Abstract

Zr-based alloys have been used in the commercial nuclear industry for decades. The wear behavior of such alloys has also attracted attention. However, the extreme operating environment that exists a nuclear reactor presents considerable experimental difficulties for investigating aspects of wear. Therefore, a robust computational model of wear, based on experimental data, could provide a useful tool to examine wear for different variables. Towards this end, specimens of Zircaloy-4 were subjected to wear testing within the aqueous environment of a high-temperature, high-pressure autoclave for a range of amplitudes at a fixed pressure. The wear surfaces before and after testing were investigated using microscopy techniques. The change in surface roughness that resulted from wear was measured and evidence of plastic deformation and wear debris was observed. Characterization of surfaces prior to testing revealed some degree of self-affinity over multiple length scales which diminishes as the evaluation length approaches tens of microns. The experimental roughness profiles of the starting surfaces were comparable to computer simulations of multiscale roughness using separate fractal and Monte Carlo techniques and demonstrate that these methods could be used to generate surfaces. Further, we demonstrate that isotropic methods of roughness simulation can be tuned to reproduce the observed departure from self-affinity, but must be modified to capture directional features. Lastly, results of FEM analysis of surfaces with RMS roughness of 1.25–94 µm showed a significant spatial variation in starting stress state with indications of localized plastic deformation at surface asperities for the applied loads used in this study, which qualitatively agreed with the observations of localized wear and plastic deformation of the worn surfaces. This work demonstrates a path by which experimental results can be coupled with computational methods to construct a means to investigate the effects of surface roughness on wear.

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