514 resultados para Asset reversibility


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Road infrastructure is a major contributor of greenhouse gas (GHG) around the world. Once constructed, a road becomes a part of a road network and is subjected to recurrent maintenance/rehabilitation activities. Studies to date are mostly aimed at the development of sustainability indicators that deal with the material and construction phases of a road when it is constructed. The operation phase is infrequently studied and there is a need for sustainability indicators to be developed relating to this phase to better understand the GHG emissions as a proper response to the climate change phenomena. During the operation phase, maintenance/rehabilitation activities are undertaken based on certain agreed intervention criteria that do not include environmental implications relating to the climate change aspect properly. Availability of appropriate indicators may, therefore, assist in sustainable road asset maintenance management. This paper presents the findings of a literature based study and has proposed a way forward to develop a key “road operation phase” environmental indicator, which can contribute to road operation phase carbon footprint management based on a comprehensive road life cycle system boundary model. The proposed indicator can address multiple aspects of high impact road operation life environmental components such as: pavement rolling resistance, albedo, material, traffic congestion and lighting, based on availability of relevant scientific knowledge. Development of the indicator to appropriate level would offset the impacts of these components significantly and contribute to sustainable road operation management.

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The Australian water sector needs to adapt to effectively deal with the impacts of climate change on its systems. Challenges as a result of climate change include increasingly extreme occurrences of weather events including flooding and droughts (Pittock, 2011). In response to such challenges, the National Water Commission in Australia has identified the need for the water sector to transition towards being readily adaptable and able to respond to complex needs for a variety of supply and demand scenarios (National Water Commission, 2013). To successfully make this transition, the sector will need to move away from business as usual, and proactively pursue and adopt innovative approaches and technologies as a means to successfully address the impacts of climate change on the Australian water sector. In order to effectively respond to specific innovation challenges related to the sector, including climate change, it is first necessary to possess a foundational understanding about the key elements related to innovation in the sector. This paper presents this base level understanding, identifying the key barriers, drivers and enablers, and elements for innovative practise in the water sector. After initially inspecting the literature around the challenges stemming from climate change faced by the sector, the paper then examines the findings from the initial two rounds of a modified Delphi study, conducted with experts from the Australian water sector, including participants from research, government and industry backgrounds. The key barriers, drivers and enablers for innovation in the sector identified during the initial phase of the study formed the basis for the remainder of the investigation. Key elements investigated were: barriers – scepticism, regulation systems, inconsistent policy; drivers – influence of policy, resource scarcity, thought leadership; enablers – framing the problem, effective regulations, community acceptance. There is a convincing argument for the water sector transitioning to a more flexible, adaptive and responsive system in the face of challenges resulting from climate change. However, without first understanding the challenges and opportunities around making this transition, the likelihood of success is limited. For that reason, this paper takes the first step in understanding the elements surrounding innovation in the Australian water sector.

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Many researchers in the field of civil structural health monitoring (SHM) have developed and tested their methods on simple to moderately complex laboratory structures such as beams, plates, frames, and trusses. Fieldwork has also been conducted by many researchers and practitioners on more complex operating bridges. Most laboratory structures do not adequately replicate the complexity of truss bridges. Informed by a brief review of the literature, this paper documents the design and proposed test plan of a structurally complex laboratory bridge model that has been specifically designed for the purpose of SHM research. Preliminary results have been presented in the companion paper.

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An effective prognostics program will provide ample lead time for maintenance engineers to schedule a repair and to acquire replacement components before catastrophic failures occur. This paper presents a technique for accurate assessment of the remnant life of machines based on health state probability estimation technique. For comparative study of the proposed model with the proportional hazard model (PHM), experimental bearing failure data from an accelerated bearing test rig were used. The result shows that the proposed prognostic model based on health state probability estimation can provide a more accurate prediction capability than the commonly used PHM in bearing failure case study.

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Many researchers in the field of civil structural health monitoring have developed and tested their methods on simple to moderately complex laboratory structures such as beams, plates, frames, and trusses. Field work has also been conducted by many researchers and practitioners on more complex operating bridges. Most laboratory structures do not adequately replicate the complexity of truss bridges. This paper presents some preliminary results of experimental modal testing and analysis of the bridge model presented in the companion paper, using the peak picking method, and compares these results with those of a simple numerical model of the structure. Three dominant modes of vibration were experimentally identified under 15 Hz. The mode shapes and order of the modes matched those of the numerical model; however, the frequencies did not match.

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There is an increasing awareness of sustainability and climate change and its impact on infrastructure and engineering asset management in design, construction, and operations. Sustainability rating tools have been proposed and/or developed that provide ratings of infrastructure projects in differing phases of their life cycle on sustainability. This paper provides an overview of decision support systems using sustainability rating framework that can be used to prioritize or select tasks and activities within projects to enhance levels of sustainability outcomes. These systems can also be used to prioritize projects within an organization to optimize sustainability outcomes within an allocated budget.

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The relationship between corporate and sustainability performance continues to be controversial and unclear, not withstanding numerous theoretical and empirical studies. Despite this, views on corporate responsibilities “meet where management can show how voluntary social and environmental management contributes to the competitiveness and economic success of the company.” This approach is fundamental to the business case for infrastructure sustainability. It suggests that beyond-compliance activities undertaken by companies are commercially justified if they can be shown to contribute to profitability and shareholder value. Potential public good benefits range across a wide spectrum of economic (for example employment, local purchasing, reduced demand for electricity generation), social (indigenous employment and development, equity of access), and environmental (lower greenhouse gas emission, reduced use of non-renewable resources and potable water, less waste, enhanced biodiversity). Some of these benefits have impacts that lie in more than one of the economic, social, and environmental areas of public goods. Using a sustainability rating schemes and potential business benefits from sustainability initiatives, this paper presents a brief summary of an online survey of industry that identifies how rating scheme themes and business benefits relate. This allows for a case to be built demonstrating which sustainability themes offer particular business benefits.

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This paper presents a study on the effectiveness of two forms of reinforced grout confining systems for hollow concrete block masonry. The systems considered are: (1) a layer of grout directly confining the unreinforced masonry, and (2) a layer of grout indirectly confining the unreinforced masonry through block shells. The study involves experimental testing and finite-element (FE) modeling of six diagonally loaded masonry panels containing the two confining systems. The failure mode, the ultimate load, and the load-deformation behaviors of the diagonally loaded panels were successfully simulated using the finite-element model. In-plane shear strength and stiffness of the masonry thus determined are used to evaluate some selected models of the confined masonry shear including the strut-and-tie model reported in the literature. The evaluated strut width is compared with the prediction of the FE model and then extended for rational prediction of the strength of confined masonry shear walls.

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This paper presents the unique black markets of asset pooling and leasing services, which exposes the nature and extent of industry-specific threats. We explore how firms providing such services together with their network structures that constitute the foundations of asset pooling and leasing respond to the threat of black markets. We encapsulate detecting and encountering the threat of black markets through the theoretical lens of agility, which encompasses the elements of sensing and responding (Overby et al. 2006; Roberts and Grover 2012). This novel concept of responding to threats using the agility lens has not been adequately addressed by past studies on enterprise agility. Through a case study of a global asset pooling and leasing company, we reveal the criticality of network structures, the impracticality of IT and inadequate tracking mechanisms that challenge firms in minimizing such threats.

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Wind energy, being the fastest growing renewable energy source in the present world, requires a large number of wind turbines to transform wind energy into electricity. One factor driving the cost of this energy is the reliable operation of these turbines. Therefore, it is a growing requirement within the wind farm community, to monitor the operation of the wind turbines on a continuous basis so that a possible fault can be detected ahead of time. As the wind turbine operates in an environment of constantly changing wind speed, it is a challenging task to design a fault detection technique which can accommodate the stochastic operational behavior of the turbines. Addressing this issue, this paper proposes a novel fault detection criterion which is robust against operational uncertainty, as well as having the ability to quantify severity level specifically of the drivetrain abnormality within an operating wind turbine. A benchmark model of wind turbine has been utilized to simulate drivetrain fault condition and effectiveness of the proposed technique has been tested accordingly. From the simulation result it can be concluded that the proposed criterion exhibits consistent performance for drivetrain faults for varying wind speed and has linear relationship with the fault severity level.

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The ability to estimate the expected Remaining Useful Life (RUL) is critical to reduce maintenance costs, operational downtime and safety hazards. In most industries, reliability analysis is based on the Reliability Centred Maintenance (RCM) and lifetime distribution models. In these models, the lifetime of an asset is estimated using failure time data; however, statistically sufficient failure time data are often difficult to attain in practice due to the fixed time-based replacement and the small population of identical assets. When condition indicator data are available in addition to failure time data, one of the alternate approaches to the traditional reliability models is the Condition-Based Maintenance (CBM). The covariate-based hazard modelling is one of CBM approaches. There are a number of covariate-based hazard models; however, little study has been conducted to evaluate the performance of these models in asset life prediction using various condition indicators and data availability. This paper reviews two covariate-based hazard models, Proportional Hazard Model (PHM) and Proportional Covariate Model (PCM). To assess these models’ performance, the expected RUL is compared to the actual RUL. Outcomes demonstrate that both models achieve convincingly good results in RUL prediction; however, PCM has smaller absolute prediction error. In addition, PHM shows over-smoothing tendency compared to PCM in sudden changes of condition data. Moreover, the case studies show PCM is not being biased in the case of small sample size.

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The aim of this thesis is to examine how risk tolerance and risk perception, two important but often misunderstood constructs, jointly influence client investment decisions in a financial advice context. By distinguishing the roles of these two risk constructs in client decision-making, in this thesis a new direction in studying financial/investment risks is provided while practice and regulation in the financial services industry is potentially informed. Based on the literature relating to risks and individual decision-making, a theoretical framework is developed and relevant hypotheses are tested in two studies with financial adviser clients in Australia. Results reveal that financial risk tolerance influences asset allocation both directly and indirectly through risk perception. The intervening role of risk perception suggests that risk tolerance affects how clients perceive the riskiness of an investment product which influences client decision-making.

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This paper discusses three different ways of applying the single-objective binary genetic algorithm into designing the wind farm. The introduction of different applications is through altering the binary encoding methods in GA codes. The first encoding method is the traditional one with fixed wind turbine positions. The second involves varying the initial positions from results of the first method, and it is achieved by using binary digits to represent the coordination of wind turbine on X or Y axis. The third is the mixing of the first encoding method with another one, which is by adding four more binary digits to represent one of the unavailable plots. The goal of this paper is to demonstrate how the single-objective binary algorithm can be applied and how the wind turbines are distributed under various conditions with best fitness. The main emphasis of discussion is focused on the scenario of wind direction varying from 0° to 45°. Results show that choosing the appropriate position of wind turbines is more significant than choosing the wind turbine numbers, considering that the former has a bigger influence on the whole farm fitness than the latter. And the farm has best performance of fitness values, farm efficiency, and total power with the direction between 20°to 30°.

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In the coming decades the design, construction and maintenance of roads will face a range of new issues and as such will require a number of new approaches. In particular, road authorities will be required to consider and respond to a range of issues related to climate change, and associated extreme weather events, such as the extensive flooding in January 2011 in Queensland, Australia Figure 1). Coupled with diminishing access to road construction supplies (such as aggregate), water scarcity, and the potential for increases in oil and electricity prices, this range of challenges bear little resemblance to those previously faced. In Australia, state and federal authorities face further pressures given the variety of needs resulting from the country's geographical and population diversity, expansive road networks, road freight requirements and relatively small population base.

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Although road construction and use provides significant economic and social benefits its environmental impact is of growing concern. Roads are one of the greatest greenhouse gas contributors both directly through fossil energy consumed in mining, transporting, earthworks, and paving work, along with in-direct emissions from road use by vehicles. This discussion paper will outline opportunities within the Australian context for reducing environmental pressure in road building and consider the future environmental impacts of road projects.