Novel Methodology for Experimental Characterization of Micro-Sandwich Materials

Lightweight components are in demand from the automotive industry, due to legislation regulating greenhouse gas emissions, e.g., CO2. Traditionally, lightweighting has been done by replacing mild steels with ultra-high strength steel. The development of micro-sandwich materials has received increasing attention due to their formability and potential for replacing steel sheets in automotive bodies. A fundamental requirement for micro-sandwich materials to gain significant market share within the automotive industry is the possibility to simulate manufacturing of components, e.g., cold forming. Thus, reliable methods for characterizing the mechanical properties of the micro-sandwich materials, and in particular their cores, are necessary. In the present work, a novel method for obtaining the out-of-plane properties of micro-sandwich cores is presented. In particular, the out-of-plane properties, i.e., transverse tension/compression and out-of-plane shear are characterized. Test tools are designed and developed for subjecting micro-sandwich specimens to the desired loading conditions and digital image correlation is used to qualitatively analyze displacement fields and fracture of the core. A variation of the response from the material tests is observed, analyzed using statistical methods, i.e., the Weibull distribution. It is found that the suggested method produces reliable and repeatable results, providing a better understanding of micro-sandwich materials. The results produced in the present work may be used as input data for constitutive models, but also for validation of numerical models.

Automated summary

This study presents a new method for obtaining the out-of-plane properties of micro-sandwich materials and highlights their importance and application prospects in the automotive industry. By designing test tools and using digital image correlation for analysis, it is found that the method is reliable and repeatable, providing better data support for manufacturing and simulation.