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100 1 _ |a Ganesh, Vishnu
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245 _ _ |a Determination of mechanical properties of tungsten/steel composites using image based microstructure modelling
260 _ _ |a Amsterdam [u.a.]
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520 _ _ |a Graded tungsten/steel composite is a potential interlayer to alleviate the thermal expansion mismatch between tungsten (W) armour and steel structure in the first wall (FW) of a future fusion reactor. However, existing thermomechanical finite element (FE) numerical simulations of the FW featuring this graded interlayer have modelled the composites inappropriately by assuming their properties to follow an elementary rule of mixtures; linear interpolation of the properties of W and steel based on the volume content of W. This opens up the question of determining the properties of the composites appropriately. Thus, in this study, a microstructural image based modelling technique is proposed to predict the macroscopic mechanical properties of the composites. As a case study, plasma sprayed W/steel composites of three compositions were investigated. FE simulations of the corresponding microstructures, captured via scanning electron microscopy (SEM), were carried out with the help of an open source code (OOF2) which transforms the SEM images into a 2-dimensional mesh. For the determination of macroscopic mechanical properties, image based finite element (FE) simulations of the mapped mesh were carried out. These simulations were done on microstructures of different physical sizes, including mesoscale and microscale morphological artefacts. Also, for each physical size, several SEM images were captured at different sites in the composites to consider the randomness of the material. FE simulations were conducted at various virtual temperatures between 20 °C and 700 °C. The predicted mechanical properties agreed much better with the few available experimentally determined literature values of the composites than the simple linear interpolation.
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700 1 _ |a Dorow-Gerspach, Daniel
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700 1 _ |a Linsmeier, Christian
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773 _ _ |a 10.1016/j.nme.2023.101496
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