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.

The supervision of doctoral dissertations using a collaborative cohort model

The Collaborative Cohort Model (CCM) for research supervision was developed and piloted as an alternative to the Apprentice Master Model (AMM), which is currently used with most doctoral dissertations. The CCM was developed in response to concerns about completion rates and the quality of research supervision. The feedback from the initial cohort of doctoral students who have experienced the model is presented.

A feasibility study for model based estimating for concrete bridges.

Designing and estimating civil concrete structures is a complex process which to many practitioners is tied to manual or semi-manual processes of 2D design and cannot be further improved by automated, interacting design-estimating processes. This paper presents a feasibility study for the development an automated estimator for concrete bridge design. The study offers a value proposition: an efficient automated model-based estimator can add value to the whole bridge design-estimating process, i.e., reducing estimation errors, shortening the duration of success estimates, and increasing the benefit of doing cost estimation when compared with the current practice. This is then followed by a description of what is in an efficient automated model-based estimator and how it should be used. Finally the process of model-based estimating is compared with the current practice to highlight the values embedded in the automated processes.

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

Energy efficient multi storey residential developments

Worldwide, the current pattern of urban development is unsustainable and metropolitan planning and development strategies deliver poor environmental outcomes in relation to energy production. As a result, an increasing number of governments and private sector development companies are initiating projects that aim to deliver enhanced environmental outcomes rather than a ‘business as usual’ approach. This paper will summarise the findings from a study that explored the link between building orientation and energy efficiencies in sub-tropical and tropical climates. The study used a new thermal modelling software tool developed by CSIRO that responds more accurately to residential heating and cooling energy performance in those climate zones. This software tool responds to industry criticisms regarding cold climate modelling systems that do not make sufficient allowance for natural ventilation. The study examined a range of low, medium and high-density dwelling types and investigated the impact of orientation, insulation, ventilation and shading devices on energy efficiencies. This paper will examine the findings from the medium and high-density case study developments as these are relevant to residential developments in many South East Asian countries, such as Singapore, Hong Kong and Malaysia. Finally, the paper will explore the potential benefits that medium and high-density residential developments have in the development of ‘solar cities’ and ‘solar suburbs’.

A collaborative model for learning and assessment of legal placements

This paper will report on the evaluation of a new undergraduate legal workplace unit, LWB421 Learning in Professional Practice. LWB421 was developed in response to the QUT’s strategic planning and a growing view that work experience is essential to developing the skills that law graduates need in order to be effective legal practitioners (Stuckey, 2007). Work integrated learning provides a context for students to develop their skills, to see the link between theory and practice and support students in making the transition from university to practice (Shirley, 2006). The literature in Australian legal education has given little consideration to the design of legal internship subjects (as distinct from legal clinic programs). Accordingly the design of placement subjects needs to be carefully considered to ensure alignment of learning objectives, learning tasks and assessment. Legal placements offer students the opportunity to develop their professional skills in practice, reflect on their own learning and job performance and take responsibility for their career development and planning. This paper will examine the literature relating to the design of placement subjects, particularly in a legal context. It will propose a collaborative model to facilitate learning and assessment of legal work placement subjects. The basis of the model is a negotiated learning contract between the student, workplace supervisor and academic supervisor. Finally the paper will evaluate the model in the context of LWB421. The evaluation will be based on data from surveys of students and supervisors and focus group sessions.

Harmonising procurement policy environment - identifying key themes towards the development of a conceptual model

Capital works procurement and its regulatory policy environment within a country can be complex entities. For example, by virtue of Australia’s governmental division between the Commonwealth, states and local jurisdictions and the associated procurement networks and responsibilities at each level, the tendering process is often convoluted. There are four inter-related key themes identified in the literature in relation to procurement disharmony, including decentralisation, risk & risk mitigation, free trade & competition, and tendering costs. This paper defines and discusses these key areas of conflict that adversely impact upon the business environments of industry through a literature review, policy analysis and consultation with capital works procurement stakeholders. The aim of this national study is to identify policy differences between jurisdictions in Australia, and ascertain whether those differences are a barrier to productivity and innovation. This research forms an element of a broader investigation with an aim of developing efficient, effective and nationally harmonised procurement systems. Keywords: capital works, procurement policy reform Acknowledgement: The research described in this paper carried out by the Australian Cooperative Research Centre for Construction Innovation.

A model for the uptake of E-business by building small and medium enterprises

The adoption of e-business by Small and Medium Enterprises (SMEs) in construction lags from other service and product businesses within the building sector. This paper develops a model to facilitate the uptake of electronic business, especially in relation to SMEs within the Australian construction sector. Ebusiness is defined here as “the undertaking of business-related transactions, communications and information exchanges utilising electronic medium and environment”, the elicited model highlights significant changes needed including skills development, social, economic and cultural issues. The model highlights barriers for SMEs to migrate towards e-transactions, e-bidding, e-tendering and ecollaboration and provides learning and skills development components. The model is derived from case study fieldwork and is to inform diffusion and awareness models for best practice. Empirical techniques included ‘focus group’ interviews and one to one ‘interviews’. Data was transcribed and analysed using cluster analyses. Preliminary results reveal that current models for e-business adoption are not effective within the construction context as they have emerged from other service and product industries - such as retail or tourism. These generic models have largely ignored the nature of the construction industry, and some modifications appears to be required. This paper proposes an alternative adoption model which is more sensitive to the nature of the industry – particularly for e-business uptake in building SME’s.

Linking early design decisions across multiple disciplines

The early stages of the building design process are when the most far reaching decisions are made regarding the configuration of the proposed project. This paper examines methods of providing decision support to building designers across multiple disciplines during the early stage of design. The level of detail supported is at the massing study stage where the basic envelope of the project is being defined. The block outlines on the building envelope are sliced into floors. Within a floor the only spatial divisions supported are the “user” space and the building core. The building core includes vertical transportation systems, emergency egress and vertical duct runs. The current focus of the project described in the paper is multi-storey mixed use office/residential buildings with car parking. This is a common type of building in redevelopment projects within and adjacent to the central business districts of major Australian cities. The key design parameters for system selection across the major systems in multi-storey building projects - architectural, structural, HVAC, vertical transportation, electrical distribution, fire protection, hydraulics and cost – are examined. These have been identified through literature research and discussions with building designers from various disciplines. This information is being encoded in decision support tools. The decision support tools communicate through a shared database to ensure that the relevant information is shared across all of the disciplines. An internal data model has been developed to support the very early design phase and the high level system descriptions required. A mapping to IFC 2x2 has also been defined to ensure that this early information is available at later stages of the design process.

Situated case-based reasoning as a constructive memory model for design reasoning

This paper describes an extended case-based reasoning model that addresses the notion of situatedness in designing through constructive memory. The model is illustrated through an application for predicting the corrosion rate for a specific material on a specific building.

Concurrent multi-scale modeling of civil infrastructures for analyses on structural deteriorating—Part II : Model updating and verification

This paper is a continuation of the paper titled “Concurrent multi-scale modeling of civil infrastructure for analyses on structural deteriorating—Part I: Modeling methodology and strategy” with the emphasis on model updating and verification for the developed concurrent multi-scale model. The sensitivity-based parameter updating method was applied and some important issues such as selection of reference data and model parameters, and model updating procedures on the multi-scale model were investigated based on the sensitivity analysis of the selected model parameters. The experimental modal data as well as static response in terms of component nominal stresses and hot-spot stresses at the concerned locations were used for dynamic response- and static response-oriented model updating, respectively. The updated multi-scale model was further verified to act as the baseline model which is assumed to be finite-element model closest to the real situation of the structure available for the subsequent arbitrary numerical simulation. The comparison of dynamic and static responses between the calculated results by the final model and measured data indicated the updating and verification methods applied in this paper are reliable and accurate for the multi-scale model of frame-like structure. The general procedures of multi-scale model updating and verification were finally proposed for nonlinear physical-based modeling of large civil infrastructure, and it was applied to the model verification of a long-span bridge as an actual engineering practice of the proposed procedures.

A model for assessing and correcting project Health

Maintaining the health of a construction project can help to achieve the desired outcomes of the project. An analogy is drawn to the medical process of a human health check where it is possible to broadly diagnose health in terms of a number of key areas such as blood pressure or cholesterol level. Similarly it appears possible to diagnose the current health of a construction project in terms of a number of Critical Success Factors (CSFs) and key performance indicators (KPIs). The medical analogy continues into the detailed investigation phase where a number of contributing factors are evaluated to identify possible causes of ill health and through the identification of potential remedies to return the project to the desired level of health. This paper presents the development of a model that diagnoses the immediate health of a construction project, investigates the factors which appear to be causing the ill health and proposes a remedy to return the project to good health. The proposed model uses the well-established continuous improvement management model (Deming, 1986) to adapt the process of human physical health checking to construction project health.

Relative entropy rate based multiple hidden Markov Model Approximation

This paper proposes a novel relative entropy rate (RER) based approach for multiple HMM (MHMM) approximation of a class of discrete-time uncertain processes. Under different uncertainty assumptions, the model design problem is posed either as a min-max optimisation problem or stochastic minimisation problem on the RER between joint laws describing the state and output processes (rather than the more usual RER between output processes). A suitable filter is proposed for which performance results are established which bound conditional mean estimation performance and show that estimation performance improves as the RER is reduced. These filter consistency and convergence bounds are the first results characterising multiple HMM approximation performance and suggest that joint RER concepts provide a useful model selection criteria. The proposed model design process and MHMM filter are demonstrated on an important image processing dim-target detection problem.

The BEE Undergraduate Model for Knowledge Development applied to the QUT Spatial Science Course : Diversity in Surveying Curriculum

This paper provides an overview of the current QUT Spatial Science undergraduate program based in Brisbane, Queensland, Australia. It discusses the development and implementation of a broad-based educational model for the faculty of built environment and engineering courses and specifically to the course structure of the new Bachelor of Urban Development (Spatial Science) study major. A brief historical background of surveying courses is discussed prior to the detailing of the three distinct and complementary learning themes of the new course structure with a graphical course matrix. Curriculum mapping of the spatial science major has been undertaken as the course approaches formal review in late 2010. Work-integrated learning opportunities have been embedded into the curriculum and a brief outline is presented. Some issues relevant to the tertiary surveying/ spatial sector are highlighted in the context of changing higher education environments in Australia.

Bayesian model averaging for harmful algal bloom prediction

Harmful Algal Blooms (HABs) are a worldwide problem that have been increasing in frequency and extent over the past several decades. HABs severely damage aquatic ecosystems by destroying benthic habitat, reducing invertebrate and fish populations and affecting larger species such as dugong that rely on seagrasses for food. Few statistical models for predicting HAB occurrences have been developed, and in common with most predictive models in ecology, those that have been developed do not fully account for uncertainties in parameters and model structure. This makes management decisions based on these predictions more risky than might be supposed. We used a probit time series model and Bayesian Model Averaging (BMA) to predict occurrences of blooms of Lyngbya majuscula, a toxic cyanophyte, in Deception Bay, Queensland, Australia. We found a suite of useful predictors for HAB occurrence, with Temperature figuring prominently in models with the majority of posterior support, and a model consisting of the single covariate average monthly minimum temperature showed by far the greatest posterior support. A comparison of alternative model averaging strategies was made with one strategy using the full posterior distribution and a simpler approach that utilised the majority of the posterior distribution for predictions but with vastly fewer models. Both BMA approaches showed excellent predictive performance with little difference in their predictive capacity. Applications of BMA are still rare in ecology, particularly in management settings. This study demonstrates the power of BMA as an important management tool that is capable of high predictive performance while fully accounting for both parameter and model uncertainty.