931 resultados para MAGNESIA-BASED INVESTMENT


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Literature addressing methodological issues in organisational research is extensive and multidisciplinary, encompassing debates about methodological choices, data-collection techniques, epistemological approaches and statistical procedures. However, little scholarship has tackled an important aspect of organisational research that precedes decisions about data collection and analysis – access to the organisations themselves, including the people, processes and documents within them. This chapter looks at organisational access through the experiences of three research fellows in the course of their work with their respective industry partners. In doing so, it reveals many of the challenges and changing opportunities associated with access to organisations, which are rarely explicitly addressed, but often assumed, in traditional methods texts and journal publications. Although the level of access granted varied somewhat across the projects at different points in time and according to different organisational contexts, we shared a number of core and consistent experiences in attempting to collect data and implement strategies.

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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.

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Reliable budget/cost estimates for road maintenance and rehabilitation are subjected to uncertainties and variability in road asset condition and characteristics of road users. The CRC CI research project 2003-029-C ‘Maintenance Cost Prediction for Road’ developed a method for assessing variation and reliability in budget/cost estimates for road maintenance and rehabilitation. The method is based on probability-based reliable theory and statistical method. The next stage of the current project is to apply the developed method to predict maintenance/rehabilitation budgets/costs of large networks for strategic investment. The first task is to assess the variability of road data. This report presents initial results of the analysis in assessing the variability of road data. A case study of the analysis for dry non reactive soil is presented to demonstrate the concept in analysing the variability of road data for large road networks. In assessing the variability of road data, large road networks were categorised into categories with common characteristics according to soil and climatic conditions, pavement conditions, pavement types, surface types and annual average daily traffic. The probability distributions, statistical means, and standard deviation values of asset conditions and annual average daily traffic for each type were quantified. The probability distributions and the statistical information obtained in this analysis will be used to asset the variation and reliability in budget/cost estimates in later stage. Generally, we usually used mean values of asset data of each category as input values for investment analysis. The variability of asset data in each category is not taken into account. This analysis method demonstrated that it can be used for practical application taking into account the variability of road data in analysing large road networks for maintenance/rehabilitation investment analysis.

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In this paper, the stability of an autonomous microgrid with multiple distributed generators (DG) is studied through eigenvalue analysis. It is assumed that all the DGs are connected through Voltage Source Converter (VSC) and all connected loads are passive. The VSCs are controlled by state feedback controller to achieve desired voltage and current outputs that are decided by a droop controller. The state space models of each of the converters with its associated feedback are derived. These are then connected with the state space models of the droop, network and loads to form a homogeneous model, through which the eigenvalues are evaluated. The system stability is then investigated as a function of the droop controller real and reac-tive power coefficients. These observations are then verified through simulation studies using PSCAD/EMTDC. It will be shown that the simulation results closely agree with stability be-havior predicted by the eigenvalue analysis.

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This paper describes the operation of a microgrid that contains a custom power park (CPP). The park may contain an unbalanced and/or nonlinear load and the microgrid may contain many dis-tributed generators (DGs). One of the DGs in the microgrid is used as a compensator to achieve load compensation. A new method is proposed for current reference generation for load compensation, which takes into account the real and reactive power to be supplied by the DG connected to the compensator. The real and reactive power from the DGs and the utility source is tightly regulated assuming that dedicated communication channels are available. Therefore this scheme is most suitable in cases where the loads in CPP and DGs are physically located close to each other. The proposal is validated through extensive simulation studies using EMTDC/PSCAD software package (version 4.2).

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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.

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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.

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An estimation of costs for maintenance and rehabilitation is subject to variation due to the uncertainties of input parameters. This paper presents the results of an analysis to identify input parameters that affect the prediction of variation in road deterioration. Road data obtained from 1688 km of a national highway located in the tropical northeast of Queensland in Australia were used in the analysis. Data were analysed using a probability-based method, the Monte Carlo simulation technique and HDM-4’s roughness prediction model. The results of the analysis indicated that among the input parameters the variability of pavement strength, rut depth, annual equivalent axle load and initial roughness affected the variability of the predicted roughness. The second part of the paper presents an analysis to assess the variation in cost estimates due to the variability of the overall identified critical input parameters.

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One of the key issues facing public asset owners is the decision of refurbishing aged built assets. This decision requires an assessment of the “remaining service life” of the key components in a building. The remaining service life is significantly dependent upon the existing condition of the asset and future degradation patterns considering durability and functional obsolescence. Recently developed methods on Residual Service Life modelling, require sophisticated data that are not readily available. Most of the data available are in the form of reports prior to undertaking major repairs or in the form of sessional audit reports. Valuable information from these available sources can serve as bench marks for estimating the reference service life. The authors have acquired similar informations from a public asset building in Melbourne. Using these informations, the residual service life of a case study building façade has been estimated in this paper based on state-of-the-art approaches. These estimations have been evaluated against expert opinion. Though the results are encouraging it is clear that the state-of-the-art methodologies can only provide meaningful estimates provided the level and quality of data are available. This investigation resulted in the development of a new framework for maintenance that integrates the condition assessment procedures and factors influencing residual service life

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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

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Decentralized and regional load-frequency control of power systems operating in normal and near-normal conditions has been well studied; and several analysis/synthesis approaches have been developed during the last few decades. However in contingency and off-normal conditions, the existing emergency control plans, such as under-frequency load shedding, are usually applied in a centralized structure using a different analysis model. This paper discusses the feasibility of using frequency-based emergency control schemes based on tie-line measurements and local information available within a control area. The conventional load-frequency control model is generalized by considering the dynamics of emergency control/protection schemes and an analytic approach to analyze the regional frequency response under normal and emergency conditions is presented.

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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.

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The road and transport industry in Australia and overseas has come a long way to understanding the impact of road traffic noise on the urban environment. Most road authorities now have guidelines to help assess and manage the impact of road traffic noise on noise-sensitive areas and development. While several economic studies across Australia and overseas have tried to value the impact of noise on property prices, decision-makers investing in road traffic noise management strategies have relatively limited historic data and case studies to go on. The perceived success of a noise management strategy currently relies largely on community expectations at a given time, and is not necessarily based on the analysis of the costs and benefits, or the long-term viability and value to the community of the proposed treatment options. With changing trends in urban design, it is essential that the 'whole-of-life' costs and benefits of noise ameliorative treatment options and strategies be identified and made available for decisionmakers in future investment considerations. For this reason, CRC for Construction Innovation Australia funded a research project, Noise Management in Urban Environments to help decision-makers with future road traffic noise management investment decisions. RMIT University and the Queensland Department of Main Roads (QDMR) have conducted the research work, in collaboration with the Queensland Department of Public Works, ARUP Pty Ltd, and the Queensland University of Technology. The research has formed the basis for the development of a decision-support software tool, and helped collate technical and costing data for known noise amelioration treatment options. We intend that the decision support software tool (DST) should help an investment decision-maker to be better informed of suitable noise ameliorative treatment options on a project-by-project basis and identify likely costs and benefits associated with each of those options. This handbook has been prepared as a procedural guide for conducting a comparative assessment of noise ameliorative options. The handbook outlines the methodology and assumptions adopted in the decision-support framework for the investment decision-maker and user of the DST. The DST has been developed to provide an integrated user-friendly interface between road traffic noise modelling software, the relevant assessment criteria and the options analysis process. A user guide for the DST is incorporated in this handbook.

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A common challenge among OECD countries has been the development of education and training pathways that accommodate student needs and interests at the upper secondary level (OECD, 2000). The introduction of trade-focussed Australian Technical Colleges (ATCs) has met with mixed response. The ATCs aim to create a supported transition from school to work through dual pathway programs enabling students to follow a trade career while completing their upper secondary studies. There has been little explicit examination of the effectiveness of such senior secondary school arrangements. Using one such Australian Technical College as a case-study, this paper investigates the perceptions of the employers and students who were associated with the college. Using mixed-methods consisting of quantitative perception surveys and focus interviews, the results of this study show that students and employers are very satisfied with the College and illustrate that students have made significant gains in relating their learning to the workplace and everyday life.