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CORROSION PROPERTIES, CHEMICAL COMPOSITION, AND SURFACE MORPHOLOGY OF NON-FERROUS METALS AFTER TESTS AT DIFFERENT TEMPERATURE AND HUMIDITY CONDITIONS
Abstract
In order to predict the shelf life of non-ferrous metals in warehouses, the laboratory studies of the kinetics of corrosion processes of metals
under various temperature and humidity conditions were performed. The paper presents the results of 12 months corrosion tests of non-ferrous metals:
aluminium, cobalt, copper, nickel, tin, lead, and zinc at various values of relative humidity and air temperature. It is shown that all metals studied are
corrosion-resistant under atmospheric conditions at a relative humidity of no more than 80% and an air temperature of no more than 30 °C. An increase
in air humidity from 70 to 95% and air temperature from 20 to 50 °C leads to an increase in corrosion losses of metals, primarily for zinc, cobalt and lead.
During the tests, changes in the appearance of the samples surface were recorded, and chemical, phase composition and morphology of the oxide
films on the metal surface were studied after different test periods. The results will be used in the development of a method to predict the shelf life of
non-ferrous metals.
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The atmospheric corrosion of metallic materials causes great economic loss every year worldwide. Thus, it is meaningful to predict the corrosion loss in different field environments. Generally, the corrosion prediction method includes three parts of work: the modelling of the corrosive environment, the calibration of the corrosion effects, and the establishment of the corrosion kinetics. This paper gives an overview of the existing methods as well as promising tools and technologies which can be used in corrosion prediction. The basic corrosion kinetic model is the power function model and it is accurate for short-term corrosion process. As for the long-term corrosion process, the general linear models are more appropriate as they consider the protective effect of the corrosion products. Most corrosion effect models correlate the environmental variables, which are characterized by the annual average value in most cases, with corrosion parameters by linear equations which is known as the dose-response function. Apart from these conventional methods, some mathematical and numerical methods are also appropriate for corrosion prediction. The corrosive environment can be described by statistical distributions, time-varying functions and even geographic information system (GIS), while the corrosion effect can be captured via response surface models and statistical learning methods.
A technique for calculation of coefficients in the power-linear function for long-term prediction of corrosion losses of structural metals is presented. The formula consists of a power function at the initial corrosion stage and a linear function at the stationary stage. Conditions for application of the power and power-linear functions for long-term prediction of corrosion losses of technically important metals in various regions of the world are shown. A comparative estimate of predicted corrosion losses of metals based on the equations provided in this study and in ISO CORRAG 9224:2012(E) standard is given.
In the present paper, a study of the atmospheric corrosion of copper, zinc and aluminium exposed on three test sites indoors and outdoors (coastal, urban-industrial and rural) under different exposure conditions up to 18 months is reported. Corrosion results are treated statistically and adjusted to a model previously proposed for steel [A.R. Mendoza, F. Corvo, Corrosion Science 41(1) (1999) 75–86.] based on the influence of environmental parameters and main pollutants (SO2 and chlorides) on the atmospheric corrosion of metals. The interaction between the chloride deposition rate with the time of rainfall (outdoors) and with the time of wetness at temperature between 5°C and 25°C (indoors) were found to be the most significant variables influencing the corrosion of the three metals investigated; although other variables appeared to be important in the corrosion process depending on the metal nature. The results obtained confirm and allow us to expand the model previously proposed for steel to non-ferrous metals. A classification of the atmospheric corrosion aggressivity of the test sites based both on environmental data and corrosion rate measurements was made according to ISO 9223. The corrosion aggressivity prognostic of this standard is not always in agreement with the results obtained in Cuban atmospheric conditions.
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