Publikationen

2022

• 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 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. doi: 10.11128/arep.17.a17155.

2021

• 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.

2019

• 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.

2018

• 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.

2017

• 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.

2016

• 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.

2015

• 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.

2014

• 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.

2013

• 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.

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.

2009

• Albrecht F. 2009. Local Discontinuous Galerkin Verfahren für die Stokes Gleichungen und Homogenisierung in porösen Medien (Diplomarbeit).