NASA Scientific and Technical Aerospace Reports
NASA Scientific and Technical Aerospace Reports
NASA Scientific and Technical Aerospace Reports
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ecursive least squares estimation. Flight test results from the SPHERES implementation, as flown aboard the <strong>NASA</strong> KC-1<br />
35A 0-g simulator aircraft in November 2003 are presented.<br />
Author<br />
Fault Detection; Thrustors; Isolation; System Identification<br />
20040046899 Smithsonian Astrophysical Observatory, Cambridge, MA, USA<br />
High-Resolution Spectroscopic Database for the <strong>NASA</strong> Earth Observing System Program<br />
Rothman, Laurence S.; March 2004; 24 pp.; In English<br />
Contract(s)/Grant(s): NAG5-8420; No Copyright; Avail: CASI; A03, Hardcopy<br />
The purpose of this project is to develop <strong>and</strong> enhance the HITRAN molecular spectroscopic database <strong>and</strong> associated -<br />
software to support the observational programs of the Earth observing System (EOS). In particular, the focus is on the EOS<br />
projects: the Atmospheric Infrared Sounder (AIRS), the High-Resolution Dynamics Limb Sounder (HIRDLS), Measurements<br />
of Pollution in the Troposphere (MOPITT), the Tropospheric Emission Spectrometer (TES), <strong>and</strong> the Stratospheric Aerosol <strong>and</strong><br />
Gas Experiment (SAGE III). The HITRAN program is also involved in the Ozone Monitoring Experiment (OMI). The data<br />
requirements of these programs in terms of spectroscopy are varied with respect to constituents being observed, required<br />
remote-sensing parameters, <strong>and</strong> spectral coverage. A general requisite is for additional spectral parameters <strong>and</strong> improvements<br />
to existing molecular b<strong>and</strong>s sufficient for the simulation of the observations leading to retrieval of the atmospheric state. In<br />
addition cross-section data for heavier molecular species must be exp<strong>and</strong>ed <strong>and</strong> made amenable to modeling in remote<br />
sensing. The effort in the project also includes developing software <strong>and</strong> distribution to make access, manipulation, <strong>and</strong> use<br />
HITRAN functional to the EOS program.<br />
Author<br />
Molecular Gases; Spectroscopy; Data Bases; Computer Programs; Spectrum Analysis; Ozone; Atmospheric Chemistry<br />
20040050302 Institute for Human <strong>and</strong> Machine Cognition, Pensacola, FL, USA<br />
CmapTools: A Software Environment for Knowledge Modeling <strong>and</strong> Sharing<br />
Canas, Alberto J.; January 2004; 10 pp.; In English<br />
Contract(s)/Grant(s): NCC2-1297; No Copyright; Avail: CASI; A02, Hardcopy<br />
In an ongoing collaborative effort between a group of <strong>NASA</strong> Ames scientists <strong>and</strong> researchers at the Institute for Human<br />
<strong>and</strong> Machine Cognition (IHMC) of the University of West Florida, a new version of CmapTools has been developed that<br />
enable scientists to construct knowledge models of their domain of expertise, share them with other scientists, make them<br />
available to anybody on the Internet with access to a Web browser, <strong>and</strong> peer-review other scientists models. These software<br />
tools have been successfully used at <strong>NASA</strong> to build a large-scale multimedia on Mars <strong>and</strong> in knowledge model on Habitability<br />
Assessment. The new version of the software places emphasis on greater usability for experts constructing their own<br />
knowledge models, <strong>and</strong> support for the creation of large knowledge models with large number of supporting resources in the<br />
forms of images, videos, web pages, <strong>and</strong> other media. Additionally, the software currently allows scientists to cooperate with<br />
each other in the construction, sharing <strong>and</strong> criticizing of knowledge models. Scientists collaborating from remote distances,<br />
for example researchers at the Astrobiology Institute, can concurrently manipulate the knowledge models they are viewing<br />
without having to do this at a special videoconferencing facility.<br />
Author<br />
Computer Programs; Video Communication; Exobiology; Cognition<br />
20040050333 Massachusetts Inst. of Tech., Cambridge, MA, USA<br />
Reliability <strong>and</strong> Productivity Modeling for the Optimization of Separated Spacecraft Interferometers<br />
Kenny, Sean, <strong>Technical</strong> Monitor; Wertz, Julie; May 2002; 211 pp.; In English<br />
Contract(s)/Grant(s): NAG1-01025<br />
Report No.(s): SSL-9-02; Copyright; Avail: CASI; A10, Hardcopy<br />
As technological systems grow in capability, they also grow in complexity. Due to this complexity, it is no longer possible<br />
for a designer to use engineering judgement to identify the components that have the largest impact on system life cycle<br />
metrics, such as reliability, productivity, cost, <strong>and</strong> cost effectiveness. One way of identifying these key components is to build<br />
quantitative models <strong>and</strong> analysis tools that can be used to aid the designer in making high level architecture decisions. Once<br />
these key components have been identified, two main approaches to improving a system using these components exist: add<br />
redundancy or improve the reliability of the component. In reality, the most effective approach to almost any system will be<br />
some combination of these two approaches, in varying orders of magnitude for each component. Therefore, this research tries<br />
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