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Development of a machine-learning approach for predicting the corrosion rate of steel in aqueous electrolytes
The object of research is the corrosion of St20 steel in aqueous electrolytes of different salt compositions under aerated and deoxygenated conditions. The problem addressed is the development and comparative evaluation of corrosion rate prediction models based on a limited experimental dataset, with the possibility of...