The presence of residual stresses in engineering components may significantly affect damage evolution and progression towards failure. Correct evaluation of residual stress is of crucial importance for assessing mechanical components, predicting response and ensuring reliability. For example, when failure occurs due to cyclic loading, the underlying damage begins at the nano-, and then micro-scale. It is clear that improving engineering reliability at the micro-scale requires the ability to evaluate residual stress and mechanical properties at the appropriate scale. The key objective of the thesis is to advance the understanding and practice of residual stress evaluation at the micro-scale, and to examine the implications and applications that follow. Significant effort was devoted to the evaluation of two aspects of the relatively novel FIB-DIC micro-ring-core experimental technique: assessing the effects of Ga-ion damage and the quantification of uncertainty in stress evaluation due to unknown crystal orientation. FIB-DIC micro-ring-core milling was then used alongside with synchrotron XRD to study residual stress effects on fatigue crack growth propagation rate following the occurrence of overload or underload. The effects of the two principal mechanisms of crack retardation following an overload, residual stress and crack closure, were separated by testing samples at different loading ratios. Whilst, the acceleration after an underload was studied using validated non-linear FEM analyses. Conceptual focus was placed on the macro-micro-nano residual stress decomposition into Type I, II & III according to scale and, detailed examination was conducted experimentally and numerically. In the context of shot-peening surface treatment, residual stresses were modelled using a novel eigenstrain-based modelling procedure for arbitrarily shaped components. Furthermore, a fine scale characterisation was performed of the recast layer produced by EDM, with particular attention paid to the residual stress. The investigations presented in this thesis open new perspectives for the assessment of material reliability. Improved failure prediction models will be elaborated based on the insights obtained in the present study.
Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:740928 |
Date | January 2017 |
Creators | Salvati, Enrico |
Contributors | Korsunsky, Alexander M. |
Publisher | University of Oxford |
Source Sets | Ethos UK |
Detected Language | English |
Type | Electronic Thesis or Dissertation |
Source | https://ora.ox.ac.uk/objects/uuid:b737925e-a200-4a61-87f1-0d834d642d7b |
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