Designed especially for neurobiologists, FluoRender is an interactive tool for multi-channel fluorescence microscopy data visualization and analysis.
Deep brain stimulation
BrainStimulator is a set of networks that are used in SCIRun to perform simulations of brain stimulation such as transcranial direct current stimulation (tDCS) and magnetic transcranial stimulation (TMS).
Developing software tools for science has always been a central vision of the SCI Institute.

SCI Publications

2003


 C.R. Johnson, A.R. Sanderson. “A Next Step: Visualizing Errors and Uncertainty,” In IEEE Computer Graphics and Applications, Vol. 23, No. 5, pp. 6--10. September/October, 2003.


R.M. Kirby, G.E. Karniadakis. “De-Aliasing on Non-Uniform Grids: Algorithms and Applications,” In J. Comp. Phys., Vol. 191, No. 1, pp. 267--282. October, 2003.


D. Lucor, D. Xiu, C.-H. Su, G.E. Karniadakis. “Predictability and Uncertainty in CFD,” In International Journal for Numerical Methods in Fluids, Vol. 43, No. 5, pp. 483--505. 2003.
DOI: 10.1002/fld.500

ABSTRACT

CFD has reached some degree of maturity today, but the new question is how to construct simulation error bars that reflect uncertainties of the physical problem, in addition to the usual numerical inaccuracies. We present a fast Polynomial Chaos algorithm to model the input uncertainty and its propagation in incompressible flow simulations. The stochastic input is represented spectrally by Wiener–Hermite functionals, and the governing equations are formulated by employing Galerkin projections. The resulted system is deterministic, and therefore existing solvers can be used in this new context of stochastic simulations. The algorithm is applied to a second-order oscillator and to a flow-structure interaction problems. Open issues and extensions to general random distributions are presented.

Keywords: computational fluid dynamics, polynomial chaos, Wiener–Hermite functionals, incompressible flows

2002


 R.M. Kirby, G.E. Karniadakis. “Coarse Resolution Turbulence Simulations With Spectral Vanishing Viscosity - Large-Eddy Simulations (SVV-LES),” In J. Fluids Eng., Vol. 124, No. 4, pp. 886-891. 2002.

2001


 C.E. Goodyer, R. Fairlie, M. Berzins, L.E. Scales. “Adaptive Mesh Methods for Elastohydrodynamic Lubrication,” In ECCOMAS CFD 2001: Computational Fluid Dynamics Conference Proceedings, Institute of Mathematics and its Applications, 2001.
ISBN: 0-905-091-12-4


C.R. Johnson, Y. Livnat, L. Zhukov, D. Hart, G. Kindlmann. “Computational Field Visualization,” In Mathematics Unlimited -- 2001 and Beyond, Vol. 2, Edited by B. Engquist and W. Schmid, Springer-Verlag, pp. 605--630. 2001.


M. Walkley, P.K. Jimack, M. Berzins. “Anisotropic Adaptivity for Finite Element Solutions of 3-D Convection-Dominated Problems,” In Numerical Methods for Fluid Dynamics VII, Edited by M.J. Baines, ICFD, Oxford, pp. 525--531. 2001.
ISBN: 0 9524929 2 X


M. Walkley, P.K. Jimack, M. Berzins. “Mesh Quality and Anisotropic Adaptivity for Finite Element Solutions of 3-D Convection-Dominated Problems,” In Proceedings of ECCOMAS Computational Fluid Dynamics Conference 2001, Swansea, UK, 2001.
ISBN: 0 905 091 12 4

2000


 R. Westermann, C.R. Johnson, T. Ertl. “A Level-Set Method for Flow Visualization,” In Proceeding of IEEE Visualization 2000, IEEE Computer Society, Salt Lake City pp. 147--154. 2000.

1999


 J. Nash, M. Berzins, P. Selwood. “A Structured SADT Approach to the Support of a Parallel Adaptive 3D CFD Code,” In Euro-Par'99 Parallel Processing, Springer Nature, pp. 651--658. 1999.
DOI: 10.1007/3-540-48311-x_91

1998


 N. Touheed, P. Selwood, P.K. Jimack, M. Berzins. “Parallel Dynamic Load-Balancing for the Solution of Transient CFD Problems Using Adaptive Tetrahedral Meshes,” In Parallel Computational Fluid Dynamics - Recent Developments and Advances Using Parallel Computers, Edited by D.R. Emerson and A. Ecer and J. Periaux and N. Satufoka and P. Fox, Elsevier Science, pp. 81--88. 1998.

1997


 P. Selwood, N.A. Verhoeven, J.M. Nash, M. Berzins, N.P. Weatherill, P.M. Dew, K. Morgan. “Parallel Mesh Generation and Adaptivity : Partitioning and Analysis,” In Parallel C.F.D.- Proc. of Parallel CFD 96 Conference, Capri, Italy, Edited by A.Ecer and J.Periaux and N.Satufoka and P.Schiano, Elesvier Science BV, May, 1997.
ISBN: 0-444 823271

1995


 M. Berzins, P. Gaskell, A. Sleigh, A.S. Tomlin, J. Ware. “An adaptive CFD solver for time-dependent environmental flow problems,” In Proceedings of the Institute of Computational Fluid Dynamics Conference, Edited by K.W. Morton, M.J. Baines, Oxford University Press, pp. 311-317. 1995.


D.C. Hodgson, P.K. Jimack, P. Selwood, M. Berzins. “Scalable, Parallel Generation of Partitioned Unstructured Meshes,” In Parallel C.F.D. -- Implementations and Results using Parallel Computers, Parallel CFD Conference 1995, pasadena, California, Edited by A. Ecer and J. Periaux and N. Satufoka and S. Taylor, pp. 665-672. June, 1995.
ISBN: 0-444 823220


C. Walshaw, M. Berzins. “Adaptive Time-dependent CFD on Distributed Unstructured Meshes,” In Parallel Computational Fluid Dynamics: New Trends and Advances, Elsevier Science, pp. 191--198. 1995.

1992


 M. Berzins, P.M. Dew, S. Hillen. “Exploiting Parallelism for Adaptive CFD Software,” In Parallelogram, pp. 14--16. February, 1992.