Vera, R., Araya, R., Garin, C., Ossandon, S., & Rojas, P. (2019). Study on the effect of atmospheric corrosion on mechanical properties with impact test: Carbon steel and Galvanized steel. Mater. Corros., 70(7), 1151–1161.
Abstract: The present work presents the behavior of carbon steel and galvanized steel against atmospheric corrosion after 3 years of exposure at seven locations around the region of Valparaiso, Chile. Results show a relation between corrosion rates and environmental and meteorological conditions, categorized as CX for the Quintero zone, and C3 and C2 in the remaining six zones. Corrosion rate behaviors and material toughness losses were modeled using power functions and neural networks, found to be a function of environmental exposure time. Losses were greater for carbon steel in coastal and industrial environments, reaching 70 to 80%. This effect was reduced in galvanized steel, not exceeding 15% over the same period of exposure. The relationship between corrosion rate and loss of toughness of both materials was modeled using neural networks.
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Zhang, H. L., Baeyens, J., Degreve, J., & Caceres, G. (2013). Concentrated solar power plants: Review and design methodology. Renew. Sust. Energ. Rev., 22, 466–481.
Abstract: Concentrated solar power plants (CSPs) are gaining increasing interest, mostly as parabolic trough collectors (PTC) or solar tower collectors (STC). Notwithstanding CSP benefits, the daily and monthly variation of the solar irradiation flux is a main drawback. Despite the approximate match between hours of the day where solar radiation and energy demand peak, CSPs experience short term variations on cloudy days and cannot provide energy during night hours unless incorporating thermal energy storage (TES) and/or backup systems (BS) to operate continuously. To determine the optimum design and operation of the CSP throughout the year, whilst defining the required TES and/or BS, an accurate estimation of the daily solar irradiation is needed. Local solar irradiation data are mostly only available as monthly averages, and a predictive conversion into hourly data and direct irradiation is needed to provide a more accurate input into the CSP design. The paper (i) briefly reviews CSP technologies and STC advantages; (ii) presents a methodology to predict hourly beam (direct) irradiation from available monthly averages, based upon combined previous literature findings and available meteorological data; (iii) illustrates predictions for different selected STC locations; and finally (iv) describes the use of the predictions in simulating the required plant configuration of an optimum STC. The methodology and results demonstrate the potential of CSPs in general, whilst also defining the design background of STC plants. (C) 2013 Elsevier Ltd. All rights reserved.
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