No abstract

No abstract

No abstract

No abstract

SUMMARYIn contrast to the traditional approach that computes the reliability index in the uncorrelated standard normal space (u-space), the reliability analysis that is simply realized in the original space (x-space, non-Gaussian type) would be more efficient for practical use, for example, with the Low and Tang's constrained optimization approach. On the other hand, a variant of Hasofer, Lind, Rackwits and Fiessler algorithm for firstorder reliability method is derived in this paper. Also, the new algorithm is simply formulated in x-space and requires neither transformation of the random variables nor optimization tools. The algorithm is particularly useful for reliability analysis involving correlated non-Gaussian random variables subjected to implicit limit state function. The algorithm is first verified using a simple example with closed-form solution. With the aid of numerical differentiation analysis in x-space, it is then illustrated for a strut with complex support and for an earth slope with multiple failure modes, both cases involving implicit limit state surfaces.

Cast iron was the dominant material for buried pipes for water networks prior to the 1970s in Australia and overseas. At present, many water utilities still have a significant amount of ageing cast iron pipes. Cast iron is a brittle material and when large diameter cast iron pipes (diameters above 300mm) further deteriorate, the consequences of failure can be substantial. Focusing on the likelihood of failure to assist risk assessment, this paper examines the performance of large-diameter cast iron pipes using probabilistic analysis, incorporating uncertainties of governing variables. Finite element analysis is first conducted to study the physical mechanism of buried pipes subjected to complex environmental conditions. The deterioration of cast iron pipes due to corrosion is considered on the basis of recent research. The uncertainties of governing variables, such as the physical properties of soil, cast iron, water pressure and corrosion patterns, in pipe failure risk assessment are considered. Using probabilistic physical modelling, the lifetime probability of failure is derived and a time-dependent sensitivity analysis is presented. The results of this probabilistic physical modelling are compared with cohorts of failure data from two Australian water utilities to examine the underlying trends from both physical modelling and statistical analysis.

No abstract

No abstract