Case definition and holistic model modifications required for building elements

This project is an extension of a previous CRC project (220-059-B) which developed a program for life prediction of gutters in Queensland schools. A number of sources of information on service life of metallic building components were formed into databases linked to a Case-Based Reasoning Engine which extracted relevant cases from each source.

Preliminary report on data mining techniques for life prediction

This project is an extension of a previous CRC project (220-059-B) which developed a program for life prediction of gutters in Queensland schools. A number of sources of information on service life of metallic building components were formed into databases linked to a Case-Based Reasoning Engine which extracted relevant cases from each source. In the initial software, no attempt was made to choose between the results offered or construct a case for retention in the casebase. In this phase of the project, alternative data mining techniques will be explored and evaluated. A process for selecting a unique service life prediction for each query will also be investigated. This report summarises the initial evaluation of several data mining techniques.

Report : analysis of maintenance database inputs

In the previous phase of this project, 2002-059-B Case-Based Reasoning in Construction and Infrastructure Projects, demonstration software was developed using a case-base reasoning engine to access a number of sources of information on lifetime of metallic building components. One source of information was data from the Queensland Department of Public Housing relating to maintenance operations over a number of years. Maintenance information is seen as being a particularly useful source of data about service life of building components as it relates to actual performance of materials in the working environment. If a building is constructed in 1984 and the maintenance records indicate that the guttering was replaced in 2006, then the service life of the gutters was 22 years in that environment. This phase of the project aims to look more deeply at the Department of Housing data, as an example of maintenance records, and formulate methods for using this data to inform the knowledge of service lifetimes.

Report : holistic model modifications for selected building elements

This project is an extension of a previous CRC project (220-059-B) which developed a program for life prediction of gutters in Queensland schools. A number of sources of information on service life of metallic building components were formed into databases linked to a Case-Based Reasoning Engine which extracted relevant cases from each source.

Report : effect of natural cleaning on salt deposition on Queensland bridges

Maintenance of bridge structures is a major issue for the Queensland Department of Main Roads. In the previous phase of this CRC project an initial approach was made towards the development of a program for lifetime prediction of metallic bridge components. This involved the analysis of five representative bridge structures with respect to salt deposition (a major contributor to metallic corrosion) to determine common elements to be used as “cases” - those defined for buildings are not applicable. The five bridges analysed included the Gladstone Port Access Road Overpass, Stewart Road Overpass, South Johnstone River Bridge, Johnson Creek Bridge and the Ward River Bridge.

Report : school survey to collect data on material performance

A survey of a number of schools in a number of different climates was carried out to determine the condition of building components of interest in the project. Schools in Melbourne, the Victorian Surf Coast, Brisbane, Townsville and the Sunshine Coast were inspected. A rating system was devised to categorise the components and the results collated in tables. Analysis of the data (where sufficient examples permitted) resulted in formulae to predict the service of the components and a database was derived.

Report : colorbond degradation model

This report documents work carried out in order to develop and prove a model for predicting the lifetime of painted metal components, with a particular emphasis on Colorbond® due to its prominent use throughout Australia. This work continues on from previous developments reported in 2002-059-B No. 12 [1]. Extensions of work included the following research: (1) Experimental proving of the leaching of chromate inhibitors from Colorbond® materials. (2) Updated models for the accumulation of salts and the time of wetness for gutters, based upon field observations. (3) Electrochemical Impedance Spectroscopy investigations aimed at correlating the corrosion rates of weathered Colorbond® with those predicted by modeling.

Technological barriers to learning : designing hybrid pedagogy to minimise cognitive load and maximise understanding

Information and Communication Technologies (ICTs) provide great promise for the future of education. In the Asia-Pacific region, many nations have started working towards the comprehensive development of infrastructure to enable the development of strong networked educational systems. In Queensland there have been significant initiatives in the past decade to support the integration of technology in classrooms and to set the conditions for the enhancement of teaching and learning with technology. One of the great challenges is to develop our classrooms to make the most of these technologies for the benefit of student learning. Recent research and theory into cognitive load, suggests that complex information environments may well impose a barrier on student learning. Further, it suggests that teachers have the capacity to mitigate against cognitive load through the way they prepare and support students engaging with complex information environments. This chapter compares student learning at different levels of cognitive load to show that learning is enhanced when integrating pedagogies are employed to mitigate against high-load information environments. This suggests that a mature policy framework for ICTs in education needs to consider carefully the development of professional capacities to effectively design and integrate technologies for learning.

Report : review of the literature : maintenance and rehabilitation costs for roads (Risk-based Analysis)

Realistic estimates of short- and long-term (strategic) budgets for maintenance and rehabilitation of road assessment management should consider the stochastic characteristics of asset conditions of the road networks so that the overall variability of road asset data conditions is taken into account. The probability theory has been used for assessing life-cycle costs for bridge infrastructures by Kong and Frangopol (2003), Zayed et.al. (2002), Kong and Frangopol (2003), Liu and Frangopol (2004), Noortwijk and Frangopol (2004), Novick (1993). Salem 2003 cited the importance of the collection and analysis of existing data on total costs for all life-cycle phases of existing infrastructure, including bridges, road etc., and the use of realistic methods for calculating the probable useful life of these infrastructures (Salem et. al. 2003). Zayed et. al. (2002) reported conflicting results in life-cycle cost analysis using deterministic and stochastic methods. Frangopol et. al. 2001 suggested that additional research was required to develop better life-cycle models and tools to quantify risks, and benefits associated with infrastructures. It is evident from the review of the literature that there is very limited information on the methodology that uses the stochastic characteristics of asset condition data for assessing budgets/costs for road maintenance and rehabilitation (Abaza 2002, Salem et. al. 2003, Zhao, et. al. 2004). Due to this limited information in the research literature, this report will describe and summarise the methodologies presented by each publication and also suggest a methodology for the current research project funded under the Cooperative Research Centre for Construction Innovation CRC CI project no 2003-029-C.

Report : development of a methodology for assessing variation in maintenance and rehabilitation costs

In the previous research CRC CI 2001-010-C “Investment Decision Framework for Infrastructure Asset Management”, a method for assessing variation in cost estimates for road maintenance and rehabilitation was developed. The variability of pavement strength collected from a 92km national highway was used in the analysis to demonstrate the concept. Further analysis was conducted to identify critical input parameters that significantly affect the prediction of road deterioration. In addition to pavement strength, rut depth, annual traffic loading and initial roughness were found to be critical input parameters for road deterioration. This report presents a method developed to incorporate other critical parameters in the analysis, such as unit costs, which are suspected to contribute to a certain degree to cost estimate variation. Thus, the variability of unit costs will be incorporated in this analysis. Bruce Highway located in the tropical east coast of Queensland has been identified to be the network for the analysis. This report presents a step by step methodology for assessing variation in road maintenance and rehabilitation cost estimates.

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.