QUT Digital Repository: http://eprints.qut.edu.au/27064

Innovation in construction will not be. responsible for the results of any action taken by the Client or third parties based on the information in this Report or other information provided by Construction Innovation nor for any errors or omissions that may be contained in this report. The single sided product has a 20 µm thick UV resistant top layer and a 5 µm gray backing layer covering the primer (Bluescope Steel, 2005). the gutters are assembled so that the backing layer forms the inside of the gutter and the colored top layer forms the outer gutter. Figures 1 and 2 show the appearance of each of the samples after two rinse cycles and seven rinse cycles, respectively.

During the test period, Colorbond samples were exposed to aqueous solutions at pH 2. The release during the first 24 hours was modeled using Fick's second law of diffusion [3], where a plot of log[dC/dt] ( the concentration change over time) against log t gives a slope representing the exponent of the inhibitor release. The rate of chromate degradation of a damaged top layer (with holes according to cell 5) and an undamaged back layer of Colorbond materials was determined during the first 24 hour period and was then estimated from the solution concentrations of strontium ions.

Rather, the increased rate of degradation in humid environments is handled elsewhere in the model in terms of the rate at which the corrosion inhibitor is consumed within a polymeric film. Failure of the topcoat and backcoat results in an increased loss of chromate from the undercoat. In the current model, new data from chromate leaching experiments at pH 2 have developed relationships linking the rate of chromate removal to the rate at which the underlying metal is removed.

The amount of chromate removed in the accelerated experiment can be about 100 times that at pH 6.

Table 1. Experimental details of leaching studies.

Degradation of damaged (with pinholes) Colorbond topcoats

Degradation of undamaged Colorbond backcoats

Correlations between the concentration (in mol L-1) of strontium released into solution and the concentration of zincalum and steel in an aqueous solution acidified to pH 2 with HCl. Where Crt×0.417 represents zinc loss, Crt×1.066 represents aluminum loss, and the remainder of the equation is a scaling factor relating the rate of zincalum loss from laboratory tests in 0.01 M chloride to the average daily field salinity (mg/m2.day). Correlations between the concentration of strontium released into solution and the concentration of zincalum and steel in an aqueous solution acidified to pH 2 with HCl.

Application of model to other painted metal building products

5 MODELS FOR THE SETUP OF SALT AND THE TIME OF WETNESS IN GUTTS (reworked). The main causes of these variations observed during roof surveys are: i) the presence of dirt or leaf litter in the gutter, or (ii) improperly installed or damaged gutters that retain pools of moisture. For modeling purposes it is assumed that the time of wetness (TOW) experienced by gutters is the same as that of an open roof, but only if it is clean and well drained (i.e. the gutter is wet when the roof is wet).

For modeling purposes, a dirty or water-bearing gutter is assumed to be wet unless the relative humidity (RH) is less than the critical humidity (defined by the type of salts present) for more than 240 hours. The accumulation of salt in gutters is modeled by assuming that all salt entering the gutters originates from the roof. Therefore, the following inputs must be specified for the calculation of TOW and salt concentration within gutters:.

Clean and well-drained gutter 2. Dirty or water retaining gutter 3. Details of the implemented model for the calculation of TOW and salinity are included in Table 2. A comparison of old and new implementations for the calculation of salt concentration and time of wetness in gutters. mg/m2.day) - seasonal values from previous implementation. An example of the model's performance is given by the calculated data for Brookfield State School in Queensland.

Estimates of salt accumulation in gutters at Brookfield State School calculated from rainfall runoff and accumulation using the legacy model. The old model has an average accumulated salt concentration of 10.7 mg/m2, while the new model. However, the presence of dirt in gutters and improperly installed gutters keep them wet for longer periods of time.

The constant phase element has the form given in equation 16, where a constant phase element can be used instead of the double layer capacitance [13]. When a CPE is placed in parallel with a resistor, a Cole Element (semi-suppressed) is produced similar to that of the short-circuit Warburg resistor. The CPE element is most often used in place of a capacitor to compensate for inhomogeneity in the system.

Figure 11. The relationship between roof area and gutter area. Roof area = L/0.1 (or 10 × L) times the gutter area

Experimental Details

Results for unexposed Colorbond®

Estimates of corrosion rate based upon polarization resistance

That is, it is assumed that the high rates measured after 29 years would be obtained from a much larger metal solution contact area due to paint delamination. However, the key result from Tables 5 and 6 is the correctly predicted corrosion magnitudes and the reproducibility of the model to distinguish between high and low corrosivity sites. A comparison of EIS measured corrosion rates, estimated corrosion rates for the equivalent time period (from model) and the estimated time to failure (given as the time to complete removal of the protective zincalume).

A comparison of EIS measured corrosion rates, estimated corrosion rates for the equivalent time period (from model) and the estimated time to failure (given as the time to complete removal of the protective zinc alum). The model for predicting the service life of painted metal components has been updated and improved. The corrosion rates predicted by the model have been validated to some extent by field measurements using electrochemical impedance spectroscopy.

The field measurements were limited to several schools in coastal Queensland, and therefore further validation would be required to ensure their accuracy for wider Australia. There are numerous factors that determine the rate of degradation of painted components and some of these factors remain to be investigated. For example, the rate at which paint delaminates and how this affects the removal of corrosion inhibitors and the occurrence of corrosion damage.

The performance of the currently presented model in damage prediction should be finally validated through further long-term experimental studies, which would be required to demonstrate statistical significance in its predictions. A holistic model for atmospheric corrosion: part 1 - theoretical framework for the production, transport and deposition of marine salts.