CHAPTER ONE
1.0 INTRODUCTIONThe word corrosion is derived from the latin corrosus which means eaten away or consumed by degrees; an unpleasant word for an unpleasant process[1]. Corrosion is defined as the destruction of materials caused by chemical or electrochemical action of the surrounding environment. This phenomenon is experienced in day to day living. The most common examples of corrosion include rusting, discoloration and tarnishing[2]. Corrosion is an ever occurring material disease. It can only be reduced it cannot be prevented because thermodynamically it is a spontaneous phenomena.
In fact, economy of any country would be drastically changed if there were no corrosion. For example, automobiles, ships, underground pipelines and house-hold appliances would not require coatings. The stainless steel industry would disappear and copper would be used for electrical applications. Although corrosion is inevitable, its cost could be reduced.
Corrosion can be fast or slow. Sensitized 18-8 stainless steel is badly attacked in hours by polythionic acid. Railroad tracks usually show slight rusting not sufficient to affect their performance over many years. The famous iron Delhi Pillar in India was made almost 2000 years ago and is almost as good as new. Its height is 32 feet and dia 2 feet. It should be noted however, that it has been exposed mostly to arid conditions [3].
1.1 BACKGROUND OF THE STUDY
Atmospheric corrosion is probably the most common form of corrosion and is defined as the corrosion or degradation of material exposed to the air and its pollutants.
Therefore, it is important to know the specific corrosion rate in a given application environment in order to affectively use metals in outdoor structures. A common method for estimating the life of metals has been the use of various types of metals and alloys for the different types of atmospheres. Recognition of marked differences in corrosivity has made it convenient to divide atmospheres into types. The major types are rural, urban, industrial, marine, or a combination of these.
Many investigators have examined the corrosion rates of various metals exposed to different atmospheres (Upham, 1967; Knotkova et al., 1995; Kucera and Fitz, 1995; Mikhailov et al., 1995). These exposure studies were conducted to evaluate the relative corrosion resistance of various metals to different atmospheric environmental conditions. A metal resisting one atmosphere may lack effective resistance elsewhere, and hence, relative performance of metals changes with location. For example, galvanized iron performs well in rural atmospheres but it is relatively less resistant to industrial atmospheres (Uhlig and Revie, 1985).
The term corrosion products refer to the substances produced during a corrosion reaction. These can be soluble or insoluble compounds. The presence of corrosion products is the way in which corrosion is detected (e.g. rust). In general, the properties of the corrosion product are often the determining factors in the atmospheric corrosion behaviour of metals.
Models for predicting the corrosion damage of metals in the atmosphere are useful for answering questions regarding the durability of metallic structures, determining the economic costs of damages associated with the degradation of materials, and acquiring knowledge about the effect of environmental variables on corrosion kinetics (Feliu and Morcillo, 1993; Feliu et al., 1993). These models have been shown to be effective in these areas:
• Determination of the influence of pollutants in corrosion or degradation rate by obtaining regression equations between the different variables.
• Predictions about corrosion aggressivity of the atmosphere can be made based on the characteristics of the environment and the materials.
Both deterministic and statistical models have been developed for better understanding the environment. Deterministic models are based on fundamental mathematical descriptions of atmospheric processes, in which effects (air pollution) are generated by causes (emissions). Examples of the deterministic types are Euler and Gaussian models (Zannetti, 1983, 1994). On the other hand, Statistical models are based on semi-emprical statistical relations among available data and measurements. They do not necessarily reveal any relation between cause and effect.
They attempt to determine the underlying relationship between sets of input data (predictors) and targets (predictands). Examples of statistical models are regression analysis (Abdul-Wahab et al., 1996), time series analysis (Hsu, 1992) and artificial neural networks (Abdul-Wahab, 2001; Abdul-Wahab and Al-Alawi, 2001; Elkamel et al., 2001).
1.2 OBJECTIVE OF THE STUDY
The main objective of this work is to assess the degrading effects of atmospheric corrosion on various metals that are mostly used in the engineering systems.. The common materials like aluminum, brass, copper, epoxy, galvanized, mild steel and stainless steel. This paper is to use regression analysis to predict corrosion rates of various metals at specific locations and the atmospheric corrosion of common metals was studied.
1.3 SCOPE OF THE STUDY
This work is dealing essentially with atmospheric corrosion to assess the degrading effects of air pollutions on various metals that are mostly used in the engineering systems. The common materials like aluminum, brass, copper, epoxy, galvanized, mild steel and stainless steel were used for investigation. The sites of exposure were chosen at five locations where the metals are likely to be used. Additive models using median polish were used to investigate the patterns of corrosion by metal type and location. Regression analysis was also used to develop a number of predictor models for corrosion, based on metal type, location, number of months of exposure, and number of degrading pollutants in the air.
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