Articles

BOUNDARY PROCEDURES FOR THE TIME - DEPENDENT BURGERS’EQUATION UNDER UNCERTAINTY

  • Per Pettersson ,
  • Jan Nordstrom ,
  • Gianluca Iaccarino
Expand
  • 1.Mechanical Engineering and |Institute for Computational Mathematical Engineering, Stanford University, Stanford, CA94305, USA;

    2.Division of Scientific Computing, Department of Information Technology, Uppsala University, Box 337, SE-75105 Uppsala, Sweden;

    3.School of Mechanical, Industrial and Aeronautical Engineering, University of the Witvatersrand, PO WITS 2050, Johannesburg, South Africa; 4.Department of Aeronautics and Systems Integration, FOI, The Swedish Defense Research Agency, SE-164 90 Stockholm, Sweden

Received date: 2009-12-16

  Online published: 2010-03-20

Supported by

Supported by the US Department of Energy under the PSAAP Program.

Abstract

The Burgers' equation with uncertain initial and boundary conditions is approximated using a Polynomial Chaos Expansion (PCE) approach where the solution is represented as a series of stochastic, orthogonal polynomials. The resulting truncated PCE system is solved using a novel numerical discretization method based on spatial derivative operators satisfying the summation by parts property and weak boundary conditions to ensure stability. The resulting PCE solution yields an accurate quantitative description of the stochastic evolution of the system, provided that appropriate boundary conditions are available. The specification of the boundary data  is shown to influence the solution; we will 
discuss the problematic implications of the lack of precisely characterized boundary data and possible ways of imposing stable and accurate boundary conditions.

Cite this article

Per Pettersson , Jan Nordstrom , Gianluca Iaccarino . BOUNDARY PROCEDURES FOR THE TIME - DEPENDENT BURGERS’EQUATION UNDER UNCERTAINTY[J]. Acta mathematica scientia, Series B, 2010 , 30(2) : 539 -550 . DOI: 10.1016/S0252-9602(10)60061-6

References

[1]  Carpenter Mark H, Gottlieb David, Abarbanel Saul. Time-stable boundary conditions for finite-difference schemes solving hyperbolic systems: methodology and application to high-order compact schemes. J Comput Phys, 1994, 111(2): 220--236


[2]  Carpenter Mark H, Nordstr\"om Jan, Gottlieb David. A stable and conservative interface treatment of arbitrary spatial accuracy. J Comput Phys, 1999, 148(2): 341--365


[3]  Chauvi\`ere C, Hesthaven J S, Lurati L. Computational modeling of uncertainty in time-domain electromagnetics. SIAM J Sci Comput, 2006,  28(2): 751--775


[4]  Christie Mike, Demyanov Vasily, Erbas Eemet. Uncertainty quantification for porous media flows. J Comput Phys, 2006, 217(1): 143--158


[5]  Ghanem R, Doostan A, Red-Horse J. A probabilistic construction of model validation. Comput Methods Appl Mech Eng, 2008, 197: 2585--2595


[6]  Gottlieb D, Hesthaven J S. Spectral methods for hyperbolic problems. J Comput Appl Math, 2001, 128(1/2): 83--131


[7]  Gustafsson Beril, Kreiss Heinz-Otto, Oliger Joseph. Time Dependent Problems and Difference Methods. Wiley, 1995


[8]  Mattsson Ken, Sv\"ard Magnus, Nordstr\"om Jan. Stable and accurate artificial dissipation. J Sci Comput, 2004, 21(1): 57--79


[9]  Nordstr\"om Jan. Conservative finite difference formulations, variable coefficients, energy estimates and artificial dissipation. J Sci Comput, 2006, 29(3): 375--404


[10]  Nordstrom Jan, Carpenter Mark H. Boundary and interface conditions for high-order finite-difference methods applied to the Euler and Navier-Stokes equations. J Comput Phys, 1999, 148(2): 621--645


[11]  Nordstr\"om Jan, Carpenter Mark H. High-order finite difference methods, multidimensional linear problems, and curvilinear coordinates. J Comput Phys, 2001, 173(1): 149--174


[12]  Pettersson Per, Iaccarino Gianluca, Nordstrom Jan. Numerical analysis of the Burgers equation in the presence of uncertainty. J Comput Phys, 2009, 228: 8394--8412


[13]  Poroseva S, Letschert J, Hussaini M Y. Uncertainty quantification in hurricane path forecasts using evidence theory. APS Meeting Abstracts, 2005


[14]  Reagan Matthew T, Najm Habib N, Ghanem Roger G, Knio Omar M. Uncertainty quantification in reacting-flow simulations through non-intrusive spectral projection. Combustion and Flame, 2003: 545--555


[15]  Yu Y, Zhao M, Lee T, Pestieau N, Bo W, Glimm J, Grove J W. Uncertainty quantification for chaotic computational fluid dynamics. J Comput Phys, 2006, 217(1): 200--216

Outlines

/