Abstract
The incineration of municipal solid waste as the main process of Waste-to-Energy (WTE) plants is often associated with high temperature corrosion problems. On the way to increase the electric power generating efficiency and reduce the total cost of WTE units, it is important to develop preventive maintenance strategies based on accurate predictive methods, which result in economic savings and resource optimization. The main purpose of this study is to propose a statistical methodology for lifetime prediction modeling over a wide range of conditions of these complex environments and discuss the results regarding the mechanisms described in the literature. In order to create a quantitative tool for evaluating material corrosion performances based on adapting corrosion tests and the definition of accurate criteria for life assessment, a database with 1595 test results has been built from several high temperature corrosion published studies, the data distribution was analyzed by descriptive statistic approaches, the procedure of Principal Components Analysis (PCA) was applied to determine the most important parameters that govern the corrosion process. The statistical results were matched with the experimental findings of the authors to create a model by Multiple Regression Analysis whose accuracy and physical sense were discussed.
