PU tensile tests: conventional and digital image correlation analysis Academic Article Conference Paper uri icon

abstract

  • Polyurethane (PU) is a polymer, used as coating, paint, foam, adhesive, and even in biomedical devices. To furthermore expand its applications, it can be combined with additives such as Calcium Carbonate (CaCO3), an inexpensive material, widely available in nature, or with fibers, such as glass fibers explored in several sectors, likewise the aerospace and automobile industries. To determine the mechanical properties of these materials, the tensile test is the most used due to its great ease of application and flexibility. However, conventional processes, such as the use of strain gauges or crosshead displacement data, may not provide detailed information about the strain field, or cannot be able to evaluate the Poisson's ratio and the true stresses for the entire stressstrain curve. Thus, digital image correlation (DIC) methods are a promising alternative, consisting of strain field measurement without contact with the surface of the structure. In this context, this study carried out the tensile characterization of two main polyurethane samples: one petrochemical, distributed by Sika (R), reinforced with type E glass fiber: and the other, natural, manufactured by Kehl (R) from castor oils, and combined with CaCO3 particles. During the tests, DIC was applied to evaluate the Poisson's ratio and, subsequently, Scanning Electron Microscopy (SEM) analyses were performed, revealing a higher number of bubbles on Sika's polymer, which contributes to the reduction of the maximum supported stresses, since these pores, with dimensions of up to 25 hm, were regions where the cracks started and headed the breakage. Poisson's ratios were all around 0.4 and the highest tensile strength values were obtained from E-glass reinforced samples (TS015), around 117.24 +/- 13.20MPa. CaCO3 particles also acted as reinforced, increasing maximum stress reached from 20MPa to values between 29 and 37MPa.
  • This research was partially funded through the base funding from the following research units: UIDB/00690/2020 (CIMO).

publication date

  • February 1, 2022