Click for next page ( 23

The National Academies | 500 Fifth St. N.W. | Washington, D.C. 20001
Copyright © National Academy of Sciences. All rights reserved.
Terms of Use and Privacy Statement

Below are the first 10 and last 10 pages of uncorrected machine-read text (when available) of this chapter, followed by the top 30 algorithmically extracted key phrases from the chapter as a whole.
Intended to provide our own search engines and external engines with highly rich, chapter-representative searchable text on the opening pages of each chapter. Because it is UNCORRECTED material, please consider the following text as a useful but insufficient proxy for the authoritative book pages.

Do not use for reproduction, copying, pasting, or reading; exclusively for search engines.

OCR for page 22
22 For the purpose of this comparison it is assumed that all near the wall face due to the potential for infiltration of storm samples in Figure 9 are still coated with zinc. Thus, for the water and relatively higher levels of oxygen within the fill at AASHTO model, the corrosion rate remains constant after these locations. However, the majority of the data as described 2 years (4 m/yr). The AASHTO model appears to be a good in the interim report indicates that location does not have a upper limit for metal loss throughout the experience period significant effect on measured corrosion rates. Data from one and most of the data points lie well below the envelope site in New York exhibits higher corrosion rates for samples described by the AASHTO model (note that many of the data located near the face compared to the backside of the rein- points in Figure 9 overlap one another). Many of these data forced fill. Data from several sites in California, where inspec- represent metal loss that is less than half of what is computed tion elements were placed along three rows at vertical spacing with the AASHTO model. This is consistent with the analysis of 10 feet, suggest that increased corrosion activity may occur of metal loss and corrosion rate measurements reported by near the top of the walls. Given the limited amount of data Gladstone et al. (2006). and lack of a clear trend, spatial variability is considered to be Appendix B includes data for which LPR measurements are random for the purpose of the reliability analysis and calibra- directly compared with visual observations. Much of these data tion of resistance factor. are from elements extracted during fieldwork for Task 6 per- formed in cooperation with Caltrans. These data demonstrate that the ratio of maximum metal loss (i.e., loss of tensile Temporal Variations strength) to average corrosion rate or metal loss from LPR The effect of time on corrosion rates is apparent in the measurements ranges from 1.2 to 4.8 with a mean of 2.4. This data. For galvanized reinforcement and fill materials that factor appears to be inversely proportional to severity of cor- meet AASHTO requirements for electrochemical parame- rosion and tends to range between 2 and 3 when more severe ters, on average, lower corrosion rates are realized from sam- loss of cross section is observed. ples with ages between 2 and 16 years compared to those that For galvanized elements, corrosion rates via LPR correlate are younger than 2, or older than 16 years. This is due to the best with the percentage of zinc remaining on the surface. When attenuation of corrosion rate with respect to time, and the more than 70% of the surface is covered by zinc, corrosion rates possibility that higher corrosion rates prevail as zinc is con- measured via LPR reflect the rate of zinc loss. However, there sumed from galvanized samples. Although the upper bound may be instances in which localized corrosion of steel may not of corrosion rate measurements for galvanized reinforce- be reflected in the LPR measurement of corrosion rate. This is ments less than 2 years old is close to 15 m/yr, which is the more of an issue at sites with relatively poor or marginal qual- rate included in the AASHTO model for young (<2 years ity fill materials where metal loss is less uniform and localized old) galvanized steel reinforcements, the mean of the mea- loss of zinc is observed. In general, corrosion rates from LPR surements in this time frame is only about twice as high as measurements are consistent with observations of maximum metal loss considering a factor between 2 and 3 relates the aver- measurements obtained after 2 years of service. Higher cor- age to the maximum metal loss. This is consistent with the fac- rosion rates measured after 16 years of service may be due to tor of 2 commonly used to relate loss of tensile strength to zinc loss and exposure of base steel; however, the measured uniform corrosion losses, as discussed by Elias (1990). corrosion rates are much lower than those measured for plain black steel. Corrosion rates for plain steel attenuate with respect to Trends time, but not as rapidly as those for galvanized elements. This Data were analyzed to identify trends from corrosion rate is consistent with corrosion rate models that are based on measurements with respect to spatial and temporal variations, Equation (1). The Darbin model, Equation (2), applies an climate, environment (marine vs. non-marine), and fill char- exponent of 0.65 to the time factor to describe metal loss of acteristics described in terms of electrochemical parameters galvanized reinforcements and Elias (1990) applies an expo- (min, pH, Cl-, SO4) and organics content. Details of results nent of 0.8 in Equation (3) to describe metal loss of plain steel from data analysis and identification of trends are described elements. A higher exponent reflects a lower attenuation of in Appendix D and in the interim report that was submitted corrosion rate with respect to time. These temporal variations for the project in April 2007. were considered in the reliability analysis and calibration of resistance factor. Corrosion rates do not necessarily attenuate when fill Spatial Variations materials are of marginal quality (i.e., do not meet AASHTO Consideration is given to elevation (top vs. bottom) and criteria), indicating that a less favorable environment (e.g., distance from the wall face (front vs. back). One would expect high in chlorides) interferes with the formation and suste- to observe increased corrosion near the top of the wall and nance of a passive film layer.

OCR for page 22
23 Climate cant impact on the performance of galvanized reinforcements, however, there was a significant effect observed for plain steel Four regions within the United States were considered reinforcements. These data demonstrate that plain steel rein- including the northeastern, southeastern, high plains and forcements should not be used in marine environments. Effects western states. These regions are distinguished by differences on corrosion rate from use of deicing salts were not apparent in climate, availability of suitable fill materials, use of deicing in the data. salts, and prevalence of reinforcement type. For galvanized reinforcements no significant differences were observed. Mean corrosion rates ranged between approximately 1 m/yr and Effect of Backfill Character 2 m/yr, with slightly higher means observed for the north- The electrochemical properties of reinforced fill have a eastern and western regions. Because there does not appear to profound effect on corrosion rates, and resistivity appears to be a significant effect of climate on measured corrosion rates, have the strongest influence, although a few data from sites measurements from different regions are combined to evalu- with low pH (pH<4) also exhibit very high corrosion rates. ate the effects of backfill character, time, and reinforcement Figure 10 depicts observed corrosion rates from galvanized type on corrosion rates and observations of metal loss for gal- reinforcements versus measurements of resistivity from sam- vanized reinforcements. Thus, data from all the regions were ples of fill that are most often taken from stockpiles prior to used to generate statistics for galvanized reinforcements used construction. Figure 10 incorporates 489 data points from in the reliability analysis and calibration of resistance factor. 53 sites distributed amongst the states of California, Florida, More significant variations were observed relative to cor- Kentucky, North Carolina, Nevada, and New York. Reinforce- rosion rates for plain steel reinforcements. Mean corrosion ment ages range from 1 to 30 years with an average of 13. rates for plain steel ranged between approximately 3 m/yr Therefore, data points in Figure 10 generally depict corrosion and 20 m/yr, with much higher corrosion rates observed for rates for zinc, particularly for > 3,000 -cm. the western region. However, climate may not be the only fac- Figure 10 depicts scatter that is significantly higher consider- tor, as the western states tend to use fill materials with less ing lower levels of fill resistivity. This may be due to the variabil- favorable electrochemical parameters (higher salt contents) ity of fill conditions at sites that are characterized as having compared to other regions including the Northeast and South- lower quality fill, uncertainty regarding the correlation between east. These different fill conditions were considered for the sources of samples and fill placed during construction, and reliability analysis and calibration of resistance factors. Thus, the possibility that zinc may be consumed in less than 10 years the statistics for these different climates were considered sep- when < 3,000 -cm. On average, observations from sites arately for plain steel reinforcements. with fill resistivities less than 3,000 -cm are approximately an order of magnitude higher than observations from sites with fill resistivity greater than 3,000 -cm. Observations from Environmental Conditions (Marine vs. Non-marine) sites with fill resistivities between 3,000 and 10,000 -cm Data from coastal/marine environments, that come from have average corrosion rates slightly higher than those locations near the coast, but are not submerged or in direct associated with resistivity greater than 10,000 -cm. Based contact with saltwater, were separated from non-marine on these data a power law was regressed to achieve the "best environments. Marine environments did not have a signifi- fit" with the data rendering the following equation, which 50 40 CR (m/yr) 30 20 CR = 1400-0.75 R2 = 0.4644 10 0 100 1000 10000 100000 (-cm) Figure 10. Observed corrosion rates versus fill resistivity for galvanized reinforcements (CR corrosion rate).