The global automotive industry faces the challenge of increasing engine efficiency, reducing fuel consumption and the size of them gradually. Not only the engine block must reduce its size, but also other components, requiring more compact and flexible designs using materials such as thermoplastic elastomers. That kind of materials are used due to their characteristics, such as ability of deformation, durability, recyclability, and its cost/weight ratio. They are able to hold large deformations and they have very good damping characteristics, making them suitable for use in energy dissipation. Characterization of the dynamic mechanical properties of these materials is essential to make a correct analysis and modeling of the behavior of components. Although the constitutive models of these materials are complex due to high deformability, quasi-incompressibility, softening, and time dependent effects, typically, these materials have a mechanical behavior which can be represented by a phenomenological hyperelastic model. While it is easy to fit a model of elastic behavior, set a model for a hyperelastic material is a very complex task, so in practice simplified models are used. This paper proposes a comprehensive comparison of six hyperelastic models to simulate the behavior of Santoprene 101-73 material manufactured by ExxonMobil. The ability of these models to reproduce different types of loading conditions is analyzed through uniaxial tensile data obtained experimentally. The parameters of each of the hyperelastic models are determined by a least-squares fit and then a classification of these six models is established, highlighting those that are most suitable for characterizing the material.
Abstract:In this work a nonlinear phenomenological visco-hyperelastic model including damage consideration is developed to simulate the behavior of Santoprene 101-73 material. This type of elastomeric material is widely used in the automotive and aeronautic sectors, as it has multiple advantages. However, there are still challenges in properly analyzing the mechanical phenomena that these materials exhibit. To simulate this kind of material a lot of theories have been exposed, but none of them have been endorsed unanimously. In this paper, a new model is presented based on the literature, and on experimental data. The test samples were extracted from an air intake duct component of an automotive engine. Inelastic phenomena such as hyperelasticity, viscoelasticity and damage are considered singularly in this model, thus modifying and improving some relevant models found in the literature. Optimization algorithms were used to find out the model parameter values that lead to the best fit of the experimental curves from the tests. An adequate fitting was obtained for the experimental results of a cyclic uniaxial loading of Santoprene 101-73.
Most of the mechanical components manufactured in rubber materials experience fluctuating loads, which cause material fatigue, significantly reducing their life. Different models have been used to approach this problem. However, most of them just provide life prediction only valid for each of the specific studied material and type of specimen used for the experimental testing. This work focuses on the development of a new generalized model of multiaxial fatigue for rubber materials, introducing a multiparameter variable to improve fatigue life prediction by considering simultaneously relevant information concerning stresses, strains, and strain energies. The model is verified through its correlation with several published fatigue tests for different rubber materials. The proposed model has been compared with more than 20 different parameters used in the specialized literature, calculating the value of the R2 coefficient by comparing the predicted values of every model, with the experimental ones. The obtained results show a significant improvement in the fatigue life prediction. The proposed model does not aim to be a universal and definitive approach for elastomer fatigue, but it provides a reliable general tool that can be used for processing data obtained from experimental tests carried out under different conditions.
The influence of the composition of magnesium alloys on their environmental impact was analyzed. In order to perform a more accurate environmental impact calculation, life cycle assessment (LCA) with the ReCiPe 2016 Endpoint and IPCC 2013 GWP (100 y) methodology was used, taking the EcoInvent AZ91 magnesium alloy dataset as reference. This dataset has been updated with the material composition range of several alloys included in the European standard EN 1753:2019. The balanced, maximum, and minimum environmental impact values were obtained. In general, the overall impact of the studied magnesium alloys varied from 3.046 Pt/kg to 4.853 Pt/kg and from 43.439 kg CO2 eq./kg to 55.427 kg CO2 eq./kg, depending on the composition. In the analysis of maximum and minimum environmental impacts, the alloy that had the highest uncertainty was 3.5251, with a range of ±7.20%. The element that contributed the most to increase its impact was silver. The AZ91 alloy, provided by the EcoInvent dataset, had a lower environmental impact than all the magnesium alloys studied in this work. The content of critical raw materials (CRMs) was also assessed, showing a high content in CRMs, between 89.72% and 98.22%.
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