Lehrstuhl für Angewandte Mathematik

Adresse:
Cauerstraße 11
91058 Erlangen



Untergeordnete Organisationseinheiten

Professur für Angewandte Mathematik
Professur für Angewandte Mathematik
Professur für Angewandte Mathematik (Mathematische Modellierung)


Forschungsbereiche

Multicomponent reactive transport in natural porous media
Multiscale modeling, analysis and simulation of reaction-diffusion processes in porous media. Application to carbohydrat
Geophysical free surface flows
Multiphase flow in natural porous media
Emergence in natural porous media
Stochastic modeling of transport processes in porous media


Forschungsprojekt(e)

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(DFG RU 2179 “MAD Soil - Microaggregates: Formation and turnover of the structural building blocks of soils”):
Mechanistische Modellierung der Formation und Konsolidierung von Mikroaggregaten in Böden
Dr. Alexander Prechtel; Dr. Nadja Ray
(01.01.2016 - 31.12.2019)


Distributed High Performance Computing in Common Lisp
Prof. Dr. Eberhard Bänsch; PD Dr. Nicolas Neuß
(01.10.2015 - 31.03.2016)


DAAD Austauschprogramm: PPP Finnland 2017: Bayesian Inverse Problems in Banach Space
Prof. Dr. Martin Burger
(25.01.2015 - 31.12.2017)


LifeInverse: Variational Methods for Dynamic Inverse Problems in the Life Sciences
Prof. Dr. Martin Burger
(01.03.2014 - 28.02.2019)


Implementierung und Optimierung von Stencil-Operationen auf gestaffelten hierarchischen Gittern
Prof. Dr. Eberhard Bänsch; PD Dr. Nicolas Neuß
(01.06.2013 - 01.10.2014)



Publikationen (Download BibTeX)

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Hajduk, H., Kuzmin, D., & Aizinger, V. (2019). New directional vector limiters for discontinuous Galerkin methods. Journal of Computational Physics, 384, 308-325. https://dx.doi.org/10.1016/j.jcp.2019.01.032
Reuter, B., Rupp, A., Aizinger, V., & Knabner, P. (2019). Discontinuous Galerkin method for coupling hydrostatic free surface flows to saturated subsurface systems. Computers & Mathematics With Applications, 77(9), 2291-2309. https://dx.doi.org/10.1016/j.camwa.2018.12.020
Schulz, R. (2019). Biofilm modeling in evolving porous media with Beavers-Joseph condition. ZAMM - Zeitschrift für angewandte Mathematik und Mechanik, 99(3). https://dx.doi.org/10.1002/zamm.201800123
Burger, M., Korolev, Y., & Rasch, J. (2019). Convergence rates and structure of solutions of inverse problems with imperfect forward models. Inverse Problems, 35(2). https://dx.doi.org/10.1088/1361-6420/aaf6f5
Brunner, F., & Knabner, P. (2019). A global implicit solver for miscible reactive multiphase multicomponent flow in porous media. Computational Geosciences, 23(1), 127-148. https://dx.doi.org/10.1007/s10596-018-9788-7
Knodel, M., Targett-Adams, P., Grillo, A., Herrmann, E., & Wittum, G. (2019). Advanced Hepatitis C Virus Replication PDE Models within a Realistic Intracellular Geometric Environment. International Journal of Environmental Research and Public Health, 16(3). https://dx.doi.org/10.3390/ijerph16030513
Liu, C., Frank, F., & Rivière, B. (2019). Numerical error analysis for nonsymmetric interior penalty discontinuous Galerkin method of Cahn–Hilliard equation. Numerical Methods For Partial Differential Equations. https://dx.doi.org/10.1002/num.22362
Bungert, L., Burger, M., & Tenbrinck, D. (2019). Computing Nonlinear Eigenfunctions via Gradient Flow Extinction. (Unpublished, Accepted).
Bungert, L., & Burger, M. (2019). Solution paths of variational regularization methods for inverse problems. (Unpublished, In review).
Bungert, L., Burger, M., Chambolle, A., & Novaga, M. (2019). Nonlinear Spectral Decompositions by Gradient Flows of One-Homogeneous Functionals. (Unpublished, Submitted).
Gahn, M., Neuss-Radu, M., & Knabner, P. (2018). EFFECTIVE INTERFACE CONDITIONS FOR PROCESSES THROUGH THIN HETEROGENEOUS LAYERS WITH NONLINEAR TRANSMISSION AT THE MICROSCOPIC BULK-LAYER INTERFACE. Networks and Heterogeneous Media, 13(4), 609-640. https://dx.doi.org/10.3934/nhm.2018028
Föcke, J., Baumgarten, D., & Burger, M. (2018). The inverse problem of magnetorelaxometry imaging. Inverse Problems, 34(11). https://dx.doi.org/10.1088/1361-6420/aadbbf
Mu, X., Frank, F., Rivière, B., Alpak, F.O., & Chapman, W.G. (2018). Mass-conserved density gradient theory model for nucleation process. Industrial & Engineering Chemistry Research. https://dx.doi.org/10.1021/acs.iecr.8b03389
Frank, F., Liu, C., Alpak, F.O., Berg, S., & Rivière, B. (2018). Direct numerical simulation of flow on pore-scale images using the phase-field method. Spe Journal, 23(5), 1–18. https://dx.doi.org/10.2118/182607-PA
Rupp, A., Totsche, K.U., Prechtel, A., & Ray, N. (2018). Discrete-Continuum Multiphase Model for Structure Formation in Soils Including Electrostatic Effects. Frontiers in Environmental Science, 6. https://dx.doi.org/10.3389/fenvs.2018.00096
Burger, M. (2018). Dynamic MRI reconstruction from undersampled data with an anatomical prescan. Inverse Problems, 34(7). https://dx.doi.org/10.1088/1361-6420/aac3af
Alpak, F.O., Samardžić, A., & Frank, F. (2018). A distributed parallel direct simulator for pore-scale two-phase flow on digital rock images using a finite difference implementation of the phase-field method. Journal of Petroleum Science and Engineering, 166, 806–824. https://dx.doi.org/10.1016/j.petrol.2017.11.022
Reips, L., Burger, M., & Engbers, R. (2018). Towards dynamic PET reconstruction under flow conditions: Parameter identification in a PDE model. Journal of Inverse and Ill-posed Problems, 26(2), 185-200. https://dx.doi.org/10.1515/jiip-2015-0016
Burger, M. (2018). Sparsity-promoting and edge-preserving maximum a posteriori estimators in non-parametric Bayesian inverse problems. Inverse Problems, 34(4). https://dx.doi.org/10.1088/1361-6420/aaacac
Burger, M. (2018). Dynamic inverse problems: modelling-regularization-numerics Preface. Inverse Problems, 34(4). https://dx.doi.org/10.1088/1361-6420/aab0f5

Zuletzt aktualisiert 2018-31-08 um 23:50