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 Schwerpunktprogramm 2089 “Rhizosphere Spatiotemporal Organisation – a Key to Rhizosphere Functions”):
Mehrskalenmodellierung mit veränderlicher Mikrostruktur: Ein Ansatz
zur Emergenz in der Rhizosphäre mit effektiven Bodenfunktionen
Dr. Alexander Prechtel; Dr. Raphael Schulz
(01.02.2019 - 31.01.2022)


PPP Frankreich 2019 Phase I
Prof. Dr. Martin Burger
(01.01.2019 - 31.12.2020)


(Nonlocal Methods for Arbitrary Data Sources):
NoMADS: Nonlocal Methods for Arbitrary Data Sources
Prof. Dr. Martin Burger
(01.10.2018 - 28.02.2022)


SBCL-Vektor: Implementation von Vektoroperationen für SBCL
Marco Heisig; PD Dr. Nicolas Neuß
(10.07.2018 - 31.03.2019)


Buchgutscheine: Innovationsfonds 2017: Urkunden und Buchgutscheine für gute Leistungen in Anfängervorlesungen
PD Dr. Nicolas Neuß
(01.07.2017 - 30.09.2020)



Publikationen (Download BibTeX)

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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
Neuß, N. (2018). Interactive flow simulation with Common Lisp. In EPITA (Eds.), Proceedings of the European Lisp Symposium 2018 (pp. 78-79). Marbella.
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
Bungert, L., Ehrhardt, M.J., Coomes, D., Rasch, J., Reisenhofer, R., & Schönlieb, C.-B. (2018). Blind image fusion for hyperspectral imaging with the directional total variation. Inverse Problems, 34(4). https://dx.doi.org/10.1088/1361-6420/aaaf63
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). Dynamic inverse problems: modelling-regularization-numerics Preface. Inverse Problems, 34(4). https://dx.doi.org/10.1088/1361-6420/aab0f5
Burger, M. (2018). Pattern formation of a nonlocal, anisotropic interaction model. Mathematical Models & Methods in Applied Sciences, 28(3), 409-451. https://dx.doi.org/10.1142/S0218202518500112
Fried, M., Aizinger, V., & Bungert, L. (2018). Comparison of two local discontinuous Galerkin formulations for the subjective surfaces problem. Computing and Visualization in Science. https://dx.doi.org/10.1007/s00791-018-0291-4
Totsche, K.U., Amelung, W., Gerzabek, M.H., Guggenberger, G., Klumpp, E., Knief, C.,... Kögel-Knabner, I. (2018). Microaggregates in Soils. Journal of Plant Nutrition and Soil Science, 181(1), 104-136. https://dx.doi.org/10.1002/jpln.201600451
Frank, F., Liu, C., Alpak, F.O., & Rivière, B. (2018). A finite volume/discontinuous Galerkin method for the advective Cahn–Hilliard equation with degenerate mobility on porous domains stemming from micro-CT imaging. Computational Geosciences, 22(2), 543–563. https://dx.doi.org/10.1007/s10596-017-9709-1
Burger, M. (2018). Dynamic SPECT reconstruction with temporal edge correlation. Inverse Problems, 34(1). https://dx.doi.org/10.1088/1361-6420/aa9a94
Marx, A., Conrad, M., Aizinger, V., Prechtel, A., van Geldern, R., & Barth, J. (2018). Groundwater data improve modelling of headwater stream CO2 outgassing with a stable DIC isotope approach. Biogeosciences, 15(10), 3093-3106. https://dx.doi.org/10.5194/bg-15-3093-2018
Jaust, A., Reuter, B., Aizinger, V., Schütz, J., & Knabner, P. (2018). FESTUNG: A MATLAB/GNU Octave toolbox for the discontinuous Galerkin method. Part III: Hybridized discontinuous Galerkin (HDG) formulation. Computers & Mathematics With Applications, 75(12), 4505-4533. https://dx.doi.org/10.1016/j.camwa.2018.03.045
Hajduk, H., Hodges, B.R., Aizinger, V., & Reuter, B. (2018). Locally Filtered Transport for computational efficiency in multi-component advection-reaction models. ENVIRON MODELL SOFTW , 102, 185-198. https://dx.doi.org/10.1016/j.envsoft.2018.01.003
Himmelsbach, D., Neuss-Radu, M., & Neuß, N. (2018). Mathematical modelling and analysis of nanoparticle gradients induced by magnetic fields. Journal of Mathematical Analysis and Applications, 461(2), 1544-1560. https://dx.doi.org/10.1016/j.jmaa.2017.12.026
Rupp, A., Knabner, P., & Dawson, C. (2018). A local discontinuous Galerkin scheme for Darcy flow with internal jumps. Computational Geosciences, 22(4), 1149-1159. https://dx.doi.org/10.1007/s10596-018-9743-7
Aizinger, V., Rupp, A., Schütz, J., & Knabner, P. (2018). Analysis of a mixed discontinuous Galerkin method for instationary Darcy flow. Computational Geosciences, 22(1), 179-194. https://dx.doi.org/10.1007/s10596-017-9682-8
Ray, N., Rupp, A., Schulz, R., & Knabner, P. (2018). Old and New Approaches Predicting the Diffusion in Porous Media. Transport in Porous Media, 124(3), 803-824. https://dx.doi.org/10.1007/s11242-018-1099-x
Wacker, P.K., Blömker, D., & Schillings, C. (2018). A STRONGLY CONVERGENT NUMERICAL SCHEME FROM ENSEMBLE KALMAN INVERSION. SIAM Journal on Numerical Analysis, 56(4), 2537-2562. https://dx.doi.org/10.1137/17M1132367
Knodel, M. (2018). Quantitative Analysis of Hepatitis C NS5A Viral Protein Dynamics on the ER Surface. Viruses-Basel, 10(1). https://dx.doi.org/10.3390/v10010028

Zuletzt aktualisiert 2019-24-04 um 10:19