Variance reduction through robust design of boundary conditions for stochastic hyperbolic systems of equations
2015 (English)In: Journal of Computational Physics, ISSN 0021-9991, E-ISSN 1090-2716, Vol. 282, 1-22 p.Article in journal (Refereed) Published
We consider a hyperbolic system with uncertainty in the boundary and initial data. Our aim is to show that different boundary conditions gives different convergence rates of the variance of the solution. This means that we can with the same knowledge of data get a more or less accurate description of the uncertainty in the solution. A variety of boundary conditions are compared and both analytical and numerical estimates of the variance of the solution is presented. As applications, we study the effect of this technique on Maxwell's equations as well as on a subsonic outflow boundary for the Euler equations.
Place, publisher, year, edition, pages
Elsevier, 2015. Vol. 282, 1-22 p.
Uncertainty quantification, hyperbolic system, initial boundary value problems, well posed, stability, boundary conditions, stochastic data, variance reduction, robust design, summation-by parts
IdentifiersURN: urn:nbn:se:liu:diva-111893DOI: 10.1016/j.jcp.2014.10.061ISI: 000346430700001OAI: oai:DiVA.org:liu-111893DiVA: diva2:761621