Final report : a software diagnostic tool for evaluating distress mechanisms in bridges exposed to aggressive environments

Durability issues of reinforced concrete construction cost millions of dollars in repair or demolition. Identification of the causes of degradation and a prediction of service life based on experience, judgement and local knowledge has limitations in addressing all the associated issues. The objective of this CRC CI research project is to develop a tool that will assist in the interpretation of the symptoms of degradation of concrete structures, estimate residual capacity and recommend cost effective solutions. This report is a documentation of the research undertaken in connection with this project. The primary focus of this research is centred on the case studies provided by Queensland Department of Main Roads (QDMR) and Brisbane City Council (BCC). These organisations are endowed with the responsibility of managing a huge volume of bridge infrastructure in the state of Queensland, Australia. The main issue to be addressed in managing these structures is the deterioration of bridge stock leading to a reduction in service life. Other issues such as political backlash, public inconvenience, approach land acquisitions are crucial but are not within the scope of this project. It is to be noted that deterioration is accentuated by aggressive environments such as salt water, acidic or sodic soils. Carse, 2005, has noted that the road authorities need to invest their first dollars in understanding their local concretes and optimising the durability performance of structures and then look at potential remedial strategies.

Towards a rule-based matrix for evaluating distress mechanisms in bridges

The effective management of bridge stock involves making decisions as to when to repair, remedy, or do nothing, taking into account the financial and service life implications. Such decisions require a reliable diagnosis as to the cause of distress and an understanding of the likely future degradation. Such diagnoses are based on a combination of visual inspections, laboratory tests on samples and expert opinions. In addition, the choice of appropriate laboratory tests requires an understanding of the degradation mechanisms involved. Under these circumstances, the use of expert systems or evaluation tools developed from “realtime” case studies provides a promising solution in the absence of expert knowledge. This paper addresses the issues in bridge infrastructure management in Queensland, Australia. Bridges affected by alkali silica reaction and chloride induced corrosion have been investigated and the results presented using a mind mapping tool. The analysis highights that several levels of rules are required to assess the mechanism causing distress. The systematic development of a rule based approach is presented. An example of this application to a case study bridge has been used to demonstrate that preliminary results are satisfactory.

A framework for predicting the residual load carrying capacity of concrete structures exposed to aggressive environments

Reinforced concrete structures are susceptible to a variety of deterioration mechanisms due to creep and shrinkage, alkali-silica reaction (ASR), carbonation, and corrosion of the reinforcement. The deterioration problems can affect the integrity and load carrying capacity of the structure. Substantial research has been dedicated to these various mechanisms aiming to identify the causes, reactions, accelerants, retardants and consequences. This has improved our understanding of the long-term behaviour of reinforced concrete structures. However, the strengthening of reinforced concrete structures for durability has to date been mainly undertaken after expert assessment of field data followed by the development of a scheme to both terminate continuing degradation, by separating the structure from the environment, and strengthening the structure. The process does not include any significant consideration of the residual load-bearing capacity of the structure and the highly variable nature of estimates of such remaining capacity. Development of performance curves for deteriorating bridge structures has not been attempted due to the difficulty in developing a model when the input parameters have an extremely large variability. This paper presents a framework developed for an asset management system which assesses residual capacity and identifies the most appropriate rehabilitation method for a given reinforced concrete structure exposed to aggressive environments. In developing the framework, several industry consultation sessions have been conducted to identify input data required, research methodology and output knowledge base. Capturing expert opinion in a useable knowledge base requires development of a rule based formulation, which can subsequently be used to model the reliability of the performance curve of a reinforced concrete structure exposed to a given environment.

Strategies for minimising the whole of life cycle cost of reinforced concrete bridge exposed to aggressive environments

n design of bridge structures, it is common to adopt a 100 year design life. However, analysis of a number of case study bridges in Australia has indicated that the actual design life can be significantly reduced due to premature deterioration resulting from exposure to aggressive environments. A closer analysis of the cost of rehabilitation of these structures has raised some interesting questions. What would be the real service life of a bridge exposed to certain aggressive environments? What is the strategy of conducting bridge rehabilitation? And what are the life cycle costs associated with rehabilitation? A research project funded by the CRC for Construction Innovation in Australia is aimed at addressing these issues. This paper presents a concept map for assisting decision makers to appropriately choose the best treatment for bridge rehabilitation affected by premature deterioration through exposure to aggressive environments in Australia. The decision analysis is referred to a whole of life cycle cost analysis by considering appropriate elements of bridge rehabilitation costs. In addition, the results of bridges inspections in Queensland are presented

Evaluation of distress mechanisms in bridges exposed to aggressive environments.

There are about 2500 bridges in Queensland, Australia. Majority of these structures require significant repairs around the halfway mark of their design life with probably 1% or less reaching a 100 year design life. (Carse, 2005). This is due to the fact that bridges constructed in aggressive environments such as the coastal regions experience accelerated deterioration. As a result, maintaining the service delivery of these assets has become one of the important issues for the Queensland Department of Main Roads (QDMR).

Challenges in residual service life assessment for refurbishment

A need for an efficient life care management of building portfolio is becoming increasingly due to increase in aging building infrastructure globally. Appropriate structural engineering practices along with facility management can assist in optimising the remaining life cycle costs for existing public building portfolio. A more precise decision to either demolish, refurbish, do nothing or rebuilt option for any typical building under investigation is needed. In order to achieve this, the status of health of the building needs to be assessed considering several aspects including economic and supply-demand considerations. An investment decision for a refurbishment project competing with other capital works and/or refurbishment projects can be supported by emerging methodology residual service life assessment. This paper discusses challenges in refurbishment projects of public buildings and with a view towards development of residual service life assessment methodology

Optimisation of maintenance expenditure for buildings : refurbish or demolish

With an increase in growing number of aging public building infrastructure globally, there is an opportunity for an efficient life care management rather then mere demolition and rebuild. By carefully implementing appropriate structural engineering practices with facility management, the whole of life cycle costs for public building assets can be optimised and public money can be saved and better utilised elsewhere. A need of decision support tool/methodology which can assist asset manager make better decision among demolish, refurbish, do nothing or rebuilt option for any typical building under consideration is growing in order to optimise maintenance funds. The paper is part of research project focusing on development of such methodology known as residual service life prediction. The paper is mainly focusing on following three major aspects of public building infrastructure; first, issues and challenges in optimisation of maintenance funds, second, residual service life prediction methodology and issues and challenges in the development of such methodology. The paper concludes with the authors’ observations and further research potentials

The user query based learning system for lifetime prediction of metallic components

Real-World Data Mining Applications generally do not end up with the creation of the models. The use of the model is the final purpose especially in prediction tasks. The problem arises when the model is built based on much more information than that the user can provide in using the model. As a result, the performance of model reduces drastically due to many missing attributes values. This paper develops a new learning system framework, called as User Query Based Learning System (UQBLS), for building data mining models best suitable for users use. We demonstrate its deployment in a real-world application of the lifetime prediction of metallic components in buildings

A user driven data mining process model and learning system

This paper deals with the problem of using the data mining models in a real-world situation where the user can not provide all the inputs with which the predictive model is built. A learning system framework, Query Based Learning System (QBLS), is developed for improving the performance of the predictive models in practice where not all inputs are available for querying to the system. The automatic feature selection algorithm called Query Based Feature Selection (QBFS) is developed for selecting features to obtain a balance between the relative minimum subset of features and the relative maximum classification accuracy. Performance of the QBLS system and the QBFS algorithm is successfully demonstrated with a real-world application

Defining reference service life : an open innovation approach

The endeavour to obtain estimates of durability of components for use in lifecycle assessment or costing and infrastructure and maintenance planning systems is large. The factor method and the reference service life concept provide a very valuable structure, but do not resolve the central dilemma of the need to derive an extensive database of service life. Traditional methods of estimating service life, such as dose functions or degradation models, can play a role in developing this database, however the scale of the problem clearly indicates that individual dose functions cannot be derived for each component in each different local and geographic setting. Thus, a wider range of techniques is required in order to devise reference service life. This paper outlines the approaches being taken in the Cooperative Research Centre for Construction Innovation project to predict reference service life. Approaches include the development of fundamental degradation and microclimate models, the development of a situation-based reasoning ‘engine’ to vary the ‘estimator’ of service life, and the development of a database on expert performance (Delphi study). These methods should be viewed as complementary rather than as discrete alternatives. As discussed in the paper, the situation-based reasoning approach in fact has the possibility of encompassing all other methods.