Publications

Daniel Köster, Oliver Kriessl, and Kunibert G. Siebert. Design of Finite Element Tools for Coupled Surface and Volume Meshes. Numerical Mathematics: Theory, Methods and Applications, (1)3:245-274, 2008. [PUMA: design software scientific Adaptive finite element software, methods, vorlaeufig] URL

Alfred Schmidt, and Kunibert G. Siebert. ALBERT --- Software for Scientific Computations and Applications. Acta Mathematica Universitatis Comenianae, New Ser., (70)1:105-122, 2001. [PUMA: design software scientific Adaptive finite element software, methods, vorlaeufig] URL

Tobias Köppl, Gabriele Santin, Bernard Haasdonk, and Rainer Helmig. Numerical modelling of a peripheral arterial stenosis using dimensionally reduced models and kernel methods. International Journal for Numerical Methods in Biomedical Engineering, (0)ja:e3095, 2018. [PUMA: models, peripheral kernel simulations reduced mixed-dimension methods, blood simulations, stenosis, real-time dimensionally surrogate vorlaeufig flow] URL

F. D. Gaspoz, P. Morin, and A. Veeser. A posteriori error estimates with point sources in fractional sobolev spaces. Numerical Methods for Partial Differential Equations, (33)4:1018--1042, 2017. [PUMA: a Dirac estimators, error finite fractional methods, posteriori adaptivity, element spaces mass, Sobolev vorlaeufig] URL

D. Wirtz, and B. Haasdonk. Efficient a-posteriori error estimation for nonlinear kernel-based reduced systems. Systems and Control Letters, (61)1:203 - 211, 2012. [PUMA: subspace error dynamical kernel a-posteriori methods, systems, nonlinear offline/online decomposition, projection estimates, model vorlaeufig reduction,] URL

Daniel Wirtz, and Bernard Haasdonk. A-posteriori error estimation for parameterized kernel-based systems. Proc. MATHMOD 2012 - 7th Vienna International Conference on Mathematical Modelling, 2012. [PUMA: subspace error dynamical kernel a-posteriori methods, systems, nonlinear offline/online decomposition, parameterized projection estimates, model vorlaeufig reduction,] URL

F. D. Gaspoz, C. Kreuzer, K. Siebert, and D. Ziegler. A convergent time-space adaptive $dG(s)$ finite element method for parabolic problems motivated by equal error distribution. Submitted, 2017. [PUMA: a equation estimators, convergence, error finite methods, posteriori adaptivity, element vorlaeufig heat] URL