TU Darmstadt / ULB / TUbiblio

Browse by Person

Up a level
Export as [feed] Atom [feed] RSS 1.0 [feed] RSS 2.0
Group by: No Grouping | Item Type | Date | Language
Number of items: 26.

Ullmann, Sebastian and Lang, Jens (2018):
Stochastic Galerkin reduced basis methods for parametrized linear elliptic PDEs.
In: SIAM / ASA Journal on Uncertainty Quantification, [Online-Edition: https://arxiv.org/abs/1812.08519],
[Article]

Gräßle, Carmen and Hinze, Michael and Lang, Jens and Ullmann, Sebastian (2018):
POD model order reduction with space-adapted snapshots for incompressible flows.
In: Advances in Computational Mathematics, Springer US, ISSN 1019-7168,
[Online-Edition: https://arxiv.org/abs/1810.03892],
[Article]

Ullmann, Sebastian (2018):
Model order reduction for space-adaptive simulations of unsteady incompressible flows.
In: Conference on the Numerical Solution of Differential and Differential-Algebraic Equations (NUMDIFF-15), Martin Luther University Halle-Wittenberg (Germany), 3 - 7 September 2018, [Conference or Workshop Item]

Müller, Christopher and Ullmann, Sebastian and Lang, Jens
Schäfer, Michael and Behr, Marek and Mehl, Miriam and Wohlmuth, Barbara (eds.) (2018):
A Bramble-Pasciak conjugate gradient method for discrete Stokes problems with lognormal random viscosity.
In: Recent Advances in Computational Engineering, Cham, Springer International Publishin, pp. 63-87, DOI: 10.1007/978-3-319-93891-2_5,
[Online-Edition: https://link.springer.com/chapter/10.1007/978-3-319-93891-2_...],
[Book Section]

Spannring, Christopher and Ullmann, Sebastian and Lang, Jens
Schäfer, Michael and Behr, Marek and Mehl, Miriam and Wohlmuth, Barbara (eds.) (2018):
A weighted reduced basis method for parabolic PDEs with random data.
In: Recent Advances in Computational Engineering, Cham, Springer International Publishing, pp. 145-161, DOI: 10.1007/978-3-319-93891-2_9,
[Online-Edition: https://link.springer.com/chapter/10.1007/978-3-319-93891-2_...],
[Book Section]

Ullmann, Sebastian (2018):
Stochastic Galerkin reduced basis methods for parametrized random elliptic PDEs.
In: Uncertainty quantification for complex systems: theory and methodologies, Isaac Newton Institute, Cambridge, UK, 03.01.2018 - 29.06.2018, [Online-Edition: https://www.newton.ac.uk/seminar/20180529140015002],
[Conference or Workshop Item]

Ullmann, Sebastian (2018):
Stochastic Galerkin reduced basis methods for parametrized random elliptic PDEs.
In: MoRePaS 2018, Nantes, France, 10 - 13 April 2018, [Online-Edition: https://www.scienceopen.com/document?vid=47586c39-45b8-42b6-...],
[Conference or Workshop Item]

Ullmann, Sebastian (2018):
Stochastic Galerkin reduced basis methods for parametrized random elliptic PDEs.
In: Reducing dimensions and cost for UQ in complex systems, Isaac Newton Institute for Mathematical Sciences, Cambridge, UK, 5-9 March 2018, [Online-Edition: https://www.newton.ac.uk/event/unqw03],
[Conference or Workshop Item]

Müller, Christopher and Ullmann, Sebastian and Lang, Jens (2018):
A Bramble-Pasciak conjugate gradient method for discrete Stokes equations with random viscosity.
In: SIAM/ASA Journal on Uncertainty Quantification (JUQ), [Online-Edition: https://arxiv.org/abs/1801.01838],
[Article]

Ullmann, Sebastian (2017):
CFD under uncertainty: combining model order reduction with spatial adaptivity.
In: Frontiers of Uncertainty Quantification in Engineering (FrontUQ), Munich, 6-8 September 2017, [Conference or Workshop Item]

Müller, Christopher and Ullmann, Sebastian (2017):
Conjugate gradient methods for stochastic Galerkin finite element matrices with saddle point structure.
In: FoMICS-Workshop, Lugano, Switzerland, 15.-19.12.2016, [Conference or Workshop Item]

Müller, Christopher and Ullmann, Sebastian and Lang, Jens (2017):
Conjugate gradient methods for stochastic Galerkin finite element matrices with saddle point structure.
In: Quantification of Uncertainty: Improving Efficiency and Technology (QUIET), Triest, Italy, 18.-21.07.2017, [Conference or Workshop Item]

Spannring, Christopher and Ullmann, Sebastian and Lang, Jens (2017):
Reduced Basis Method for Linear Parabolic Problems with Random Data.
In: FoMICS-Workshop, Lugano, Switzerland, 15.-19.12.2016, [Conference or Workshop Item]

Spannring, Christopher and Ullmann, Sebastian and Lang, Jens (2017):
Reduced Basis Method for Parabolic Problems with Random Data.
In: SIMAI (Societa Italiana Di Matematica Applicata E Industriale) 2016, Milano, Italy, 13.-16.09.2016, [Conference or Workshop Item]

Spannring, Christopher and Ullmann, Sebastian and Lang, Jens (2017):
Weighted Reduced Basis Method for Parabolic PDEs with Random Data.
In: Quantification of Uncertainty: Improving Efficiency and Technology (QUIET), Triest, Italy, 18.-21.07.2017, [Conference or Workshop Item]

Spannring, Christopher and Ullmann, Sebastian and Lang, Jens (2017):
A Weighted Reduced Basis Method for Parabolic PDE with Random Data.
In: Reduced Basis Summer School 2017, Goslar, Germany, 19.-22.09.2017, [Conference or Workshop Item]

Spannring, Christopher and Ullmann, Sebastian and Lang, Jens (2017):
A Weighted Reduced Basis Method for Parabolic PDE with Random Data.
In: 4th International Conference on Computational Engineering (ICCE 2017), Darmstadt, Germany, Sep 28-29, 2017, [Conference or Workshop Item]

Spannring, Christopher and Ullmann, Sebastian and Lang, Jens (2017):
A Weighted Reduced Basis Method for Parabolic PDEs with Random Data.
In: SIAM Conference on Uncertainty Quantification, Garden Grove 2018, Garden Grove, California, USA, April 16-19, [Conference or Workshop Item]

Ullmann, Sebastian and Rotkvic, Marko and Lang, Jens (2016):
POD-Galerkin reduced-order modeling with adaptive finite element snapshots.
In: Journal of Computational Physics, pp. 244-258, 325, ISSN 0021-9991,
[Online-Edition: http://dx.doi.org/10.1016/j.jcp.2016.08.018],
[Article]

Spannring, Christopher and Ullmann, Sebastian and Lang, Jens (2016):
Reduced Basis Method for Parabolic Problems with Random Data.
In: Reduced Basis Summer School 2016, Hedersleben, Germany, 04.-07.10.2016, [Conference or Workshop Item]

Ullmann, Sebastian and Lang, Jens
Garcke, J. and Pflüger, D. (eds.) (2014):
POD-Galerkin Modeling and Sparse-Grid Collocation for a Natural Convection Problem with Stochastic Boundary Conditions.
In: Sparse Grids and Applications - Munich 2012, Springer, pp. 295-315, [Online-Edition: http://link.springer.com/chapter/10.1007%2F978-3-319-04537-5...],
[Book Section]

Ullmann, Sebastian (2014):
POD-Galerkin Modeling for Incompressible Flows with Stochastic Boundary Conditions.
Munich, Verlag Dr. Hut, ISBN 9783843915687,
[Online-Edition: http://tuprints.ulb.tu-darmstadt.de/4296/],
[Book]

Ullmann, Sebastian (2014):
POD-galerkin modeling for incompressible flows with stochastic boundary conditions.
München, Dr. Hut, TU Darmstadt, ISBN 978-3-8439-1568-7,
[Online-Edition: http://www.dr.hut-verlag.de/9783843915687.html],
[Ph.D. Thesis]

Ullmann, Sebastian and Löbig, Stefan and Lang, Jens
Janicka, J. and Sadiki, Amsini and Schäfer, Michael and Heeger, Christof (eds.) (2013):
Adaptive Large Eddy Simulation and Reduced-Order Modeling.
In: Flow and Combustion in Advanced Gas Turbine Combustors, Dordrecht, Springer Netherlands, pp. 349-378, DOI: 10.1007/978-94-007-5320-4₁₂,
[Online-Edition: https://doi.org/10.1007/978-94-007-5320-4_12],
[Book Section]

Ullmann, Sebastian and Lang, Jens (2012):
POD and CVT Galerkin reduced-order modeling of the flow around a cylinder.
In: Proceedings in Applied Mathematics and Mechanics (PAMM), John Wiley and Sons, pp. 697-698, 12, (1), ISSN 1617-7061,
[Online-Edition: http://onlinelibrary.wiley.com/doi/10.1002/pamm.201210337/pd...],
[Article]

Ullmann, Sebastian and Lang, Jens
A POD-Galerkin Reduced Model with Updated Coefficients for Smagorinsky LES.
In: Proceedings of the V European Conference on Computational Fluid Dynamics ECCOMAS CFD 2010, [Online-Edition: http://www.mathematik.tu-darmstadt.de/preprint.php?id=2610],
[Article]

This list was generated on Sat Jun 15 01:13:31 2019 CEST.