NASA Scientific and Technical Aerospace Reports

the movement, without the effects of aging of the culture, swimming behavior was analyzed in aliquots from a series of
dilutions obtained from a stock culture. Results showed that at low concentrations cells swim randomly. As the concentration
increases, upswimming patterns overtake random swimming. Gradually, up and down movement patterns prevail,
representative of bioconvection. This oriented swimming of P. carterae occurs in a wide range of concentrations, adding to the
list of flexible requirements, in this case, cell concentration, to be used for spaceflight studies addressing cell motility and
bioconvection in a unicellular model of biologically directed mineralization.
Author
Calcification; Low Concentrations; Polarity; Dilution; Algae
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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.
20040068169 NASA Ames Research Center, Moffett Field, CA, USA
Three-Dimensional High-Order Spectral Volume Method for Solving Maxwell’s Equations on Unstructured Grids
Liu, Yen; Vinokur, Marcel; Wang, Z. J.; January 15, 2004; 1 pp.; In English; 2004 International Conference on Spectral and
High Order Methods (ICOSAHOM), 21-25 Jun. 2004, Providence, RI, USA; No Copyright; Avail: CASI; A01, Hardcopy
A three-dimensional, high-order, conservative, and efficient discontinuous spectral volume (SV) method for the solutions
of Maxwell’s equations on unstructured grids is presented. The concept of discontinuous 2nd high-order loca1 representations
to achieve conservation and high accuracy is utilized in a manner similar to the Discontinuous Galerkin (DG) method, but
instead of using a Galerkin finite-element formulation, the SV method is based on a finite-volume approach to attain a simpler
formulation. Conventional unstructured finite-volume methods require data reconstruction based on the least-squares
formulation using neighboring cell data. Since each unknown employs a different stencil, one must repeat the least-squares
inversion for every cell at each time step, or to store the inversion coefficients. In a high-order, three-dimensional computation,
the former would involve impractically large CPU time, while for the latter the memory requirement becomes prohibitive. In
the SV method, one starts with a relatively coarse grid of triangles or tetrahedra, called spectral volumes (SVs), and partition
each SV into a number of structured subcells, called control volumes (CVs), that support a polynomial expansion of a desired
degree of precision. The unknowns are cell averages over CVs. If all the SVs are partitioned in a geometrically similar manner,
the reconstruction becomes universal as a weighted sum of unknowns, and only a few universal coefficients need to be stored
for the surface integrals over CV faces. Since the solution is discontinuous across the SV boundaries, a Riemann solver is thus
necessary to maintain conservation. In the paper, multi-parameter and symmetric SV partitions, up to quartic for triangle and
cubic for tetrahedron, are first presented. The corresponding weight coefficients for CV face integrals in terms of CV cell
averages for each partition are analytically determined. These discretization formulas are then applied to the integral form of
the Maxwell equations. All numerical procedures for outer boundary, material interface, zonal interface, and interior SV face
are unified with a single characteristic formulation. The load balancing in a massive parallel computing environment is
therefore easier to achieve. A parameter is introduced in the Riemann solver to control the strength of the smoothing term.
Important aspects of the data structure and its effects to communication and the optimum use of cache memory are discussed.
Results will be presented for plane TE and TM waves incident on a perfectly conducting cylinder for up to fifth order of
accuracy, and a plane wave incident on a perfectly conducting sphere for up to fourth order of accuracy. Comparisons are made
with exact solutions for these cases.
Author
Maxwell Equation; Unstructured Grids (Mathematics); Three Dimensional Models; Conservation Equations
20040068179 NASA Ames Research Center, Moffett Field, CA, USA
Unifying Temporal and Structural Credit Assignment Problems
Agogino, Adrian K.; Tumer, Kagan; 2004; 8 pp.; In English; Autonomous Agents and Multi-Agent Systems Conference,
19-23 Jul. 2004, New York, NY, USA; No Copyright; Avail: CASI; A02, Hardcopy
Single-agent reinforcement learners in time-extended domains and multi-agent systems share a common dilemma known
as the credit assignment problem. Multi-agent systems have the structural credit assignment problem of determining the
contributions of a particular agent to a common task. Instead, time-extended single-agent systems have the temporal credit
assignment problem of determining the contribution of a particular action to the quality of the full sequence of actions.
Traditionally these two problems are considered different and are handled in separate ways. In this article we show how these
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