This thesis describes innovative methods used to predict high-stress amplitude, low cycle fatigue (LCF) behavior of a material commonly used in gas turbine blade design with the absence of such data. A combination of extrapolation and estimation techniques from both prior and current studies has been explored with the goal of developing a method to accurately characterize such high-temperature fatigue of IN738LC, a dual-phase Ni-base superalloy. A method capable of predicting high-stress (or strain) amplitude fatigue from incessantly available low-stress amplitude, high cycle fatigue (HCF) would lower the costs of inspection, repair, and replacement on certain turbine components. Three sets of experimental data at different temperatures are used to evaluate and examine the validity of extrapolation methods such as anchor points and hysteresis energy trends. Stemming from extrapolation techniques developed earlier by Coffin, Manson, and Basquin, the techniques exercised in this study purely implement tensile test and HCF data with limited plastic strain during the estimation processes. A standard practice in engineering design necessitates mechanical testing closely resembling planned service conditions; for design against fatigue failure, HCF and tensile data are the experiments of choice. High stress amplitude data points approaching the ultimate strength of the material were added to the pre-existing HCF base data to achieve a full-range data set that could be used to test the legitimacy of the different prediction methods. While some methods proved to be useful for bounding estimates, others provided for superior estimation.

The global market for wind energy is expanding rapidly, and in the last decade, Sweden has constructed thousands of wind turbines. The high installation pace suggests that a similarly rapid decommissioning rate is to be anticipated in the near future, notwithstanding the small number of turbines that have been retired thus far. There will be serious questions about the viability of wind power as a clean energy option if the decommissioned material by unfunctional turbines is not managed in a proper manner. The purpose of this research is to provide the distribution of Swedish installed wind turbine with the aspect of age, brand & model, hub height & rotor diameter, and nameplate capacity and also a reliable estimate of the total amount of decommissioned material that will be produced by wind turbines in Sweden over the next two decades. The results will represent to current characteristic of an industry to benefit the operation & maintenance activity and wind industry market research. Moreover, this will also help the waste management sector prepare for the inevitable increase in decommissioned material. The estimates are based on the installation dates, rotor diameter and other pertinent data included in vbk.lansstyrelsen.se, a Swedish national wind turbine map service. Applying the available data set with logarithmic function of rotor diameter and material fraction technique, the quantity of steel, iron, copper,aluminium, blade material, and electronics were generated. The material of each turbine is considered to be dismantled as wastes at 20 years after the installation date due to the industry average and comparison with empirical facts. As the results, the distributions show that most of Swedish wind turbines were installed between 2007 and 2016 and the most popular rated capacity ranged between 2 MW to 3 MW. Furthermore, the biggest market share belonged to Vestas, Enercon, and Siemens, respectively. The forecasted numbers reveal a large increase in decommissioned material weights year by year, and the blade material end-of-life management is the key concern when comparing the estimated number to Sweden's waste management capacity. Limitations associated with the suggested methodology and adopting data set are presented and discussed.