Forschung

Publikationen

• 2023
• 2022
• 2021
• 2020
• 2019
• 2018
• 2017
• 2016
• 2015
• 2014
• 2013
• 2012
• 2011
• 2010
• 2009
• 2008
• 2007
• 2006
• 2005
• 2004
• 2003
• 2002
• 2001
• 2000
• 1999
• 1998
• 1997

2023

• Wenzel, Tizian; Haasdonk, Bernard; Kleikamp, Hendrik; Ohlberger, Mario; Schindler, Felix. 2023. Application of Deep Kernel Models for Certified and Adaptive RB-ML-ROM Surrogate Modeling arXiv. doi: 10.48550/ARXIV.2302.14526. [eingereicht / in Begutachtung]
• Keil Tim, Ohlberger Mario, Schindler Felix. 2023. Adaptive Localized Reduced Basis Methods for Large Scale Parameterized Systems arXiv. doi: 10.48550/arXiv.2303.03074. [eingereicht / in Begutachtung]
• Ohlberger, M.; Banholzer, S.; Haasdonk, B.; Keil, T., Kleikamp, H.; Mechelli, L.; Oguntola, M;, Schindler,F.; Volkwein, S.; Wenzel, T. 2023. ‘Model Reduction and Learning for PDE Constrained Optimization.’ Contributed to the Oberwolfach Workshop on Optimization Problems for PDEs in Weak Space-Time Form, Oberwolfach. [eingereicht / in Begutachtung]

2022

• Himpe C, Grundel S, Benner P. 2022. ‘Efficient Gas Network Simulations.’ In German Success Stories in Industrial Mathematics, edited by Bock HG, Küfer KH, Maass P, Milde A, Schulz V, 17––22. doi: 10.1007/978-3-030-81455-7_4.
• Gavrilenko Pavel, Haasdonk Bernard, Iliev Oleg, Ohlberger Mario, Schindler Felix, Toktaliev Pavel, Wenzel Tizian, Youssef Maha. 2022. ‘A full order, reduced order and machine learning model pipeline for efficient prediction of reactive flows.’ In Large-Scale Scientific Computing, edited by Lirkov Ivan, Margenov Svetozar, 378–386. Cham: Springer VDI Verlag. doi: 10.1007/978-3-030-97549-4_43.
• Banholzer S, Keil T, Mechelli L, Ohlberger M, Schindler F, Volkwein S. 2022. ‘An adaptive projected Newton non-conforming dual approach for trust-region reduced basis approximation of PDE-constrained parameter optimization.’ Pure and Applied Functional Analysis 7, Nr. 5: 1561–1596.
• Haasdonk B, Kleikamp H, Ohlberger M, Schindler F, Wenzel T. 2022. ‘A new certified hierarchical and adaptive RB-ML-ROM surrogate model for parametrized PDEs.’ SIAM Journal on Scientific Computing 2022. doi: 10.48550/arXiv.2204.13454. [akzeptiert / in Druck (unveröffentlicht)]
• Fokina, D, Iliev O, Toktaliev P, Oseledets I, Schindler F. 2022. ‘On the Performance of Machine Learning Methods for Breakthrough Curve Prediction.’ arXiv [physics.flu-dyn] 2204.11719. doi: 10.48550/arXiv.2204.11719. [eingereicht / in Begutachtung]
• Haasdonk B, Ohlberger M, Schindler F. 2022. ‘An adaptive model hierarchy for data-augmented training of kernel models for reactive flow.’ In MATHMOD 2022 Discussion Contribution Volume, edited by Breitenecker, Felix; Kemmetmüller, Wolfgang; Körner, Andreas; Kugi, Andreas; Troch, Inge, 67–68. 17. Aufl. Vienna: ARGESIM Verlag. doi: 10.11128/arep.17.a17155.
• Keil Tim, Ohlberger Mario. 2022. ‘Model Reduction for Large Scale Systems.’ In Large-Scale Scientific Computing, edited by Lirkov Ivan, Margenov Svetozar, 16–28. Cham: Springer International Publishing. doi: 10.1007/978-3-030-97549-4_2.
• Keil Tim, Ohlberger Mario. 2022. ‘A relaxed localized trust-region reduced basis approach for optimization of multiscale problems.’ arXiv 2022. doi: 10.48550/arXiv.2203.09964. [eingereicht / in Begutachtung]
• Kleikamp Hendrik, Ohlberger Mario, Rave Stephan. 2022. ‘Nonlinear Model Order Reduction using Diffeomorphic Transformations of a Space-Time Domain.’ ARGESIM Reports 17. doi: 10.11128/arep.17.a17129.
• Brecher C, Buchmeiser MR, Burkert A, Busemeyer MR, Conermann S, Ertl T, Friedrich M, Helmig, R, Hohmann V, Johnston AJ, Kollmeier B, Larkum M, Louis J, Menges A, Morgner U, Müller J, Niessen C, Ohlberger M, Schäffner W, Schmidt P, Schmitz D, Seeger W, Stammer D, Thomas A, Traninger A, Wegener M, Colomb J, Hermann S, Kopsch-Xhema J, Range J, Flemisch B. 2022. „Commitment zu aktivem Daten- und -softwaremanagement in großen Forschungsverbünden: Commitment to active data and software management in large research alliances.“ Bausteine Forschungsdatenmanagement 1: 121–123. doi: 10.17192/bfdm.2022.1.8412.
• Keil T, Kleikamp H, Lorentzen R, Oguntola M, Ohlberger M. 2022. ‘Adaptive machine learning based surrogate modeling to accelerate PDE-constrained optimization in enhanced oil recovery.’ Advances in Computational Mathematics 2022, Nr. 48: 73. doi: 10.1007/s10444-022-09981-z.
• Landstorfer M, Ohlberger M, Rave S, Tacke M. 2022. ‘A Modeling Framework for Efficient Reduced Order Simulations of Parametrized Lithium-Ion Battery Cells.’ European Journal of Applied Mathematics 2022: 1–38. doi: 10.1017/S0956792522000353.
• Benner, P.; Burger, M.; Göddeke, D.; Himpe, C.; Hintermüller, M.; Heiland, J.; Koprucki, T.; Ohlberger, M.; Rave, S.; Reidelbach, M.; Saak, J.; Schöbel, A.; Tabelow, K. 2022. „Die Mathematische Forschungsdateninitiative in der NFDI: MaRDI (Mathematical Research Data Initiative).“ GAMM Rundbrief 1/2022: 40–43.
• Singh, A; Thale, S; Leibner, T; Ricker, A; Nüsse, H; Klingauf, J; Ohlberger, M; Matis, M. 2022. ‘Dynamic interplay of protrusive microtubule and contractile actomyosin forces drives tissue extension.’ eLife 2022. doi: 10.1101/2022.06.21.496930. [eingereicht / in Begutachtung]
• Leibner Tobias. 2022. Model reduction for kinetic equations: moment approximations and hierarchical approximate proper orthogonal decomposition Dissertationsschrift, Universität Münster.
• Julia Schleuß, Kathrin Smetana. 2022. ‘Optimal local approximation spaces for parabolic problems.’ Multiscale Model. Simul. 20, Nr. 1: 551–582. doi: 10.1137/20M1384294.
• Julia Schleuß, Kathrin Smetana, Lukas ter Maat. 2022. ‘Randomized quasi-optimal local approximation spaces in time.’ arXiv 2022. [eingereicht / in Begutachtung]

2021

• Fehr J, Himpe C, Rave S, Saak J. 2021. ‘Sustainable Research Software Hand-Over.’ Journal of Open Research Software 9, Nr. 1. doi: 10.5334/jors.307/.
• Himpe C. 2021. ‘Comparing (Empirical-Gramian-Based) Model Order Reduction Algorithms.’ In Model Reduction of Complex Dynamical Systems, edited by Benner P, Breiten T, Faßbender H, Hinze M, Stykel T, Zimmermann R, 141––164. doi: 10.1007/978-3-030-72983-7_7.
• Himpe C, Grundel S, Benner P. 2021. ‘Model Order Reduction for Gas and Energy Networks.’ Journal of Mathematics in Industry 11: 13. doi: 10.1186/s13362-021-00109-4.
• Clees T, Baldin A, Benner P, Grundel S, Himpe C, Klaassen B, Küsters F, Marheineke N, Nikitina L, Nikitin I, Pade J, Stahl N, Strohm C, Tischendorf C, Wirsen A. 2021. ‘MathEnergy – Mathematical Key Technologies for Evolving Energy Grids.’ In Mathematical Modeling, Simulation and Optimization for Power Engineering and Management, edited by Göttlich S, Herty M, Milde A, 233–262. doi: 10.1007/978-3-030-62732-4_11.
• Buhr Andreas, Iapichino Laura, Ohlberger Mario, Rave Stephan, Schindler Felix, Smetana Kathrin. 2021. ‘Localized model reduction for parameterized problems.’ In Model Order Reduction: Volume 2 Snapshot-Based Methods and Algorithms, edited by Benner P, Grivet-Talocia S, Quarteroni A, Rozza G, Schilders W, Sileira L, 245 – 306. doi: 10.1515/9783110671490-006.
• Keil T, Mechelli L, Ohlberger M, Schindler F, Volkwein S. 2021. ‘A non-conforming dual approach for adaptive Trust-Region Reduced Basis approximation of PDE-constrained optimization.’ ESAIM: Mathematical Modelling and Numerical Analysis 55: 1239–1269. doi: 10.1051/m2an/2021019.
• Bastian P, Blatt M, Dedner A, Dreier N, Engwer C, Fritze R, Gräser C, Kempf D, Klöfkorn R, Ohlberger M, Sander O. 2021. ‘The DUNE Framework: Basic Concepts and Recent Developments.’ Computers & Mathematics with Applications 81: 75–112. doi: 10.1016/j.camwa.2020.06.007.
• Leibner T, Ohlberger M. 2021. ‘A new entropy-variable-based discretization method for minimum entropy moment approximations of linear kinetic equations.’ ESAIM: Mathematical Modelling and Numerical Analysis 55: 2567–2608. doi: 10.1051/m2an/2021065.
• Leibner T, Matis M, Ohlberger M, Rave S. 2021. ‘Distributed model order reduction of a model for microtubule-based cell polarization using HAPOD.’ arXiv [math.NA] 2111.00129. [eingereicht / in Begutachtung]
• Gander Martin, Rave Stephan. 2021. Localized Reduced Basis Additive Schwarz Methods. [eingereicht / in Begutachtung]
• Brunken Julia. 2021. Stable and efficient Petrov-Galerkin methods for certain (kinetic) transport equations Dissertationsschrift, Universität Münster.

2020

• Bastian P, Altenbernd M, Dreier N, Engwer C, Fahlke J, Fritze R, Geveler M, Göddeke D, Iliev O, Ippisch O, Mohring J, Müthing S, Ohlberger M, Ribbrock D, Shegunov N, Turek S. 2020. ‘Exa-Dune -- Flexible PDE Solvers, Numerical Methods and Applications.’ In Software for Exascale Computing - SPPEXA 2016-2019, edited by Bungartz Hans-Joachim, Reiz Severin. Uekermann Benjamin, Neumann Philipp, Nagel Wolfgang E, 225–269. Cham: Springer International Publishing. doi: 10.1007/978-3-030-47956-5_9.
• Ohlberger Mario, Schweizer Ben, Urban Maik, Verfürth Barbara. 2020. ‘Mathematical analysis of transmission properties of electromagnetic meta-materials.’ Networks and Heterogeneous Media 15, Nr. 1: 29–56. doi: 10.3934/nhm.2020002.
• Buchfink P, Haasdonk B, Rave S. 2020. ‘PSD-Greedy Basis Generation for Structure-Preserving Model Order Reduction of Hamiltonian Systems.’ Contributed to the ALGORITMY 2020, Vysoké Tatry.
• Anzt H, Bach F, Druskat S, Löffler F, Loewe A, Renard B, Seemann G, Struck A, Achhammer E, Aggarwal P, Appel F, Bader M, Brusch L, Busse C, Chourdakis G, Dabrowski P, Ebert P, Flemisch B, Friedl S, Fritzsch B, Funk M, Gast V, Goth F, Grad J, Hermann S, Hohmann F, Janosch S, Kutra D, Linxweiler J, Muth T, Peters-Kottig W, Rack F, Raters F, Rave S, Reina G, Reißig M, Ropinski T, Schaarschmidt J, Seibold H, Thiele J, Uekermann B, Unger S, Weeber R. 2020. ‘An environment for sustainable research software in Germany and beyond: current state, open challenges, and call for action.’ F1000Research 9, Nr. 295. doi: 10.12688/f1000research.23224.1.
• Bansal H, Rave S, Iapichino L, Schilders WHA, van de Wouw N. 2020. ‘Model order reduction framework for problems with moving discontinuities.’ Contributed to the Proceedings of ENUMATH 2019, Egmond aan Zee. [online first]
• Rave S, Saak J. 2020. ‘A Non-stationary Thermal-Block Benchmark Model for Parametric Model Order Reduction.’ Contributed to the ENUMATH 2019, Graz. [akzeptiert / in Druck (unveröffentlicht)]
• Mlinarić P, Rave S, Saak J. 2020. ‘Parametric model order reduction using pyMOR.’ Contributed to the MODRED 2019, Graz. [akzeptiert / in Druck (unveröffentlicht)]
• Brunken Julia Smetana Kathrin. 2020. ‘Stable and efficient Petrov-Galerkin methods for a kinetic Fokker-Planck equation.’ arXiv 2020. [eingereicht / in Begutachtung]
• Schneider Florian, Leibner Tobias. 2020. ‘First-order continuous- and discontinuous-Galerkin moment models for a linear kinetic equation: Model derivation and realizability theory.’ Journal of Computational Physics 416: 109547. doi: 10.1016/j.jcp.2020.109547.
• Hellman Fredrik, Keil Tim, Målqvist Axel. 2020. ‘Numerical Upscaling of Perturbed Diffusion Problems.’ SIAM Journal on Scientific Computing 2020, Nr. Volume 42, Issue 4: A2014–A2036. doi: 10.1137/19M1278211.

2019

• Benner P, Himpe C. 2019. ‘Cross-Gramian-Based Dominant Subspaces.’ Advances in Computational Mathematics 45, Nr. 5: 2533–2553. doi: 10.1007/s10444-019-09724-7.
• Grundel S, Himpe C, Saak J. 2019. ‘On Empirical System Gramians.’ Contributed to the 90th Annual Meeting of the International Association of Applied Mathematics and Mechanics (GAMM), Wien, Österrreich. doi: 10.1002/pamm.201900006.
• Rave Stephan, Schindler Felix. 2019. ‘A locally conservative reduced flux reconstruction for elliptic problems.’ In Special Issue: 90th Annual Meeting of the International Association of Applied Mathematics and Mechanics (GAMM), edited by Eberhardsteiner J, Schöberl M.: Wiley. doi: 10.1002/pamm.201900026.
• Feinauer J, Hein S, Rave S, Schmidt S, Westhoff D, Zausch J, Iliev O, Latz A, Ohlberger M, Schmidt V. 2019. ‘MULTIBAT: Unified workflow for fast electrochemical 3D simulations of lithium-ion cells combining virtual stochastic microstructures, electrochemical degradation models and model order reduction.’ Journal of Computational Science 31: 172–184. doi: 10.1016/j.jocs.2018.03.006.
• Hain S, Ohlberger M, Radic M, Urban K. 2019. ‘A Hierarchical A-Posteriori Error Estimatorfor the Reduced Basis Method.’ Advances in Computational Mathematics 45: 2191–2214. doi: 10.1007/s10444-019-09675-z.
• Ohlberger M, Buhr A, Eikhorn D, Engwer C, Rave S. 2019. ‘Advances in Model Order Reduction for Large Scale or Multi-Scale Problems.’ Oberwolfach Reports 16, Nr. 3: 2510–2512. doi: 10.4171/OWR/2019/40.
• Lehrenfeld Christoph, Rave Stephan. 2019. ‘Mass Conservative Reduced Order Modeling of a Free Boundary Osmotic Cell Swelling Problem.’ Advances in Computational Mathematics 45, Nr. 5: 2215–2239. doi: 10.1007/s10444-019-09691-z.
• Balicki L, Mlinarić P, Rave S, Saak J. 2019. ‘System-theoretic model order reduction with pyMOR.’ PAMM 19. doi: 10.1002/pamm.201900459.
• Brunken Julia, Smetana Kathrin, Urban Karsten. 2019. ‘(Parametrized) First Order Transport Equations: Realization of Optimally Stable Petrov-Galerkin Methods.’ SIAM Journal on Scientific Computing 41, Nr. 1. doi: 10.1137/18M1176269.
• Schneider Florian, Leibner Tobias. 2019. ‘First-order continuous- and discontinuous-Galerkin moment models for a linear kinetic equation: realizability-preserving splitting scheme and numerical analysis.’ arXiv 2019. [eingereicht / in Begutachtung]
• Hellman Fredrik, Keil Tim, Målqvist Axel. 2019. ‘Multiscale methods for perturbed diffusion problems.’ Oberwolfach Reports 2019. [online first]
• Julia Schleuß. 2019. Optimal local approximation spaces for parabolic problems (Master's thesis).

2018

• Himpe C, Leibner T, Rave S. 2018. ‘Hierarchical Approximate Proper Orthogonal Decomposition.’ SIAM Journal on Scientific Computing 40, Nr. 5: A3267–A3292.
• Benner P, Himpe C, Mitchell T. 2018. ‘On Reduced Input-Output Dynamic Mode Decomposition.’ Advances in Computational Mathematics 44, Nr. 6: 1751–1768. doi: 10.1007/s10444-018-9592-x.
• Benner P, Grundel S, Himpe C, Huck C, Streubel T, Tischendorf C. 2018. ‘Gas Network Benchmark Models.’ In Applications of Differential-Algebraic Equations: Examples and Benchmarks, edited by Campbell S, Ilchmann A, Mehrmann V, Reis T, 171–197. doi: 10.1007/11221_2018_5.
• Himpe C. 2018. ‘emgr - The Empirical Gramian Framework.’ Algorithms 11, Nr. 7: 91. doi: 10.3390/a11070091.
• Benner P, Grundel S, Himpe C. „Parametric Model Order Reduction for Gas Flow Models.“ contributed to the MoRePaS 4 - Model Reduction for Parameterized Systems, Nantes, Frankreich, 2018. doi: 10.14293/P2199-8442.1.SOP-MATH.EJOCET.v1.
• Himpe C, Leibner T, Rave S. „HAPOD - Fast, Simple and Reliable Distributed POD Computation.“ contributed to the MATHMOD 2018- 9th Vienna International Conference on Mathematical Modelling, Vienna, 2018. doi: 10.11128/arep.55.a55283.
• Ohlberger Mario, Schaefer Michael, Schindler Felix. 2018. ‘Localized Model Reduction in PDE Constrained Optimization.’ In Shape Optimization, Homogenization and Optimal Control – DFG-AIMS workshop held at the AIMS Center Senegal, March 13-16, 2017, edited by Schulz V, Seck D, 143–163. Basel: Birkhäuser. doi: 10.1007/978-3-319-90469-6_8.
• Ohlberger Mario, Rave Stephan, Schindler Felix, Wedemeier Tobias. 2018. ‘Model reduction for parameterized systems and inverse problems.’ Oberwolfach Reports 2018, Nr. 39: 2454–2457. doi: 10.4171/OWR/2018/39.
• Ohlberger M, Verfürth B. 2018. ‘A new Heterogeneous Multiscale Method for the Helmholtz equation with high contrast.’ Multiscale Modeling and Simulation: A SIAM Interdisciplinary Journal 16, Nr. 1: 385–411. doi: 10.1137/16M1108820.
• Verfürth B. 2018. ‘Heterogeneous Multiscale Method for the Maxwell equations with high contrast.’ ESAIM Math. Model. Numer. Anal. xx. [akzeptiert / in Druck (unveröffentlicht)]
• Gallistl D, Henning P, Verfürth B. 2018. ‘Numerical homogenization of H(curl)-problems.’ SIAM J. Numer. Anal. 56, Nr. 3: 1570–1596. doi: 10.1137/17M1133932.
• Verfürth B. 2018. Numerical multiscale methods for Maxwell's equations in heterogeneous media Dissertationsschrift, Universität Münster.
• Dennis Eickhorn. 2018. Randomisierte lokalisierte Modellreduktion mit Robin-Transferoperator (Masterarbeit).

2017

• Baur U, Benner P, Haasdonk B, Himpe C, Martini I, Ohlberger M. 2017. ‘Comparison of methods for parametric model order reduction of instationary problems.’ In Model Reduction and Approximation: Theory and Algorithms., edited by Benner P, Cohen A, Ohlberger, M, Willcox K, 377–408. 1. Aufl. Philadelphia, PA: SIAM Publications. doi: 10.1137/1.9781611974829.ch9.
• Himpe C, Ohlberger M. 2017. ‘Cross-Gramian-Based Model Reduction: A Comparison.’ In Model Reduction of Parametrized Systems, edited by Benner P, Ohlberger M, Patera A, Rozza G, Urban K, 271–283. Cham: Springer International Publishing. doi: 10.1007/978-3-319-58786-8_17.
• Himpe C, Leibner T, Rave S, Saak J. 2017. ‘Fast Low-Rank Empirical Cross Gramians.’ PAMM 17, Nr. 1: 841–842. doi: 10.1002/pamm.201710388.
• Ohlberger M, Schindler F. 2017. ‘Non-Conforming Localized Model Reduction with Online Enrichment: Towards Optimal Complexity in PDE constrained Optimization.’ In Finite Volumes for Complex Applications VIII - Hyperbolic, Elliptic and Parabolic Problems: FVCA 8, Lille, France, June 2017, edited by Cancès C, Omnes P, 357–365. Cham: Springer International Publishing. doi: 10.1007/978-3-319-57394-6_38.
• Leibner T, Milk R, Schindler F. 2017. ‘Extending DUNE: The dune-xt modules.’ Archive of Numerical Software 5, Nr. 1: 193–216. doi: 10.11588/ans.2017.1.27720.
• Ohlberger M, Rave S, Schindler F. 2017. ‘True Error Control for the Localized Reduced Basis Method for Parabolic Problems.’ In Model Reduction of Parametrized Systems, edited by Benner P., Ohlberger M., Patera A., Rozza G., Urban K., 169–182. Cham: Springer International Publishing. doi: 10.1007/978-3-319-58786-8_11.
• Smetana K, Ohlberger M. 2017. ‘Hierarchical model reduction of nonlinear partial differential equations based on the adaptive empirical projection method and reduced basis techniques.’ M2AN Math. Model. Numer. Anal. 51, Nr. 2: 641–677. doi: 10.1051/m2an/2016031.
• Buhr Andreas, Smetana Kathrin. 2017. Randomized Local Model Order Reduction : arXiv:1706.09179, 2017. [eingereicht / in Begutachtung]
• Ohlberger Mario. 2017. ‘Book review of: A. Quarteroni et al., Reduced basis methods for partial differential equations. An introduction.’ SIAM Rev. 59, Nr. 3: 690–692.
• Benner P, Ohlberger M, Patera A, Rozza G, Urban K (Eds.): 2017. Model Reduction of Parametrized Systems. 1. Aufl. Cham: Springer International Publishing. doi: 10.1007/978-3-319-58786-8.
• Barth T, Herbin R, Ohlberger M. 2017. ‘Finite Volume Methods: Foundation and Analysis.’ In Encyclopedia of Computational Mechanics, edited by Stein E, de Borst R, Hughes T, –. 2. Aufl. John Wiley & Sons. doi: 10.1002/9781119176817.ecm2010.
• Benner P, Cohen A, Ohlberger M, Willcox K. 2017. Model Reduction and Approximation: Theory and Algorithms. Philadelphia, PA: SIAM Publications. doi: 10.1137/1.9781611974829.
• Ohlberger M, Rave S. 2017. ‘Localized Reduced Basis Approximation of a Nonlinear Finite Volume Battery Model with Resolved Electrode Geometry.’ In Model Reduction of Parametrized Systems, edited by Benner P., Ohlberger M., Patera A., Rozza G., Urban K., 201–212. Cham: Springer International Publishing. doi: 10.1007/978-3-319-58786-8_13.
• Buhr A, Engwer C, Ohlberger M, Rave S. 2017. ‘ArbiLoMod: Local Solution Spaces by Random Training in Electrodynamics.’ In Model Reduction of Parametrized Systems, edited by Benner P., Ohlberger M., Patera A., Rozza G., Urban K., 137–148. Cham: Springer International Publishing. doi: 10.1007/978-3-319-58786-8_9.
• Ohlberger M, Verfürth B. 2017. ‘Localized Orthogonal Decomposition for two-scale Helmholtz-type problems.’ AIMS Mathematics 2, Nr. 3: 458–478. doi: 10.3934/Math.2017.2.458.
• Buhr A, Engwer C, Ohlberger M, Rave S. 2017. ‘ArbiLoMod, a Simulation Technique Designed for Arbitrary Local Modifications.’ SIAM Journal on Scientific Computing 39, Nr. 4: A1435–A1465. doi: 10.1137/15M1054213.
• Andreas Dedner, Stefan Girke, Robert Klöfkorn, Tobias Malkmus. 2017. ‘The DUNE-FEM-DG module.’ Archive of Numerical Software 5, Nr. 1: 21––61. doi: 10.11588/ans.2017.1.28602.
• Verfürth B. 2017. ‘Numerical homogenization for indefinite H(curl)-problems.’ In Proceedings of Equadiff 2017 Conference, edited by Mikula K, Sevcovic D, Urban J, 137–146.
• Verfürth B. „Heterogeneous Multiscale Method for a Helmholtz problem with high contrast.“ contributed to the Winter school on Numerical Analysis of Multiscale Problems, HIM Bonn, Germany, 2017.
• Keil Tim. 2017. Variational crimes in the Localized orthogonal decomposition method (master's thesis).

2016

• Himpe C, Ohlberger M. 2016. ‘A note on the cross Gramian for non-symmetric systems.’ System Science and Control Engineering 4, Nr. 1: 199–208. doi: 10.1080/21642583.2016.1215273.
• Fehr J, Heiland J, Himpe C, Saak J. 2016. ‘Best Practices for Replicability, Reproducibility and Reusability of Computer-Based Experiments Exemplified by Model Reduction.’ AIMS Mathematics 1, Nr. 3: 261--281. doi: 10.3934/Math.2016.3.261.
• Ohlberger M, Rave S, Schindler F. 2016. ‘Model Reduction for Multiscale Lithium-Ion Battery Simulation.’ In Numerical Mathematics and Advanced Applications ENUMATH 2015, edited by Karasözen B, Manguoğlu M, Teuer-Sezgin M, Göktepe S, Uğur Ö, 317–331.: Springer. doi: 10.1007/978-3-319-39929-4_31.
• Schindler, F. 2016. Model reduction for parametric multi-scale problems Dissertationsschrift, Westfälische Wilhelms-Universität Münster.
• Milk R, Rave S, Schindler F. 2016. ‘pyMOR - Generic algorithms and interfaces for model order reduction.’ SIAM Journal on Scientific Computing 38, Nr. 5: S194–S216. doi: 10.1137/15M1026614.
• Ohlberger M, Rave S, Schindler F. 2016. ‘Adaptive Localized Model Reduction.’ Oberwolfach Reports 13, Nr. 3: 2406–2409. doi: 10.4171/OWR/2016/42.
• Ohlberger M, Smetana K. 2016. ‘Approximation of skewed interfaces with tensor-based model reduction procedures: application to the reduced basis hierarchical model reduction approach.’ J. Comp. Phys. 321: 1185–1205. doi: 10.1016/j.jcp.2016.06.021.
• Smetana Kathrin, Patera Anthony T. 2016. ‘Optimal local approximation spaces for component-based static condensation procedures.’ SIAM J. Sci. Comput. 38, Nr. 5: A3318––A3356. doi: 10.1137/15M1009603.
• Brunken Julia, Leibner Tobias, Ohlberger Mario, Smetana Kathrin. 2016. ‘Problem adapted hierachical model reduction for the Fokker-Planck equation.’ In ALGORITMY 2016 Proceedings of contributed papers and posters, edited by Handlovicova Angela, Sevcovic Daniel, 13–22. Bratislava: Slovak University of Technology in Bratislava.
• Henning P, Ohlberger M, Verfürth B. 2016. ‘A new Heterogeneous Multiscale Method for time-harmonic Maxwell's equations.’ SIAM J. Numer. Anal. 54, Nr. 6: 3493–3522. doi: 10.1137/15M1039225.
• Henning P, Ohlberger M. 2016. ‘A-posteriori error estimate for a heterogeneous multiscale approximation of advection-diffusion problems with large expected drift.’ Discrete and Continuous Dynamical Systems - Series S 9, Nr. 5: 1393–1420. doi: 10.3934/dcdss.2016056.
• Henning P, Ohlberger M, Verfürth B. 2016. ‘Analysis of multiscale methods for time-harmonic Maxwell's equations.’ Proc. Appl. Math. Mech. 16, Nr. 1: 559–560. doi: 10.1002/pamm.201610268.
• Bastian P, Engwer C, Fahlke J, Geveler M, Göddeke D, Iliev O, Ippisch O, Milk R, J M, Müthing S, Ohlberger M, Ribbrock D, Turek S. 2016. ‘Advances concerning multiscale methods and uncertainty quantification in EXA-DUNE.’ In Software for Exascale Computing - SPPEXA 2013-2015, edited by Hans-Joachim Bungartz, Philipp Neumann, Wolfgang E. Nagel, 25–43. doi: 10.1007/978-3-319-40528-5_2.
• Bastian P, Engwer C, Fahlke J, Geveler M, Göddeke D, Iliev O, Ippisch O, Milk R, J M, Müthing S, Ohlberger M, Ribbrock D, Turek S. 2016. ‘Hardware-based Efficiency Advances in the EXA-DUNE Project.’ In Software for Exascale Computing - SPPEXA 2013-2015, edited by Hans-Joachim Bungartz, Philipp Neumann, Wolfgang E. Nagel, 3–23. Springer VDI Verlag. doi: 10.1007/978-3-319-40528-5_1.
• Ohlberger M, Rave S. 2016. ‘Reduced Basis Methods: Success, Limitations and Future Challenges.’ In roceedings of ALGORITMY 2016, 20th Conference on Scientific Computing, Vysoke Tatry, Podbanske, Slovakia, March 13-18, 2016, edited by A. Handlovičova and D. Sevčovič, 1–12. Bratislava: Publishing House of Slovak University of Technology in Bratislava.
• Engwer C, Henning P, M\ralqvist A, Peterseim D. 2016. Efficient implementation of the Localized Orthogonal Decomposition method arXiv, 2016. [eingereicht / in Begutachtung]
• Lehrenfeld C, Reusken A. 2016. ‘Optimal Preconditioners for Nitsche-XFEM Discretizations of Interface Problems.’ Numerische Mathematik 2016. doi: 10.1007/s00211-016-0801-6.
• Falconi Delgado C, Lehrenfeld C, Marschall H, Meyer C, Abiev R, Bothe D, Reusken A, Schlüter M, Wörner M. 2016. ‘Numerical and Experimental Analysis of Local Flow Phenomena in Laminar Taylor Flow in a Square Mini-Channel.’ Physics of Fluids 28, Nr. 1: 012109.
• Lehrenfeld C, Schöberl J. 2016. ‘High order exactly divergence-free Hybrid Discontinuous Galerkin Methods for unsteady incompressible flows.’ Comp. Meth. Appl. Mech. Eng. 2016. doi: 10.1016/j.cma.2016.04.025. [online first]
• Lehrenfeld Christoph. 2016. ‘High order unfitted finite element methods on level set domains using isoparametric mappings.’ Comp. Meth. Appl. Mech. Eng. 300, Nr. 1: 716–733. doi: 10.1016/j.cma.2015.12.005.
• Lehrenfeld C, Reusken A. 2016. L2-estimates for a high order unfitted finite element method for elliptic interface problems : arXiv eprints, 2016. [eingereicht / in Begutachtung]
• Lehrenfeld C, Reusken A. 2016. ‘Analysis of a high order unfitted finite element method for elliptic interface problems.’ arXiv preprint arXiv:1602.02970 1602.02970. [eingereicht / in Begutachtung]

2015

• Himpe C, Ohlberger M. „The Versatile Cross Gramian.“ contributed to the Model Reduction for Parameterized Systems (MoRePaS) III, Trieste, Italy, 2015. doi: 10.14293/P2199-8442.1.SOP-MATH.PSAHPZ.v1.
• Himpe C, Ohlberger M. 2015. ‘The Empirical Cross Gramian for Parametrized Nonlinear Systems.’ Contributed to the MATHMOD 2015 - 8th Vienna International Conference on Mathematical Modelling, Vienna. doi: 10.1016/j.ifacol.2015.05.163.
• Himpe C, Ohlberger M. „Accelerating the Computation of Empirical Gramians and Related Methods.“ contributed to the 5th International Workshop on Model Reduction in Reacting Flows, Spreewald, 2015. doi: 10.5281/zenodo.46643.
• Himpe C, Ohlberger M. 2015. ‘Data-driven combined state and parameter reduction for inverse problems.’ Advances in Computational Mathematics 41, Nr. 5: 1343–1364. doi: 10.1007/s10444-015-9420-5.
• Ohlberger M, Schindler F. 2015. ‘Error control for the localized reduced basis multi-scale method with adaptive on-line enrichment.’ SIAM J. Sci. Comput. 37, Nr. 6: A2865–A2895. doi: 10.1137/151003660.
• Ohlberger Mario, Smetana Kathrin. 2015. ‘A Dimensional Reduction Approach Based on the Application of Reduced Basis Methods in the Framework of Hierarchical Model Reduction.’ Oberwolfach Reports 2/2015: 141–144. doi: 10.4171/OWR/2015/2.
• Smetana Kathrin. 2015. ‘A new certification framework for the port reduced static condensation reduced basis element method.’ Computer Methods in Applied Mechanics and Engineering 283: 352–383. doi: 10.1016/j.cma.2014.09.020.
• Henning P, Ohlberger M. 2015. ‘Error control and adaptivity for heterogeneous multiscale approximations of nonlinear monotone problems.’ Discrete and Continuous Dynamical Systems - Series S 8, Nr. 1: 119–150. doi: 10.3934/dcdss.2015.8.119.
• Benner P, Ohlberger M, Patera A, Rozza G, Sorensen D, Urban K. 2015. ‘Model order reduction of parameterized systems (MoRePaS).’ Advances in Computational Mathematics 41, Nr. 5: 955–960. doi: 10.1007/s10444-015-9443-y.
• Buhr A, Ohlberger M. 2015. ‘Interactive Simulations Using Localized Reduced Basis Methods.’ In IFAC-PapersOnLine, 729–730. doi: 10.1016/j.ifacol.2015.05.134.
• Mohring Jan, Milk Rene, Ngo Adrian, Klein Ole, Iliev Oleg, Ohlberger Mario, Bastian Peter. 2015. ‘Uncertainty Quantification for Porous Media Flow Using Multilevel Monte Carlo.’ In Proceedings of 10th International Conference on Large-Scale Scientific Computations, Sozopol 2015, edited by Lirkov I., Margenov S. D. , Wasniewski J., 145–152.: Springer International Publishing. doi: 10.1007/978-3-319-26520-9_15.
• Kaulmann S, Flemisch B, Haasdonk B, Lie K, Ohlberger M. 2015. ‘The Localized Reduced Basis Multiscale method for two-phase flows in porous media.’ International Journal for Numerical Methods in Engineering 5, Nr. 102: 1018–1040. doi: 10.1002/nme.4773.
• Henning P, Ohlberger M, Schweizer B. 2015. ‘Adaptive Heterogeneous Multiscale Methods for immiscible two-phase flow in porous media.’ Computational Geosciences 1, Nr. 19: 99––114. doi: 10.1007/s10596-014-9455-6.
• Leibner Tobias. 2015. Numerical methods for kinetic equations (Master's thesis).
• Lehrenfeld C, Reusken A. 2015. ‘Finite Element Techniques for the Numerical Simulation of Two-Phase Flows with Mass Transport.’ In Computational Methods for Complex Liquid-Fluid Interfaces, edited by CRC Press, 353–371.
• Lehrenfeld C. 2015. ‘The Nitsche XFEM-DG Space-Time Method and its Implementation in Three Space Dimensions.’ SIAM J. Sci. Comput. 37: A245–A270. doi: 10.1137/130943534.
• Lehrenfeld C. 2015. On a Space-Time Extended Finite Element Method for the Solution of a Class of Two-Phase Mass Transport Problems Dissertationsschrift, RWTH Aachen.

2014

• Himpe C, Ohlberger M. 2014. ‘Model Reduction for Complex Hyperbolic Networks.’ Contributed to the 13th European Control Conference (ECC), June 24-27, 2014, Strasbourg, France. doi: 10.1109/ECC.2014.6862188.
• Himpe C, Ohlberger M. 2014. ‘Cross-Gramian Based Combined State and Parameter Reduction for Large-Scale Control Systems.’ Mathematical Problems in Engineering 2014: 1–13. doi: 10.1155/2014/843869.
• Himpe C, Ohlberger M. 2014. ‘Combined State and Parameter Reduction.’ Contributed to the 85th Annual Meeting of the International Association of Applied Mathematics and Mechanics (GAMM), Erlangen. doi: 10.1002/pamm.201410393.
• Ohlberger M, Schindler F. 2014. ‘A-Posteriori Error Estimates for the Localized Reduced Basis Multi-Scale Method.’ In Finite Volumes for Complex Applications VII-Methods and Theoretical Aspects, edited by , Rohde C, 421–429.: Springer International Publishing. doi: 10.1007/978-3-319-05684-5_41.
• Ohlberger M, Smetana K. 2014. ‘A Dimensional Reduction Approach Based on the Application of Reduced Basis Methods in the Framework of Hierarchical Model Reduction.’ SIAM Journal on Scientific Computing 36, Nr. 2: A714–A736. doi: 10.1137/130939122.
• Berninger H, Ohlberger M, Sander O, Smetana K. 2014. ‘Unsaturated subsurface flow with surface water and nonlinear in- and outflow conditions.’ Math. Models and Methods in Appl. Sciences 24, Nr. 5: 901–936. doi: 10.1142/S0218202513500711.
• Haasdonk B, Ohlberger M. 2014. „Wenn die Probleme zahlreicher werden: Reduzierte Basis Methoden f\ür effiziente und gesicherte numerische Simulation.“ GAMM Rundbrief 2014/1: 6–13.
• Fuhrmann J, Ohlberger M, Rohde C. 2014. Finite Volumes for Complex Applications VII-Methods and Theoretical Aspects - FVCA 7, Berlin, June 2014.: Springer International Publishing. doi: 10.1007/978-3-319-05684-5.
• Fuhrmann J, Ohlberger M, Rohde C. 2014. Finite Volumes for Complex Applications VII-Elliptic, Parabolic and Hyperbolic Problems - FVCA 7, Berlin, June 2014.: Springer International Publishing. doi: 10.1007/978-3-319-05591-6.
• Girke S, Klöfkorn R, Ohlberger M. 2014. ‘Efficient Parallel Simulation of Atherosclerotic Plaque Formation Using Higher Order Discontinuous Galerkin Schemes.’ In Finite Volumes for Complex Applications VII-Elliptic, Parabolic and Hyperbolic Problems, edited by Fuhrmann J, Ohlberger M, Rohde C, 617–625.: Springer International Publishing. doi: 10.1007/978-3-319-05591-6_61.
• Ohlberger M, Rave S, Schmidt S, Zhang S. 2014. ‘A Model Reduction Framework for Efficient Simulation of Li-Ion Batteries.’ In Finite Volumes for Complex Applications VII-Elliptic, Parabolic and Hyperbolic Problems, edited by Fuhrmann J, Ohlberger M, Rohde C, 695–702.: Springer. doi: 10.1007/978-3-319-05591-6_69.
• Henning Patrick, Ohlberger Mario, Schweizer Benn. 2014. ‘An adaptive Multiscale Finite Element Method.’ Multiscale Mod. Simul. 12, Nr. 3: 1078–1107. doi: 10.1137/120886856.
• Mikula K, Ohlberger M, Urban J. 2014. ‘Inflow-Implicit/Outflow-Explicit Finite Volume Methods for Solving Advection Equations.’ Applied Numerical Mathematics 85: 16–37. doi: 10.1016/j.apnum.2014.06.002.
• Buhr A, Engwer C, Ohlberger M, Rave S. 2014. ‘A Numerically Stable A Posteriori Error Estimator for Reduced Basis Approximations of Elliptic Equations.’ In 11th World Congress on Computational Mechanics, WCCM 2014, 5th European Conference on Computational Mechanics, ECCM 2014 and 6th European Conference on Computational Fluid Dynamics, ECFD 2014, edited by E. Onate XO, Huerta A, 4094–4102.: CIMNE, Barcelona.
• Bastian P, Engwer C, Göddeke D, Iliev O, Ippisch O, Ohlberger M, Turek S, Fahlke J, Kaulmann S, Müthing S, Ribbrock D. 2014. ‘EXA-DUNE: Flexible PDE Solvers, Numerical Methods and Applications.’ In Euro-Par 2014: Parallel Processing Workshops, edited by Lopes L., Žilinskas J., Costan A., Cascella R.G., Kecskemeti G., Jeannot E., Cannataro M., Ricci L., Benkner S., Petit S., Scarano V., Gracia J., Hunold S., Scott S.L., Lankes S., Lengaue C., Carretero J., Breitbart J., Alexander M., 530–541. Springer International Publishing. doi: 10.1007/978-3-319-14313-2_45.
• Marschall H, Boden S, Lehrenfeld C, Falconi Delgado C, Hampel U, Reusken A, Wörner M, Bothe D. 2014. ‘Validation of Interface Capturing and Tracking Techniques with different Surface Tension Treatments against a Taylor Bubble Benchmark Problem.’ Comput. & Fluids 102: 336–352. doi: 10.1016/j.compfluid.2014.06.030.

2013

• Himpe C, Ohlberger M. 2013. ‘A Unified Software Framework for Empirical Gramians.’ Journal of Mathematics 2013, Nr. 2013: 1–6. doi: 10.1155/2013/365909.
• Albrecht F, Ohlberger M. 2013. ‘The localized reduced basis multi-scale method with online enrichment.’ Oberwolfach Reports 7: 406–409. doi: 10.4171/OWR/2013/07.
• Ohlberger M, Albrecht F, Drohmann M, Henning P, Kaulmann S, Schweizer B. 2013. ‘Model reduction for multiscale problems.’ Oberwolfach Reports 39: 2228–2230. doi: 10.4171/OWR/2013/39.
• Ohlberger M, Schaefer M. 2013. ‘Error Control Based Model Reduction for Parameter Optimization of Elliptic Homogenization Problems.’ In Proceedings of the 1st IFAC Workshop on Control of Systems Governed by Partial Differential Equations. doi: 10.3182/20130925-3-FR-4043.00053.
• Ohlberger M, Rave S. 2013. ‘Nonlinear reduced basis approximation of parameterized evolution equations via the method of freezing.’ C. R. Acad. Sci. Paris, Ser. I 351: 901–906. doi: 10.1016/j.crma.2013.10.028.
• Henning P, Ohlberger M, Schweizer B. 2013. ‘Homogenization of the degenerate two-phase flow equations.’ Math. Models and Methods in Appl. Sciences 23, Nr. 12: 2323–2352. doi: 10.1142/S0218202513500334.
• Schöberl J, Lehrenfeld C. 2013. ‘Domain Decomposition Preconditioning for High Order Hybrid Discontinuous Galerkin Methods on Tetrahedral Meshes.’ In Advanced Finite Element Methods and Applications, edited by Apel Thomas, Steinbach Olaf, 27–56. Springer VDI Verlag.
• Lehrenfeld C, Reusken A. 2013. ‘Analysis of a DG-XFEM Discretization for a Class of Two-Phase Mass Transport Problems.’ SIAM J. Numer. Anal. 51: 958–983. doi: 10.1137/120875260.
• Aland S, Lehrenfeld C, Marschall H, Meyer C, Weller S. 2013. ‘Accuracy of Two-Phase Flow Simulations.’ In Proc. Appl. Math. Mech., 595–598.: Springer. doi: 10.1002/pamm.201310278.

2012

• Albrecht F, Haasdonk B, Kaulmann S, Ohlberger M. 2012. ‘The Localized Reduced Basis Multiscale Method.’ Contributed to the Algoritmy 2012, Conference on Scientific Computing, Vysoke Tatry, Podbanske, September 9-14, 2012, Vysoke Tatry, Podbanske.
• Bastian P, Berninger H, Dedner A, Engwer C, Henning P, Kornhuber R, Kröner D, Ohlberger M, Sander O, Schiffler G, Shokina N, Smetana K. 2012. ‘Adaptive Modelling of Coupled Hydrological Processes with Application in Water Management.’ In Progress in Industrial Mathematics at ECMI 2010, 561––567.: Springer,. doi: 10.1007/978-3-642-25100-9_65.
• Bernard-Champmartin A, Deriaz E, Hoch P, Samba G, Schaefer M. 2012. ‘Extension of centered hydrodynamical schemes to unstructured deforming conical meshes: the case of circles.’ In CEMRACS'11: Multiscale Coupling of Complex Models in Scientific Computing, 135–162.: ESAIM: Proceedings. doi: 10.1051/proc/201238008.
• Ohlberger M, Schaefer M. 2012. ‘A reduced basis method for parameter optimization of multiscale problems.’ In Submitted to Algoritmy 2012, Conference on Scientific Computing, Vysoke Tatry, Podbanske, September 9-14, 2012.
• Drohmann Martin , Haasdonk Bernard, Ohlberger, Mario. 2012. ‘Reduced Basis Model Reduction of Parametrized Two-Phase Flow in Porous Media.’ In 7th Vienna International Conference on Mathematical Modelling, 722–727. doi: 10.3182/20120215-3-AT-3016.00128.
• Ohlberger M. 2012. ‘Error control based model reduction for multiscale problems.’ In Proceedings of Algoritmy 2012, Conference on Scientific Computing, Vysoke Tatry, Podbanske, September 9-14, 2012, edited by Slovak University of Technology in Bratislava, Publishing House of STU, 1–10.
• Rave S. 2012. On Finitely Summable K-Homology Dissertationsschrift, Universität Münster.
• Lehrenfeld Christoph, Reusken Arnold. 2012. ‘Nitsche-XFEM with Streamline Diffusion Stabilization for a Two-Phase Mass Transport Problem.’ SIAM J. Sci. Comput. 34: 2740–2759. doi: 10.1137/110855235.
• Koutschan Christoph, Lehrenfeld Christoph, Schöberl Joachim. 2012. ‘Computer Algebra meets Finite Elements: an Efficient Implementation for Maxwells Equations.’ In Numerical and Symbolic Scientific Computing: Progress and Prospects, edited by Ulrich Langer PP, 105–122. Springer VDI Verlag. doi: 10.1007/978-3-7091-0794-2_6.

2011

• Ohlberger M, Smetana K. 2011. ‘A new Hierarchical Model Reduction-Reduced Basis technique for advection-diffusion-reaction problems.’ In Proceedings of the V International Conference on Adaptive Modeling and Simulation (ADMOS 2011) held in Paris, France, 6-8 June 2011, edited by Aubry D. et al., 343–354.: International Center for Numerical Methods in Engineering (CIMNE), Barcelona.
• Haasdonk B, Dihlmann M, Ohlberger M. 2011. ‘A Training Set and Multiple Bases Generation Approach for Parametrized Model Reduction Based on Adaptive Grids in Parameter Space.’ Mathematical and Computer Modelling of Dynamical Systems 2011, Nr. 17 (4): 423––442. doi: 10.1080/13873954.2011.547674.
• Henning P, Ohlberger M. 2011. ‘A Note on Homogenization of Advection-Diffusion Problems with Large Expected Drift.’ Zeitschrift für Analysis und ihre Anwendungen 2011, Nr. 30(3): 319––339. doi: 10.4171/ZAA/1437.
• Drohmann M, Haasdonk B, Ohlberger M. 2011. ‘Adaptive Reduced Basis Methods for Nonlinear Convection-Diffusion Equations.’ In Finite Volumes for Complex Applications VI - Problems & Perspectives, edited by Fort J. et al., 369––377.: Springer. doi: 10.1007/978-3-642-20671-9_39.
• Haasdonk B, Ohlberger M. 2011. ‘Efficient reduced models and a posteriori error estimation for parametrized dynamical systems by offline/online decomposition.’ Mathematical and Computer Modelling of Dynamical Systems 17, Nr. 2: 145––161. doi: 10.1080/13873954.2010.514703.
• Mikula K, Ohlberger M. 2011. ‘Inflow-Implicit/Outflow-Explicit scheme for solving advection equations.’ In Finite Volumes for Complex Applications VI - Problems & Perspectives, edited by Fort J. et al., 683––691.: Springer. doi: 10.1007/978-3-642-20671-9_72.
• Lehrenfeld Christoph. 2011. ‘Nitsche-XFEM for a Transport Problem in Two- Phase Incompressible Flows.’ In Proc. Appl. Math. Mech., 613–614.: Wiley. doi: 10.1002/pamm.201110296.

2010

• Dedner A, Klöfkorn R, Nolte M, Ohlberger M. 2010. ‘A generic interface for parallel and adaptive scientific computing: Abstraction principles and the DUNE-FEM module.’ Computing 90, Nr. 3-4: 165–196. doi: 10.1007/s00607-010-0110-3.
• Mikula K, Ohlberger M. 2010. ‘A New Level Set Method for Motion in Normal Direction Based on a Semi-Implicit Forward-Backward Diffusion Approach.’ SIAM Journal on Scientific Computing 32, Nr. 3: 1527––1544. doi: 10.1137/09075946X.
• Henning P, Ohlberger M. 2010. ‘The heterogeneous multiscale finite element method for advection-diffusion problems with rapidly oscillating coefficients and large expected drift.’ Networks and Heterogeneous Media 5, Nr. 4: 711––744. doi: 10.3934/nhm.2010.5.711.
• Mikula K, Ohlberger M. 2010. A New Inflow-Implicit/Outflow-Explicit Finite Volume Method for Solving Variable Velocity Advection Equations , 2010.
• Ohlberger M, Smetana K. 2010. A new problem adapted hierarchical model reduction technique based on reduced basis methods and dimensional splitting , 2010.
• Drohmann M, Haasdonk B, Ohlberger M. 2010. Reduced Basis Approximation for Nonlinear Parametrized Evolution Equations based on Empirical Operator Interpolation , 2010.
• Lehrenfeld Christoph. 2010. Hybrid Discontinuous Galerkin Methods for Incompressible Flow Problems.

2009

• Albrecht F. 2009. Local Discontinuous Galerkin Verfahren für die Stokes Gleichungen und Homogenisierung in porösen Medien (Diplomarbeit).
• Ohlberger M. 2009. ‘A review of a posteriori error control and adaptivity for approximations of nonlinear conservation laws.’ International Journal for Numerical Methods in Fluids 59, Nr. International Journal for Numerical Methods in Fluids: 333––354. doi: 10.1002/fld.1686.
• Henning P, Ohlberger M. 2009. A-posteriori error estimate for a heterogeneous multiscale finite element method for advection-diffusion problems with rapidly oscillating coefficients and large expected drift. , 2009.
• Haasdonk B, Ohlberger M. 2009. ‘Efficient reduced models for parametrized dynamical systems by offline/online decomposition.’.
• Drohmann M, Haasdonk B, Ohlberger M. 2009. ‘Reduced Basis Method for Finite Volume Approximation of Evolution Equations on Parametrized Geometries.’ Contributed to the Proceedings of ALGORITMY 2009.
• Haasdonk B, Ohlberger M. 2009. ‘Space-adaptive reduced basis simulation for time-dependent problems.’.
• Haasdonk B, Ohlberger M. 2009. ‘Reduced Basis Method for Explicit Finite Volume Approximations of Nonlinear Conservation Laws.’ In Hyperbolic problems: theory, numerics and applications. Providence, RI: American Mathematical Society.
• Henning P, Ohlberger M. 2009. ‘The heterogeneous multiscale finite element method for elliptic homogenization problems in perforated domains.’ Numer. Math. 113: 601–629. doi: 10.1007/s00211-009-0244-4.

2008

• Goldsmith F, Ohlberger M, Schumacher J, Steinkamp K, Ziegler C. 2008. ‘A non-isothermal PEM fuel cell model including two water transport mechanisms in the membrane.’ Journal of Fuel Cell Science and Technology 5, Nr. Journal of Fuel Cell Science and Technology: 5. doi: 10.1115/1.2822884.
• Haasdonk B, Ohlberger M. 2008. ‘Adaptive Basis Enrichment for the Reduced Basis Method Applied to Finite Volume Schemes.’ Contributed to the Finite Volumes for Complex Applications VI Problems & Perspectives: FVCA 6, Prague.
• Klöfkorn R, Kröner D, Ohlberger M. 2008. ‘Parallel adaptive simulation of PEM fuel cells.’ In Mathematics – Key Technology for the Future, edited by Krebs, Jäger, 235–249.
• Haasdonk B, Ohlberger M. 2008. ‘Reduced Basis Method for Finite Volume Approximations of Parametrized Linear Evolution Equations.’ M2AN Math. Model. Numer. Anal. 42, Nr. 2: 277–302. doi: 10.1051/m2an:2008001.
• Haasdonk B, Ohlberger M, Rozza G. 2008. ‘A reduced basis method for evolution schemes with parameter-dependent explicit operators.’ Electronic transactions on numerical analysis 32: 145–161.
• Dedner A, Ohlberger M. 2008. ‘A new $hp$-adaptive DG scheme for conservation laws based on error control.’ In Hyperbolic Problems: Theory, Numerics, Applications, edited by Benzoni-Gavage, Serre, 187––198. Berlin. doi: 10.1007/978-3-540-75712-2_15.
• Haasdonk B, Ohlberger M, Rozza G. 2008. ‘A reduced basis method for evolution schemes with parameter-dependent explicit operators.’ Electronic transactions on numerical analysis 32: 145––161.
• Klöfkorn R, Kröner D, Ohlberger M. 2008. ‘Parallel and adaptive simulation of fuel cells in 3d.’ In Computational science and high performance computing III, 69––81. Berlin: Springer VDI Verlag. doi: 10.1007/978-3-540-69010-8_7.

2007

• Haasdonk B, Ohlberger M. 2007. ‘Basis Construction for Reduced Basis Methods by Adaptive Parameter Grids.’.
• Fuhrmann J, Haasdonk B, Holzbecher E, Ohlberger M. 2007. ‘Guest Editorial for Special Issue on Modelling and Simulation of PEM-FC.’ Journal of Fuel Cell Science and Technology 2007, Nr. Journal of Fuel Cell Science and Technology.
• Klöfkorn R, Kröner D, Ohlberger M. 2007. ‘Parallel and adaptive simulaiton of fuel cells in 3D.’.
• Dedner A, Makridakis C, Ohlberger M. 2007. ‘Error control for a class of Runge-Kutta discontinuous Galerkin methods for nonlinear conservation laws.’ SIAM J. Numer. Anal. 45: 514–538.
• Ohlberger M, Schweizer B. 2007. ‘Modelling of interfaces in unsaturated porous media.’ Discrete Contin. Dyn. Syst. , Nr. Dynamical Systems and Differential Equations. Proceedings of the 6th AIMSInternational Conference, suppl.: 794––803.
• Henning P. 2007. Die Heterogene Mehrskalenmethode f\�r elliptische Differentialgleichungen in perforierten Gebieten.
• Rave S. 2007. Über die Entscheidbarkeit gewisser Prädikate in der Theorie der C*-Algebren. Münster.

2006

• Burri A, Dedner A, Diehl D, Klöfkorn R, Ohlberger M. 2006. ‘A general object oriented framework for discretizing nonlinear evolution equations.’, 93.
• Burri A, Dedner A, Klöfkorn R, Ohlberger M. 2006. ‘An efficient implementation of an adaptive and parallel grid in DUNE.’, 91.
• Haasdonk B, Ohlberger M. 2006. Reduced Basis Method for Finite Volume Approximations of Parametrized Evolution Equations , 2006.
• Ohlberger M, Vovelle J. 2006. ‘Error estimate for the approximation of nonlinear conservation laws on bounded domains by the finite volume method.’ Math. Comp. 75: 113–150.

2005

• Dedner A, Makridakis C, Ohlberger M. 2005. ‘A new stable discontinuous Galerkin approximation for non-linear conservation laws on adaptively refined grids.’, 1095 – 1099.
• Ohlberger M. 2005. ‘A posterior error estimates for the heterogenoeous mulitscale finite element method for elliptic homogenization problems.’ SIAM Multiscale Mod. Simul. 4, Nr. 1: 88 – 114.
• Ohlberger M. 2005. ‘Error control for approximations of non-linear conservation laws.’, 85 – 100.
• Bastian P, Droske M, Engwer C, Klöfkorn R, Neubauer T, Ohlberger M, Rumpf M. 2005. ‘Towards a unified framework for scientific computing.’, 167 – 174.
• Ohlberger M. 2005. ‘A posteriori error estimates for the heterogeneous multiscale finite element method for elliptic homogenization problems.’ Multiscale Model. Simul. 4: 88–114.

2004

• Barth T, Ohlberger M. 2004. ‘Finite volume methods: foundation and analysis.’, 439 –474.
• Ohlberger M. 2004. ‘Higher order finite volume methods on selfadaptive grids for convection dominated reactive transport problems in porous media.’ Comp. Vis. Sci. 7, Nr. 1: 41–51.

2003

• Kröner D, Küther M, Ohlberger M, Rohde C. 2003. ‘A posteriori error estimates and adaptive methods for hyperbolic and convection dominates parabolic conservation laws.’, 289 – 306.
• Küther M, Ohlberger M. 2003. ‘Adaptive second order central schemes on unstructured staggered grids.’.
• Haasdonk B, Ohlberger M, Rumpf M, Schmidt A, Siebert K. 2003. ‘Multiresolution Visualization of Higher Order Adaptive Finite Element Simulations.’ Computing 70, Nr. Computing: 181––204.

2002

• Herbin R, Ohlberger M. 2002. ‘A posteriori error estimate for finite volume approximations of convection diffusion problems.’.
• Ohlberger M, Rohde C. 2002. ‘Adaptive finite volume approximations for weakly coupled convection dominated parabolic systems.’ IMA J. Numer. Anal. 22, Nr. 2: 253 –280.
• Bürkle D, Ohlberger M. 2002. ‘Adaptive finite volume methods for displacement problems in porous media.’ Comp. Vis. Sci. 5, Nr. 2: 95 – 106.
• Klöfkorn R, Kröner D, Ohlberger M. 2002. ‘Local adaptive methods for convection dominated problems.’ International Journal for Numerical Methods in Fluids 40, Nr. 1-2: 79 – 91.
• Karlsen KH, Ohlberger M. 2002. ‘A note on the uniqueness of entropy solutions of nonlinear degenerate parabolic equations.’ J. Math. Anal. Appl. 275: 439–458.

2001

• Ohlberger M. 2001. ‘A posteriori error estimate for finite volume approximations to singularly perturbed nonlinear convection-diffusion equations.’ Numerische Mathematik 87, Nr. 4: 737 – 761.
• Ohlberger M. 2001. A posteriori error estimates and adaptive methods for convection dominated transport processes.
• Haasdonk B, Ohlberger M, Rumpf M, Schmidt A, Siebert K. 2001. h-p-Multiresolution Visualization of Adaptive Finite Element Simulations , 2001.
• Ohlberger M. 2001. ‘A posteriori error estimates for vertex centered finite volume approximations of convection-diffusion-reaction equations.’ M2AN Math. Model. Numer. Anal. 35: 355–387.

2000

• Kröner D, Ohlberger M. 2000. ‘A posteriori error estimates for upwind finite volume schemes for nonlinear conservation laws in multidimensions.’ Math. Comp. 69: 25–39.

1999

• Geßner T, Haasdonk B, Kende R, Lenz M, Metscher M, Neubauer R, Ohlberger M, Rosenbaum W, Rumpf M, Schwörer R, Spielberg M, Weikard U. 1999. A Procedural Interface for Multiresolutional Visualization of General Numerical Data , 1999.
• Ohlberger M. 1999. ‘Adaptive mesh refinement for single and two phase flow problems in porous media.’.
• Ohlberger M, Rumpf M. 1999. ‘Adaptive protection operators in multiresolution scientific visualizations.’ IEEE Transactions on Visualization and Computer Graphics 5, Nr. 1: 74 – 94.
• Ohlberger M. 1999. ‘Mixed finite element-finte volume methods for two-phase flow in porous media.’.
• Grüne L, Metscher M, Ohlberger M. 1999. ‘On numerical algorithm and interactive visualization for optimal control problems.’ Comp. Visual. Sci. 1, Nr. 4: 221 – 229.

1998

• Ohlberger M, Schwörer R. 1998. Challenges in Fluid Dynamics.

1997

• Ohlberger M. 1997. ‘Convergence of a mixed finite element-finite volume method for the two phase flow in porous media.’ East-West journal of numerical mathematics 5, Nr. 3: 183 – 210.
• Neubauer R, Ohlberger M, Rumpf M, Schwörer R. 1997. ‘Efficient visualization of large-scale data on hierarchical meshes.’.
• Ohlberger M, Rumpf M. 1997. ‘Hierarchical and adaptive visualization on nested grids.’ Computing 59, Nr. Computing: 365 – 385.