Plaschkies, P.; Schumacher, A.; Vaculin, O. Accelerated Virtual Evaluation of Restraint System Performance forVehicle Occupants with Varying Bodies
15. Freiberger Crashworkshop
2024

Trilling, J.; Schumacher, A.; Zhou, M. Reinforcement learning based agents for improving layouts of automotive crash structures
Applied Intelligence (54) :1751--1769
2024

DOI: 10.1007/s10489-024-05276-6

Pakiman, A.; Garcke, J.; Schumacher, A. Knowledge discovery assistants for crash simulations with graph algorithms and energy absorption features
Applied Intelligence, 53 (16) :19217--19236
2023
ISSN: 0924-669X

DOI: 10.1007/s10489-022-04371-w

Kracker, D.; Dhanasekaran, Revan Kumar; Schumacher, A.; Garcke, J. Method for automated detection of outliers in crash simulations
International Journal of Crashworthiness, 28 (1) :96--107
2023
ISSN: 1358-8265

DOI: 10.1080/13588265.2022.2074634

Plaschkies, F.; Possoli, K.; Vaculin, O.; Schumacher, A.; Andrade, P. Evaluation Approach for Machine Learning Concepts in Occupant Protection Based on Multi-Attribute Decision Making
27th International Technical Conference on the Enhanced Safety of Vehicles (ESV)
2023

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Schumacher, A. State of the art in using deep learning algorithms and expert knowledge schemes for supporting mathematical optimization procedures
Automotive CAE Grand Challenge 2022
2022

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Plaschkies, F.; Vaculin, O.; Pelisson, A.A. Schnelle Abschätzung des Crashverhaltens von Insassen unter Berücksichtigung der Vielfalt des Menschen: Robustheit, Datenintensität und Vorhersagekraft von Metamodellen
13. VDI-Tagung Fahrzeugsicherheit
2022

DOI: 10.51202/9783181023877-313

Trilling, J.; Schumacher, A.; Zhou, M. Generation of designs for local stiffness increase of crash loaded extrusion profiles with reinforcement learning
Proceedings of the NAFEMS-Conference on Machine Learning and Artificial Intelligence in CFD and Structural Analysis, Seite 56--66
2022

Trilling, J.; Schumacher, A. Einsatz von Reinforcement Learning zur lokalen Versteifung von Extrusionsprofilen in Crashlastfällen
NAFEMS-Online-Magazin, Zeitschrift für numerische Simulation und angrenzende Gebiete (62) :59--70
2022

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Pakiman, A.; Garcke, J.; Schumacher, A. Data Representation of Crash Scenarios by Graph Structures
13th European LS-DYNA Conference & Users Meeting
2021

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Mertler, S.; Schumacher, A. Reduced Order Modeling for Correlation Analysis of Crash Structures
Automotive CAE Grand Challenge 2020
2020

Kracker, D.; Garcke, J.; Schumacher, A.; Schwanitz, P. Automatic analysis of crash simulations with dimensionality reduction algorithms such as PCA and t-SNE
16th Intl. LS-DYNA Users Conference
2020

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Diez, C.; Kunze, P.; Toewe, D.; Wieser, C.; Harzheim, L. Big-Data based rule-finding for analysis of crash simulations
In Schumacher, A. and Vietor, T. and Fiebig, S. and Bletzinger, K.-U. and Maute, K., Editor, Advances in Structural and Multidisciplinary Optimization aus Springer eBook Collection Engineering
Seite 396--410
Herausgeber: Springer, Cham
2018

DOI: 10.1007/978-3-319-67988-4_31

ISBN: 978-3-319-67988-4

Diez, C.; Wieser, C.; Harzheim, L.; Schumacher, A. Automated Generation of Robustness Knowledge for selected Crash Structures
14. LS-DYNA-Forum
2016

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Diez, C.; Harzheim, L.; Schumacher, A. Effiziente Wissensgenerierung zur Robustheitsuntersuchung von Fahrzeugstrukturen mittels Modellreduktion und Ähnlichkeitsanalyse
SIMVEC Simulation und Erprobung in der Fahrzeugentwicklung 2016
Herausgeber: VDI Verlag
2016

DOI: 10.51202/9783181022795-137

ISBN: 9783181022795

Schumacher, A.; Ortmann, C. Combining state of the art meta-models for predicting the behavior of non-linear crashworthiness structures for shape and sizing optimizations
11th World Congress on Structural and Multidisciplinary Optimisation, Seite 477--482
2015

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Dissertationen:

1. Dr.-Ing. Constantin Diez (2018):  Process for Extraction of Knowledge from Crash Simulations by means of Dimensionality Reduction and Rule Mining [https://d-nb.info/1182555063/34] 
2. Dr.-Ing. Stefan Mertler (2022): Comparative Analysis of Crash Simulation Results using Generative Nonlinear Dimensionality Reduction, Shaker Verlag, ISBN: 978-3-8440-8761-1 
3. Dr.-Ing. David Kracker (2024): Automatisierte Auswertung von Crashsimulationen unterschiedlicher Fahrzeug-Entwicklungsständen mit Methoden des maschinellen Lernens. Shaker Verlag, ISBN: 978-3-8440-9424-4 Download
4.   Dr.-Ing. Jens Trilling (2024): Unterstützung der Graphen- und Heuristikbasierten Topologieoptimierung crashbelasteter Strukturen durch Reinforcement Learning Download