SM43B-3094 L2 Charged Particle Environment Model of the Earth’s Distant Magnetotail
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The measured values are compared to values derived from a proton environment model. Spectral data are compared, the omni-directional fluxes are found, a range of assumed pitch angle distributions are established, and the values which would be seen by an idealized proton spectrometer immersed in the model environment are computed. The measured values and calculated values are summed over time, then ratiod to provide spectral correction factors. The data are tabulated according to location, pitch angle, energy, assumed pitch angle distribution, and orientation in the earth-fixed coordinate system. With the aid of this data, detailed corrections to the proton model environment are derived. Best-fit, energy-dependent pitch angle distributions are also obtained. Some information is derived concerning the east-west asymmetry.
Environmental criteria for NASA space vehicle design program, discussing monographs and environment models
Modeling the human as a controller of slowly responding systems with preview is considered. Along with control tasks, discrete noncontrol tasks occur at irregular intervals. In multitask situations such as these, it has been observed that humans tend to apply piecewise constant controls. It is believed that the magnitude of controls and the durations for which they remain constant are dependent directly on the system bandwidth, preview distance, complexity of the trajectory to be followed, and nature of the noncontrol tasks. A simple heuristic model of human control behavior in this situation is presented. The results of a simulation study, whose purpose was determination of the sensitivity of the model to its parameters, are discussed.
A baseline gaseous and particulate environment of the Shuttle bay was developed based on the various measurements which were made during the first four flights of the Shuttle. The environment is described by the time dependent pressure, density, scattered molecular fluxes, the column densities and including the transient effects of water dumps, engine firings and opening and closing of the bay doors. The particulate conditions in the ambient and on surfaces were predicted as a function of the mission time based on the available data. This basic Shuttle environment when combined with the outgassing and the particulate contributions of the payloads, can provide a description of the environment of a payload in the Shuttle bay. As an example of this application, the environment of the Space Telescope in the bay, which may be representative of the environment of several payloads, was derived. Among the many findings obtained in the process of modeling the environment, one is that the payloads environment in the bay is not substantially different or more objectionable than the self-generated environment of a large payload or spacecraft. It is, however, more severe during ground facilities operations, the first 15 to 20 hours of the flight, during and for a short period after ater was dumped overboard, and the reaction control engines are being fired.
The Long Duration Exposure Facility (LDEF) satellite was unique in many ways. It was a large structure that was in space for an extended period of time and was stable in orientation relative to the velocity vector. There are obvious and well documented effects of contamination and space environment effects on the LDEF satellite. In order to examine the interaction of LDEF with its environment and the resulting effect on the satellite, the Integrated Spacecraft Environments Model (ISEM) was used to model the LDEF-induced neutral environment at several different times and altitudes during the mission.
There has been a renaissance of interest in space radiation environment modeling. This has been fueled by the growing need to replace long time standard AP-9 and AE-8 trapped particle models, the interplanetary exploration initiative, the modern satellite instrumentation that has led to unprecedented measurement accuracy, and the pervasive use of Commercial off the Shelf (COTS) microelectronics that require more accurate predictive capabilities. The objective of this viewgraph presentation was to provide basic understanding of the components of the space radiation environment and their variations, review traditional radiation effects application models, and present recent developments.
LEGEND (LEO-to-GEO Environment Debris model) is a three-dimensional orbital debris evolutionary model that is capable of simulating the historical and future debris populations in the near-Earth environment. The historical component in LEGEND adopts a deterministic approach to mimic the known historical populations. Launched rocket bodies, spacecraft, and mission-related debris (rings, bolts, etc.) are added to the simulated environment. Known historical breakup events are reproduced, and fragments down to 1 mm in size are created. The LEGEND future projection component adopts a Monte Carlo approach and uses an innovative pair-wise collision probability evaluation algorithm to simulate the future breakups and the growth of the debris populations. This algorithm is based on a new "random sampling in time" approach that preserves characteristics of the traditional approach and captures the rapidly changing nature of the orbital debris environment. LEGEND is a Fortran 90-based numerical simulation program. It operates in a UNIX/Linux environment.
The Space Station Freedom program has established a series of natural environment models and databases for utilization in design and operations planning activities. The suite of models and databases that have either been selected from among internationally recognized standards or developed specifically for spacecraft design applications are presented. The models have been integrated with an orbit propagator and employed to compute environmental conditions for planned operations altitudes of Space Station Freedom.
Model of near-earth meteoroid environment from satellite observation data
Spacecraft surface charging during geomagnetically disturbed times is one of the most important causes of satellite anomalies. Predicting the surface charging environment is one prevalent task of the geospace environment models. Therefore, the Geospace Environment Modeling (GEM) Focus Group "Inner Magnetosphere Crossenergy/Population Interactions" initiated a communitywide challenge study to assess the capability of several inner magnetosphere ring current models in determining surface charging environment for the Van Allen Probes orbits during the 17 March 2013 storm event. The integrated electron flux between 10 and 50 keV is used as the metrics. Various skill scores are applied to quantitatively measure the modeling performance against observations. Results indicate that no model consistently perform the best in all of the skill scores or for both satellites. We find that from these simulations the ring current model with observational flux boundary condition and Weimer electric potential driver generally reproduces the most realistic flux level around the spacecraft. A simple and weaker VollandStern electric field is not capable of effectively transporting the same plasma at the boundary toward the Earth. On the other hand, if the ring current model solves the electric field selfconsistently and obtains similar strength and pattern in the equatorial plane as the Weimer model, the boundary condition plays another crucial role in determining the electron flux level in the inner region. When the boundary flux spectra based on magnetohydrodynamics (MHD) model/empirical model deviate from the shape or magnitude of the observed distribution function, the simulation produces poor skill scores along Van Allen Probes orbits.
NASA's Debris Assessment Software (DAS) has been substantially revised and expanded. DAS is designed to assist NASA programs in performing orbital debris assessments, as described in NASA s Guidelines and Assessment Procedures for Limiting Orbital Debris. The extensive upgrade of DAS was undertaken to reflect changes in the debris mitigation guidelines, to incorporate recommendations from DAS users, and to take advantage of recent software capabilities for greater user utility. DAS 2.0 includes an updated environment model and enhanced orbital propagators and reentry-survivability models. The ORDEM96 debris environment model has been replaced by ORDEM2000 in DAS 2.0, which is also designed to accept anticipated revisions to the environment definition. Numerous upgrades have also been applied to the assessment of human casualty potential due to reentering debris. Routines derived from the Object Reentry Survival Analysis Tool, Version 6 (ORSAT 6), determine which objects are assessed to survive reentry, and the resulting risk of human casualty is calculated directly based upon the orbital inclination and a future world population database. When evaluating reentry risks, the user may enter up to 200 unique hardware components for each launched object, in up to four nested levels. This last feature allows the software to more accurately model components that are exposed below the initial breakup altitude. The new DAS 2.0 provides an updated set of tools for users to assess their mission s compliance with the NASA Safety Standard and does so with a clear and easy-to-understand interface. The new native Microsoft Windows graphical user interface (GUI) is a vast improvement over the previous DOS-based interface. In the new version, functions are more-clearly laid out, and the GUI includes the standard Windows-style Help functions. The underlying routines within the DAS code are also improved.
CERES-Wheat is a computer simulation model of the growth, development, and yield of spring and winter wheat. It was designed to be used in any location throughout the world where wheat can be grown. The model is written in Fortran 77, operates on a daily time stop, and runs on a range of computer systems from microcomputers to mainframes. Two versions of the model were developed: one, CERES-Wheat, assumes nitrogen to be nonlimiting; in the other, CERES-Wheat-N, the effects of nitrogen deficiency are simulated. The report provides the comparisons of simulations and measurements of about 350 wheat data sets collected from throughout the world.
We are using the QuakeSim environment to model interacting fault systems. One goal of QuakeSim is to prepare for the large volumes of data that spaceborne missions such as DESDynI will produce. QuakeSim has the ability to ingest distributed heterogenous data in the form of InSAR, GPS, seismicity, and fault data into various earthquake modeling applications, automating the analysis when possible. Virtual California simulates interacting faults in California. We can compare output from long time history Virtual California runs with the current state of strain and the strain history in California. In addition to spaceborne data we will begin assimilating data from UAVSAR airborne flights over the San Francisco Bay Area, the Transverse Ranges, and the Salton Trough. Results of the models are important for understanding future earthquake risk and for providing decision support following earthquakes. Improved models require this sensor web of different data sources, and a modeling environment for understanding the combined data.
A principal obstacle to fielding automated planning systems is the difficulty of modeling. Physical systems are modeled conventionally based on specification documents and the modeler's understanding of the system. Thus, the model is developed in a way that is disconnected from the system's actual behavior and is vulnerable to manual error. Another obstacle to fielding planners is testing and validation. For a space mission, generated plans must be validated often by translating them into command sequences that are run in a simulation testbed. Testing in this way is complex and onerous because of the large number of possible plans and states of the spacecraft. Though, if used as a source of domain knowledge, the simulator can ease validation. This paper poses a challenge: to ground planning models in the system physics represented by simulation. A proposed, interactive model development environment illustrates the integration of planning and simulation to meet the challenge. This integration reveals research paths for automated model construction and validation.
This slide presentation reviews the ARTEMIS (Ares Real Time Environment for Modeling, Integration, and Simulation) for Ares hardware testing. It includes information on the ARTEMIS organization, SIL architecture, and I/O layer.