Pit depth measurements

The depth of a one-dimensional pit increases with the square root of time. The proportionality constant Kq depends on the imposed potential difference and the electrolyte conductivity. Pit growth under ohmic control is observed mostly in weakly conducting electrolytes, such as drinking water. Figure 7.63 shows the progression of pit depth, measured on aluminum in contact with natural water [35]. The results are in good agreement with the simple theory developed above. 

Ultrasonic measiurements can be used to supplement mechanical pit depth measurements and can be used in areas where the internal condition of the pipe must be determined. Ultrasonic measurements can be analyzed, using the same statistical approach as mechanical measurements. Additional information for ultrasonic inspection is found in ASTME212 and Ref 32. 

Reboul M., Odievre T., Warner T.J., Pit depth measurement on aluminium alloys by image analysis of radiographic films, Eurocor, Trondheim, 1997, p. 271-278. 

A portion of the original surface should be protected so as to provide a datum line for the measurement of pit depths. 

For the profile (length from 0.5 to 3 km, point interval of 50 m) sampling, both small hand-dug test pits (depth about 50 cm) and percussion drilling (sampling depth 1 to 1.5 m) have been used. Measurements were made using the ScanMobile system which is a moving... 

Laser inspection of the sample surface can also yield information on surface flaws such as the surface roughness and defects. The laser beam incident on the surface of the sample is scattered, and the scattered light intensity decreases when a crack is present on the surface. The experimental arrangement for scanning the surface of a sample is shown in Figure 2.7. A laser-based profilometer may also be used in the measurement of pit depths. 

A somewhat alternative analysis of pitting attributes pit initiation to the activation of defects in the passive film, defects such as those induced during film growth or those induced mechanically due to scratching or stress. The pit behavior is analyzed in terms of the product, xi, a parameter in which x is the pit or crevice depth (cm), and i is the corrosion current density (A/cm2) at the bottom of the pit (Ref 21). Experimental measurements confirm that, for many metal/environment systems, the active corrosion current density in a pit is of the order of 1 A/cm2. Therefore, numerical values for xi may be visualized as a pit depth in centimeters. A defect becomes a pit if the pH in the pit becomes sufficiently low to prevent maintaining the protective oxide film. Establishing the critical pH, for a specific oxide, will depend on the depth (metal ions trapped by diffiisional constraints), the current density (rate of generation of metal ions) and the external pH. In turn, the current density will be determined by the local electrochemical potential established by corrosion currents to the passive external cathodic surface or by a potentiostat. Once the critical condition for dissolution of the oxide has been reached, the pit becomes deeper and develops a still lower pH by further hydrolysis. 

Another nonelectrochemical approach to pitting involves the study of two-dimensional pits in thin-fihn samples [1,66, 73-75]. Pits in thin metallic films with thickness on the order of 10-1000 nm rapidly penetrate the metal, reach the inert substrate, and proceed to grow outward in a two-dimensional fashion with perpendicular sidewalls. The measurement of pit wall velocity from the analysis of magnified images of the growing two-dimensional pits provides a simple and direct means for determination of pit current density via Faraday s law, with no need for assumptions. Since the pit depth... 

Weight measurements are not usefijl to evaluate pitting corrosion since a small number of pits can penetrate the reactor wall and cause failme with very small weight loss. Table 7.1 lists pit depth measmement methods according to ASTM G 46-94 [5]. 

The coupon racks were visually observed every 30-40 days. Photographs were also taken periodically. Some coupon assemblies were periodically removed from the basin for pit measurements, i.e. of pitting density and pit depth. Pit measurements were performed using an optical metallurgical microscope at a magnification of 200-500 x. The coupons from rack 1 were washed in 5% phosphoric acid to remove the oxide layer prior to carrying out the measurements. The coupons from rack 2 were taken for pit examination without removing the oxide layer. 

For characterizing the corrosion damage due to pitting one measures the depth distribution of pits. From such data the evolution of maximum pit depth with time or the time to perforation can be estimated using statistical methods [23,24]. Because pitting is a random process the observed pit depth depends on the surface area taken into account. The depth L has been found to vary according to a power law (7.25) or a logarithmic law (7.26) where A is the surface area and K (i = 1,2. .) are constants. 

Figure 7.63 Pit depth on alnminum versus exposure time in natural water. The theoretical curve is calculated with equation (7.35) using K = 5.7 x 10" 2 cm , A0 = 15 mV. The different symbols represent different measurements carried out under identical conditions [35].

If valid, it could provide a quantitative methodology for relating measured pit depths to equipment life. In terms of required data, one needs to know the surface area of both the laboratory coupon and the object being examined by the coupon and the depths of the pits on the coupon. 

Another way to quantify the extent of pitting is to just examine the pitted surface of an unprepared sample under a laboratory microscope. By measuring the vertical difference, via micrometer measurements on focus knob, between the top of sample and bottom of pit, the pit depth can be measured. One should use this method with caution because pits are not always straight. Pits may travel a circuitous path, and measurement of the perceived pit bottom will result in an overly conservative depth. 

A number of statistical transformations have been proposed to quantify the distributions in pitting variables. Gumbel is given the credit for the original development of extreme value statistics (EVS) for the characterization of pit depth distribution [13]. The EVS procedure is to measure maximum pit depths on several replicate specimens that have pitted, then arrange the pit depth values in order of increasing rank. The Gumbel distribution expressed in Eq 1, where X and a are the location and scale parameters, respectively, can then be used to characterize the dataset and estimate the extreme pit depth that possibly can affect the system from which the data was initially produced. 

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