A12
Automotive - Crash

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13:20
conference time (CEST, Berlin)
Simplification of FE-Crash-Models for Optimization of Vehicle Structures
27/10/2021 13:20 conference time (CEST, Berlin)
Room: A
M. Schäffer (DLR - Deutsches Zentrum für Luft- und Raumfahrt, DEU); M. Totzke, R. Sturm (German Aerospace Center, DEU)
M. Schäffer (DLR - Deutsches Zentrum für Luft- und Raumfahrt, DEU); M. Totzke, R. Sturm (German Aerospace Center, DEU)
New simplification strategies for crash simulations are developed at the German Aerospace Center (DLR) as part of the Next Generation Car META-project. The computational costs required for the various crash load cases are challenging for optimization of vehicle structures. In this paper an automated model generation for simplified vehicle crash models is presented by using global deformation characteristics of structures which are obtained from the global crash model. Due to the obtained reduction of computational costs, structural crash optimizations can be performed. The development of a light and crash safe body-in-white structure is currently supported by lots of crash simulations. As part of these developments the increased application of virtual methods the product development process has been more than halved leading to shorter product life cycles. [1], [2] However, due to the high computational costs required for crash simulations, structural optimizations cannot be carried out with a full vehicle model. Therefore, there is a strong need for an automated generation of simplified vehicle crash models to include structural optimizations into the shorted product development process. For reduction of computational time, an automated four-step approach for the generation of a simplified vehicle model was developed in [3] and [4]. For the verification of the automated approach, crash simulations were carried out investigating the US NCAP (100%, 56 km/h) crash load case. In this load case, the vehicle is driven against a rigid wall at a speed of 56 km/h. The crash model of the Toyota Yaris [5] was taken, since the available crash model is validated for this crash load case. In comparing the global deformation of the simplified vehicle model and full vehicle model no major differences can be identified. Besides, the same overall crash kinematics between the models, also the same buckling and folding of the bonnet, deformation of the exhaust system and deformation to the chassis is obtained for the two models. The main target of simplified crash models is the reduction of computational time with a minimum influence on the simulation results. For the assessment of the time reduction potentials, all crash simulations were performed on the same CASE-2 Cluster on 24 CPUs. Through the application of the modelling approach, the number of components in the model could be reduced by 50%, and the computational time can be reduced by approximately 65% in this load case. REFERENCES [1] Duddeck, F.: Multidisciplinary optimization of car bodies. https://doi. org/10.1007/s00158- 007-0130-6; Struct. Multidisc. Optim. 35, 375–389, 2008. [2] Klaiber, M.: Use of Innovative 3D Printing Technologies for Flexible Process Chaining, 2. Technologietag Hybrider Leichtbau, Stuttgart, 2015. [3] Schäffer M, et. al, Methodological approach for reducing computational costs of vehicle frontal crashworthiness analysis by using simplified structural modelling; https://doi.org/ 10.1080/13588265.2017.1389631; International journal of Crashworthiness, 2017. [4] Schäffer M, et. al, Automated generation of physical surrogate vehicle models for crash optimization; https://doi.org/10.1007/s10999-018-9407-8; Int J Mech Mater Des, 15, 43-60, 2019. [5] NCAC, „Extended Validation of the Finite Element Model for the 2010 Toyota Yaris Passenger Sedan“. The George Washington University, 2012.
crashworthiness, safety, optimization, simplification strategies
13:40
conference time (CEST, Berlin)
Application of Physical and Mathematical Surrogate Models to Optimize the Crashworthiness of Vehicle Front Structures
27/10/2021 13:40 conference time (CEST, Berlin)
Room: A
P. Lualdi (DLR - Deutsches Zentrum für Luft- und Raumfahrt, DEU); M. Schäffer, R. Sturm (German Aerospace Center (DLR), DEU)
P. Lualdi (DLR - Deutsches Zentrum für Luft- und Raumfahrt, DEU); M. Schäffer, R. Sturm (German Aerospace Center (DLR), DEU)
Exploiting the full potential of lightweight materials and weight reduction techniques while preserving the high safety standards of a vehicle still remains one of the major challenges in the field of crashworthiness design. Such a problem, already challenging from a qualitative point of view, is also hard to be solved numerically due to the computational costs related to crash simulations of full FEM vehicle models. This factor represents also a real limitation in the field of optimization of vehicle crash structures. It is especially challenging, if load cases are investigated, which additionally involve complex impactor models such as deformable impact barriers, which are required for the certification of vehicles. Only by the use of simplification strategies and physical surrogate models the computational costs can be reduced in a way to make crashworthiness problems for cars suitable for structural optimization. Additionally, the application of mathematical surrogate models can efficiently improve the possibility to find suitable structural solutions in the respect of given design requirements compared to conventional optimization approaches. In this paper, the Urban Modular Vehicle (UMV), i.e. a battery-driven modular car concept developed by the German Aerospace Center (DLR) is investigated to improve its crash performance in the event of a front crash using physical and mathematical surrogate models. The NCAP - Mobile Progressive Deformable Barrier (MPDB) crash load case is considered as frontal crash scenario. A physical surrogate model will be used to replace the detailed crushing behavior of the MPDB model by means of kinematic descriptions. The finite element vehicle model is also simplified in a way that structural components which are assumed to only bear elastic deformations are replaced by kinematic numerical representations describing the substituted structures. Finally, a design optimization strategy based on mathematical surrogate models is successfully applied to optimize the absorption properties of the crash relevant vehicle structures. For the optimization appropriate constraint functions are included to ensure that any applied structural change does not undermine the safety requirements of the passengers. Only with these applied simplification strategies optimization can be applied to such a complex crash load case.
crashworthiness design, design optimization, surrogate models, structural optimization
14:00
conference time (CEST, Berlin)
State of the Art of Damage and Fracture Modelling in Crashworthiness Simulation
27/10/2021 14:00 conference time (CEST, Berlin)
Room: A
A. Haufe (Dynamore GmbH, DEU)
A. Haufe (Dynamore GmbH, DEU)
For many years crashworthiness simulation has been – and still is – an extremely demanding field of engineering with an ever-increasing level of complexity when it comes to constitutive or connection modelling. Many new material models for steels, alloys, elastomers and polymers, that are capable of taking various different effects into account (e.g. microstructural evolution due to different chemistry and/or heat treatment), were developed, implemented and successfully applied. Particularly if the local material properties due to pre-straining, reinforcement particles/fibers or heat treatment during part production are dominating the crashworthiness performance, this so-called virtual process chain must be considered in all its complexity as well. While all the aforementioned aspects were regarded and targeted in the past, the spatial discretization often still relies on 5-parameter shell elements based on classical Reissner-Mindlin kinematics. The present contribution will discuss the properties of shells in crashworthiness simulation and present the consequences of these assumptions in the light of material modelling. Clearly, the shown downsides can be compensated by adjusting constitutive parameters – which is the only way to go for models that suffer from too coarse spatial discretization in explicit dynamics. However, another rarely noted consequence is, that in the quest of being as predictive as possible in crashworthiness, i.e. in the postcritical regime of the stress-strain relation in the constitutive model, calibration has to be done for shell and solid discretization independently. The paper will address these topics in detail, exemplify the issues by simple examples and give concise conclusions for everyday work in this interesting field of engineering.
Crashworthiness, spatial discretization, shell & solid elements, constitutive modelling, damage & fracture.
14:20
conference time (CEST, Berlin)
A Reduced Order Model Optimization Method for Spot-weld Position and Vehicle Structure Crash Performance
27/10/2021 14:20 conference time (CEST, Berlin)
Room: A
M. Couste (Renault Technocentre, FRA); Y. Tourbier (Groupe Renault, FRA)
M. Couste (Renault Technocentre, FRA); Y. Tourbier (Groupe Renault, FRA)
In automotive industry, optimisation on vehicle structure has been a constant focus in projects. The goal is to find the best compromise between mass, cost, and performances like crash, acoustics, overall stiffness... The structure of the vehicle body is made up of 200 metal parts mainly joined with thousands of spot-welds. Each performance is simulated with increasingly accurate finite element model to reduce the number of physical tests that are still time-consuming and expensive. Despite computational power are in constant progression, simulations remain time challenging to be used in optimisation studies. For example, crash simulation takes around ten hours on HPC. Groupe RENAULT has a rich experience in the use of design of experiments (DOE) for vehicle optimisation. Furthermore, DOE will be completed or replaced with Model Order Reduction (MOR) to improve efficiency, duration, and cost. “Classical” MOR allow to lead two-steps optimisation studies: first a lot of simulations to create an abacus, then uses it to quickly determine the results for new sets of parameters. However, our studies vary tens of parameters, so classical MOR is as costly as DOE. Therefore, RENAULT developed the Regression-CUR (ReCUR) method to reduce the number of simulations. The parametrized reduced order model gives an estimation of the high-fidelity result for a new set of parameters. The accuracy of the reduced model can be balanced with less simulations. Indeed, an overall improved design is searched instead of demonstrating the global optimality. The article will focus on a combinatorial optimisation problem by finding the right balance between assembly process and crash performance (with ReCUR). The first part treats about the optimisation of the main crash criterion from certification rules and media scoring derived from structural deformations. The second part deals with the optimisation of the spot-weld risk requirements used to avoid successive spot-welds failure by applying on a simple test case and on a side-impact industrial case.
optimization, model order reduction, crashworthiness, machine learning, vehicle body
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