J. Schmalfuss, C. Riethmüller, M. Altenbernd, K. Weishaupt, and D. Göddeke. Presentations and Plenary videos to 9th edition of the International Conference on Computational Methods for Coupled Problems in Science and Engineering (COUPLED PROBLEMS 2021), Barcelona, Scipedia, S.L., (2021)
F. Weinhardt, H. Class, S. Vahid Dastjerdi, N. Karadimitriou, D. Lee, and H. Steeb. Dataset, (2021)Related to: Weinhardt, F.; Class, H.; Vahid Dastjerdi, S.; Karadimitriou, N.; Lee, D.; Steeb, H.(2021). Experimental Methods and Imaging for Enzymatically Induced Calcite Precipitation in a microfluidic cell. Accepted in Water Resources Research. doi: 10.1029/2020WR029361.
H. Hsueh. Dataset, (2021)Related to: Han-Fang Hsueh, Anneli Guthke, Thomas Wöhling, Wolfgang Nowak: Diagnosis of model-structural errors with a sliding time-window Bayesian analysis. In: Water Resource Research (submitted). arXiv: 2107.09399.
T. Praditia. Dataset, (2020)Related to: Praditia, T., Walser, T., Oladyshkin, S. and Nowak, W.: Improving Thermochemical Energy Storage dynamics forecast with Physics-Inspired Neural Network architecture. Energies 2020.
I. Banerjee. Dataset, (2021)Related to: Banerjee, I., Guthke, A., Van de Ven, C. J. C., Mumford, K. G. & Nowak, W. (2021). Overcoming the Model-Data-Fit Problem in Porous Media: A Quantitative Method to Compare Invasion-Percolation Models to High-Resolution Data. Water Resources Research, 57, e2021WR029986. doi: 10.1029/2021WR029986.
A. Gonzalez-Nicolas Alvarez. Dataset, (2021)Related to: Gonzalez-Nicolas, A.; Schwientek, M.; Sinsbeck, M; Nowak, W. Characterization of export regimes in concentration-discharge plots via an advanced time-series model and event-based sampling strategies. Water 2021, 13, 1723. doi: 10.3390/w13131723.
A. Gonzalez-Nicolas Alvarez. Software, (2021)Related to: Gonzalez-Nicolas, A.; Schwientek, M.; Sinsbeck, M; Nowak, W. Characterization of export regimes in concentration-discharge plots via an advanced time-series model and event-based sampling strategies. Water 2021, 13, 1723. doi: 10.3390/w13131723.
M. Kelm, C. Bringedal, and B. Flemisch. Dataset, (2023)Related to: Kelm, M., Gärttner, S., Bringedal, C. et al. Comparison study of phase-field and level-set method for three-phase systems including two minerals. Comput Geosci 26, 545-570 (2022). doi: 10.1007/s10596-022-10142-w.
S. Schulz, C. Bringedal, and S. Ackermann. Dataset, (2021)Related to: SimTech Project work "Herleitung reduzierter Modelle einer Zweiphasenströmung zwischen parallelen Platten mit Slip-Bedingungen".
S. Vahid Dastjerdi, H. Steeb, M. Ruf, D. Lee, F. Weinhardt, N. Karadimitriou, and H. Class. Dataset, (2021)Related to: Weinhart, F., Class, H., Vahid Dastjerdi, S., Karadimitriou, N., Lee, D., & Steeb, H. (2021). Experimental Methods and Imaging for Enzymatically Induced Calcite Precipitation in a microfluidic cell. Water Resources Research, Technical Reports: Methods. doi: 10.1029/2020WR029361.
M. Takamoto, T. Praditia, R. Leiteritz, D. MacKinlay, F. Alesiani, D. Pflüger, and M. Niepert. Dataset, (2022)Related to: Takamoto, M., Praditia, T., Leiteritz, R., MacKinlay, D., Alesiani, F., Pflüger, D. and Niepert, M.: PDEBench: An Extensive Benchmark for Scientific Machine Learning. submitted to the 36th Conference on Neural Information Processing Systems (NeurIPS 2022) Track on Datasets and Benchmarks. arXiv: 2210.07182.
T. Praditia. Dataset, (2020)Related to: Praditia, T., Walser, T., Oladyshkin, S. and Nowak, W.: Improving Thermochemical Energy Storage dynamics forecast with Physics-Inspired Neural Network architecture. Energies 2020.
T. Praditia, M. Karlbauer, S. Otte, S. Oladyshkin, M. Butz, and W. Nowak. Dataset, (2022)Related to: Praditia, T., Karlbauer, M., Otte, S., Oladyshkin, S., Butz, M.V., Nowak, W.: Learning Groundwater Contaminant Diffusion-Sorption Processes with a Finite Volume Neural Network. Earth and Space Science Open Archive (2022). doi: 10.1002/essoar.10511934.1.
F. Weinhardt, J. Deng, H. Steeb, and H. Class. Dataset, (2022)Related to: Weinhardt, F.; Deng, J.; Hommel, J.; Vahid Dastjerdi, S.; Gerlach, R.; Steeb, H.; Class, H. (2022). Spatiotemporal Distribution of Precipitates and Mineral Phase Transition During Biomineralization Affect Porosity–Permeability Relationships. Transport in Porous Media 143, 527–549 (2022). doi: 10.1007/s11242-022-01782-8.
M. Ruf, J. Hommel, and H. Steeb. Dataset, (2022)Related to: Gehring, L., Weinhardt, F., Ruf, M., Hommel, J. & Steeb, H. (2022). Effects of enzymatically induced carbonate precipitation on capillary pressure-saturation relations. Minerals, 12(10), 1186. doi: 10.3390/min12101186.
M. Ruf, J. Hommel, and H. Steeb. Dataset, (2022)Related to: Gehring, L., Weinhardt, F., Ruf, M., Hommel, J. & Steeb, H. (2022). Effects of enzymatically induced carbonate precipitation on capillary pressure-saturation relations. Minerals, 12(10), 1186. doi: 10.3390/min12101186.
M. Ruf, J. Hommel, and H. Steeb. Dataset, (2022)Related to: Gehring, L., Weinhardt, F., Ruf, M., Hommel, J. & Steeb, H. (2022). Effects of enzymatically induced carbonate precipitation on capillary pressure-saturation relations. Minerals, 12(10), 1186. doi: 10.3390/min12101186.
M. Takamoto, T. Praditia, R. Leiteritz, D. MacKinlay, F. Alesiani, D. Pflüger, and M. Niepert. Dataset, (2022)Related to: Takamoto, M., Praditia, T., Leiteritz, R., MacKinlay, D., Alesiani, F., Pflüger, D. and Niepert, M.: PDEBench: An Extensive Benchmark for Scientific Machine Learning. submitted to the 36th Conference on Neural Information Processing Systems (NeurIPS 2022) Track on Datasets and Benchmarks.