Open Access
MATEC Web Conf.
Volume 271, 2019
2019 Tran-SET Annual Conference
Article Number 01006
Number of page(s) 5
Section Structural
Published online 09 April 2019
  1. Govindasamy, A.V., Briaud, J.L, Chen, H.C., Delphia, J., Elsbury, K., Gardoni, P., Herrman, G., Kim, D., Mathewson, C.C., McClelland, M., and Olivera, F. (2008). Simplified Method for Estimating Scour at Bridges. InGeoCongress 2008: Geosustainability and Geohazard Mitigation 2008, 385–393. [Google Scholar]
  2. Arneson, L.A., Zevenbergen, L.W., Lagasse, P.F., and Clopper, P.E. (2012). evaluating scour at bridges. Washington, DC: Federal Highway Administration. [Google Scholar]
  3. Briaud, J.L., Brandimarte, L., Wang, J., and D’Odorico, P. (2007). probability of scour depth exceedance owing to hydrologic uncertainty. Georisk. 1(2), 77–88. [Google Scholar]
  4. Boldu, L.C., Gardoni, P., and Briaud, J.L. (2008). probability of exceedance estimates for scour depth around bridge piers. Journal of geotechnical and geoenvironmental engineering. 134(2), 175–84. [CrossRef] [Google Scholar]
  5. Wang, Z., Padgett, J.E., and Dueñas-Osorio, L. (2014). risk-consistent calibration of load factors for the design of reinforced concrete bridges under the combined effects of earthquake and scour hazards. Engineering Structures. 15(79), 86–95. [CrossRef] [Google Scholar]
  6. Zhu, B., Frangopol, D.M. (2016). time-dependent risk assessment of bridges based on cumulative-time failure probability. Journal of Bridge Engineering. 21(12):06016009. [Google Scholar]
  7. Kallias, A.N., and Imam, B. (2016). probabilistic assessment of local scour in bridge piers under changing environmental conditions. Structure and Infrastructure Engineering. 12(9), 1228–41. [Google Scholar]
  8. Stewart, M.G., Wang, X., and Nguyen, M.N. (2011). climate change impact and risks of concrete infrastructure deterioration. Engineering Structures. 33(4), 1326–1337. [Google Scholar]
  9. M.G. Stewart, M.G., Wang, X., and Nguyen, M.N. (2012). climate change adaptation for corrosion control of concrete infrastructure. Structural Safety. 35:29–39. [CrossRef] [Google Scholar]
  10. Chaves, I.A., Melchers, R.E., Peng, L., and Stewart, M.G. (2016). probabilistic remaining life estimation for deteriorating steel marine infrastructure under global warming and nutrient pollution. Ocean Engineering. 126,129–137. [CrossRef] [Google Scholar]
  11. Peng, L., Stewart, M.G., and Melchers, R.E. (2017). corrosion and capacity prediction of marine steel infrastructure under a changing environment. Structure and Infrastructure Engineering. 13(8), 988–1001. [CrossRef] [Google Scholar]
  12. Taylor, K. E., Stouffer, R. J., & Meehl, G. A. (2012). An overview of CMIP5 and the experiment design. Bulletin of the American Meteorological Society, 93(4), 485–498. [Google Scholar]
  13. Maloney, E.D., Camargo, S.J., Chang, E., Colle, B., Fu, R., Geil, K.L., Hu, Q., Jiang, X., Johnson, N., Karnauskas, K.B., and Kinter, J. (2014). North American climate in CMIP5 experiments: Part III: Assessment of twenty-first-century projections. Journal of Climate. 27(6), 2230–70. [CrossRef] [Google Scholar]
  14. Maurer, E.P., and Hidalgo, H.G. (2008). Utility of daily vs. monthly large-scale climate data: an intercomparison of two statistical downscaling methods, Hydraulic Earth System Sciences. [Google Scholar]
  15. Maurer, E.P., Hidalgo, H.G., Das, T., Dettinger, M.D., and Cayan, D.R. (2010). The utility of daily large-scale climate data in the assessment of climate change impacts on daily streamflow in California, Hydraulic Earth System Sciences. [Google Scholar]
  16. Brekke, L., Thrasher, B.L., Maurer, E.P., and Pruitt, T. (2013). Downscaled CMIP3 and CMIP5 climate and hydrology projections: Release of downscaled CMIP5 climate projections, comparison with preceding information, and summary of user needs. US Dept. of the Interior, Bureau of Reclamation, Technical Services Center, Denver. [Google Scholar]
  17. Liang, X., Lettenmaier, D.P., Wood, E.F., and Burges, S.J. (1994). A simple hydrologically based model of land surface water and energy fluxes for general circulation models. Journal of Geophysical Research: Atmospheres. 99(D7):14415–28. [CrossRef] [Google Scholar]
  18. Zagona, E.A., Fulp, T.J., Shane, R., Magee, T., and Goranflo, H.M. (2001). RiverWare: A generalized tool for complex reservoir system modeling. JAWRA Journal of the American Water Resources Association. 37(4), 913–929. [CrossRef] [Google Scholar]
  19. Croke, B.F., Andrews, F., Jakeman, A.J., Cuddy, S.M., Luddy, A. (2006). IHACRES Classic Plus: a redesign of the IHACRES rainfall-runoff model. Environmental Modelling & Software. 21(3), 426–7. [CrossRef] [Google Scholar]
  20. Richardson, E.V., Harrison, L.J., Richardson, J.R., and Davis, S.R. (1993). evaluating scour at bridges. Washington, DC: Federal Highway Administration. [Google Scholar]
  21. Melchers, R.E. (2003a). Modeling of marine immersion corrosion for mild and low-alloy steels— Part 1: Phenomenological model. Corrosion. 59(4), 319–34. [CrossRef] [Google Scholar]
  22. Melchers, R.E. (2003b). modeling of Marine Immersion Corrosion for Mild and Low-Alloy Steels—Part 2: Uncertainty Estimation. Corrosion. 59(4), 335–44. [CrossRef] [Google Scholar]
  23. USGS. United State Geological Survey, National Water Information Service, 2018. [Google Scholar]
  24. Melchers, R.E. (2014). Long-term immersion corrosion of steels in seawaters with elevated nutrient concentration. Corrosion Science. 81:110–6. [CrossRef] [Google Scholar]
  25. Prasad, Y.V., and Chari, T.R. (1999). lateral capacity of model rigid piles in cohesion-less soils. Soils and Foundations. 39(2), 21–29. Parsad [Google Scholar]
  26. Decò, A., and Frangopol, D.M. (2011). risk assessment of highway bridges under multiple hazards. Journal of Risk Research. 14(9), 1057–1089. [CrossRef] [Google Scholar]
  27. Stein, S.M., Young, G.K., Trent, R.E., and Pearson, D.R. (1999). prioritizing scour vulnerable bridges using risk. Journal of Infrastructure Systems. 5(3), 95–101. [CrossRef] [Google Scholar]
  28. European Committee for Standardization. Eurocode 3: design of steel structures – part 5: piling. 2007. [Google Scholar]
  29. MathWorks, M. A. T. L. A. B. SIMULINK for technical computing. Available on http://www. rnathworks. com. 2016. [Google Scholar]

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