NASA Scientific and Technical Aerospace Reports

of ices under tens of meters of stable crust, providing possible habitats for a wide range of microorganisms. We consider the
icediatoms, snow algae and cyanobacteria, bacteria and yeast of cryoconite communities which are encountered in liquid wafer
pools (meltwater) surrounding dark rocks in glaciers and the polar ice sheets as excellent analogs for the microbial ecosystems
that might possibly exist on some comets.
Author
Comets; Bacteria; Habitats; Exobiology
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MATHEMATICAL AND COMPUTER SCIENCES (GENERAL)
Includes general topics and overviews related to mathematics and computer science. For specific topics in these areas see categories
60 through 67.
20040111121 Sandia National Labs., Albuquerque, NM
One User’s Report on Sandia Data Objects: Evaluation of the DOL and PMO for Use in Feature Characterization
Koegler, W. S.; Kegelmeyer, W. P.; Nov. 2003; In English
Report No.(s): DE2004-820203; SAND2003-8591; No Copyright; Avail: National Technical Information Service (NTIS)
The Feature Characterization project (FCDMF) has the goal of building tools that can extract and analyze coherent
features in a terabyte dataset. We desire to extend our feature characterization library (FClib) to support a wider variety of
complex ASCI data, and to support parallel algorithms. An attractive alternative to extending the library’s internal data
structures is to replace them with an externally provided data object. This report is the summary of a quick exploration of two
candidate data objects in use at Sandia National Laboratories: the Data Object Library (DOL) and the Parallel Mesh Object
(PMO). It is our hope that this report will provide information for potential users of the data objects, as well as feedback for
the objects’ developers.
NTIS
Algorithms; Computer Programming
20040111133 Lawrence Livermore National Lab., Livermore, CA
Spatial Treatment of the Slab-Geometry Discrete Ordinates Equations Using Artificial Neural Networks
Brantley, P. S.; Mar. 2001; In English
Report No.(s): DE2003-15005484; UCRL-JC-143205; No Copyright; Avail: National Technical Information Service (NTIS)
An artificial neural network (ANN) method is developed for treating the spatial variable of the one-group slab-geometry
discrete ordinates (S(sub N)) equations in a homogeneous medium with linearly anisotropic scattering. This ANN method
takes advantage of the function approximation capability of multilayer ANNs. The discrete ordinates angular flux is
approximated by a multilayer ANN with a single input representing the spatial variable x and N outputs representing the
angular flux in each of the discrete ordinates angular directions. A global objective function is formulated which measures how
accurately the output of the ANN approximates the solution of the discrete ordinates equations and boundary conditions at
specified spatial points. Minimization of this objective function determines the appropriate values for the parameters of the
ANN. Numerical results are presented demonstrating the accuracy of the method for both fixed source and incident angular
flux problems.
NTIS
Anisotropy; Neural Nets; Approximation
20040111165 Lawrence Livermore National Lab., Livermore, CA
Verification and Validation: Goals, Methods, Levels and Metrics
Logan, R. W.; Nitta, C. K.; Apr. 29, 2003; 14 pp.; In English
Report No.(s): DE2004-15005139; UCRL-JC-153252; No Copyright; Avail: Department of Energy Information Bridge
This work briefly summarizes the current status of the V and V Program at LLNL regarding goals, methods, timelines,
and issues for Verification and Validation (V and V) with Uncertainty Quantification (UQ). The goals are to evaluate various
V and V methods, to apply them to computational simulation analyses, and integrate them into methods for Quantitative
Certification techniques for the nuclear stockpile. Methods include qualitative and quantitative V and V processes with
numerical values for both (qualitative) V and V Level, and (quantitative) validation statements with confidence-bounded
uncertainty bands. They describe the critical nature of high quality analyses with quantified V and V, and the essential role
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