Brand, M.: Fast low-rank modifications of the thin singular value decomposition. Linear Algebra Appl. 415(1), 20–30 (2006)
MathSciNet
MATH
CrossRef
Google Scholar
Bungartz, H.-J., Griebel, M.: Sparse grids. Acta Numer. 13, 147–269 (2004)
MathSciNet
CrossRef
Google Scholar
Chen, Q.-Y., Gottlieb, D., Hesthaven, J.S.: Uncertainty analysis for the steady-state flows in a dual throat nozzle. Journal of Computational Physics 204(1), 378–398 (2005)
MathSciNet
MATH
CrossRef
Google Scholar
Gerhold, T., Friedrich, O., Evans, J., Galle, M.: Calculation of complex three-dimensional configurations employing the DLR-tau-Code. AIAA-0167 (1997)
Google Scholar
Golub, G.H., Van Loan, C.F.: Matrix computations, 3rd edn. Johns Hopkins Studies in the Mathematical Sciences. Johns Hopkins University Press, Baltimore (1996)
MATH
Google Scholar
Griebel, M.: Sparse grids and related approximation schemes for higher dimensional problems. In: Foundations of Computational Mathematics, Santander 2005. London Math. Soc. Lecture Note Ser., vol. 331, pp. 106–161. Cambridge Univ. Press, Cambridge (2006)
CrossRef
Google Scholar
Hida, T., Kuo, H.-H., Potthoff, J., Streit, L.: White noise - An infinite-dimensional calculus. Mathematics and its Applications, vol. 253. Kluwer Academic Publishers Group, Dordrecht (1993)
MATH
Google Scholar
Hosder, S., Walters, R., Perez, R.: A non-intrusive polynomial chaos method for uncertainty propagation in cfd simulations. In: 44th AIAA Aerospace Sciences Meeting and Exhibit, Reno, Nevada, (AIAA 2006-891), pp. 209–236 (January 2006)
Google Scholar
Khoromskij, B.N., Litvinenko, A.: Data sparse computation of the Karhunen-Loève expansion. In: Numerical Analysis and Applied Mathematics: International Conference on Numerical Analysis and Applied Mathematics, AIP Conf. Proc., vol. 1048(1), pp. 311–314 (2008)
Google Scholar
Khoromskij, B.N., Litvinenko, A., Matthies, H.G.: Application of hierarchical matrices for computing the Karhunen-Loève expansion. Computing 84(1-2), 49–67 (2009)
MathSciNet
MATH
CrossRef
Google Scholar
Lanczos, C.: An iteration method for the solution of the eigenvalue problem of linear differential and integral operators. J. Research Nat. Bur. Standards 45, 255–282 (1950)
MathSciNet
CrossRef
Google Scholar
Litvinenko, A., Matthies, H.G.: Sparse data representation of random fields. In: Proceedings in Applied Mathematics and Mechanics, PAMM, vol. 9, pp. 587–588. Wiley-InterScience (2009)
Google Scholar
Litvinenko, A., Matthies, H.G.: Low-rank data format for uncertainty quantification. In: Skiadas, C.H. (ed.) International Conference on Stochastic Modeling Techniques and Data Analysis Proceedings, Chania, Greece, pp. 477–484 (2010),
http://www.smtda.net/smtda2010proceedings.html
Litvinenko, A., Matthies, H.G.: Sparse data formats and efficient numerical methods for uncertainties quantification in numerical aerodynamics. In: IV European Congress on Computational Mechanics (ECCM IV): Solids, Structures and Coupled Problems in Engineering (2010),
http://www.eccm2010.org/complet/fullpaper_1036.pdf
Litvinenko, A., Matthies, H.G.: Uncertainties quantification and data compression in numerical aerodynamics. Proc. Appl. Math. Mech. 11(1), 877–878 (2011)
CrossRef
Google Scholar
Loève, M.: Probability theory I. Graduate Texts in Mathematics, 4th edn., vol. 45, 46. Springer, New York (1977)
CrossRef
Google Scholar
Mathelin, L., Hussaini, M.Y., Zang, T.A.: Stochastic approaches to uncertainty quantification in CFD simulations. Numer. Algorithms 38(1-3), 209–236 (2005)
MathSciNet
MATH
CrossRef
Google Scholar
Matthies, H.G.: Uncertainty quantification with stochastic finite elements. Part 1. Fundamentals. In: Encyclopedia of Computational Mechanics. John Wiley and Sons, Ltd. (2007)
Google Scholar
Najm, H.N.: Uncertainty quantification and polynomial chaos techniques in computational fluid dynamics. In: Annual Review of Fluid Mechanics. Annu. Rev. Fluid Mech., vol. 41, pp. 35–52. Annual Reviews, Palo Alto (2009)
Google Scholar
Pajonk, O., Rosić, B.V., Litvinenko, A., Matthies, H.G.: A deterministic filter for non-gaussian bayesian estimation-applications to dynamical system estimation with noisy measurements. Physica D: Nonlinear Phenomena 241(7), 775–788 (2012)
MATH
CrossRef
Google Scholar
Rosic, B.V., Litvinenko, A., Pajonk, O., Matthies, H.G.: Sampling-free linear bayesian update of polynomial chaos representations. J. Comput. Physics 231(17), 5761–5787 (2012)
MathSciNet
CrossRef
Google Scholar
Saad, Y.: Numerical methods for large eigenvalue problems. Algorithms and Architectures for Advanced Scientific Computing. Manchester University Press, Manchester (1992)
Google Scholar
Simon, F., Guillen, P., Sagaut, P., Lucor, D.: A gpc-based approach to uncertain transonic aerodynamics. Computer Methods in Applied Mechanics and Engineering 199(17-20), 1091–1099 (2010)
MathSciNet
MATH
CrossRef
Google Scholar
Wan, X., Karniadakis, G.E.: Long-term behavior of polynomial chaos in stochastic flow simulations. Computer Methods in Applied Mechanics and Engineering 195(41-43), 5582–5596 (2006); John H. Argyris Memorial Issue. Part II
MathSciNet
MATH
CrossRef
Google Scholar
Wiener, N.: The homogeneous chaos. American Journal of Mathematics 60, 897–936 (1938)
MathSciNet
CrossRef
Google Scholar
Witteveen, J.A.S., Loeven, A., Bijl, H.: An adaptive stochastic finite elements approach based on newton-cotes quadrature in simplex elements. Computers & Fluids 38(6), 1270–1288 (2009)
MathSciNet
MATH
CrossRef
Google Scholar
Witteveen, J.A.S., Doostan, A., Pecnik, R., Iaccarino, G.: Uncertainty quantification of the transonic flow around the rae2822 airfoil. Annual Research Briefs, Center for Turbulence Research, pp. 93–104. Stanford University (2009)
Google Scholar