmospheric drag model calibrations for spacecraft lifetime prediction

Although solar activity prediction uncertainty normally dominates decay prediction error budget for near-Earth spacecraft, the effect of drag force modeling errors for given levels of solar activity needs to be considered. Two atmospheric density models, the modified Harris-Priester model and the Jacchia-Roberts model, to reproduce the decay histories of the Solar Mesosphere Explorer (SME) and Solar Maximum Mission (SMM) spacecraft in the 490- to 540-kilometer altitude range were analyzed. Historical solar activity data were used in the input to the density computations. For each spacecraft and atmospheric model, a drag scaling adjustment factor was determined for a high-solar-activity year, such that the observed annual decay in the mean semimajor axis was reproduced by an averaged variation-of-parameters (VOP) orbit propagation. The SME (SMM) calibration was performed using calendar year 1983 (1982). The resulting calibration factors differ by 20 to 40 percent from the predictions of the prelaunch ballistic coefficients. The orbit propagations for each spacecraft were extended to the middle of 1988 using the calibrated drag models. For the Jaccia-Roberts density model, the observed decay in the mean semimajor axis of SME (SMM) over the 4.5-year (5.5-year) predictive period was reproduced to within 1.5 (4.4) percent. The corresponding figure for the Harris-Priester model was 8.6 (20.6) percent. Detailed results and conclusions regarding the importance of accurate drag force modeling for lifetime predictions are presented.

Binebrink, A. L.↗
NASA NTRS2023

Extended Kalman Filter Performance on the Artemis-1 Mission

The Artemis Program is NASA’s campaign to explore the Moon and beyond. Artemis-1, the uncrewed exoLEO test flight of the Orion spacecraft, was completed in 2022. There were four navigation Extended Kalman Filters (EKFs) that are part of the Orion navigation system. The Atmospheric Extended Kalman Filter (ATMEKF) estimates the vehicle position, velocity, and attitude (referred to as the vehicle state) during the ascent and entry phases of flight. Once Orion is outside of Earths atmosphere, the Earth Orbit Extended Kalman Filter (EOEKF) and CisLunar Extended Kalman Filter (CLEKF) estimate the translational states, depending on the phase of flight, while the Attitude Extended Kalman Filter (ATTEKF) estimates the rotational state of the vehicle. The Kalman filters propagate the vehicle state forward in time using a combination of dynamics models and the output data from the Inertial Measurement Unit (IMU). The filters update the vehicle states and associated uncertainties, in the form of the covariance matrix, using pseudorange measurements from GPS (in ATMEKF/EOEKF), optical navigation measurements of the Earth or Moon (in CLEKF), and star tracker measurements (in ATTEKF). Simultaneously, the Kalman filters estimate error sources in the sensors, which are included in the state vectors as Exponentially Correlated Random Variables (ECRVs). This paper will summarize the performance of these filters during the Artemis-1 mission.

Artemis-1↗
NASA NTRSDate not supplied

The Spacecraft Mass Balance as a Diagnostic Tool for Cabin Air Quality

The spacecraft-level mass balance is a powerful tool for diagnosing and decoupling factors influencing cabin air quality, especially with respect to trace contaminant propagation. Successful implementation of this approach relies upon accurate and temporally relevant air quality measurements, which are often challenging to attain for emerging trace contaminants. In addition to the proper interpretation of air quality data trends, a thorough understanding of subsystem-level mass transfer is required to characterize process performance. For many Environmental Control and Life Support System processes, subsystem mass transfer may be predicted based on physicochemical properties and classic unit operation design approaches. Gaps in understanding of process performance should be supplemented with thorough ground testing. A high confidence in the fidelity of one of these two aspects, air quality data or process performance, may help offset uncertainties in the other. At minimum, thresholding assumptions and numerical methods can be imposed to constrain unknown parameters within the physical envelope of the situation at hand. Finally, the complexity of cabin-wide integrated mass balances may be reduced by implementing a phenomenological approach towards subsystem discretization.

Cabin Air-quality↗
NASA NTRS2013

Dynamics of Orbits near 3:1 Resonance in the Earth-Moon System

The Interstellar Boundary Explorer (IBEX) spacecraft is currently in a highly elliptical orbit around Earth with a period near 3:1 resonance with the Moon. Its orbit is oriented so that apogee does not approach the Moon. Simulations show this orbit to be remarkably stable over the next twenty years. This article examines the dynamics of such orbits in the Circular Restricted 3-Body Problem (CR3BP). We look at three types of periodic orbits, each exhibiting a type of symmetry of the CR3BP. For each of the orbit types, we assess the local stability using Floquet analysis. Although not all of the periodic solutions are stable in the mathematical sense, any divergence is so slow as to produce practical stability over several decades. We use Poincare maps with twenty-year propagations to assess the nonlinear stability of the orbits, where the perturbation magnitudes are related to the orbit uncertainty for the IBEX mission. Finally we show that these orbits belong to a family of orbits connected in a bifurcation diagram that exhibits exchange of stability. The analysis of these families of period orbits provides a valuable starting point for a mission orbit trade study.

Dichmann, Donald J.↗
NASA NTRS2008

On Combining Thermal-Infrared and Radio-Occultation Data of Saturn's Atmosphere

Radio-occultation and thermal-infrared measurements are complementary investigations for sounding planetary atmospheres. The vertical resolution afforded by radio occultations is typically approximately 1 km or better, whereas that from infrared sounding is often comparable to a scale height. On the other hand, an instrument like CIRS can easily generate global maps of temperature and composition, whereas occultation soundings are usually distributed more sparsely. The starting point for radio-occultation inversions is determining the residual Doppler-shifted frequency, that is the shift in frequency from what it would be in the absence of the atmosphere. Hence the positions and relative velocities of the spacecraft, target atmosphere, and DSN receiving station must be known to high accuracy. It is not surprising that the inversions can be susceptible to sources of systematic errors. Stratospheric temperature profiles on Titan retrieved from Cassini radio occultations were found to be very susceptible to errors in the reconstructed spacecraft velocities (approximately equal to 1 mm/s). Here the ability to adjust the spacecraft ephemeris so that the profiles matched those retrieved from CIRS limb sounding proved to be critical in mitigating this error. A similar procedure can be used for Saturn, although the sensitivity of its retrieved profiles to this type of error seems to be smaller. One issue that has appeared in inverting the Cassini occultations by Saturn is the uncertainty in its equatorial bulge, that is, the shape in its iso-density surfaces at low latitudes. Typically one approximates that surface as a geopotential surface by assuming a barotropic atmosphere. However, the recent controversy in the equatorial winds, i.e., whether they changed between the Voyager (1981) era and later (after 1996) epochs of Cassini and some Hubble observations, has made it difficult to know the exact shape of the surface, and it leads to uncertainties in the retrieved temperature profiles of one to a few kelvins. This propagates into errors in the retrieved helium abundance, which makes use of thermal-infrared spectra and synthetic spectra computed with retrieved radio-occultation temperature profiles. The highest abundances are retrieved with the faster Voyager-era winds, but even these abundances are somewhat smaller than those retrieved from the thermal-infrared data alone (albeit with larger formal errors). The helium abundance determination is most sensitive to temperatures in the upper troposphere. Further progress may include matching the radio-occultation profiles with those from CIRS limb sounding in the upper stratosphere.

Flasar, F. M.↗
NASA NTRSDate not supplied

Early Information Parameter-Set Analysis for Satellite Close Approaches using Machine Learning

Understanding orbital mechanics is essential in space flight and navigation applications, and leveraging modern force models for flight path projection remains an important aspect in space mission design and operation. However, force models do not capture all the dynamics or perturbations in the space environment and thus are subject to errors in predicting the state vectors. The further out the predicted miss distance between spacecraft is from the time of closest approach (TCA), the larger the propagated errors in the predicted miss distance at TCA is. The dependency on these force models for spacecraft flight state prediction calls for a more reliable method that can quantify, or even reduce, these propagated errors. With recent advances in the field artificial intelligence, specifically in machine and deep learning algorithms, a model that implements these approaches can improve on the modern force model approach. The goal for this work is to provide an early-information decision-making threshold, in order to prioritize risk assessment implementation, given the ongoing increase of space objects. In analyzing the relationship of several parameters from conjunction data messages(CDMs) and solar information, early information becomes viable in miss distance prediction with unsupervised learning techniques, which learn the parameters that are linked together with miss distance and probability of collision (Pc) variables. Another approach implemented for identifying relationships within CDMs is supervised learning, in which a shallow neural network binary classifier learns to distinguish events with Pc values¡108. These parameters detected in the unsupervised process are then applied to a regression neural network, which predicts the miss distance at TCA for a specific event within a given uncertainty bound. For the regression neural network, a Long Short Term Memory (LSTM) neural network is implemented, which yields memory about each time step in an event. Using an LSTM network, the model learns to predict miss distance within 0.2km of the value measured at TCA. Although there is a limited amount of "close miss" data to train a network, the network learns to associate parameters, like large energy dissipation rates with the secondary object, with an elevated Pc

Brianna I. Robertson↗
NASA NTRSDate not supplied

Navigation Performance of the BioSentinel Deep Space CubeSat Mission

The BioSentinel mission was recently launched aboard the SLS launch vehicle (LV) as part of the Artemis- 1 campaign. The BioSentinel navigation team successfully tracked and guided the spacecraft through a lunar gravity assist to its destination Earth-trailing heliocentric orbit. This 6U CubeSat carries live yeast cells to analyze the effects of radiation at large distances from Earth, becoming the first biological payload in Deep Space. Prelaunch activities included mission design updates, orbit determination rehearsals and the development of a tracking schedule in coordination with the Artemis-1 payload office and the Deep Space Network (DSN). An important influence on the trajectories of Artemis I secondaries was the uncertainty associated with deployment from the Interim Cryogenic Propulsion System (ICPS), the upper stage of the SLS LV. The ICPS was rotating at a rate of 1 rpm; there was also an uncertainty in the spin axis attitude, which translated into an unknown clock angle of deployment. The variability in this angle and magnitude of deployment implied the existence of a non-negligible risk of a lunar impact, which was evaluated for various potential launch dates. We present the results of Monte Carlo analyses and compute the pertinent maneuvers to avoid it. In addition, we present a comparison with the actual deployment once the mission launched by reconstructing our trajectory with tracking data. On November 16th 2022 BioSentinel successfully deployed from ICPS and the navigation team started to receive 2-way Doppler and Sequential Ranging data from the DSN. We processed early data to try to obtain a first ephemeris using Initial Orbit Determination (IOD) methods such as the least squares. Soon after deployment, the spacecraft was tumbling and entered safe mode, creating a period where the tracking data were sparse. The mission team recovered the spacecraft and after four tracking passes, we solved for a first ephemeris that was sent to the DSN for better tracking of the spacecraft. After propagating this first ephemeris solution, we determined that we avoided impact with a margin of a few hundred km from the lunar surface. More tracking data over the next few days (from DSN as well as ESA antennas) allowed for a more refined orbit solution predicting a periselene altitude of 406 km and a lunar eclipse lasting 36.5 minutes. Therefore, BioSentinel operators aborted any correction maneuvers. This periselene altitude also gave us the necessary energy to achieve a heliocentric orbit. The next challenge was due to the necessary adjustments in our orbit determination method due to the large energy boost resulting from the lunar flyby. After a series of tracking passes we were able to get a nominal solution that resulted into a stable trajectory. This paper discusses in detail the navigation performance using the X-band IRIS transponder, as well as the challenges and lessons learned prior to and during this deep space, CubeSat mission.

Andres Dono Perez↗
NASA NTRS2000

Burning in Outer Space: Microgravity

A better understanding of combustion can lead to significant technological advances, such as less polluting, more fuel-efficient vehicles. Unfortunately, gravity can interfere with the study of combustion. Gravity drags down gases that are cooler- and, therefore, denser-than heated gases. This movement mixes the fuel and the oxidizer substance that promotes burning. Because of this mixing, an observer cannot necessarily distinguish what is happening as a result of the natural combustion process and what is caused, by the pull of gravity. To remove this uncertainty, scientists can conduct experiments that simulate the negation of gravity through freefall. This condition is known as a microgravity environment. A micro-gravity experiment may take place in a chamber that is dropped down a hole or from a high-speed drop tower. The experiment also be conducted in an airplane or a rocket during freefall in a parabolic flight path. This method provides less than a minute of microgravity at most. An experiment that requires the prolonged absence of gravity may necessitate the use of an orbiting spacecraft as a venue. However, access to an orbital laboratory is difficult to acquire. High-end computing centers such as the NCCS can provide a practical alternative to operating in microgravity. Scientists can model phenomena such as combustion without gravitys observational interference. The study of microgravity combustion produces important benefits beyond increased observational accuracy. Certain valuable materials that are produced through combustion can be formed with a more uniform crystal structure-and, therefore, improved structural quality-when the pull of gravity is removed. Furthermore, understanding how fires propagate in the absence of gravity can improve fire safety aboard spacecraft.

Matkowsky, Bernard↗
NASA NTRS1994

Observation of anomalous slow-mode shock and reconnection layer in the dayside magnetospause

Plasma and magnetic field data from the International Sun-Earth Explorer ISEE 2 spacecraft recorded during an outbound crossing of the dayside, northern hemisphere magnetopause in October 29, 1979, provide evidence for a slow shock (SS) in the observed reconnection layer. This layer is found to be bounded on the magnetosheath side by the SS; near the magnetospheric side of the layer, a second current sheet is found that may have been rotational discontinuity (RD). The direction of the accelerated plasma flow, the earthward sense of the normal magnetic filed across the SS and RD, and the relative orientation of the SS and the RD all indicate that the reconection site was located south of the spacecraft. Quantitative tests show that, allowing for experiemental uncertanties, data taken upstream and downstream of the SS are consistent with coplanarity and other Rankine-Hugoniot (RH) conditions. Examiniations of the flow parameters indicates two anomalous properties of the SS: the upstream flow, viewed in the deHoffmann-Teller frame, is superalfvenic and the downstream plasma is firehose unstable. In comparison to the long-wavelength slow-mode phase speed, however, the flow in the upstream region is super slow, while in the downstream region it is subslow, as requeired for a slow-mode shock. Further properties of the shock include a large decrease in total enthalpy across it, indicating the escape of a sizable heat flux from the shock structure, and the occurrence of a polarization reversal of the tangential magnetic field within the shock layer, a feature that is predicted by linear double-polytropic Hall-MHD and results from a large increase in pressure anistropy from the upstream region, where p(sub parallel) approximately equal to p(sub perp), to the downstream region, where p(sub parrallel) greater than p(sub perp). Quantitative tests of the RD-like discontinuity show that it satisfies the necessary RH conditions within experimental uncertainties and indicate that the flow across it is earthward, that is, it is the same as for the SS. Thus the RD is propagating behind the SS in the direction away from the Earth. The reversal in the order of the discontinuities is attributed to the reversal of the slow and intermediate phase speeds produced by the pressure anistropy in the region between the RD and the SS. The linear dispersion relation and polarization properties of dispersive MHD waves in an anisotropic plasma are examined in the appendix.

Walthour, D. W↗