Gräßle, Carmen ; Hinze, Michael ; Lang, Jens ; Ullmann, Sebastian (2019):
POD model order reduction with space-adapted snapshots for incompressible flows.
In: Advances in Computational Mathematics, 45, pp. 2401-2428. Springer, ISSN 1019-7168,
DOI: 10.1007/s10444-019-09716-7,
[Article]

Müller, Christopher ; Ullmann, Sebastian ; Lang, Jens (2019):
A Bramble--Pasciak Conjugate Gradient Method for Discrete Stokes Equations with Random Viscosity.
In: SIAM/ASA Journal on Uncertainty Quantification, 7 (3), pp. 787-805. ISSN 2166-2525,
DOI: 10.1137/18m1163920,
[Article]

Ullmann, Sebastian ; Lang, Jens (2018):
Stochastic Galerkin reduced basis methods for parametrized linear elliptic PDEs.
In: SIAM / ASA Journal on Uncertainty Quantification, (submitted), [Article]

Ullmann, Sebastian (2018):
Model order reduction for space-adaptive simulations of unsteady incompressible flows.
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 ; Ullmann, Sebastian ; Lang, Jens
Schäfer, Michael ; Behr, Marek ; Mehl, Miriam ; Wohlmuth, Barbara (eds.) (2018):
A Bramble-Pasciak conjugate gradient method for discrete Stokes problems with lognormal random viscosity.
In: Lecture Notes in Computational Science and Engineering, 124, In: Recent Advances in Computational Engineering, pp. 63-87, Cham, Springer International Publishin, ISBN 978-3-319-93891-2,
DOI: 10.1007/978-3-319-93891-2_5,
[Book Section]

Spannring, Christopher ; Ullmann, Sebastian ; Lang, Jens
Schäfer, Michael ; Behr, Marek ; Mehl, Miriam ; Wohlmuth, Barbara (eds.) (2018):
A weighted reduced basis method for parabolic PDEs with random data.
In: Lecture Notes in Computational Science and Engineering, 124, In: Recent Advances in Computational Engineering, pp. 145-161, Cham, Springer International Publishing, ISBN 978-3-319-93891-2,
DOI: 10.1007/978-3-319-93891-2_9,
[Book Section]

Ullmann, Sebastian (2018):
Stochastic Galerkin reduced basis methods for parametrized random elliptic PDEs.
Cambridge, Uncertainty quantification for complex systems: theory and methodologies, Isaac Newton Institute, Cambridge, UK, 03.01.2018 - 29.06.2018, [Conference or Workshop Item]

Ullmann, Sebastian (2018):
Stochastic Galerkin reduced basis methods for parametrized random elliptic PDEs.
MoRePaS 2018, Nantes, France, 10 - 13 April 2018, [Conference or Workshop Item]

Ullmann, Sebastian (2018):
Stochastic Galerkin reduced basis methods for parametrized random elliptic PDEs.
Reducing dimensions and cost for UQ in complex systems, Isaac Newton Institute for Mathematical Sciences, Cambridge, UK, 5-9 March 2018, [Conference or Workshop Item]

Müller, Christopher ; Ullmann, Sebastian ; Lang, Jens (2018):
A Bramble-Pasciak conjugate gradient method for discrete Stokes equations with random viscosity.
In: SIAM/ASA Journal on Uncertainty Quantification (JUQ), 7 (3), pp. 787-805. [Article]

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

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

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

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

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

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

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

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

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

Ullmann, Sebastian ; Rotkvic, Marko ; Lang, Jens (2016):
POD-Galerkin reduced-order modeling with adaptive finite element snapshots.
In: Journal of Computational Physics, 325, pp. 244-258. ISSN 0021-9991,
[Article]

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

Ullmann, Sebastian ; Lang, Jens
Garcke, J. ; Pflüger, D. (eds.) (2014):
POD-Galerkin Modeling and Sparse-Grid Collocation for a Natural Convection Problem with Stochastic Boundary Conditions.
In: Lecture Notes in Computational Science and Engineering, In: Sparse Grids and Applications - Munich 2012, pp. 295-315, Springer, [Book Section]

Ullmann, Sebastian (2014):
POD-Galerkin Modeling for Incompressible Flows with Stochastic Boundary Conditions.
München, Verlag Dr. Hut, TU Darmstadt, ISBN 978-3-8439-1568-7,
[Ph.D. Thesis]

Ullmann, Sebastian ; Löbig, Stefan ; Lang, Jens
Janicka, J. ; Sadiki, Amsini ; Schäfer, Michael ; Heeger, Christof (eds.) (2013):
Adaptive Large Eddy Simulation and Reduced-Order Modeling.
In: Fluid Mechanics and Its Applications, 102, In: Flow and Combustion in Advanced Gas Turbine Combustors, pp. 349-378, Dordrecht, Springer Netherlands, ISBN 978-94-007-5320-4,
DOI: 10.1007/978-94-007-5320-4_12,
[Book Section]

Ullmann, Sebastian ; Lang, Jens (2012):
POD and CVT Galerkin reduced-order modeling of the flow around a cylinder.
In: Proceedings in Applied Mathematics and Mechanics (PAMM), 12 (1), pp. 697-698. John Wiley and Sons, ISSN 1617-7061,
[Article]

Ullmann, Sebastian ; 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, [Article]