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42 CHAPTER 4 Conclusions and Recommendations The main focus of this study is reliability of metal loss and considering the climate in the northeastern United States, modeling and service life estimates for earth reinforcements, measurements may vary by a factor of approximately 1.5 including reinforcements for MSE, soil nails, rock bolts, and throughout a given year. ground anchors. Reliability analysis is useful for the following: Data were partitioned considering different fill conditions, reinforcement type and time frames rendering COVs between 1. Describing reliability of metal loss models for use in design, approximately 40% and 60% within each category. In gen- 2. Describing effect of deviations in electrochemical proper- eral, metal loss models available from the existing literature, ties and site conditions on service life, including the AASHTO model, were found to be conserva- 3. Calibrating resistance factors for use in LRFD, and tive. Use of the AASHTO metal loss model is evaluated within 4. Providing tools for asset management that can be used to the framework of reliability-based design and calibration of estimate vulnerability and remaining service life of exist- resistance factors for LRFD. ing systems. Results from LRFD calibrations rendered resistance factors corresponding to a target reliability index of 2.3 and pf 0.01. During Phase II of this research, fieldwork was undertaken The following conclusions apply to the resistance factor cali- to broaden the database describing in situ performance of earth brations for LRFD of MSE walls: reinforcements compared to what was available at the conclu- sion of Phase I. Additional data were collected to enhance the Computed resistance factors vary depending on the method geographic distribution of sites included in the monitoring used to compute reinforcement load, that is, simplified or effort and to obtain more information representative of a range coherent gravity method. of fill conditions including high, good and marginal quality, Considering galvanized reinforcements in good backfill con- more sites with LPR measurements providing a better spatial ditions (i.e., meeting AASHTO criteria for electrochemical and temporal distribution of measurements at given sites, and parameters) the computed resistance factor is slightly more sites with older reinforcements (i.e., older than 25 years). less than what is recommended in the current AASHTO Data were also obtained to further verify the use of LPR mea- specifications. surements to estimate corrosion rate, thus providing a sound Considering galvanized reinforcements in high quality fill basis to use these measurements for statistical analysis of mea- renders resistance factors that are slightly higher than those surements and for reliability analysis of service-life estimates currently specified by AASHTO for design of MSE walls. and calibration of resistance factors for use in LRFD. Data were generated to consider plain steel (i.e., not galva- For MSE reinforcements (Type I), electrochemical proper- nized) reinforcements with fill materials that meet the ties of the fill were observed to have a significant impact on AASHTO requirements for electrochemical parameters, a performance, and the effect of time on corrosion rate is clearly conservative metal loss model, and maximum design life of indicated by these data. The spatial distribution of corrosion less than 50 years. rates appears to be random, although spatial trends are appar- Data were generated to consider marginal quality fill ent from data obtained with respect to several of the sites in (i.e., not quite meeting AASHTO criteria) with galvanized the database. No significant differences are observed between reinforcements, a very conservative metal loss model, and different climates for galvanized elements, however, marine maximum design life of less than 50 years. environments had a detrimental effect on corrosion rates for plain steel (i.e., not galvanized) reinforcements. Also, it was Type II reinforcements include rock bolts and ground found that seasonal variations affect measured corrosion rates, anchors, and their performance is related to the degree of cor-