Statistical properties of microcracking in polyurethane foams under tensile test, influence of temperature and density

We report tensile failure experiments on polyurethane (PU) foams. Experiments have been performed by imposing a constant strain rate. We work on heterogeneous materials for whom the failure does not occur suddenly and can develop as a multistep process through a succession of microcracks that end at pores. The acoustic energy and the waiting times between acoustic events follow power-law distributions. This remains true while the foam density is varied. However, experiments at low temperatures (PU foams more brittle) have not yielded power-laws for the waiting times. The cumulative acoustic energy has no power law divergence at the proximity of the failure point which is qualitatively in agreement with other experiments done at imposed strain. We notice a plateau in cumulative acoustic energy that seems to occur when a single crack starts to propagate

Investigation of the damage mechanisms for mode I delamination growth in foam core sandwich composites using acoustic emission

In this article, acoustic emission monitoring was used to identify different types of damage mechanisms which occur during delamination of sandwich structures. Features of the obtained acoustic emission signals and wavelet-based signal processing technique were utilized to discriminate failure mechanisms during the delamination test. Dominant damage mechanisms were classified based on their power spectral density in distinct frequency ranges and the energy distribution criterion in each component. The scanning electron microscopy was also employed to verify the results which were obtained from the acoustic emission investigation. It was concluded that frequency domain analysis and wavelet analysis are efficient tools for identification and discrimination of different damage mechanisms in sandwich structures

Damage Classification of Sandwich Composites Using Acoustic Emission Technique and k-means Genetic Algorithm

© 2014, Springer Science+Business Media New York. In this study acoustic emission (AE) technique was used for monitoring mode I delamination test of sandwich composites. Since, during mode I delamination test various damage mechanisms appear, their classification is of major importance. Hence, integration of k-means algorithm and genetic algorithm was applied as an efficient clustering method to discriminate different failure modes. Performing primary experiments to find the relationship between AE parameters and damage mechanisms, the AE signals of obtained clusters were assigned to distinct damage mechanisms. Also, the dominance of damage mechanisms was determined based on the distribution of AE signals in different clusters. Finally SEM observation was employed to verify obtained results. The results indicate the efficiency of the proposed method in damage classification of sandwich composites