Fatigue is one of the main failure mechanisms in engineering. Mechanical surface treatments are being widely used to reduce the incidence of fatigue failures. A new surface treatment, laser shock peening, or laser peening (LP) is being widely studied especialJy in the aerospace industry. LP-induced beneficial residual stresses (RS) act against structural loads leading to an increase in fatigue resistance. Therefore, one of the main parameters determining the fatigue life improvement after LP is the RS fields. Hence, it is crucial that the RS measurement and optimization is carried to obtain the most prolonged fatigue life after LP. RS after LP were obtained by incremental hole drilling, surface X-ray diffraction, synchrotron X-ray diffraction and neutron diffraction. The contour method of stress measurement was developed for thin samples and near-surface measurements in thick samples. Near-surface RS as well as RS in thin plates after LP, which are very challenging to obtain in a reliable manner due to geometrical and material constraints, were measured by at least two different methods to increase the confidence in the results. The possibility of application of LP to thin sections was investigated in this dissertation. After examining different LP parameters and systems, a beneficial RS field after LP was obtained. RS measurements and fatigue tests by Cranfield University, UK, suggest that LP can be applied to thin plates to have a significant increase in fatigue resistance as long as LP parameters are chosen appropriately. RS measurements were also conducted for thick samples after LP. RS results with fatigue tests conducted by EADS lW, Germany, confirm the increase in fatigue performance. Increase in surface roughness and geometrical distortion after LP were also observed for both thin and thick aluminium alloy samples after LP.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:582812 |
| Date | January 2012 |
| Creators | Toparli, Muhammed Burak |
| Publisher | Open University |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
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