This investigation primarily focused on the validation of the software being developed for crack growth and remaining life prediction using SCADA data. A total of nine pressure spectra, four for oil pipelines and five for gas pipelines, have been collected and used as inputs for the software. It was found that these spectra could be categorized as the underload-, the meanload- and the overload-dominant spectra; each of them have shown different effects on crack growth: the underload spectra, typical of pressure fluctuations at the discharging sites, are most susceptible to crack growth because of load interactions between the minor pressure fluctuations and the unload cycles; while the overload spectra, often found at the suction site, have exhibited retarded crack growth due to the retardation effects caused by overloading. The relative severity of the load interactions in terms of crack growth rate for a given spectrum was quantified using a parameter termed as the Spectrum Factor. A Spectrum Factor greater than one indicates the enhanced crack growth rate by load interactions, such as the case where unloading is frequently present in the pressure spectra, while a Spectrum Factor lower than one may be associated with a retarded crack growth, which can be seen in pressure spectra with predominant overloading events. The predictions made by the models being developed were also compared with those made by the rainflow counting method. The software allows for the SCADA/pressure fluctuation data, in excel spreadsheet format, to be directly analyzed producing a projected remaining life of the pipeline based on the past pressure fluctuations and the assumed future pressure fluctuations.

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