Dynamic-mechanical-thermal analysis of hybrid continuous–discontinuous sheet molding compounds

Sheet molding compounds (SMC) are very promising for the production of lightweight structural components, due to the specific mechanical properties combined with the suitability for a large-scale manufacturing process. Automotive industry already implements SMC materials for structural components in their vehicle concepts. Polymeric materials, hence also fiber reinforced polymers, show a viscoelastic behavior and dynamic-mechanical-thermal analysis (DMTA) is an important method of determining the influence of temperature and loading speed of this material class. In this work, SMC which based on a novel hybrid resin system were examined under bending loads using a electric-dynamic test system to realize high-force dynamic-mechanical-thermal analysis. The examined SMC materials were either discontinuously (Dico) or continuously (Co) reinforced. In addition a hybrid continuous–discontinuous reinforcement was realized by stacking different SMC materials. The mechanical characterization aimed to investigate the influence of the reinforcement architecture and the effect of hybridization on the temperature- and frequency-dependent material properties. Glass transition temperature of the hybrid SMC was comparable to glass transition temperature of the discontinuous glass fiber reinforced component. Compared to the continuous carbon fiber SMC, the decrease of storage modulus of the hybrid SMC could be shifted to higher temperatures and damping was also significantly increased due to hybridization

Fatigue behavior of hybrid continuous-discontinuous fiber-reinforced sheet molding compound composites under application-related loading conditions

Hybrid continuous-discontinuous sheet molding compound (SMC) composites are considered suitable candidates for structural automotive applications, due to their high mass-specific mechanical properties combined with high geometrical flexibility and low costs. Since structural automotive parts are subject to repeated loading, profound knowledge of their fatigue behavior is required. This paper presents an experimental study on the bending fatigue behavior of hybrid SMC with discontinuous glass fibers in the core and unidirectional continuous carbon fibers in the face layers. Effects of hybridization on the S-N behavior and stiffness degradation have been analyzed in constant amplitude fatigue tests under 3-point bending load at different temperatures and frequencies. Microscopic investigations on polished specimen edges were used to study the damage behavior. The ultimate flexural strength at quasi-static (UFS$^S$) and fatigue strain rate (UFS$^F$) of the hybrid composite was 54 % and 59 % higher than that of discontinuous SMC, respectively. In contrast, the flexural fatigue strength at 2.6⋅10S$^6$ cycles increased by 258 %. The relative stiffness degradation of the hybrid composites was smaller during most of their fatigue lives due to the continuous carbon fiber reinforcement. The carbon fiber ply on the compression loaded side was the first ply to fail. Fatigue stress significantly decreased at 80 °C due to early kinking of the continuous carbon fiber-reinforced ply on the compression loaded side. Variation of frequency had no significant effect on the fatigue behavior of both discontinuous and continuous-discontinuous SMC

Study of material homogeneity in the long fiber thermoset injection molding process by image texture analysis

To quantify the homogeneity of fiber dispersion in short fiber-reinforced polymer composites, a method for image texture analysis of 3-dimensional X-ray micro computed tomography (µCT) images is presented in this work. The adaption of the method to the specific requirements of the composite material is accomplished using a statistical region merging approach. Subsequently, the method is applied for evaluating the homogeneity of specimens from an intermediate step of the long fiber thermoset injection molding process as well as molded parts. This new injection molding process enables the manufacturing of parts with a flexible combination of short and long glass fibers. By using a newly developed screw element based on the Maddock mixing element design, the material homogeneity of parts molded in the long fiber injection molding process is improved

Implementation and comparison of algebraic and machine learning based tensor interpolation methods applied to fiber orientation tensor fields obtained from CT images

Fiber orientation tensors (FOT) are used as a compact form of representing the mechanically important quantity of fiber orientation in fiber reinforced composites. While they can be obtained via image processing methods from micro computed tomography scans (CT), the specimen size needs to be sufficiently small for adequate resolution – especially in the case of carbon fibers. In order to avoid massive workload by scans and image evaluation when determining full-field FOT distributions for a plaque or a part, e.g., for comparison with process simulations, the possibilities of a direct interpolation of a few measured FOT at specific support points were opened in this paper. Hence, three different tensor interpolation methods were implemented and compared qualitatively with the help of visualization through tensor glyphs and quantitatively by calculating originally measured tensors at support points and evaluating the deviations. The methods compared in this work include two algebraic approaches, firstly, a Euclidean component averaging and secondly, a decomposition approach based on separate invariant and quaternion weighting, as well as an artificial intelligence (AI)-based method using an artificial neural network (ANN). While the decomposition method showed the best results visually, quantitatively the component averaging method and the neural network behaved better (that is for the type of quantitative error assessment used in this paper) with mean absolute errors of 0.105 and 0.114 when calculating previously measured tensors and comparing the components. With each method providing different advantages, the use for further application as well as necessary improvement is discussed. The authors would like to highlight the novelty of the methods being used with small and CT-based tensor datasets

Manufacturing and characterization of interpenetrating SiC lightweight composites

AbstractThe current work deals with the gas pressure infiltration of SiC - preforms of selected porosities with an aluminum alloy in order to manufacture an interpenetrating composite with higher ductility in comparison to SiC bulk material and a higher temperature and creep resistance in comparison to aluminum bulk materials. The quality of the manufactured composite is analyzed metallographically which attests a good infiltration of the composite. The residual porosity is also determined and can be attributed to the closed porosity and insufficient infiltration of open porosity. It can be shown that the infiltration of the preform leads to an increase in compressive strength with reasonable ductility in comparison to the unreinforced matrix material

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