Clemens Zimmerling

Karlsruhe Institute of Technology — Germany

Engineering · Physical Sciences

9h-index453citations28works2.32yr avg
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Research Topics

Manufacturing Process and Optimization(14), Advanced machining processes and optimization(9), Metal Forming Simulation Techniques(6), Mechanical Behavior of Composites(5), Additive Manufacturing and 3D Printing Technologies(5)

Publications28 total

A submodeling approach for efficient prediction of local temperature profiles in component-scale additive manufacturing
The International Journal of Advanced Manufacturing Technology·2024· 2 citedOpen Access
Combining simulation methods and machine learning for efficient forming process development
Elsevier eBooks·2024· 1 cited
Physics-informed MeshGraphNets (PI-MGNs): Neural finite element solvers for non-stationary and nonlinear simulations on arbitrary meshes
Computer Methods in Applied Mechanics and Engineering·2024· 10 citedOpen Access
Physics-informed MeshGraphNets (PI-MGNs): Neural finite element solvers for non-stationary and nonlinear simulations on arbitrary meshes
arXiv (Cornell University)·2024Open Access
A Submodeling Approach for Efficient Prediction of Local Temperature Profiles in Component-Scale Additive Manufacturing
SSRN Electronic Journal·2024Open Access
How Domain Knowledge can Improve Machine Learning Surrogates for Manufacturing Process Optimization – a Comparative Study
Procedia CIRP·2024· 1 citedOpen Access
Physics-informed neural networks for data-free surrogate modelling and engineering optimization – An example from composite manufacturing
Materials & Design·2023· 35 citedOpen Access
Forming process optimisation for variable geometries by machine learning – Convergence analysis and assessment
Materials research proceedings·2023· 1 citedOpen Access
Formability Assessment of Variable Geometries Using Machine Learning - Analysis of the Influence of the Database
Key engineering materials·2022· 6 citedOpen Access
Optimisation of layup type and fibre orientation in continuous-fibre reinforced components via anisotropy analysis
Composite Structures·2022· 5 citedOpen Access
Optimisation of manufacturing process parameters for variable component geometries using reinforcement learning
Materials & Design·2022· 37 citedOpen Access
Deep neural networks as surrogate models for time-efficient manufacturing process optimisation
ESAFORM 2021·2021· 5 citedOpen Access
Estimation of Load-Time Curves Using Recurrent Neural Networks Based On Can Bus Signals
2021· 1 citedOpen Access
Estimating Optimum Process Parameters in Textile Draping of Variable Part Geometries - A Reinforcement Learning Approach
Procedia Manufacturing·2020· 34 citedOpen Access
Rapid Determination of Suitable Reinforcement Type in Continuous-Fibre-Reinforced Composites For Multiple Load Cases
Repository KITopen (Karlsruhe Institute of Technology)·2020Open Access
Virtual Product Development Using Simulation Methods and AI
Lightweight Design worldwide·2019· 5 citedOpen Access
Virtuelle Produktentwicklung mittels Simulationsmethoden und KI
Lightweight Design·2019· 1 citedOpen Access
Development of a Modular Draping Test Bench for Analysis of Infiltrated Woven Fabrics in Wet Compression Molding
Key engineering materials·2019· 2 citedOpen Access
A machine learning assisted approach for textile formability assessment and design improvement of composite components
Composites Part A Applied Science and Manufacturing·2019· 55 citedOpen Access
An approach for rapid prediction of textile draping results for variable composite component geometries using deep neural networks
AIP conference proceedings·2019· 29 citedOpen Access
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Frequent Co-authors

Luise Kärger(25), Christian Poppe(8), Frank Henning(7), Dominik Dörr(5), Constantin Krauß(4), Benedikt Fengler(4), Tobias Würth(3), Julius Pfrommer(2), Jinzhao Liu(2), Jürgen Beyerer(2), Siegfried Galkin(2), Niklas Freymuth(2), Gerhard Neumann(2), Julian Seuffert(2), Felix Frölich(2), Florian Wittemann(2), Johannes Maximillian Linden(1), André Oeckerath(1), Kläus Wolf(1), Oliver Stein(1)