Publications

Improved Importance Sampling Methods for Structural System Reliability Calculation

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.

Sample-specific linearization in reliability analysis of off-shore structures

The reliability analysis of off-shore structures under dynamic non-Gaussian wave, wind and water current loading is considered using an outcrossing approach and directional simulation in the space of the load processes. To circumvent the non-Gaussianity of the load processes for which results for mean outcrossing rate are not generally available, the “sample-specific linearization method” is proposed. This method is based on well-known results for Gaussian processes and uses the functional relationships between the non-Gaussian wave, wind and water current loads and the corresponding velocities. The proposed method is applied to a simple model off-shore structure. The structure is analyzed also to obtain probability of failure by means of Monte Carlo simulation and using time domain simulation of the load processes. This was found to be extremely expensive of computer time. The results were found to compare very favourably with those obtained by the proposed method, both in terms of accuracy and computation required.

Bi-modal trending for corrosion loss of steels buried in soils

Corrosion loss data from the 1957 NBS study for steels buried in a large variety of soils and exposed over 12–17 years are re-interpreted, supported with estimates for scatter in the data. This shows that losses predominantly are consistent with the bi-modal trending pattern also previously observed for steel exposed in a variety of other environments. For short-term and low time of wetness exposures the trends are consistent with mode 1 of the bi-modal trend. These reinterpretations should permit development of better understanding of the factors important for short- and-long term corrosion trends and for improved modelling and prediction.

An analysis of safety control effectiveness

The cost of injuries and “accidents” to an organisation is very important in establishing how much it should spend on safety control. Despite the usefulness of information about the cost of a company's accidents, it is not customary accounting practice to make these data available. Of the two kinds of costs incurred by a company through occupational injuries and accidents, direct costs and indirect costs; the direct costs are much easier to estimate. However, the uninsured costs are usually more critical and should be estimated by each company. The authors investigate a general model to estimate the above costs and hence to establish efficient safety control. One construction company has been a pilot for this study. By analysing actual company data for three years, it is found that the efficient safety control cost should be 1.2–1.3% of total contract costs.

Corrosion and odour management in sewers: the state of the art and key challenges

Reliability Analysis of Maintained Ships Under Correlated Fatigue and Corrosion

No abstract is provided for this article.

Contributor contact details

Unknown

Directional importance sampling for ill-proportioned spaces

Directional importance sampling is considered in the original space of loads when the loads are highly correlated and/or highly out of proportion. Under these conditions, the joint probability density function contours are elongated and the application of unbiased directional sampling may result in poor and unstable results. It is shown that a major improvement can be achieved by applying importance sampling to the directional sampling technique. In this way better and quite stable results can be obtained. Also, it is shown that uncertainties in structural strength may affect directional sampling in load space. Some illustrative examples are given.

Applications of statistics and probability : civil engineering reliability and risk analysis : proceedings of the ICASP 8 Conference, Sydney, New South Wales, Australia, 12-15 December 1999

No abstract is provided for this article.

Using models to interpret data for monitoring and life prediction of deteriorating infrastructure systems

For environmental and for economic reasons, there is increased emphasis on extending the life of existing infrastructure and to design new infrastructure for longer, safe and effective service lives. Increasing use is being made of monitoring of performance and estimation of long-term reliability and safety, allowing also for the likelihood of long-term deterioration. To obtain optimal decision outcomes, reliance should be placed not only on data but also on accumulated scientific and engineering knowledge. In engineering, this is embodied in mathematical models. Ideally, these are of good quality, calibrated to ‘real world’ data and have prediction capabilities. Recently, developed models of this type are described for the corrosion of steel in marine environments and simplified to models suitable for engineering applications. An example is given of the prediction of the expected corrosion loss and of the likely future rate of corrosion for a mild steel structural element exposed to temperate seawater.Keywords:: corrosionmodelspredictionprobabilityremaining lifesteel AcknowledgementsThe continued financial support of the Australian Research Council through two successive Australian Professorial Fellowships and various Discovery Grants is acknowledged with gratitude.

A load space formulation for probabilistic finite element analysis of structural reliability

A load space formulation for calculating the failure probability of complex structures for which the limit state functions are implicit is described in this paper. This formulation is used in conjunction with probabilistic finite element (PEE) analysis and employs a directional simulation to calculate the structural reliability. Apart from the advantage that a lower order space is used, the main advantage of the load space formulation proposed in this paper is that the number of inversions of the structural stiffness matrix and/or its gradients with respect to the material property random variables is reduced dramatically when compared with the usual Monte Carlo simulation (MCS) method. When used in a finite element reliability analysis, this procedure can save significant amounts of CPU time. Numerical examples are presented to show the efficiency and accuracy of the proposed approach.

Reliability based evaluation of commonly applied corrosion mitigation techniques

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.

Validity and Quality of Deterioration Models for Structural Reliability Assessment

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.

Long-term corrosion of steels exposed to marine environments

This paper presents an overview of the principal features of the recently developed model for the short and the long-term marine corrosion of steels. In marine environments such as immersion, tidal and coastal atmospheric, chlorides conventionally are considered to play a major role in causing corrosion loss. The actual corrosion process is considerably more complex and besides oxidation by dissolved or atmospheric oxygen there is an important influence from the metabolic products of sulphate-reducing bacteria. The model also deals with temperature, oxygen availability, pollution and various other influences. Although the fundamental corrosion processes are all electrochemical in nature, the model does not deal specifically with these. Instead the model is built around the governing corrosion-rate controlling processes. For engineering purposes the rate of loss of material is the critical issue. The main emphasis is on the behaviour of structural and other low alloy steels. The paper closes with some observations about the applicability of the model to stainless and weathering steels and its recent extension to reinforcement corrosion in concrete structures. RÉSUMÉ Cet article présente une revue d'ensemble des principales caractéristiques des modèles récemment développés pour la corrosion marine des aciers à court et long termes. Dans des environnements marins tels que l'immersion, le marnage et l'atmosphère côtière, on considère usuellement que les chlorures jouent un rôle majeur pour la perte de matériau. On montre que les processus réels de corrosion sont considérablement plus complexes et qu'audelà de l'oxydation par l'oxygène dissous ou atmosphérique, il y a une grande influence des produits métaboliques des bactéries sulphoréductrices. Le modèle tient aussi compte de la température, de la disponibilité de l'oxygène, de la pollution et d'autres influences diverses. Quoique les processus de base de la corrosion soient tous électrochimiques par nature, le modèle est plutôt bâti autour des processus qui contrôlent le taux de corrosion. Pour les applications en ingénierie, le taux de perte de matière est la question clé. L'article se termine avec quelques observations relatives à l'applicabilité du modèle pour les aciers inoxydables et il trace quelques pistes de recherche pour la corrosion des aciers du béton armé. KEYWORDS: corrosionsteelmarinemodelsmathematical modelsMOTS-CLÉS: aciercorrosionenvironnement marinmodèlesmodèles mathématiques

Effect of response surface parameter variation on structural reliability estimates

In the reliability estimation of complex structures, response surface methodology has been suggested as a way to estimate the actual but implicit limit state function. Typically the response surface is constructed from a polynomial function and fitted to the implicit function at a number of points. The location of these points has been noted as being an issue but the effect of varying their location has had little attention in the literature. In the present paper some simple examples are used to indicate possible effects. It is noted that the probability can be both under- and over-estimated, depending on the choice of points, but that no clear guidance for point selection can be given in any one case. A particularly disturbing feature is that for some types of problems there can be instability in the probability estimate as the location of the points is changed. This is demonstrated through a previously well-discussed example.

Rejoinder

Click to increase image sizeClick to decrease image size Additional informationNotes on contributorsR. E. MelchersEmail: rob.melchers@newcastle.edu.au

A reinterpretation of the Romanoff NBS data for corrosion of steels in soils

Data published in the 1957 Romanoff National Bureau of Standards report for the corrosion of steels buried in soils for up to 17 years are re-interpreted using the bi-modal model for corrosion in wet environments. The relevant soil properties are those of the backfill, not those of the undisturbed soil at the depth of the steel samples. Using estimated backfill properties shows that stiff clays, calcareous loams and gravelly loams corrosion transitioned from Mode 1 to Mode 2 after 4–8 years, following severe corrosion and deep pitting. For most other backfill soils, the transition occurred later and corrosion was less severe. These differences are attributed to the relative influence of differential aeration and localised corrosion caused by air-voids at the soil–metal interface. The declining rate of corrosion in the later part of Mode 2 is attributed to backfill consolidation decreasing the diffusion of oxygen and possibly also of moisture.

Long-term corrosion of cast iron cement lined pipes

SUMMARY: The corrosion of ferrous water mains is a signific ant problem for the Australian Water Industry. A significant proportion of Australia’s a geing water infrastructure is composed of cast iron and steel cement lined pipes, which are prone to co rrosion on the external surfaces that are in contac t with soil. Internal corrosion is not a significant issue for cement-lined pipes. For the water industr y to manage these ageing assets effectively, quantitativ e predictions of the damage likely to result from long-term corrosion are highly desirable. Many of t he fundamental corrosion mechanisms are known and there is considerable practical experience on t he corrosion of buried iron. However, the predictio n of the long-term corrosion losses, of pit depths an d pitting extent are not well developed, including understanding and prediction of the quantitative in fluences of external soil conditions. In this paper the basic mechanisms involved in the corrosion of ferro us metals in contact with soil are reviewed and the likely effects of various influencing factors such as soil moisture content, soil type and soil water chemistry on long-term corrosion are described. The review has found that long-term corrosion is controlled by diffusion processes and is a function of soil moisture content, soil density, and soil w ater quality. The review is followed by an outline of an approach to modelling long-term corrosion of cast iron pipes. It involves developing a realistic mode l for the prediction of pipe corrosion in soil and its calibration to field and historical data. Both the modelling approach and field data collection requirements are outlined.