In this paper a mechanism-based model is presented, which is able to describe the evolution of microcracks under pure low cycle fatigue (LCF) and combined LCF and high cycle fatigue (HCF) loading conditions. In order to verify the model and to calibrate the model parameters, the crack length evolution of microcracks is followed at room temperature for pure LCF and combined LCF/HCF loading in a 10%-chromium steel. These studies reveal accelerated crack growth rates under LCF/HCF interaction as soon as a critical crack length is reached. The model is capable of accounting for this effect and needs only few parameters, including the threshold for fatigue crack growth, whose knowledge is crucial for the accuracy of the model

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In this paper the thermomechanical fatigue properties of 1.4849 cast steel, which is used for exhaust manifolds and turbochargers, are investigated and a fracture mechanics based approach is used for fatigue life prediction. Isothermal low-cycle fatigue tests and thermomechanical fatigue tests are conducted in the temperature range from room temperature up to 1 000 °C. Fractographic investigations show that fracture occurs predominantly intergranularly at 600 °C, whereas mixed transgranular and intergranular crack growth is found otherwise. The methodology for fatigue life prediction is based on a time and temperature dependent cyclic plasticity model, which describes the transient stresses and strains, and on a law for time and temperature dependent microcrack growth. The crack growth law assumes that the increment in crack length in each cycle, da/dN, is correlated with the cyclic crack-tip opening displacement, δCTOD. An analytical fracture mechanics based estimate of δCTOD is used, which is derived for non-isothermal loadings. The fatigue lives of the low-cycle and the thermomechanical fatigue tests are predicted well with the model. Only predictions for the low-cycle fatigue tests at 600 °C, where integranular fracture is predominant, are non-conservative.

In this perspective article, we present the project initiative Materials-open-Laboratory (Mat-o-Lab) that aims to provide a collaborative environment for domain experts to digitize their research results and processes and make them fit for data-driven materials research and development. The overarching challenge is to generate connection points to further link data from other domains to harness the promised potential of big materials data and harvest new knowledge.

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