Clemens Zimmerling CZ

Dr.-Ing. Clemens Zimmerling

Research Focus

  • Coordination of the research field 'AI-supported lightweight engineering'
  • Virtual Optimisation of Textile Forming Processes
  • Application of Machine Learning Techniques for component and process design
  • Design and Structural Simulation of continuous-fibre reinforced composite components

Publications


Machine Learning for Efficient Process Optimization in Textile Draping for Composite Production
Zimmerling, C.
2023, September 26. ITA Reinforced! Innovation Day: “Automation” and “Composite Testing and Sensor Integration” (2023), Aachen, Germany, September 26, 2023
Forming process optimisation for variable geometries by machine learning – Convergence analysis and assessment
Zimmerling, C.; Kärger, L.
2023. Material Forming 26th International ESAFORM Conference on Material Forming (ESAFORM 2023) Krakau, Polen, 19.04.2023–21.04.2023, 1155–1166, Materials Research Forum LLC. doi:10.21741/9781644902479-126
Machine learning algorithms for efficient process optimisation of variable geometries at the example of fabric forming | Lionel Fourment PhD-prize for Industrial Research
Zimmerling, C.
2023, April 20. 26th International ESAFORM Conference on Material Forming (ESAFORM 2023), Krakow, Poland, April 19–21, 2023
Techniken des Maschinenlernens zur effizienten Prozessoptimierung bei veränderlichen Bauteilgeometrien am Beispiel der Textilumformung
Zimmerling, C.
2023, March 22. 27. Nationales SAMPE Symposium Deutschland (2023), Munich, Germany, March 21–22, 2023
Machine learning algorithms for efficient process optimisation of variable geometries at the example of fabric forming. PhD dissertation
Zimmerling, C.
2023, January 18. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000154623
Formability Assessment of Variable Geometries Using Machine Learning - Analysis of the Influence of the Database
Zimmerling, C.; Fengler, B.; Kärger, L.
2022. Key Engineering Materials, 926, 2247–2257. doi:10.4028/p-1o0007
Optimisation of manufacturing process parameters for variable component geometries using reinforcement learning
Zimmerling, C.; Poppe, C.; Stein, O.; Kärger, L.
2022. Materials and Design, 214, Art.-Nr.: 110423. doi:10.1016/j.matdes.2022.110423
Deep neural networks as surrogate models for time-efficient manufacturing process optimisation
Zimmerling, C.; Schindler, P.; Seuffert, J.; Kärger, L.
2021. ESAFORM 2021 - 24th International Conference on Material Forming, ULiège Library. doi:10.25518/esaform21.3882
Estimation of Load-Time Curves Using Recurrent Neural Networks Based On Can Bus Signals
Herz, D.; Krauß, C.; Zimmerling, C.; Grupp, B.; Gauterin, F.
2021. 14th World Congress on Computational Mechanics - WCCM & ECCOMAS Congress 2020 : virtual congress, 11-15 January, 2021 / IACM, ECCOMAS. Ed.: F. Chinesta, International Centre for Numerical Methods in Engineering (CIMNE). doi:10.23967/wccm-eccomas.2020.138
Rapid Determination of Suitable Reinforcement Type in Continuous-Fibre-Reinforced Composites For Multiple Load Cases
Zimmerling, C.; Fengler, B.; Wen, H.; Fan, Z.; Kärger, L.
2020, September 1. 23rd / 6th Joint Event: International Conference on Composite Structures - International Conference on Mechanics of Composites (ICCS / MECHCOMP 2020), Porto, Portugal, September 1–4, 2020
Virtual Product Development Using Simulation Methods and AI
Zimmerling, C.; Poppe, C.; Kärger, L.
2019. Lightweight Design worldwide, 12 (6), 12–19. doi:10.1007/s41777-019-0064-x
Virtuelle Produktentwicklung mittels Simulationsmethoden und KI
Zimmerling, C.; Poppe, C.; Kärger, L.
2019. Lightweight design, 12 (6), 12–19. doi:10.1007/s35725-019-0069-8
Zeit- und kosteneffiziente Prozess und Produktentwicklung für den Hochleistungs-Faserverbundleichtbau unterstützt durch Techniken des Maschinellen Lernens
Zimmerling, C.; Kärger, L.; Carosella, S.; Middendorf, P.; Henning, F.
2019, May 20. 6. Technologietag Hybrider Leichtbau (2019), Leinfelden-Echterdingen, Germany, May 20–21, 2019
Development of a modular draping test bench for analysis of infiltrated woven fabrics in wet compression molding
Albrecht, F.; Zimmerling, C.; Poppe, C.; Kärger, L.; Henning, F.
2019. Key engineering materials, 809, 35–40. doi:10.4028/www.scientific.net/KEM.809.35
An approach for rapid prediction of textile draping results for variable composite component geometries using deep neural networks
Zimmerling, C.; Trippe, D.; Fengler, B.; Kärger, L.
2019. Proceedings of the 22nd International ESAFORM Conference on Material Forming ; Vitoria-Gasteiz, Spain, 8–10 May 2019. Ed.: L. Galdos, Art.-Nr.: 020007, American Institute of Physics (AIP). doi:10.1063/1.5112512
Forming optimisation embedded in a CAE chain to assess and enhance the structural performance of composite components
Kärger, L.; Galkin, S.; Zimmerling, C.; Dörr, D.; Linden, J.; Oeckerath, A.; Wolf, K.
2018. Composite structures, 192, 143–152. doi:10.1016/j.compstruct.2018.02.041
Advanced Macroscopic Modelling Approaches for FE Composite Forming Simulation Using Abaqus
Dörr, D.; Poppe, C.; Zimmerling, C.; Krauß, C.; Schäfer, B.; Henning, F.; Kärger, L.
2018. SIMULIA Regional User Meeting (2018), Hanau, Germany, December 4, 2018
Continuous Process Simulation for Continuous Fiber Reinforced Composites
Kärger, L.; Dörr, D.; Poppe, C.; Seuffert, J.; Bernath, A.; Galkin, S.; Zimmerling, C.; Henning, F.
2018. International VDI Conference - Simulation in Automotive Lightweight Engineering (2018), Amsterdam, Netherlands, April 25–26, 2018
Application and Evaluation of Meta-Model Assisted Optimisation Strategies for Gripper-Assisted Fabric Draping in Composite Manufacturing
Zimmerling, C.; Pfrommer, J.; Liu, J.; Beyerer, J.; Henning, F.; Kärger, L.
2018. 18th European Conference on Composite Materials (ECCM 2018), Athen, GR, June 24-28, 2018
Optimisation of manufacturing process parameters using deep neural networks as surrogate models
Pfrommer, J.; Zimmerling, C.; Liu, J.; Kärger, L.; Henning, F.; Beyerer, J.
2018. 51st CIRP Conference on Manufacturing Systems, CIRP CMS 2018; Stockholm Waterfront Congress CentreStockholm; Sweden; 16 May 2018 through 18 May 2018. Ed.: T. Kjellberg, 426–431, Elsevier. doi:10.1016/j.procir.2018.03.046
A meta-model based approach for rapid formability estimation of continuous fibre reinforced components
Zimmerling, C.; Dörr, D.; Henning, F.; Kärger, L.
2018. Proceedings of the 21st International ESAFORM Conference on Material Forming : ESAFORM 2018 : Palermo, Italy, 23-25 April 2018. Ed.: L. Fratini, Art.Nr. 020042, American Institute of Physics (AIP). doi:10.1063/1.5034843
Zeit- und kosteneffiziente Prozess- und Produktentwicklung für den Hochleistungs-Faserverbundleichtbau mittels Nasspresstechnologie
Poppe, C.; Fial, J.; Kärger, L.; Carosella, S.; Albrecht, F.; Zimmerling, C.; Draskovic, M.; Engelfried, M.
2017, May 30. 4. Technologietag Hybrider Leichtbau (2017), Stuttgart, Germany, May 30–31, 2017
Zeit- und kosteneffiziente Prozess- und Produktentwicklung für den Hochleistungs-Faserverbundleichtbau im Rahmen der Nasspresstechnologie
Poppe, C.; Zimmerling, C.; Albrecht, F.; Hüttl, J.; Fial, J.; Engelfried, M.
2017, January 31. Marktplatz Leichtbau (2017), Ludwigsburg, Germany, January 31, 2017