%0 Generic %1 kneifl2023crash %A Kneifl, Jonas %A Fehr, Jörg Christoph %D 2023 %K %R 10.18419/darus-3789 %T Crash Simulations of a Racing Kart's Structural Frame Colliding against a Rigid Wall %X Crash Simulations of a Racing Kart Frame Model This dataset contains results for several crash simulations of the frame of a racing kart colliding against a rigid wall. The wall and the frame itself are modeled as finite element models, implemented in the commercial software tool LS-Dyna. The latter comprises 9314 nodes, each possessing 3 translational degrees of freedom. The simulated scenario involves the kart colliding against a rigid wall, with the impact speed varying between 5 and 30 m/s, the impact angle between -45 and 45 degrees and the yield stress between 168 and 758 MPa.The impact angle is the angle between the wall normal and the orientation of the kart, while the yield stress influences the effective plastic stress-strain curve of the kart material. This curve matches that of typical steel, but is adjusted based on the unique yield stress of each simulation.Each crash simulation covers a time span of 0.003 seconds with a sampling interval of 0.3 milliseconds, resulting in 101 samples per simulation. A total of 128 parameter combinations were generated with Halton sequences.Moreover, the source code of the finite element model itself, written for the commercial simulation software LS-DYNA, is included as well. Content Model * input files for the FE simulation software LS-DYNA containing the model descriptionKart Dataset * simulation results containing the node displacements and simulation parameters. The units are N,m,s.

@misc{kneifl2023crash, abstract = {Crash Simulations of a Racing Kart Frame Model This dataset contains results for several crash simulations of the frame of a racing kart colliding against a rigid wall. The wall and the frame itself are modeled as finite element models, implemented in the commercial software tool LS-Dyna. The latter comprises 9314 nodes, each possessing 3 translational degrees of freedom. The simulated scenario involves the kart colliding against a rigid wall, with the impact speed varying between 5 and 30 m/s, the impact angle between -45 and 45 degrees and the yield stress between 168 and 758 MPa.The impact angle is the angle between the wall normal and the orientation of the kart, while the yield stress influences the effective plastic stress-strain curve of the kart material. This curve matches that of typical steel, but is adjusted based on the unique yield stress of each simulation.Each crash simulation covers a time span of 0.003 seconds with a sampling interval of 0.3 milliseconds, resulting in 101 samples per simulation. A total of 128 parameter combinations were generated with Halton sequences.Moreover, the source code of the finite element model itself, written for the commercial simulation software LS-DYNA, is included as well. Content Model * input files for the FE simulation software LS-DYNA containing the model descriptionKart Dataset * simulation results containing the node displacements and simulation parameters. The units are [N,m,s]. }, added-at = {2023-11-21T13:29:33.000+0100}, affiliation = {Kneifl, Jonas/University of Stuttgart, Fehr, Jörg/University of Stuttgart}, author = {Kneifl, Jonas and Fehr, Jörg Christoph}, biburl = {https://puma.ub.uni-stuttgart.de/bibtex/25167863991bebe29420e218cfa4ff8a8/unibiblio}, doi = {10.18419/darus-3789}, howpublished = {Software}, interhash = {b1c2b84e1cf4be479bb3b4fac22141c1}, intrahash = {5167863991bebe29420e218cfa4ff8a8}, keywords = {}, note = {Related to: Kneifl, J., Kutz, J. N., Brunton, S.L., Fehr, J.: Multi-Hierarchical Surrogate Learning of Structural Dynamical Systems Using Graph Convolutional Neural Networks. To be submitted (2023)}, orcid-numbers = {Kneifl, Jonas/0000-0003-3934-6968, Fehr, Jörg/0000-0003-2850-1440}, timestamp = {2023-11-21T12:29:33.000+0100}, title = {Crash Simulations of a Racing Kart's Structural Frame Colliding against a Rigid Wall}, year = 2023 }