This research uses nonlinear Rayleigh surface waves to characterize stress corrosion cracking (SCC) damage in sensitized 304 Stainless Steel (304 SS). 304 SS is widely used in reactor pressure vessels and fuel pipelines, where a corrosive environment in combination with applied stress due to high internal pressures can cause SCC. SCC poses great risk to these structures as it initiates cracks late in the lifetime and often unexpectedly. The initiated microcracks grow and accumulate very quickly to form macroscopic cracks that lead to material failure. Welds and the nearby heat affected zones (HAZ) in the vessels and pipework are particularly affected by SCC as welding induces sensitization in the material. SCC damage results in microstructural changes such as dislocation movement and microcrack initiation that in the long term lead to reduced structural integrity and material failure. Therefore, the early detection of SCC is crucial to ensure safe operation. It has been shown that the microstructural changes caused by SCC can generate higher harmonic waves when excited harmonically. This research considers different levels of SCC damage induced in samples of sensitized 304 SS by applying stress to a specimen held in a corrosive medium (Sodium Thiosulfate). Nonlinear Rayleigh surface waves are introduced in the material and the fundamental and the second harmonic waves are measured. The nonlinearity parameter that relates the fundamental and the second harmonic amplitudes, is computed to quantify the SCC damage in each sample. The results obtained are used to demonstrate the feasibility of using nonlinear Rayleigh waves to characterize SCC damage.
Identifer | oai:union.ndltd.org:GATECH/oai:smartech.gatech.edu:1853/53025 |
Date | 12 January 2015 |
Creators | Morlock, Florian |
Contributors | Jacobs, Laurence J. |
Publisher | Georgia Institute of Technology |
Source Sets | Georgia Tech Electronic Thesis and Dissertation Archive |
Language | en_US |
Detected Language | English |
Type | Thesis |
Format | application/pdf |
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