Benefits of Semi-Analytical Model Polymer Techniques (SAMP-1 with GISSMO Failure) for Crashworthiness of Critical Thermoplastic Automotive Structural Parts

<div class="section abstract"><div class="htmlview paragraph">The emergence of thermoplastics in automotive structural parts is constantly increasing as designers recognize the benefits thermoplastics bring, such as light-weighting, cost effectiveness, the ability to integrate parts, the flexibility to design intricate shapes, and the materials’ high specific energy absorption capacity. In order to predict the behavior of plastics by simulation using finite elemental analysis (FEA) tools such as LS-DYNA®¹, an extensive understanding of properties and implementation using FEA is very important. In order to obtain reliable results from simulation, the FEA solver should support material models which predict the behavior of plastics accurately.</div><div class="htmlview paragraph">LS-DYNA® supports several material models which are used to predict behaviour of plastics, and one, the Semi-Analytical Model for Polymers (SAMP-1 with GISSMO failure), was developed exclusively for plastics. This model captures characteristics such as strain-rate dependency, visco-elastic and visco-plastic behavior, non-isochoric plastic deformation, and pressure dependency of failure strain and loss in material stiffness due to damage.</div><div class="htmlview paragraph">Standard tests (tension, compression and shear) were conducted to create the input data for the SAMP-1 model. The model is studied in a stepwise manner by initially simulating a single element for various states of stress, followed by simulating all of the standard tests and validating with the experimental results. A Dynatup test, which is a good representation of biaxial state of stress, is simulated and the results are used to further refine and validate the material card.</div><div class="htmlview paragraph">The validated SAMP-1 model is then used to analyze different automotive parts’ subjection to impact at different energy levels and temperatures. The simulation results correlate well with the test in the different conditions, which enhances the confidence in the material model.</div></div>