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A one-dimensional simulation procedure is developed for use in estimating structural reliability in multi-dimensional load and resistance space with the loads represented as stochastic process. The technique employed is based on the idea of using ‘strips’ of points parallel to each other and sampled on the limit state hyperplanes. The ‘local’ outcrossing rate and the zero time failure probability P f (0) associated with the narrow strips are derived using the conditional reliability index. When the domain boundary consists of a set of limit states, second order bounds are used to obtain a lower bound approximation of the outcrossing rate and P f (0) associated with the union of a set of λ strips. It is shown by examples that for high reliability problems, λ may be much less than the number of limit states without significant loss of accuracy and with considerable saving in computation time. It was also found that the rate of convergence of the simulations is quite fast even without using importance sampling.
The importance of human error in structural engineering reliability assessments is reviewed and some recent research results on human error in simple design tasks given. Design processes such as table-look-up, calculation and ranking of numbers are considered. A tentative procedure to allow for human error in reliability theory is also outlined.
Longer-term pitting corrosion of mild steel under field exposure conditions has been shown to occur in the entirely anaerobic environment created by the build-up of corrosion products. There is evidence of lateral pit growth and pit coalescence, both for sub-extremal and extremal depth pits. Statistically this implies the generation of a new population of pits, not directly dependent on earlier pit depth distributions. Moreover, new pits have been shown to initiate in the subsequent anaerobic environment without obvious reference to the pattern of earlier pitting. These observations have implications for the application of an extreme-value statistical theory for modeling maximum pit depth in the anaerobic range. Data from multiple replicate coupons exposed to marine immersion corrosion are reviewed and reinterpreted. Extreme-value distributions are examined for consistency with the data and a new statistical model for extreme depth pitting in the anaerobic range is proposed—the Frechet distribution. It predicts a greater probability of occurrence for a given depth of pitting than does the conventional Gumbel distribution for the same data set. This has important practical implications where long-term pitting is governed by anaerobic conditions.
For coastal infrastructure the long-term durability of new steel structures and the remaining life of existing steel structures is of central interest to their proper maintenance and asset management. This is particularly the case where protective measures such as paint coatings, galvanizing, or cathodic protection will become or are already ineffective or are nonexistent. Guidelines currently available for new design and for assessment are largely empirical and have a high degree of uncertainty. To address this recent research has produced better quality models for the progression of corrosion with time. These employ fundamental characteristics of steel corrosion as obtained from actual field observations and from laboratory-based electrochemical and other observations. The models are reviewed herein and an illustrative application to a typical infrastructure component is presented. It is shown that seawater temperature has an important influence on the rate of early corrosion and also has longer-term effects not predicted by short-term observations. Also, the influence on corrosion of small changes in metal composition and in water velocity, salinity, and pollution are described.
A transcript of a discussion on earthquake hazard analysis, and what is needed to thoroughly carry out a seismic zoning, in the aftermath of the Newcastle earthquake of 1989.
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No abstract is provided for this article.
Based on the general form of Paris’ law a new method is proposed for estimating the rate of cracking of metals under Hydrogen-Assisted Fatigue. It is based on relating the fatigue crack growth rate of hydrogen embrittled metal to the fatigue crack growth rate of the metal without hydrogen embrittlement. One-dimensional hydrogen diffusion is assumed. Simulations using the proposed method on steel types X52, X70–80 and X80 are in agreement with published experimental tests results. The new method obviates numerical modelling of crack propagation and much reduces the computational costs.
Cast iron piers of a disused 90 year old multispan railway bridge located close to the Pacific Ocean were extensively sampled for remaining wall thickness to determine corrosion loss and pit depth. From this, a corrosion loss model for the full 90 years was developed. In addition, the statistics for uncertainty in corrosion loss were obtained. Corrosion varied with elevation relative to mean water level and was negligible in the atmospheric zone, about 2–3 mm in the immersion zone and 5–6 mm in the splash and lower tidal zones. This variation is consistent with accelerated low water corrosion. It indicates that water pollution occurred sometime during the life of the bridge. Maximum pit depths were determined and analysed using extreme value statistics. The corrosion model for such long term exposure and the related statistical results are unique and important for assessment of remaining life of the many other cast iron structures still in existence in many parts of the world.
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This paper deals with the analysis of uncertain creep and shrinkage effects, and in particular the computation of the probability of serviceability failure for a reinforced concrete structure subjected to stochastic loadings. A sustained load of uncertain magnitude, a stationary Gaussian loading process, and a Poisson loading process are considered. To model the creep and shrinkage phenomena. Bažant‐Panula model is employed. The resulting time‐variant reliability problem is an upcrossing problem in stochastic process theory that is, in general, difficult or computationally demanding to solve. The problem can be simplified to allow prediction at end of a given time period, using the so‐called time‐independent reliability theory (e.g., the first‐order second‐moment method). However, this can be achieved only once the statistics of the load effects have been obtained by Monte Carlo simulation, but is considerably less demanding than a complex Monte Carlo solution. A numerical example is given to illustrate the method, and the results are compared with simulation results.
By identifying possible degradation threats and assessing remaining asset serviceability corrosion risk assessment is normally used to assign priorities for corrosion control and monitoring such as timely application of coatings, cathodic protection or ultrasonic inspection programs. Since these methods rely on probabilistic modelling of limited representable data, it follows that prediction of information reliability is of interest in modern asset management. The present paper interprets literature statistical data for (i) pitting corrosion depth as a function of time, (ii) dry film thickness, (iii) ultrasonic wall loss measurements and (iv) cathodic protection current fluctuations. It is shown that representation and predictions can be highly influenced by the choice of distribution used to fit the data. This has direct implications for future likelihood predictions. The reasons are discussed.
There are increasing pressures to extend the service lives of existing infrastructure and to provide optimal management of their maintenance. Structural reliability theory now provides a very comprehensive approach to assessing risks for complex infrastructure systems. It requires probabilistic models for the predic- tion of the long-term changes to structural capacity and resistance as may result, for example, from changes in the management or operation of the asset or from material deterioration in harsh operational environments. While empirical mod- els may be sufficient in some cases, it is preferable for the models to be based on fundamental science and to deal with remaining uncertainty in a probabilistic man- ner. Herein models for the prediction of the corrosion of structural steel in marine environments are considered. The issues involved are reviewed and some of the pitfalls in model development are considered. These include (i) models based on inadequate underlying theories, (ii) use of inhomogeneous populations, (iii) use of inappropriate influencing factors, (iv) use of laboratory test results rather than field results, (v) insufficient attention to limitations and conditions, (vi) insufficient understanding of the changes in conditions with time, and (vii) invoking model simplifications too early. Drawing on material that has already been published in the literature, examples are given of each to show how these matters may provide misleading information to potential end-users.
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This paper is concerned with the mechanisms governing reinforcement corrosion in concretes in marine environments and how they influence the manner of local failure of the concrete. Despite the high pH of the concrete, air voids from inadequate concrete compaction can, under chloride conditions, produce localized pitting corrosion of adjacent steel bars. This may continue, under the hydrogen evolution cathodic reaction with the build-up of rusts causing localized concrete failure, followed by exposure of the steel to the environment, removal of the elevated concrete pH, and a subsequent much higher rate of corrosion. A completely separate deterioration process is the gradual dissolution and loss of concrete alkalis with time. This can lower the concrete pH sufficiently to permit general corrosion of steel to be thermodynamically feasible, it increases concrete permeability and it facilitates access to the environment to permit corrosion by oxygen reduction. The two processes produce different types of concrete failure. Examples drawn from actual reinforced concrete structures are given and the mechanisms explained, including the often-observed build-up of FeOOH-type rusts on the outside of magnetite rust layers well inside concretes. The implications that follow and research needs are discussed.
Improvements can be made to importance sampling by recognising some of the essential features of the time-independent structural reliability problem. Thus non-interesting regions in the integration domain can be deleted from consideration using a priori information and updating techniques. These can also be used to obtain the point(s) of maximum likelihood, a central parameter for importance sampling in cartesian co-ordinates.
