SDL Engineering for Energy and Mobility
The Simulation and Data Life Cycle Lab (shortly SimDataLab or SDL) "Engineering for Energy and Mobility" is a team of researchers at SCC which works within the strategic framework of the National high-performance computing alliance. The SDL is established to meet the constantly evolving supercomputing and data-research needs of SCC-users in the fields of Energy and Mobility which represent two scientific topics of a high priority for KIT and for its Energy Centrum.
The main goal of the SDL is to support and strengthen the methodological competence of the engineering community in using supercomputing methods and related data management for research problems in energy and mobility. In order to achieve the above goal, two groups of scientists within SCC will join their expertise - one group with the main background in scientific computing and mathematics and one group with the main focus on data research and data analytics.
Projects
Project 1: NHR@KIT - Collaboration with University of Rostock
Project title:
Development and validation of a hybrid grid/particle method for turbulent flows supported by high performance computations with OpenFOAM
Cooperation with:
Prof. Nikolai Kornev (University of Rostock), Faculty of Mechanical Engineering and Marine Technology, Chair of Modelling and Simulation
Duration:
3 years
Coordination within SCC:
Dr.-Ing. J.A. Denev (SCC-PI: Prof. Martin Frank)
Short description:
The main goal of the present project is the further development and validation of a new computational fluid dynamics (CFD) method using a combination of grid-free (particles) and grid-based techniques. A fundamental assumption of this novel approach is the decomposition of any physical quantity into the grid based (large scale) and the fine scale parts, whereas large scales are resolved on the grid and fine scales are represented by particles. Dynamics of large and fine scales is calculated from two coupled transport equations one of which is solved on the grid whereas the second one utilizes the Lagrangian grid free Vortex Particle Method (VPM).
Application areas:
These problems include external flow problems, e.g. flows around vehicles like ships, cars, trucks or airplanes with a strong relation to energy (energy savings) and mobility. Particularly, the new hybrid method will be utilized for the prediction of efficiency and design of new energy saving devices (ESD) for model and real scale ships. ESD allow to reduce the delivered power up to ten percent.
Open source software:
OpenFOAM
Project 2: NHR@KIT - Collaboration with Engler-Bunte Institute and Institute for Piston Engines at KIT
Project title:
GPU-based machine learning methods to develop predictive models for estimation of exhaust gas properties from internal combustion engines during cold starts from real-world experimental data
Cooperation with:
Prof. Dr.-Ing. Dimosthenis Trimis (KIT, Engler-Bunte Institute, Combustion Division) and Prof. Dr. sc.-techn. Thomas Koch (KIT, Institute for Piston Engines)
Duration:
3 years
Coordination within SCC:
Dr.-Ing. J.A. Denev (SCC-PI: Prof. Martin Frank)
Short description:
Through extensive experiments large data sets have been obtained recently on internal combustion engine performance at cold starts and first few driving kilometers. The data sets contain measurements of more than 1000 parameters recorded simultaneously at steps of 0.1 seconds comprising among other engine performance parameters, detailed multi-component composition of the exhaust gas as well as corresponding properties of nanometer-sized particles compiled from electron microscopic images. The objective of the project is to apply machine learning (ML) methods to this inexhaustible amount of data to develop models capable of predicting the exhaust gas composition including particulate matter concentrations and nanostructural/molecular properties during variable non-stationary cold start conditions.
Application areas:
Bringing together the data from the different experimental and analytical techniques of both the engine parameters and the exhaust gas composition from the investigated engines will result in ML-derived predictive models and lead to a better understanding of the fundamental influencing parameters on pollutant formation. This will help to design intelligent engine operating strategies that can be employed for future biofuel and reFuel based engines.
Open source software:
HeAT (Helmholtz Analytics Toolkit) library
OpenFOAM
Publications SDL-EEM
Aversa, R.; Azmi, E.; Fischer, M.; Götz, M.
2024, May 2. Strategic Advisory Board (SAB) meeting for the Helmholtz Program EDF (2024), Karlsruhe, Germany, May 2, 2024
Grigorov, E.; Kirov, B.; Denev, J. A.; Galabov, V.
2023. 2023 International Scientific Conference on Computer Science (COMSCI), Sozopol, 18th-20th September 2023, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/COMSCI59259.2023.10315880
Kornev, N.; Darji, J.; Tofighian, H.; Denev, J. A.
2023. Proceedings of the 10th International Conference on Vortex Flow Mechanics (ICVFM 2023)
Markov, D.; Grigorov, E.; Kirov, B.; Denev, J. A.; Galabov, V.; Marinov, M. B.
2023. Micro, 3 (2), 537–548. doi:10.3390/micro3020036
Zhu, J.; Zirwes, T.; Zhang, F. C.; Li, Z. J.; Zhang, Y.; Pan, J. F.
2024. Chemical Engineering Science, 283, 119391. doi:10.1016/j.ces.2023.119391
Zirwes, T.; Sontheimer, M.; Zhang, F.; Abdelsamie, A.; Pérez, F. E. H.; Stein, O. T.; Im, H. G.; Kronenburg, A.; Bockhorn, H.
2023. Flow, Turbulence and Combustion, 111 (2), 567–602. doi:10.1007/s10494-023-00449-8
Kaiser, T. L.; Varillon, G.; Polifke, W.; Zhang, F.; Zirwes, T.; Bockhorn, H.; Oberleithner, K.
2023. Combustion and Flame, 253, Art.-Nr.: 112778. doi:10.1016/j.combustflame.2023.112778
Kaddar, D.; Steinhausen, M.; Zirwes, T.; Bockhorn, H.; Hasse, C.; Ferraro, F.
2022. Proceedings of the Combustion Institute, 39 (2), 2199–2208. doi:10.1016/j.proci.2022.08.060
Steinhausen, M.; Zirwes, T.; Ferraro, F.; Scholtissek, A.; Bockhorn, H.; Hasse, C.
2022. Proceedings of the Combustion Institute, 39 (2), 2149–2158. doi:10.1016/j.proci.2022.09.026
Zirwes, T.; Zhang, F.; Bockhorn, H.
2022. Proceedings of the Combustion Institute, 39 (2), 2349–2358. doi:10.1016/j.proci.2022.07.187
Eckart, S.; Pio, G.; Zirwes, T.; Zhang, F.; Salzano, E.; Krause, H.; Bockhorn, H.
2023. Fuel, 335, Art.-Nr.: 126929. doi:10.1016/j.fuel.2022.126929
Tavakkol, S.; Zirwes, T.; Denev, J. A.; Bockhorn, H.; Stapf, D.
2023. Thermal Science and Engineering Progress, 38, Article no: 101545. doi:10.1016/j.tsep.2022.101545
Zhang, F.; Zirwes, T.; Häber, T.; Bockhorn, H.; Trimis, D.; Suntz, R.; Stapf, D.
2022. Proceedings of the Combustion Institute, 39 (2), 2037–2045. doi:10.1016/j.proci.2022.10.010
Zhang, F.
2022, July. 39th International Symposium on Combustion (2022), Vancouver, Canada, July 24–29, 2022
Zhang, F.; Zirwes, T.; Wachter, S.; Jakobs, T.; Habisreuther, P.; Zarzalis, N.; Trimis, D.; Kolb, T.; Bockhorn, H.; Stapf, D.
2023. International journal of multiphase flow, 158, Art.-Nr.: 104304. doi:10.1016/j.ijmultiphaseflow.2022.104304
Wang, Y.; Han, W.; Zirwes, T.; Zhang, F.; Bockhorn, H.; Chen, Z.
2022. Proceedings of the Combustion Institute, 39 (2), 1515–1524. doi:10.1016/j.proci.2022.07.024
Zhang, F.; Zirwes, T.; Wang, Y.; Chen, Z.; Bockhorn, H.; Trimis, D.; Stapf, D.
2022. Physics of Fluids, 34 (8), Art.-Nr.: 085121. doi:10.1063/5.0098883
Casel, M.; Oberleithner, K.; Zhang, F.; Zirwes, T.; Bockhorn, H.; Trimis, D.; Kaiser, T. L.
2022. Combustion and Flame, 236, Art.-Nr.: 111695. doi:10.1016/j.combustflame.2021.111695
Tavakkol, S.
2022. Proceedings of the 13th European Conference on Industrial Furnaces and Boilsers (INFUB)
Zhang, F.; Kurjata, M.; Sebbar, N.; Zirwes, T.; Fedoryk, M.; Harth, S.; Wang, R.; Habisreuther, P.; Trimis, D.; Bockhorn, H.
2022. Energy and Fuels, 36 (7), 4094–4106. doi:10.1021/acs.energyfuels.1c04007
Steinhausen, M.; Zirwes, T.; Ferraro, F.; Popp, S.; Zhang, F.; Bockhorn, H.; Hasse, C.
2022. International Journal of Heat and Fluid Flow, 93, Art.-Nr.: 108913. doi:10.1016/j.ijheatfluidflow.2021.108913
Zirwes, T.; Zhang, F.; Denev, J. A.; Habisreuther, P.; Bockhorn, H.; Trimis, D.
2021. High Performance Computing in Science and Engineering ’19 – Transactions of the High Performance Computing Center, Stuttgart (HLRS) 2019. Ed.: W. Nagel, 225–239, Springer International Publishing. doi:10.1007/978-3-030-66792-4_16
Wen, X.; Zirwes, T.; Scholtissek, A.; Böttler, H.; Zhang, F.; Bockhorn, H.; Hasse, C.
2022. Combustion and Flame, 238, Art.Nr. 111808. doi:10.1016/j.combustflame.2021.111808
Wen, X.; Zirwes, T.; Scholtissek, A.; Böttler, H.; Zhang, F.; Bockhorn, H.; Hasse, C.
2022. Combustion and Flame, 238, Art.Nr. 111815. doi:10.1016/j.combustflame.2021.111815
Hagen, A.; Jackson, S.; Kahn, J.; Strube, J.; Haide, I.; Pazdernik, K.; Hainje, C.
2021
Coquelin, D.; Debus, C.; Götz, M.; Lehr, F. von der; Kahn, J.; Siggel, M.; Streit, A.
2021. Springer. doi:10.21203/rs.3.rs-832355/v1
Mayer, Z.; Kahn, J.; Hou, Y.; Volk, R.
2021. EG-ICE 2021 Workshop on Intelligent Computing in Engineering. Ed.: Jimmy Abualdenien, André Borrmann, Lucian-Constantin Ungureanu, Timo Hartmann, 497–507, Universitätsverlag der TU Berlin
Mayer, Z.; Hou, Y.; Kahn, J.; Beiersdörfer, T.; Volk, R.
2021, May 18. doi:10.5281/zenodo.4767772
Tavakkol, S.; Zirwes, T.; Denev, J. A.; Jamshidi, F.; Weber, N.; Bockhorn, H.; Trimis, D.
2021. Renewable & sustainable energy reviews, 139, Art.-Nr.: 110582. doi:10.1016/j.rser.2020.110582
Pitchurov, G.; Gromke, C.; Denev, J. A.; Cesar Cunha Galeazzo, F.
2020. E3S Web of Conferences, 207, Art.-Nr.: 02010. doi:10.1051/e3sconf/202020702010
Götz, M.; Debus, C.; Coquelin, D.; Krajsek, K.; Comito, C.; Knechtges, P.; Hagemeier, B.; Tarnawa, M.; Hanselmann, S.; Siggel, M.; Basermann, A.; Streit, A.
2020. 2020 IEEE International Conference on Big Data (Big Data), 276–287, Institute of Electrical and Electronics Engineers (IEEE)
Zirwes, T.; Zhang, F.; Habisreuther, P.; Hansinger, M.; Bockhorn, H.; Pfitzner, M.; Trimis, D.
2021. Flow, turbulence and combustion, 106 (2), 373–404. doi:10.1007/s10494-020-00228-9
Zirwes, T.; Zhang, F.; Wang, Y.; Habisreuther, P.; Denev, J. A.; Chen, Z.; Bockhorn, H.; Trimis, D.
2021. Proceedings of the Combustion Institute, 38 (2), 2057–2066. doi:10.1016/j.proci.2020.07.033
Zirwes, T.; Häber, T.; Zhang, F.; Kosaka, H.; Dreizler, A.; Steinhausen, M.; Hasse, C.; Stagni, A.; Trimis, D.; Suntz, R.; Bockhorn, H.
2021. Flow, turbulence and combustion, 106, 649–679. doi:10.1007/s10494-020-00215-0
Schieβl R.; Denev, J. A.
2020. Combustion theory and modelling, 24 (6), 983–1001. doi:10.1080/13647830.2020.1800102
Zhang, F.; Zirwes, T.; Häber, T.; Bockhorn, H.; Trimis, D.; Suntz, R.
2021. Proceedings of the Combustion Institute, 38 (2), 1955–1964. doi:10.1016/j.proci.2020.06.058
Kornev, N.; Denev, J.; Samarbakhsh, S.
2020. Fluids, 5 (2), Article: 45. doi:10.3390/fluids5020045
Denev, J.; Barthel, R.; Frank, M. (Eds.)
2019. Karlsruher Institut für Technologie (KIT)
Zhang, F.; Zirwes, T.; Habisreuther, P.; Zarzalis, N.; Bockhorn, H.; Trimis, D.
2021. Combustion science and technology, 193 (4), 594–610. doi:10.1080/00102202.2019.1665520
Denev, J. A.; Naydenova, I.; Zhang, F.; Zirwes, T.; Bockhorn, H.
2019. 9th European Combustion Meeting (ECM), Lissabon, Portugal, 14 - 17 April 2019
Zirwes, T.; Zhang, F.; Denev, J. A.; Habisreuther, P.; Bockhorn, H.; Trimis, D.
2019. High Performance Computing in Science and Engineering ’18 - Transactions of the High Performance Computing Center, Stuttgart (HLRS) 2018. Ed.: W. E. Nagel, 209–224, Springer International Publishing
Galeazzo, F. C. C.; Fukumasu, N. K.; Denev, J. A.; Krieger Filho, G. C.
2018. Joint Meeting of the German and Italian Sections of the Combustion Institute (2018), Sorrento, Italy, May 23–26, 2018
Zirwes, T.; Zhang, F.; Denev, J. A.; Habisreuther, P.; Bockhorn, H.
2018. High Performance Computing in Science and Engineering ’ 17 - Transactions of the High Performance Computing Center, Stuttgart (HLRS) 2017. Ed.: W. Nagel, 189–204, Springer-Verlag. doi:10.1007/978-3-319-68394-2_11
Name | Tel. | |
---|---|---|
Dr. Denev, Jordan | +49 721 608-25771 +49 721 608-42807 |
jordan denev ∂ kit edu |
Name | Tel. | |
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Weiel, Marie | marie weiel ∂ kit edu | |
Dr. Piccioni Koch, Daniela | +49 721 608-23304 | daniela piccioni ∂ kit edu |
Dr. Götz, Markus | +49 721 608-29334 | markus goetz ∂ kit edu |
3 additional persons visible within KIT only. |