We present a stochastic approach combining Bayesian Inference (BI) with homogenization theories in order to identify, on the one hand, the parameters inherent to the model assumptions and, on the other hand, the composite material constituents behaviors, including their variability. In particular, we characterize the model parameters of a Mean-Field Homogenization (MFH) model and the elastic matrix behavior, including the inherent dispersion in its Young's modulus, of non-aligned Short Fibers Reinforced Polymer (SFRP) composites. The inference is achieved by considering as observations experimental tests conducted at the SFRP composite coupons level. The inferred model and material law parameters can in turn be used in Mean-Field Homogenization (MFH)-based multi-scale simulations and can predict the confidence range of the composite material responses.
The fracture mechanics of random discontinuous Carbon Fiber Sheet Molding Compound (C-SMC) materials compared to traditional carbon fiber composites are not well understood. An experimental study was carried out to characterize the fracture behavior of such C-SMC materials. Mode I tests, using double cantilever beam specimens, and mode II tests, adopting the four-point bend, end-notched flexure configuration, were performed. Results show high variations in the forcedeflection responses and scatter in the fracture toughness properties GIc and GIIc, due to the complex mesostructure defined by random oriented carbon fiber chips. To investigate the influence of the mesostructure, tensile tests with varying specimen width and thickness were assessed by stochastic measures to find the representative specimen size.
Abstract. A variety of steels, cast iron grades and other metals have long been used for the production of machine components. In recent years, however, new materials such as sintered materials and plastics become increasingly important. Because of the large number of different fibers, matrices, stacking sequences, processing conditions and processes and the variety of resulting material configurations it is not possible to rely on proven fatigue models for conventional materials. Moreover, the development of models, which are valid for all composites are generally extremely difficult.In this work, a possible application of high-performance composites as materials for machine elements are investigated. This study attempts to predict the fatigue behavior and the consequent durability, based on laboratory measurements. Using the statistics program JMP, the aquired data was subjected to a reliability analysis in order to ensure the plausibility, validity and accuracy of the measured values.
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