Optimization and robustness of complex material model simulations with modeFRONTIER
Experimental quasi-static and dynamic tests were conducted over different types of advanced material samples, such as composite sandwich, in order to derive both mechanical and numerical input parameters for LS-DYNA material models. The characterization of models addressed to reproduce the behaviour of real materials takes great importance in order to simulate accurately complex phenomena such as crash tests and impact events. This work deals with an innovative procedure aimed to calibrate the constitutive parameters of LS- DYNA advanced material models, and use them for prediction, design optimization and robustness analysis, hence reducing the need of further expensive experimental tests. This kind of approach allows also to understand the influence of physical and geometrical variables on composite dynamic structural response, or to get improved solution for industrial case studies. More in details, the available experimental data were imported in the modeFRONTIER Process Integration and Design Optimization software. An efficient stochastic optimization algorithm performed the calibration of the mechanical and numerical parameters of the existing LS-DYNA models, with a fully automated process. Such models could then be handled by modeFRONTIER to steer LS-DYNA simulation campaigns improving the design of composite and sandwich laminates. Any kind of free parameters to be investigated can be included in such a process, and the constraints to be respected and the multiple objectives to be pursued too. A short description of the most innovative techniques to do that will be given. An experimental-numerical procedure example from Automobili Lamborghini Composite Technical Department is shown.
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Optimization and robustness of complex material model simulations with modeFRONTIER
Experimental quasi-static and dynamic tests were conducted over different types of advanced material samples, such as composite sandwich, in order to derive both mechanical and numerical input parameters for LS-DYNA material models. The characterization of models addressed to reproduce the behaviour of real materials takes great importance in order to simulate accurately complex phenomena such as crash tests and impact events. This work deals with an innovative procedure aimed to calibrate the constitutive parameters of LS- DYNA advanced material models, and use them for prediction, design optimization and robustness analysis, hence reducing the need of further expensive experimental tests. This kind of approach allows also to understand the influence of physical and geometrical variables on composite dynamic structural response, or to get improved solution for industrial case studies. More in details, the available experimental data were imported in the modeFRONTIER Process Integration and Design Optimization software. An efficient stochastic optimization algorithm performed the calibration of the mechanical and numerical parameters of the existing LS-DYNA models, with a fully automated process. Such models could then be handled by modeFRONTIER to steer LS-DYNA simulation campaigns improving the design of composite and sandwich laminates. Any kind of free parameters to be investigated can be included in such a process, and the constraints to be respected and the multiple objectives to be pursued too. A short description of the most innovative techniques to do that will be given. An experimental-numerical procedure example from Automobili Lamborghini Composite Technical Department is shown.