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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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NASA NTRS1989

OMV mission simulator

The Orbital Maneuvering Vehicle (OMV) will be remotely piloted during rendezvous, docking, or proximity operations with target spacecraft from a ground control console (GCC). The real-time mission simulator and graphics being used to design a console pilot-machine interface are discussed. A real-time orbital dynamics simulator drives the visual displays. The dynamics simulator includes a J2 oblate earth gravity model and a generalized 1962 rotating atmospheric and drag model. The simulator also provides a variable-length communication delay to represent use of the Tracking and Data Relay Satellite System (TDRSS) and NASA Communications (NASCOM). Input parameter files determine the graphics display. This feature allows rapid prototyping since displays can be easily modified from pilot recommendations. A series of pilot reviews are being held to determine an effective pilot-machine interface. Pilots fly missions with nominal to 3-sigma dispersions in translational or rotational axes. Console dimensions, switch type and layout, hand controllers, and graphic interfaces are evaluated by the pilots and the GCC simulator is modified for subsequent runs. Initial results indicate a pilot preference for analog versus digital displays and for two 3-degree-of-freedom hand controllers.

Cok, Keith E.↗
NASA NTRS1990

TOPEX/POSEIDON orbit maintenance maneuver design

The Ocean Topography Experiment (TOPEX/POSEIDON) mission orbit requirements are outlined, as well as its control and maneuver spacing requirements including longitude and time targeting. A ground-track prediction model dealing with geopotential, luni-solar gravity, and atmospheric-drag perturbations is considered. Targeting with all modeled perturbations is discussed, and such ground-track prediction errors as initial semimajor axis, orbit-determination, maneuver-execution, and atmospheric-density modeling errors are assessed. A longitude targeting strategy for two extreme situations is investigated employing all modeled perturbations and prediction errors. It is concluded that atmospheric-drag modeling errors are the prevailing ground-track prediction error source early in the mission during high solar flux, and that low solar-flux levels expected late in the experiment stipulate smaller maneuver magnitudes.

Bhat, R. S.↗
NASA NTRS1993

SeaWiFS technical report series. Volume 11: Analysis of selected orbit propagation models for the SeaWiFS mission

An analysis of orbit propagation models was performed by the Mission Operations element of the Sea-viewing Wide Field-of-View Sensor (SeaWiFS) Project, which has overall responsibility for the instrument scheduling. The orbit propagators selected for this analysis are widely available general perturbations models. The analysis includes both absolute accuracy determination and comparisons of different versions of the models. The results show that all of the models tested meet accuracy requirements for scheduling and data acquisition purposes. For internal Project use the SGP4 propagator, developed by the North American Air Defense (NORAD) Command, has been selected. This model includes atmospheric drag effects and, therefore, provides better accuracy. For High Resolution Picture Transmission (HRPT) ground stations, which have less stringent accuracy requirements, the publicly available Brouwer-Lyddane models are recommended. The SeaWiFS Project will make available portable source code for a version of this model developed by the Data Capture Facility (DCF).

Patt, Frederick S.↗
NASA NTRS2013

Dynamics and Control of a Disordered System in Space

In this paper, we present some ideas regarding the modeling, dynamics and control aspects of granular spacecraft. Granular spacecraft are complex multibody systems composed of a spatially disordered distribution of a large number of elements, for instance a cloud of N grains in orbit, with N greater than 10(exp 3). These grains can be large (Cubesat-size) or small (mm-size), and can be active, i.e., a fully equipped vehicle capable sensing their own position and attitude, and enabled with propulsion means, or entirely passive. The ultimate objective would be to study the behavior of the single grains and of large ensembles of grains in orbit and to identify ways to guide and control the shape of a cloud composed of these grains so that it can perform a useful function in space, for instance, as an element of an optical imaging system for astrophysical applications. This concept, in which the aperture does not need to be continuous and monolithic, would increase the aperture size several times compared to large NASA observatories such as ATLAST, allowing for a true Terrestrial Planet Imager that would be able to resolve exo-planet details and do meaningful spectroscopy on distant world. In the paper, we address the modeling and autonomous operation of a distributed assembly (the cloud) of large numbers of highly miniaturized space-borne elements (the grains). A multi-scale, multi-physics model is proposed of the dynamics of the cloud in orbit, as well as a control law for cloud shape maintenance, and preliminary simulation studies yield an estimate of the computational effort, indicating a scale factor of approximately N(exp 1.4) as a function of the number of grains. A granular spacecraft can be defined as a collection of a large number of space-borne elements (in the 1000s) designed and controlled such that a desirable collective behavior emerges, either from the interactions among neighboring grains, and/or between the grains and the environment. In this paper, each grain is considered to be a highly miniaturized spacecraft which has limited size and mass, hence it has limited actuation, limited propulsive capability, limited power, limited sensing, limited communication, limited computational resources, limited range of motion, limited lifetime, and may be expendable. The modeling and dynamics of clouds of vehicles is more challenging than with conventional vehicles because we are faced with a probabilistic vehicle composed of a large number of physically disconnected vehicles. First, different scales of motion occur simultaneously in a cloud: translations and rotations of the cloud as a whole (macro-dynamics), relative rotation and translation of one cloud member with respect to another (meso-dynamics), and individual cloud member dynamics (micro-dynamics). Second, the control design needs to be tolerant of the system complexity, of the system architecture (centralized vs. decentralized large scale system control) as well as robust to un-modeled dynamics and noise sources. Figure 1, top left, shows the kinematic parameters of a 1000 element cloud in orbit. The motion of the system is described with respect to a local vertical-local horizontal (LV-LH) orbiting reference frame (x,y,z)=F(sub ORF) of origin O(sub ORF) which rotates with mean motion omega and orbital semi-major axis R(sub 0). The orbital geometry at the initial time is defined in terms of its six orbital elements, and the orbital dynamics equation for point O(sub ORF) is propagated forward in time under the influence of the gravitational field of the primary and other external perturbations, described below. The origin of this frame coincides with the initial position of the center of mass of the system, and the coordinate axes are z along the local vertical, x toward the flight direction, and y in the orbit normal direction. The assumptions we used to model the dynamics are as follows: 1) The inertial frame is fixed at Earth's center. 2) The orbiting Frame ORF follows Keplerian orbit. 3) the cloud system dynamics is referred to ORF. 4) the attitude of each grain uses the principal body frame as body fixed frame. 5) the atmosphere is assumed to be rigidly rotating with the Earth. Regarding the grains forming the cloud: 1) each grain is modeled as a rigid body; 2) a simple attitude estimator provides attitude estimates, 3) a simple guidance logic commands the position and attitude of each grain, 4) a simple local feedback controller based on PD control of local states is used to stabilize the attitude of the vehicle. Regarding the cloud: 1) the cloud as a whole is modeled as an equivalent rigid body in orbit, and 2) an associated graph establishes agent connectivity and enables coupling between modes of motion at the micro and macro scales; 3) a simple guidance and estimation logic is modeled to estimate and command the attitude of this equivalent rigid body; 4) a cloud shape maintenance controller is based on the dynamics of a stable virtual truss in the orbiting frame. Regarding the environmental perturbations acting on the cloud: 1) a non-spherical gravity field including JO (Earth's spherical field) zonal component, J2 (Earth's oblateness) and J3 zonal components is implemented; 2) atmospheric drag is modeled with an exponential model; 3) solar pressure is modeled assuming the Sun is inertially fixed; and 4) the Earth's magnetic field is model using an equivalent dipole model. The equations of motion are written in a referential system with respect to the origin of the orbiting frame and the state is propagated forward in time using an incremental predictor-corrector scheme. A representative cloud with varying number of grains is simulated to identify the limitations in computation time as the number of grains grows. We derive a control law to track a desired surface in the ORF (equivalently to maintain a reference cloud shape) by defining an error from a desired surface shape, and designing a control law that is exponentially stable and reduces the tracking error to zero. Figure 1 (top right) shows a comparison of various requirements for simulation of single spacecraft vs. granular spacecraft, indicating the high degree of complexity that needs to be taken into consideration. The ORF components of control force required by one of the grains is, for this particular case, in the micro-Newton range. However, no attempt has been made yet to reconfigure (or re-orient) the cloud configuration internally, for which forces in the milli-Newton level are expected, depending on the time required to do the reconfiguration. Figure 1, bottom, shows the computation time as a function of the number of grains, indicating an order N(exp 1.43) scaling on a 8 Gb, 1067 MHz RAM MacOSX computer with a 3.06 GHz Intel Core 2 Duo processor. With this metric, the same simulation for a system of N=1000 grains would take 5.4 hours, and 146 hours (i.e., 6 days) for a system with N=10,000 grains. Therefore, efficient ways to simulate this complex system, where not only the time scales of natural system dynamics, but also the sampling times of the Guidance, Navigation, and Control are included, remain to be explored. Additional details on the cloud modeling, dynamics, and control will be described in the paper.

simulation↗
NASA NTRS1975

Analyses of the solid earth and ocean tidal perturbations on the orbits of the GEOS-1 and GEOS-2 satellites

The luni-solar tidal perturbations in the inclination of the GEOS-I and GEOS-II satellite orbits were analyzed for the solid Earth and ocean tide conditions. Precision reduced camera and TRANET Doppler observations spanning periods of over 600 days for each satellite were used to derive mean orbital elements. Perturbations due to the earth's gravity field, solar radiation pressure, and atmospheric drag were modelled, and the resulting inclination residuals were analyzed for tidal effects. The amplitudes of the observed total tidal effects were about 1.2 arc seconds (36 meters) in the inclination of GEOS-I and 4.5 arc seconds (135 meters) for GEOS-II. The solid earth tides were then modelled using earth tide measurements, earth rotation observations, and seismic data. The resulting inclination residuals were analyzed for ocean tide parameters. The derived parameters consist of one second degree coefficient and an accompanying phase angle in a spherical harmonic expansion of the ocean tidal potential for each tidal constituent. The results are presented.

Felsentreger, T. L.↗
NASA NTRS1976

Analyses of the solid earth and ocean tidal perturbations on the orbits of the Geos 1 and Geos 2 satellites

Perturbations in the inclination of the Geos 1 and Geos 2 satellite orbits have been analyzed for the solid earth and ocean tide contributions. Precision reduced camera and Tranet Doppler observations spanning periods of over 600 days for each satellite were used to derive mean orbital elements. Perturbations due to the earth's gravity field, solar radiation pressure, and atmospheric drag were modeled, and the resulting inclination residuals were analyzed for tidal effects. The amplitudes of the observed total tidal effects were about 1.2 arc sec (36 m) in the inclination of Geos 1 and 4.5 arc sec (135 m) for Geos 2. The solid earth tides were then modeled by using the Love number 0.30. The resulting inclination residuals were then analyzed for ocean tide spherical harmonic parameters.

Felsentreger, T. L.↗
NASA NTRS1990

Selecting a model of the neutral atmosphere

The characteristics and applicability of some of the more frequently used atmospheric models covering the thermosphere are discussed from the point of view of selecting the most appropriate model for an engineering or scientific problem. Models based on satellite atmospheric drag are the earliest examples of global models and are still widely used for engineering studies. Later models based on satellite instrumentation and ground based measurements were originally aimed at scientific studies of the atmosphere, but their absolute accuracies for total densities are now similar to those of drag based models while providing better thermospheric temperature, composition, and winds. Theoretical models are now approaching the accuracy of climatological empirical models and may surpass them in the near future. Each new model generation, however, is more complicated and costly to run on a computer.

Hedin, A. E.↗
NASA NTRS1994

Evaluation of semiempirical atmospheric density models for orbit determination applications

This paper presents the results of an investigation of the orbit determination performance of the Jacchia-Roberts (JR), mass spectrometer incoherent scatter 1986 (MSIS-86), and drag temperature model (DTM) atmospheric density models. Evaluation of the models was performed to assess the modeling of the total atmospheric density. This study was made generic by using six spacecraft and selecting time periods of study representative of all portions of the 11-year cycle. Performance of the models was measured for multiple spacecraft, representing a selection of orbit geometries from near-equatorial to polar inclinations and altitudes from 400 kilometers to 900 kilometers. The orbit geometries represent typical low earth-orbiting spacecraft supported by the Goddard Space Flight Center (GSFC) Flight Dynamics Division (FDD). The best available modeling and orbit determination techniques using the Goddard Trajectory Determination System (GTDS) were employed to minimize the effects of modeling errors. The latest geopotential model available during the analysis, the Goddard earth model-T3 (GEM-T3), was employed to minimize geopotential model error effects on the drag estimation. Improved-accuracy techniques identified for TOPEX/Poseidon orbit determination analysis were used to improve the Tracking and Data Relay Satellite System (TDRSS)-based orbit determination used for most of the spacecraft chosen for this analysis. This paper shows that during periods of relatively quiet solar flux and geomagnetic activity near the solar minimum, the choice of atmospheric density model used for orbit determination is relatively inconsequential. During typical solar flux conditions near the solar maximum, the differences between the JR, DTM, and MSIS-86 models begin to become apparent. Time periods of extreme solar activity, those in which the daily and 81-day mean solar flux are high and change rapidly, result in significant differences between the models. During periods of high geomagnetic activity, the standard JR model was outperformed by DTM. Modification of the JR model to use a geomagnetic heating delay of 3 hours, as used in DTM, instead of the 6.7-hour delay produced results comparable to or better than the DTM performance, reducing definitive orbit solution ephermeris overlap differences by 30 to 50 percent. The reduction in the overlap differences would be useful for mitigating the impact of geomagnetic storms on orbit prediction.

Cox, C. M.↗
NASA NTRS1977

Prediction of Skylab attitude motion for space shuttle revisit

Computer simulations were employed to generate results, based on a fairly complicated analytical model. Environmental effects considered include atmospheric drag and gravity gradients. Mathematical models were based on Euler's moment equations and transformations from the body frame to inertial frame. A range of altitudes was considered, from 278 kilometers to 417 kilometers. Skylab is predicted to be in this orbital range during the 1979-1980 period. Results indicated that there will be a cyclic attitude motion due to the combined effect of gravity gradient and atmosphere drag. This motion can be characterized as being a slow tumble.

Alexander, S. G.↗
NASA NTRS1980

Venus upper atmosphere structure

Atmospheric densities of Venus were measured from the orbital decay of the Pioneer Venus from Dec. 9, 1978 to Aug. 7, 1979 near the 16 deg latitude between 140 and 190 km during the entire day. Comparative atmospheric densities on earth at 150 km are higher by a factor of 3.5 with only a 1% diurnal variation; an atmospheric composition, temperature, and density model based on the orbiter atmospheric drag (OAD) vertical structure is presented. The model shows that atomic oxygen is the major component in the Venus atmosphere above 145 km at night and above 160 km during the day with mixing ratios over 0.1 near 140 km; drag measurements indicate O concentrations from 1 x 10 to the 9th/cu cm in daytime to 3 x 10 to the 7th/cu cm at night. It is concluded that the neutral upper atmosphere of Venus is surprisingly insensitive to solar extreme UV variations and changes in the solar wind.

Keating, G. M.↗
NASA NTRS2018

Preliminary Saturn Atmospheric Density Results From Cassini's Final Plunge

The Cassini spacecraft made its final descent into the planet Saturn on September 15, 2017, capping a twenty year mission full of scientific discoveries. The high gain antenna was held on Earth-point until torques from atmospheric drag caused the spacecraft to lose line-of-sight lock with Earth. The Doppler data collected during the final plunge contains information about the spacecraft’s acceleration due to atmospheric drag, and therefore, the density of Saturn’s atmosphere. In this work, we present preliminary analysis of the end of mission Doppler data and its implications regarding the density of Saturn’s upper atmosphere. Are construction of the spacecraft’s final trajectory is discussed and used to fit a model of Saturn’s atmosphere to the Doppler data taken during the final plunge. The Cassini navigation team’s experience flying the spacecraft through the final five low altitude Saturn periapses is also discussed in the context of atmospheric drag and density models.

Roth, Duane↗
NASA NTRS1993

Preliminary GPS orbit determination results for the Extreme Ultraviolet Explorer

A single-frequency Motorola Global Positioning System (GPS) receiver was launched with the Extreme Ultraviolet Explorer mission in June 1992. The receiver utilizes dual GPS antennas placed on opposite sides of the satellite to obtain full GPS coverage as it rotates during its primary scanning mission. A data set from this GPS experiment has been processed at the Jet Propulsion Laboratory with the GIPSY-OASIS 2 software package. The single-frequency, dual antenna approach and the low altitude (approximately 500 km) orbit of the satellite create special problems for the GPS orbit determination analysis. The low orbit implies that the dynamics of the spacecraft will be difficult to model, and that atmospheric drag will be an important error source. A reduced-dynamic solution technique was investigated in which ad hoc accelerations were estimated at each time step to absorb dynamic model error. In addition, a single-frequency ionospheric correction was investigated, and a cycle-slip detector was written. Orbit accuracy is currently better than 5 m. Further optimization should improve this to about 1 m.

Gold, Kenn↗