SCI Publications
2006
T. Munzner, C.R. Johnson, R. Moorhead, H. Pfister, P. Rheingans, T.S. Yoo.
“NIH-NSF Visualization Research Challenges Report Summary,” Note: NIH-NSF, pp. 20--24. March/April, 2006.
S. Nagarajan, O. Portniaguine, D. Hwang, C.R. Johnson, K. Sekihara.
“Controlled Support MEG Imaging,” In NeuroImage, Vol. 15;33, No. 3, pp. 878--885. 2006.
V. Natarajan, Y. Wang, P.-T. Bremer, V. Pascucci, B. Hamann.
“Segmenting Molecular Surfaces,” In Computer Aided Geometric Design, Special Issue on Applications of Geometric Modeling in the Life Sciences, Vol. 23, No. 6, Note: (To appear), pp. 495--509. 2006.
B. Nelson, R.M. Kirby.
“Ray-Tracing Polymorphic Multi-Domain Spectral/hp Elements for Isosurface Rendering,” In IEEE Transactions on Visualization and Computer Graphics, Vol. 12, No. 1, pp. 114--125. 2006.
O. Nemitz, M. Rumpf, T. Tasdizen, R.T. Whitaker.
“Anisotropic Curvature Motion for Structure Enhancing Smoothing of 3D MR Angiography Data,” In Journal of Mathematical Imaging and Vision, Vol. 27, No. 3, pp. 217--229. April, 2006.
J.T. Oden, J. Fish, C.R. Johnson, A. Laub, D. Srolovitz, T. Belytschko, T.J.R. Hughes, D. Keys, L. Petzold, S. Yip.
“NSF Blue Ribbon Panel Report on Simulation Based Engineering Science,” Note: NSF Report, 2006.
Purpose: To explore the emerging discipline of Simulation Simulation-Based Engineering Science, its major components, its importance to the nation, the challenges and barriers to its advancement, and to recommend to the NSF and the broader community concerned with science and engineering in the United States, steps that could be taken to advance development in this discipline.
R. Palmer, S. Barrus, Y. Yang, G. Gopalakrishnan, R.M. Kirby.
“Gauss: A Framework for Verifying Scientific Computing Software,” In Electronic Notes on Theoretical Computer Science (ENTCS), Vol. 144, No. 3, pp. 95--106. February, 2006.
S.G. Parker.
“A Component-Based Architecture for Parallel Multi-physics PDE Simulation,” In Future Generation Computer Systems (FGCS), Vol. 22, No. 1-2, Elsevier, pp. 204--216. 2006.
S.G. Parker, K. Zhang, K. Damevski, C.R. Johnson.
“Integrating Component-Based Scientific Computing Software,” In Parallel Processing for Scientific Computing, Edited by M.A. Heroux and P. Raghavan and H.D. Simon, SIAM Press, pp. 271--288. 2006.
ISBN: 0-89871-619-5
S.G. Parker, J. Guilkey, T. Harman.
“A Component-based Parallel Infrastructure for the Simulation of Fluid Structure Interaction,” In Engineering with Computers, Vol. 22, No. 3-4, Springer London, pp. 277--292. 2006.
S.G. Parker.
“Composition of Components in Multiphysics Applications,” In Proceedings of the 12th SIAM Conference on Parallel Processing for Scientific Computing, San Francisco, CA, Note: Presented at the Minisymposium on Parallel Dynamic Data Management Infrastructures for Scientific & Engineering Applications, 2006.
S.G. Parker.
“Component-Based Multi-Physics Simulations of Fires and Explosions,” In Proceedings of the 12th SIAM Conference on Parallel Processing for Scientific Computing, San Francisco, CA, Note: Presented at the Minisymposium on Parallel Dynamic Data Management Infrastructures for Scientific & Engineering Applications, 2006.
S.G. Parker.
“Why do Software Engineering Methods Fail for HPC?,” In Presented at Architectures and Algorithms for Petascale Computing, Schloss Dagstuhl, Germany, Vol. Seminar 06071, February, 2006.
S. Parker, K. Zhang, C. Damevski, C.R. Johnson.
“Integrating Component-Based Scientific Computing Software,” In Parallel Processing for Scientific Computing, Edited by M.A. Heroux and P. Raghavan and H.D. Simon, SIAM, pp. 271--288. January, 2006.
V. Pascucci.
“Topology Diagrams of Scalar Fields in Scientific Visualisation,” In Topological Data Structures for Surfaces, Note: UCRL-BOOK-200013, Edited by Sanjay Rana and Jo Wood, Wiley-Blackwell, pp. 121--129. May, 2006.
DOI: 10.1002/0470020288.ch8
R.P. Pawlowski, J.N. Shadid, J.P. Simonis, H.F. Walker.
“Globalization Techniques for Newton--Krylov Methods and Applications to the Fully-coupled Solution of the Navier-Stokes Equations,” In SIAM Review, Vol. 48, No. 4, pp. 700--721. 2006.
DOI: 10.1137/S0036144504443511
A Newton-Krylov method is an implementation of Newton's method in which a Krylov subspace method is used to solve approximately the linear subproblems that determine Newton steps. To enhance robustness when good initial approximate solutions are not available, these methods are usually globalized, i.e., augmented with auxiliary procedures (globalizations) that improve the likelihood of convergence from a starting point that is not near a solution. In recent years, globalized Newton-Krylov methods have been used increasingly for the fully coupled solution of large-scale problems. In this paper, we review several representative globalizations, discuss their properties, and report on a numerical study aimed at evaluating their relative merits on large-scale two- and three-dimensional problems involving the steady-state Navier–Stokes equations.
V. Pegoraro, S.G. Parker.
“Physically-Based Realistic Fire Rendering,” In Proceedings of the 2006 Eurographics Workshop on Natural Phenomena, pp. 51--59. 2006.
S. Pervez, G. Gopalakrishnan, R.M. Kirby, R. Thakur, W. Gropp.
“Formal Verification of Programs that use MPI One-Sided Communications,” In Proceedings of EuroPVM-MPI 2006, Bonn, Germany, September 17-20, 2006.
A.R. Sanderson, R.M. Kirby, C.R. Johnson, L. Yang.
“Advanced Reaction-Diffusion Models for Texture Synthesis,” In Journal of Graphics Tools, Vol. 11, No. 3, pp. 47--71. 2006.
A. Santamaria, F. Mondragon, A Molina, N.D. Marsh, E.G. Eddings, A.F. Sarofim.
“FT-IR and 1H-NMR Characterization of the Products of an Ethylene Inverse Diffusion Flame,” In Combustion and Flame, Vol. 146, No. 1-2, pp. 52--62. July, 2006.
DOI: 10.1016/j.combustflame.2006.04.008
Knowledge of the chemical structure of young soot and its precursors is very useful in the understanding of the paths leading to soot particle inception. This paper presents analyses of the chemical functional groups, based on FT-IR and 1H NMR spectroscopy of the products obtained in an ethylene inverse diffusion flame. The trends in the data indicate that the soluble fraction of the soot becomes progressively more aromatic and less aliphatic as the height above the burner increases. Results from 1H NMR spectra of the chloroform-soluble soot samples taken at different heights above the burner corroborate the infrared results based on proton chemical shifts (Ha, Hα, Hβ, and Hγ). The results indicate that the aliphatic β and γ hydrogens suffered the most drastic reduction, while the aromatic character increased considerably with height, particularly in the first half of the flame.
Keywords: Soot, FT-IR, 1H NMR, Inverse diffusion flame