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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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The ADC model is a charge-collection model derived for simple p-n junction silicon diodes having a single reverse-biased p-n junction at one end and an ideal substrate contact at the other end. The present paper extends the model to include multiple junctions, and the goal is to estimate how collected charge is shared by the different junctions.
A three-dimensional, time dependent current collection model of a satellite has been developed for the TSS-1 system. The system has been simulated particularly for the Research of Plasma Electrodynamics (ROPE) experiment. The Maxwellian distributed particles with the geomagnetic field effects are applied in this numerical simulation. The preliminary results indicate that a ring current is observed surrounding the satellite in the equatorial plane. This ring current is found between the plasma sheath and the satellite surface and is oscillating with a time scale of approximately 1 microsec. This is equivalent to the electron plasma frequency. An hour glass shape of electron distribution was observed when the viewing direction is perpendicular to the equatorial plane. This result is consistent with previous findings from Linson (1969) and Antoniades et al. (1990). Electrons that are absorbed by the satellite are limited from the background ionosphere as indicated by Parker and Murphy (1967).
Results are reported from numerical simulations of current collection by a tethered satellite moving in the earth magnetic field. The focus is on the instruments of the Research on Orbital Plasma Electrodynamics (ROPE) experiment planned for the TSS-1 mission (scheduled launch 1991). The derivation of the governing equations is outlined, and the results of simulations with and without the geomagnetic field are presented in graphs. It is predicted that beam-beam interaction will occur when no magnetic effect is present, especially when the instrument bias is lower than the local potential; with the magnetic effect, there should be complex multiple-stream interactions, magnetic-field shielding covering 30 percent or more of the satellite surface when the B field is greater than 0.35 G, and nearly complete collection of the electrons by the instrument arm.
A detector array charge collection model has been developed for use as an engineering tool to aid in the design of optical sensor missions for operation in the space radiation environment. This model is an enhancement of the prototype array charge collection model that was developed for the Next Generation Space Telescope (NGST) program. The primary enhancements were accounting for drift-assisted diffusion by Monte Carlo modeling techniques and implementing the modeling approaches in a windows-based code. The modeling is concerned with integrated charge collection within discrete pixels in the focal plane array (FPA), with high fidelity spatial resolution. It is applicable to all detector geometries including monolithc charge coupled devices (CCDs), Active Pixel Sensors (APS) and hybrid FPA geometries based on a detector array bump-bonded to a readout integrated circuit (ROIC).
The importance of collecting high quality ground truth before a SAR mission over a forested area is two fold. First, the ground truth is used in the analysis and interpretation of the measured backscattering properties; second, it helps to justify the use of a scattering model to fit the measurements. Unfortunately, ground truth is often collected based on visual assessment of what is perceived to be important without regard to the mission itself. Sites are selected based on brief surveys of large areas, and the ground truth is collected by a process of selecting and grouping different scatterers. After the fact, it may turn out that some of the relevant parameters are missing. A three-layer canopy model based on the radiative transfer equations is used to determine, before hand, the relevant parameters to be collected. Detailed analysis of the contribution to scattering and attenuation of various forest components is carried out. The goal is to identify the forest parameters which most influence the backscattering as a function of frequency (P-, L-, and C-bands) and incident angle. The influence on backscattering and attenuation of branch diameters, lengths, angular distribution, and permittivity; trunk diameters, lengths, and permittivity; and needle sizes, their angular distribution, and permittivity are studied in order to maximize the efficiency of the ground truth collection efforts. Preliminary results indicate that while a scatterer may not contribute to the total backscattering, its contribution to attenuation may be significant depending on the frequency.
Collection of computer programs analyzes arrays of optical cube corners used in laser ranging. Programs compute impulse-response and interference effects of reflected pulses from optical cube corners and calculates interference-effects histogram and far-field diffraction patterns.
A dynamical system which mimics collective purposeful activities of a set of units of intelligence is introduced and discussed. A global control of the unit activities is replaced by the probabilistic correlations between them. These correlations are learned during a long term period of performing collective tasks, and are stored in the synaptic interconnections. The model is represented by a system of ordinary differential equations with terminal attractors and repellers, and does not contain any man-made digital devices.
While the Adaptive Cruise Control (ACC) system in automated vehicles (AVs) is expected to impact transportation energy significantly, existing AV energy consumption models only directly adopt those developed with Human-driven Vehicle (HV) data without even slight adaptation or calibration to accommodate unique AV energy consumption features. This study will investigate how accurately HV data-based models can predict the energy consumption of AVs. Empirical trajectory data and corresponding instantaneous energy consumption rates from both AVs and HVs were collected. We adopted two classical HV data-based models to fit these data. The calibration results indicated that these models yield around 20 30% prediction errors for AVs. To further improve the prediction accuracy, this study designed an AV-Micro model by incorporating components of multiple classic energy consumption models that better capture ACC energy consumption features, including piecewise driving behavior. With this, the AV-Micro model achieves lower than 10% prediction errors. The AV-Micro model’s high consistency across different test runs was verified with statistical significance tests, demonstrating its adaptability in different driving profiles. To confirm the discrepancies between the energy consumption features of AVs and HVs, more statistical significance tests were conducted to show that the AV-Micro model cannot be directly applied to HV data. The findings by calibrated AV-Micro models revealed that AVs consume approximately 80.5–146.4 J more energy than HVs for each meter traveled. Furthermore, the frequency analysis of energy consumption indicates that there is still some room for AVs to improve energy efficiency, particularly given their larger amplitude high-frequency fluctuations.
A model of plasma contractors is being developed, which can be used to describe electron collection in a laboratory test tank and in the space environment. To validate the model development, laboratory experiments are conducted in which the source plasma is separated from the background plasma by a double layer. Model calculations show that an increase in ionization rate with potential produces a steep rise in collected current with increasing potential.
Quantifying aerosol compositions (e.g., type, loading) from remotely sensed measurements by spaceborne, suborbital and ground-based platforms is a challenging task. In this study, the first and second-order spectral derivatives of aerosol optical depth (AOD) with respect to wavelength are explored to determine the partitions of the major components of aerosols based on the spectral dependence of their particle optical size and complex refractive index. With theoretical simulations from the Second Simulation of a Satellite Signal in the Solar Spectrum (6S) model, AOD spectral derivatives are characterized for collective models of aerosol types, such as mineral dust (DS) particles, biomass-burning (BB) aerosols and anthropogenic pollutants (AP), as well as stretching out to the mixtures among them. Based on the intrinsic values from normalized spectral derivatives, referenced as the Normalized Derivative Aerosol Index (NDAI), a unique pattern is clearly exhibited for bounding the major aerosol components; in turn, fractions of the total AOD (fAOD) for major aerosol components can be extracted. The subtlety of this NDAI method is examined by using measurements of typical aerosol cases identified carefully by the ground-based Aerosol Robotic Network (AERONET) sun–sky spectroradiometer. The results may be highly practicable for quantifying fAOD among mixed-type aerosols by means of the normalized AOD spectral derivatives.
The Landsat Collection-2 distribution introduces a new global Digital Elevation Model (DEM) for scene orthorectification. The new global DEM is a composite of the latest and most accurate freely available DEM sources and will include reprocessed Shuttle Radar Topographic Mission (SRTM) data (called NASADEM), high-resolution stereo optical data (ArcticDEM), a new National Elevation Dataset(NED) and various publicly available national datasets including the Canadian Digital Elevation Model (CDEM) and DEMs for Sweden, Norway and Finland (SNF). The new DEM will be available world-wide with few exceptions. It is anticipated that the transition from theCollection-1 DEM at 3 arcsecond to the new DEM will be seamless because processing methods to maintain a seamless transition were employed, void filling techniques were used, where persistent gaps were found, and the pixel spacing is the same between the two collections. Improvements to the vertical accuracy were realized by differencing accuracies of other elevation datasets to the new DEM. The greatest improvement occurred where ArcticDEM data were used, where an improvement of 35 meters was measured. By using theses improved vertical values in a line of sight algorithm, horizonta improvements were noted in some of the most mountainous regions over multiple 30-meter Landsat pixels. This new DEM will be used to process all of the scenes from Landsat 1-8 in Collection-2 processing and will be made available to the public by the end of 2020.
Initial results from the PIC simulation and the LEM simulation have been presented. The PIC simulation results show that more detailed study is required to refine the ISS solar array current collection model and to understand the development of the current collection in time. The initial results from the LEM demonstrate that is it possible the transients are caused by solar array interaction with the environment, but there are presently too many assumptions in the model to be certain. Continued work on the PIC simulation will provide valuable information on the development of the barrier potential, which will allow refinement the LEM simulation and a better understanding of the causes and effects of the transients.
Geographic information systems (GIS) deal with collecting, modeling, man- aging, analyzing, and integrating spatial (locational) and non-spatial (attribute) data required for geographic applications. Examples of spatial data are digital maps, administrative boundaries, road networks, and those of non-spatial data are census counts, land elevations and soil characteristics. GIS shares common areas with a number of other disciplines such as computer- aided design, computer cartography, database management, and remote sensing. None of these disciplines however, can by themselves fully meet the requirements of a GIS application. Examples of such requirements include: the ability to use locational data to produce high quality plots, perform complex operations such as network analysis, enable spatial searching and overlay operations, support spatial analysis and modeling, and provide data management functions such as efficient storage, retrieval, and modification of large datasets; independence, integrity, and security of data; and concurrent access to multiple users. It is on the data management issues that we devote our discussions in this monograph. Traditionally, database management technology have been developed for business applications. Such applications require, among other things, capturing the data requirements of high-level business functions and developing machine- level implementations; supporting multiple views of data and yet providing integration that would minimize redundancy and maintain data integrity and security; providing a high-level language for data definition and manipulation; allowing concurrent access to multiple users; and processing user transactions in an efficient manner. The demands on database management systems have been for speed, reliability, efficiency, cost effectiveness, and user-friendliness. Significant progress have been made in all of these areas over the last two decades to the point that many generalized database platforms are now available for developing data intensive applications that run in real-time. While continuous improvement is still being made at a very fast-paced and competitive rate, new application areas such as computer aided design, image processing, VLSI design, and GIS have been identified by many as the next generation of database applications. These new application areas pose serious challenges to the currently available database technology. At the core of these challenges is the nature of data that is manipulated. In traditional database applications, the database objects do not have any spatial dimension, and as such, can be thought of as point data in a multi-dimensional space. For example, each instance of an entity EMPLOYEE will have a unique value corresponding to every attribute such as employee id, employee name, employee address and so on. Thus, every Employee instance can be thought of as a point in a multi-dimensional space where each dimension is represented by an attribute. Furthermore, all operations on such data are one-dimensional. Thus, users may retrieve all entities satisfying one or more constraints. Examples of such constraints include employees with addresses in a certain area code, or salaries within a certain range. Even though constraints can be specified on multiple attributes (dimensions), the search for such data is essentially orthogonal across these dimensions.
A predictive, multiple model control strategy is developed by extension of self-organizing map (SOM) local dynamic modeling of nonlinear autonomous systems to a control framework. Multiple SOMs collectively model the global response of a nonautonomous system to a finite set of representative prototype controls. Each SOM provides a codebook representation of the dynamics corresponding to a prototype control. Different dynamic regimes are organized into topological neighborhoods where the adjacent entries in the codebook represent the global minimization of a similarity metric. The SOM is additionally employed to identify the local dynamical regime, and consequently implements a switching scheme that selects the best available model for the applied control. SOM based linear models are used to predict the response to a larger family of control sequences which are clustered on the representative prototypes. The control sequence which corresponds to the prediction that best satisfies the requirements on the system output is applied as the external driving signal.
The Dynamic Global Core Plasma Model (DGCPM) is a parameterized model for core or thermal plasma in the magnetosphere. The model accounts for dayside ionospheric outflow and nightside inflow. It accounts for the global pattern of convection and corotation. The model is capable of being coupled to ring current and superthermal electron models for the purpose of providing thermal plasma spatial distributions and for the purpose of accepting the dynamic influences of these plasma populations back upon the thermal plasma. The DGCPM is designed to operate alone or to operate as part of a larger integrated package. The convection electric field and magnetic field used within the DGCPM can be shared with models of other plasma populations, in addition to the exchange of parameters important to the collective modeling of whole plasma systems in the inner magnetosphere. This talk will present the features of the DGCPM model code and the various forms of information that can be exchanged with other cooperating codes.
Current collection in plasmas by a static bare tether is studied. Considering the geometry effect, we modify the static Parker-Murphy current collection model to accommodate a cylindrical probe. It is shown that a long cylindrical configuration (length is much greater than diameter) can collect more current than the spherical configuration whose effective surface area and surface potential are identical. However, when the cylinder is not long (length and diameter are same order), it collects less current than the effective sphere. This indicates that Myers et al. might over estimate the PM current when they neglected the geometry effect. Compared to the orbit limit model and the chamber experiment, our predictions are in the range of the adiabatic limits and the upper-bound currents obtained by Rubinstein and Laframboise. It shows that the present results are in agreement with the bare tether chamber test experimental data given by Sorenson, Stone, and Wright. In addition we have applied this model to study the IR drop and the orientation effects which are important in the space condition.
A predictive, multiple model control strategy is developed based on an ensemble of local linear models of the nonlinear system dynamics for a transonic wind tunnel. The local linear models are estimated directly from the weights of a self-organizing map (SOM). Multiple self-organizing maps collectively model the global response of the wind tunnel to a finite set of representative prototype controls. These prototype controls partition the control space and incorporate experiential knowledge gained from decades of operation. Each SOM models the combination of the tunnel with one of the representative controls, over the entire range of operation. The SOM based linear models are used to predict the tunnel response to a larger family of control sequences which are clustered on the representative prototypes. The control sequence which corresponds to the prediction that best satisfies the requirements on the system output is applied as the external driving signal.
We present an overview of the data and models collected for the Whole Heliosphere Interval, an international campaign to study the three-dimensional solar heliospheric planetary connected system near solar minimum. The data and models correspond to solar Carrington Rotation 2068 (20 March 16 April 2008) extending from below the solar photosphere, through interplanetary space, and down to Earth's mesosphere. Nearly 200 people participated in aspects of WHI studies, analyzing and interpreting data from nearly 100 instruments and models in order to elucidate the physics of fundamental heliophysical processes. The solar and inner heliospheric data showed structure consistent with the declining phase of the solar cycle. A closely spaced cluster of low-latitude active regions was responsible for an increased level of magnetic activity, while a highly warped current sheet dominated heliospheric structure. The geospace data revealed an unusually high level of activity, driven primarily by the periodic impingement of high-speed streams. The WHI studies traced the solar activity and structure into the heliosphere and geospace, and provided new insight into the nature of the interconnected heliophysical system near solar minimum.