Corrosion tests curve fitting

ASTM G 16, Guide for Applying Statistics to Analysis of Corrosion Data—Statistical analysis methods are presented. The methods discussed in this standard allow investigators to determine the significance of their results with the inherent variation observed in corrosion testing. This method includes error analysis, variability measures, standard statistical tests, curve fitting methods, and sample calculations. 

Corrosion scientists seldom have enough replicate data to analyze distributions using such techniques as histograms and tests of fit. Sometimes, however, enough data are available to order and plot as a function of linearized forms of the different kinds of probability distributions. Also, nonlinear least squares curve fitting may be used. The best approach is to choose the type of distribution that cleeirly produces the best approximation to a straight line. If an extreme value distribution is only slightly better than a normal distribution, a normal distribution may be assumed because the statistical techniques are easier to use and more universally understood. 

An extension of the ECT method described above that has been used to evaluate alloys for service on North Sea oil platforms [97,98] htis been referred to as cyclic ther-mammetry [99]. The technique involves exposing a coupion fitted with an MCA to a test solution under eui applied potential that simulates a process environment. The current density of the crevice specimen is monitored eis the temperature of the test solution is slowly chemged (e.g., 4°C/24 h) in a cychc mEinner up to a critical vcJue smd then back towEird room temperature. The test results Eire in the form of a curve (Fig. 5) that looks very much like a conventional Emodic polEirization curve [97] with the exception that temperature rather than applied potential is the independent variable. VEdues for a critical crevice corrosion... 

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