Controlled compression test applied to composite materials reinforced with particles to predict fracture formation

• Main Authors: Gonzalez R, M. Fernanda, De la Torre-I, Manuel H, Sanchez A, Araceli, Mendoza Santoyo, Fernando
• Format: Conference Proceeding
• Language: English
• Published: SPIE 07.09.2018
• ISBN: 9781510622975; 1510622977
• ISSN: 0277-786X
• DOI: 10.1117/12.2318669

Composite materials are continuously being developed for all kinds of applications, making an impossible task to test each one during their development. The main purpose of these new and advanced materials is to improve the physical and mechanical properties of two or more materials by combining them. Without this combination each material by its own does not meet the specifications that the composite one will. New composite materials are subject to several types of tests trying to predict their behavior under specific chemical and mechanical conditions. In this work we deal with the mechanical characterization under a controlled compression test in circular composite probes. The use of a home-made specifically designed testing machine for non-destructive optical testing allows repeatable and controlled compression loads. Associating this testing machine with the well-known analysis capabilities of digital holographic interferometry in high speed mode, makes it possible to register and analyze the precise instant where the composite samples develop a crack by compression, its propagation and finally the fracture formation. A series of composite samples with three different concentrations of metallic particles (reinforcement) within the polymer (matrix) were manufactured. These specimens were subjected to a controlled compression and the obtained interferometric results show that it is possible to estimate an unknown particle concentration density of the composite material by identifying the load value when the crack appears. The latter is possible if a data base of similar samples are characterized before and then the crack load point is correlated to estimate this reinforcement.