Alexander Bezold

On the Statistical Determination of Yield Strength, Ultimate Strength, and Endurance Limit of a Particle Reinforced Metal Matrix Composite (PRMMC)

In this paper we present a numerical methodology to determine the load bearing capacity of a random heterogeneous material. It is applied to a particulate reinforced metal matrix composite (PRMMC), WC-30 Wt.% Co, to predict its strength against both monotonic and cyclic loads. In this approach, limit and shakedown analysis based on Melan’s static theorem [30] is performed on representative volume element (RVE) models generated from real material microstructure and the obtained results are converted to macroscopic load domains through homogenization. To evaluate microstructure’s impact on the overall material strength, the relationship between strength and composite structure is investigated by means of statistics. Meanwhile, several numerical issues, e.g. the impact of RVE’s size, mesh density, as well as the discrepancy between 2D and 3D models, are studied.

A model for predicting crack initiation in forged M3:2 tool steel under high cycle fatigue

AISI type M3 class 2 tool steel (or in German designation DIN: HS6-5-3 tool steel) is most commonly used in tooling industry, and also in some engine parts. Those components are usually subjected to cyclic stresses and mostly fail by fatigue. Fatigue crack initiation in this material occupies large fraction of total lifetime and strongly depends on microstructural features of primary and eutectic carbides, such as shape, shape ratio, volume fraction, the distribution of carbides as well as load ratio. To model fatigue initiation mechanisms of forged M3:2 tool steel, McDowell’s model was modified and developed for different length-scales. For fatigue crack formation and short crack growth, a hierarchical approach was used and the life time of these stages were estimated based on the local cyclic plasticity. Through this relation the effect of microstructural features on both fatigue crack formation and short crack growth in the material were identified. The results of the proposed model have explicitly reflected the influence of microstructural features on both fatigue crack formation and propagation in forged M3:2 tool steel. Moreover, the model can be used for improving the fatigue resistance of a tool steel component.

On the Size of the Representative Volume Element Used for the Strength Prediction: A Statistical Survey Applied to the Particulate Reinforce Metal Matrix Composites (PRMMCs)

Particulate reinforced metal matrix composites (PRMMCs) are typical random heterogeneous materials whose global behavior depends on the microstructural characterisics. Recently a numerical approach was developed (Hachemi et al., Int J Plast 63:124–137, 2014 [1], Chen et al. Direct methods for limit and shakedown analysis of structures, 2015 [2]), by applying it to a typical PRMMC material WC/Co, we presented how the ultimate strength and endurance limit can be predicted from the material microstructures. Due to the randomness in the microstructures of PRMMCs, size of the representative volume element (RVE) has a nontrivial influence over the predicted effective behaviors. In order to understand how size of RVEs contribute to the result and based on that to eliminate its influence, a numerical investigation is performed in the present study. In this study, a large number of representative volume element (RVE) samples representing a representative PRMMC material, WC-20 Wt% Co, were built from artificial microstructures. The samples are obviously different in size, and by deploying the established numerical approach to these samples, ultimate strength and endurance limit were calculated. Afterwards, the derived material strengths were analyzed by multiple inferential statistical models. The statistical study reveals how strength and other effective material properties react to the change of the RVE size. On that basis, the study proposed a feasible and computationally inexpensive solution to minimize the size effect.