Variance reduction through robust design of boundary conditions for stochastic hyperbolic systems of equations
2014 (English)Report (Other academic)
We consider a hyperbolic system in one space dimension with uncertainty in the boundary and initial data. Our aim is to show that di erent 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 an application, we study the effect of this technique on a subsonic outow boundary for the Euler equations.
Place, publisher, year, edition, pages
Linköping University Electronic Press, 2014. , 38 p.
LiTH-MAT-R, ISSN 0348-2960 ; 2014:03
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-104433ISRN: LiTH-MAT-R--2014/03--SEOAI: oai:DiVA.org:liu-104433DiVA: diva2:697009