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Concrete In Australia : March 2008
TECHNICAL observed. It was concluded in a report of condition review that the pier pilecaps were suffering from chloride induced corrosion while the primary reason for cracks on piles was ASR (from personal communication with Dr John Fenwick of the Queensland Department of Main Roads). The report provided most data for inputs of the risk assessment model. The remainder unspecifi ed likelihoods were assumed to be “medium”. Headstocks and columns were not assessed because the report does not mention any details for them. In this case study, the risk of stress corrosion is assumed to be “low” by reason of insuffi cient data about the properties of the steel. To avoid overlooking the high risks of individual failure modes, both individual risk ratings and total scaled risk ratings are required when comparing between projects or bridge components. As presented in Figure 7, the primary failure mode of piles is ASR with a “high” risk and other failure modes all have acceptable risks. For pilecaps; chloride induced corrosion is the major problem, followed by ASR, with questionable risk. The result of total scaled ratings indicates that pilecaps have a higher risk of failure than piles. Pilecaps Stress Corrosion Plastic Shrinkage Carbonation Chloride Induced Corrosion Alkali-Silicia Reaction Piles mechanisms and neglects many others. It requires highly detailed information to estimate the likelihood of various basic events of different components of bridges. The result of the risk analysis is very sensitive to the consequence ratings. The accuracy of the model could be substantially enhanced by using fi ve point scales in the assignment of likelihoods and consequences, as well as establishing more specific and authoritative guidelines for the assignment. Acknowledgement Dr John Fenwick, of the Queensland Department of Main Roads, is kindly acknowledged for provision of data for this work. References 1. AS/NZS 4360, 2004 Risk management, Standards Australia. 2. Creagh M S, Wijeyakulasuriya V and Williams D J 2006, Fault tree analysis and risk assessment for the performance of unbound granular paving materials, 22nd ARRB conference- research into practice, Canberra. 3. Ericson CA, 2005, Fault tree analysis, CA Ericson, Hazard analysis techniques for system safety, 183-222, Hoboken, Wiley. 4. Faber M H, 2006, Logical trees, M H Faber, Risk and safety in civil, surveying and environmental engineering, 133-140, http://www.ibk.ethz.ch 5. Guirguis S, 1980, Durability of concrete structures, Cement and Concrete Association of Australia. 6. 0 Failure Modes Alkali-Silicia Reaction Chloride Induced Corrosion Cabonation Plastic Shrinkage Stress Corrosion 1 2 Consequence Ratings Piles High High Medium Low High 2.67 0.79 0.02 0.73 1 Figure 7. Risk ratings of case study bridge piers. Sensitivity analysis Sensitivity analysis of likelihoods and consequences mainly focuses on their contribution to total risk rating. Consequence ratings for each failure mode are the most sensitive factors. Changing the consequence rating will result in a notable difference in total risk rating. In the likelihoods of various basic events, the ones in the material properties group are the most infl uential contributors. The use of poor material will produce a signifi cant risk of poor performance and durability. The risk will be more severe if the bridge element is exposed to an aggressive environment. Conclusions The paper has demonstrated a structured method of ranking the performance risks of distressed reinforced concrete bridges. Fault tree analysis has been used to model the likelihood of occurrence of major distress mechanisms. This model can be used to identify the important risks for particular bridge components and their relative severity and to rank the performance trends of bridges. At this stage, this model has many limitations as it examines only several major distress 54 Concrete in Australia Vol 34 No 1 Pilecaps 1.92 2.29 0.77 0.73 1 3 Risk Ratings Total Scaled Risk Ratings Piles Pilecaps Johnson PA, 1999, Fault tree analysis of bridge failure due to scour and channel instability, Journal of Infrastructure Systems 5(1): 35-41. 1.04 1.34 7. LeBeau K H and Wadia-Fascetti S J, 2000, A fault tree model of bridge deterioration. 8th ASCE specialty conference on probabilistic mechanics and structural reliability. 8. Mahar D J and Wilbur J W, 1990, Fault tree analysis application guide, Reliability Analysis Center (US), Rome, NY. 9. Personal communication, Dr. John Fenwick, Queensland Dept. of Main Roads. 10. Rendell F, Jauberthie, R and Grantham M, 2002, Deterioration of concrete, Deteriorated concrete: inspection and physicochemical analysis:29-54, London: Thomas Telford. 11. Ropke J C, 1982, Concrete repairs, Concrete problems: causes and cures, 99-100, New York, McGraw-Hill. 12. Sianipar P R M and Adams T M, 1997, Fault-tree model of bridge element deterioration due to interaction. Journal of Infrastructure Systems 3(3): 103 13. Venkatesan S, Setunge S, Molyneaux T and Fenwick J 2006. Evaluation of distress mechanisms in bridges exposed to aggressive environments, Second International Conference of the CRC for Construction Innovation, Australia. 14. Vick S G, 2002, Reliability, risk and probabilistic methods, Degrees of belief: subjective probability and engineering judgment: 132-139. Reston: ASCE Press. Vicroads, 1995, Vicroads bridge inspection manual, Kew, Vicroads. 15. Williams D J, Gowan M and Golding B 2001, Literature review and commentary, ACARP Project C8039 Final report, risk assessment of Bowen Basin spoil rehabilitation. University of Queensland.