152 resultados para Building thermal model,Demand response,Demand side management,Energy management system


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Prefabricated construction is regarded by many as an effective and efficient approach to improving construction processes and productivity, ensuring construction quality and reducing time and cost in the construction industry. However, many problems occur with this approach in practice, including higher risk levels and cost or time overruns. In order to solve such problems, it is proposed that the IKEA model of the manufacturing industry and VP technology are introduced into a prefabricated construction process. The concept of the IKEA model is identified in detail and VP technology is briefly introduced. In conjunction with VP technology, the applications of the IKEA model are presented in detail, i.e. design optimization, production optimization and installation optimization. Furthermore, through a case study of a prefabricated hotel project in Hong Kong, it is shown that the VP-based IKEA model can improve the efficiency and safety of prefabricated construction as well as reducing cost and time.

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Emergency health is a critical component of Australia’s health system and one which is increasingly congested from growing demand and blocked access to inpatient beds. The Emergency Health Services Queensland (EHSQ) study aims to identify the factors driving increased demand for emergency health and to evaluate strategies which may safely reduce the future demand growth. This monograph addresses the characteristics of users of emergency health services with an aim to identify those that appear to contribute to demand growth. This study utilises data on patients treated by Emergency Departments (ED) and Queensland Ambulance Service (QAS) across Queensland. ED data was derived from the Emergency Department Information System (EDIS) for the period 2001-02 through to 2010-11. Ambulance data was extracted from the QAS’ Ambulance Information Management System (AIMS) and electronic Ambulance Report Form (eARF) for the period 2001-02 through to 2009-10. Due to discrepancies and comparability issues for ED data, this monograph compares data from the 2003-04 time period with 2010-11 data for 21 of the reporting EDs. Also a snapshot of users for the 2010-11 financial year for 31 reporting EDs is used to describe the characteristics of users and to compare those characteristics with population demographics. For QAS data, the 2002-03 and 2009-10 time periods were selected for detailed analyses to identify trends. • Demand for emergency health care services is increasing, representing both increased population and increased relative utilisation. Per capita demand for ED attention has increased by 2% per annum over the last decade and for ambulance attention by 3.7% per annum. • The growth in ED demand is prominent in more urgent triage categories with actual decline in less urgent patients. An estimated 55% of patients attend hospital EDs outside of normal working hours. There is no evidence that patients presenting out of hours are significantly different to those presenting within working hours; they have similar triage assessments and outcomes. • Patients suffering from injuries and poisoning comprise 28% of the ED workload (an increase of 65% in the study period), whilst declines of 32% in cardiovascular and circulatory conditions, and musculoskeletal problems have been observed. • 25.6% of patients attending EDs are admitted to hospital. 19% of admitted patients and 7% of patients who die in the ED are triage category 4 or 5 on arrival. • The average age of ED patients is 35.6 years. Demand has grown in all age groups and amongst both men and women. Men have higher utilisation rates for ED in all age groups. The only group where the growth rate in women has exceeded men is in the 20-29 age group; this growth is particularly in the injury and poisoning categories. • Considerable attention has been paid publicly to ED performance criteria. It is worth noting that 50% of all patients were treated within 33 minutes of arrival. • Patients from lower socioeconomic areas appear to have higher utilisation rates and the utilisation rate for indigenous people appears to exceed those of European and other backgrounds. The utilisation rates for immigrant people is generally less than that of Australian born however it has not been possible to eliminate the confounding impact of different age and socioeconomic profiles. • Demand for ambulance service is also increasing at a rate that exceeds population growth. Utilisation rates have increased by an average of 5% per annum in Queensland compared to 3.6% nationally, and the utilisation rate in Queensland is 27% higher than the national average. • The growth in ambulance utilisation has also been amongst the more urgent categories of dispatch and utilisation rates are higher in rural and regional areas than in the metropolitan area. The demand for ambulance increases with age but the growth in demand for ambulance service has been more prominent in younger age groups. These findings contribute significantly to an understanding of the growth in demand for emergency health. It shows that the growth is amongst patients in genuine need of emergency healthcare and public rhetoric that the congestion of emergency health services is due to inappropriate attendees is unable to be substantiated. The consistency of the growth in demand over the last decade reflects not only the changing demographics of the Australian population but also the changes in health status, standards of acute health care and other social factors. The growth is also amongst patients with acute injury and poisoning which is inconsistent with rates of chronic disease as a fundamental driver. We have also interviewed patients in regard to their decision making choices for acute health care and the factors that influence these decisions and this will be the subject of a third Monograph and publications.

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The building sector is the dominant consumer of energy and therefore a major contributor to anthropomorphic climate change. The rapid generation of photorealistic, 3D environment models with incorporated surface temperature data has the potential to improve thermographic monitoring of building energy efficiency. In pursuit of this goal, we propose a system which combines a range sensor with a thermal-infrared camera. Our proposed system can generate dense 3D models of environments with both appearance and temperature information, and is the first such system to be developed using a low-cost RGB-D camera. The proposed pipeline processes depth maps successively, forming an ongoing pose estimate of the depth camera and optimizing a voxel occupancy map. Voxels are assigned 4 channels representing estimates of their true RGB and thermal-infrared intensity values. Poses corresponding to each RGB and thermal-infrared image are estimated through a combination of timestamp-based interpolation and a pre-determined knowledge of the extrinsic calibration of the system. Raycasting is then used to color the voxels to represent both visual appearance using RGB, and an estimate of the surface temperature. The output of the system is a dense 3D model which can simultaneously represent both RGB and thermal-infrared data using one of two alternative representation schemes. Experimental results demonstrate that the system is capable of accurately mapping difficult environments, even in complete darkness.

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Emergency health is a critical component of health systems; one increasingly congested from growing demand and blocked access to care. The Emergency Health Services Queensland (EHSQ) study aimed to identify the factors driving increased demand for emergency healthcare. This study examined data on patients treated by the ambulance service and Emergency Departments across Queensland. Data was derived from the Queensland Ambulance Service’s (QAS) Ambulance Information Management System and electronic Ambulance Report Form and from the Emergency Department Information System (EDIS). Data was obtained for the period 2001-02 through to 2009-10. A snapshot of users for the 2009-10 year was used to describe the characteristics of users and comparisons made with the year 2003-04 to identify trends. Per capita demand for EDs has increased by 2% per annum over the decade and for ambulance by 3.7% per annum. The growth in ED demand is most significant in more urgent triage categories with decline in less urgent patients. The growth is most prominent amongst patients suffering injuries and poisoning, amongst both men and women and across all age groups. Patients from lower socioeconomic areas appear to have higher utilisation rates and the utilisation rate for indigenous people exceeds those of other backgrounds. The utilisation rates for immigrant people is less than Australian born however it has not been possible to eliminate the confounding impact of age and socioeconomic profiles. These findings contribute to an understanding of the growth in demand for emergency health. It is evident that the growth is amongst patients in genuine need of emergency healthcare and public rhetoric that congested emergency health services is due to inappropriate attendees is unsustainable. The growth in demand over the last decade reflects not only on changing demographics of the Australian population but also changes in health status, standards of acute health care and other social factors.

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The overall aim of this research project was to provide a broader range of value propositions (beyond upfront traditional construction costs) that could transform both the demand side and supply side of the housing industry. The project involved gathering information about how building information is created, used and communicated and classifying building information, leading to the formation of an Information Flow Chart and Stakeholder Relationship Map. These were then tested via broad housing industry focus groups and surveys. The project revealed four key relationships that appear to operate in isolation to the whole housing sector and may have significant impact on the sustainability outcomes and life cycle costs of dwellings over their life cycle. It also found that although a lot of information about individual dwellings does already exist, this information is not coordinated or inventoried in any systematic manner and that national building information files of building passports would present value to a wide range of stakeholders.

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Agent-based modelling (ABM), like other modelling techniques, is used to answer specific questions from real world systems that could otherwise be expensive or impractical. Its recent gain in popularity can be attributed to some degree to its capacity to use information at a fine level of detail of the system, both geographically and temporally, and generate information at a higher level, where emerging patterns can be observed. This technique is data-intensive, as explicit data at a fine level of detail is used and it is computer-intensive as many interactions between agents, which can learn and have a goal, are required. With the growing availability of data and the increase in computer power, these concerns are however fading. Nonetheless, being able to update or extend the model as more information becomes available can become problematic, because of the tight coupling of the agents and their dependence on the data, especially when modelling very large systems. One large system to which ABM is currently applied is the electricity distribution where thousands of agents representing the network and the consumers’ behaviours are interacting with one another. A framework that aims at answering a range of questions regarding the potential evolution of the grid has been developed and is presented here. It uses agent-based modelling to represent the engineering infrastructure of the distribution network and has been built with flexibility and extensibility in mind. What distinguishes the method presented here from the usual ABMs is that this ABM has been developed in a compositional manner. This encompasses not only the software tool, which core is named MODAM (MODular Agent-based Model) but the model itself. Using such approach enables the model to be extended as more information becomes available or modified as the electricity system evolves, leading to an adaptable model. Two well-known modularity principles in the software engineering domain are information hiding and separation of concerns. These principles were used to develop the agent-based model on top of OSGi and Eclipse plugins which have good support for modularity. Information regarding the model entities was separated into a) assets which describe the entities’ physical characteristics, and b) agents which describe their behaviour according to their goal and previous learning experiences. This approach diverges from the traditional approach where both aspects are often conflated. It has many advantages in terms of reusability of one or the other aspect for different purposes as well as composability when building simulations. For example, the way an asset is used on a network can greatly vary while its physical characteristics are the same – this is the case for two identical battery systems which usage will vary depending on the purpose of their installation. While any battery can be described by its physical properties (e.g. capacity, lifetime, and depth of discharge), its behaviour will vary depending on who is using it and what their aim is. The model is populated using data describing both aspects (physical characteristics and behaviour) and can be updated as required depending on what simulation is to be run. For example, data can be used to describe the environment to which the agents respond to – e.g. weather for solar panels, or to describe the assets and their relation to one another – e.g. the network assets. Finally, when running a simulation, MODAM calls on its module manager that coordinates the different plugins, automates the creation of the assets and agents using factories, and schedules their execution which can be done sequentially or in parallel for faster execution. Building agent-based models in this way has proven fast when adding new complex behaviours, as well as new types of assets. Simulations have been run to understand the potential impact of changes on the network in terms of assets (e.g. installation of decentralised generators) or behaviours (e.g. response to different management aims). While this platform has been developed within the context of a project focussing on the electricity domain, the core of the software, MODAM, can be extended to other domains such as transport which is part of future work with the addition of electric vehicles.

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The introduction of Building Information Modelling (BIM) to the design, construction and operation of buildings is changing the way that the building construction industry works. BIM involves the development of a full 3D virtual model of a building which not only contains the 3D information necessary to show the building as it will appear, but also contains significant additional data about each component in the building. BIM represents both physical and virtual objects in a building. This includes the rooms and spaces within and around the building. The additional data stored on each part of the building can support building maintenance opera- tions and, more importantly from the perspective of this paper, support the generation and running of simula- tions of the operation of the building and behaviour of people within it under both normal and emergency scenarios. The initial discussion is around the use of BIM to support the design of resilient buildings which references the various codes and standards that define current best practice. The remainder of the discussion uses various recent events as the basis for discussion on how BIM could have been used to support rapid recovery and re- building.

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This paper offers one explanation for the institutional basis of food insecurity in Australia, and argues that while alternative food networks and the food sovereignty movement perform a valuable function in building forms of social solidarity between urban consumers and rural producers, they currently make only a minor contribution to Australia’s food and nutrition security. The paper begins by identifying two key drivers of food security: household incomes (on the demand side) and nutrition-sensitive, ‘fair food’ agriculture (on the supply side). We focus on this second driver and argue that healthy populations require an agricultural sector that delivers dietary diversity via a fair and sustainable food system. In order to understand why nutrition-sensitive, fair food agriculture is not flourishing in Australia we introduce the development economics theory of urban bias. According to this theory, governments support capital intensive rather than labour intensive agriculture in order to deliver cheap food alongside the transfer of public revenues gained from rural agriculture to urban infrastructure, where the majority of the voting public resides. We chart the unfolding of the Urban Bias across the twentieth century and its consolidation through neo-liberal orthodoxy, and argue that agricultural policies do little to sustain, let alone revitalize, rural and regional Australia. We conclude that by observing food system dynamics through a re-spatialized lens, Urban Bias Theory is valuable in highlighting rural–urban socio-economic and political economy tensions, particularly regarding food system sustainability. It also sheds light on the cultural economy tensions for alternative food networks as they move beyond niche markets to simultaneously support urban food security and sustainable rural livelihoods.

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This paper investigates the long- and short-run relationships between energy consumption and economic growth in Australia using the bound testing and the ARDL approach. The analytical framework utilized in this paper includes both production and demand side models and a unified model comprising both production and demand side variables. The energy-GDP relationships are investigated at aggregate as well as several disaggregated energy categories, such as coal, oil, gas and electricity. The possibilities of one or more structural break(s) in the data series are examined by applying the recent advances in techniques. We find that the results of the cointegration tests could be affected by the structural break(s) in the data. It is, therefore, crucial to incorporate the information on structural break(s) in the subsequent modelling and inferences. Moreover, neither the production side nor the demand side framework alone can provide sufficient information to draw an ultimate conclusion on the cointegration and causal direction between energy and output. When alternative frameworks and structural break(s) in time series are explored properly, strong evidence of a bidirectional relationship between energy and output can be observed. The finding is true at both the aggregate and the disaggregate levels of energy consumption.

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Rapid growth in the global population requires expansion of building stock, which in turn calls for increased energy demand. This demand varies in time and also between different buildings, yet, conventional methods are only able to provide mean energy levels per zone and are unable to capture this inhomogeneity, which is important to conserve energy. An additional challenge is that some of the attempts to conserve energy, through for example lowering of ventilation rates, have been shown to exacerbate another problem, which is unacceptable indoor air quality (IAQ). The rise of sensing technology over the past decade has shown potential to address both these issues simultaneously by providing high–resolution tempo–spatial data to systematically analyse the energy demand and its consumption as well as the impacts of measures taken to control energy consumption on IAQ. However, challenges remain in the development of affordable services for data analysis, deployment of large–scale real–time sensing network and responding through Building Energy Management Systems. This article presents the fundamental drivers behind the rise of sensing technology for the management of energy and IAQ in urban built environments, highlights major challenges for their large–scale deployment and identifies the research gaps that should be closed by future investigations.

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The paper presents an interim summary of research and case studies being undertaken in the Sydney Opera House FM Exemplar Project covering procurement, benchmarking and building information models. The final outcomes of the FM Exemplar Project will be presented through various forums open to all FM practitioners and published in Australia and elsewhere through relevant journals. Sydney Opera House is an Australian icon, attracting some 4.5 million visitors per year who admire its built form and enjoy an evening of theatre. The building is the attraction, part of the experience. Therefore, facilities management is critical to the success of the Sydney Opera House enterprise and an ideal subject for the study of facilities management. Significantly the three research themes are heavily intertwined – effective risk sharing in procurement requires historic information and benchmarks for future performance, benchmarking gathers vast quantities of data that can only be exploited if properly related to one another and a building information model provides the means to manage such data. The case studies are emerging as real-life examples of how one organisation is addressing FM issues common to many, and will provide useful lessons for practitioners pursing similar strategies in their own organisations.

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Facility managers have to acquire, integrate, edit and update diverse facility information ranging from building elements & fabric data, operational costs, contract types, room allocation, logistics, maintenance, etc. With the advent of standardized Building Information Models (BIM) such as the Industry Foundation Classes (IFC) new opportunities are available for Facility Managers to manage their FM data. The usage of IFC supports data interoperability between different software systems including the use of operational data for facility management systems. Besides the re-use of building data, the Building Information Model can be used as an information framework for storing and retrieving FM related data. Currently several BIM driven FM systems are available including IFC compliant ones. These systems have the potential to not only manage primary data more effectively but also to offer practical systems for detailed monitoring, and analysis of facility performance that can underpin innovative and more cost effective management of complex facilities.

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Purpose –The introduction of Building Information Model tools over the last 20 years is resulting in radical changes in the Architectural, Engineering and Construction industry. One of these changes concerns the use of Virtual Prototyping - an advanced technology integrating BIM with realistic graphical simulations. Construction Virtual Prototyping (CVP) has now been developed and implemented on ten real construction projects in Hong Kong in the past three years. This paper reports on a survey aimed at establishing the effects of adopting this new technology and obtaining recommendations for future development. Design/methodology/approach – A questionnaire survey was conducted in 2007 of 28 key participants involved in four major Hong Kong construction projects – these projects being chosen because the CVP approach was used in more than one stage in each project. In addition, several interviews were conducted with the project manager, planning manager and project engineer of an individual project. Findings –All the respondents and interviewees gave a positive response to the CVP approach, with the most useful software functions considered to be those relating to visualisation and communication. The CVP approach was thought to improve the collaboration efficiency of the main contractor and sub-contractors by approximately 30 percent, and with a concomitant 30 to 50 percent reduction in meeting time. The most important benefits of CPV in the construction planning stage are the improved accuracy of process planning and shorter planning times, while improved fieldwork instruction and reducing rework occur in the construction implementation stage. Although project teams are hesitant to attribute the use of CVP directly to any specific time savings, it was also acknowledged that the workload of project planners is decreased. Suggestions for further development of the approach include incorporation of automatic scheduling and advanced assembly study. Originality/value –Whilst the research, development and implementation of CVP is relatively new in the construction industry, it is clear from the applications and feedback to date that the approach provides considerable added value to the organisation and management of construction projects.

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The selection criteria for contractor pre-qualification are characterized by the co-existence of both quantitative and qualitative data. The qualitative data is non-linear, uncertain and imprecise. An ideal decision support system for contractor pre-qualification should have the ability of handling both quantitative and qualitative data, and of mapping the complicated nonlinear relationship of the selection criteria, such that rational and consistent decisions can be made. In this research paper, an artificial neural network model was developed to assist public clients identifying suitable contractors for tendering. The pre-qualification criteria (variables) were identified for the model. One hundred and twelve real pre-qualification cases were collected from civil engineering projects in Hong Kong, and eighty-eight hypothetical pre-qualification cases were also generated according to the “If-then” rules used by professionals in the pre-qualification process. The results of the analysis totally comply with current practice (public developers in Hong Kong). Each pre-qualification case consisted of input ratings for candidate contractors’ attributes and their corresponding pre-qualification decisions. The training of the neural network model was accomplished by using the developed program, in which a conjugate gradient descent algorithm was incorporated for improving the learning performance of the network. Cross-validation was applied to estimate the generalization errors based on the “re-sampling” of training pairs. The case studies show that the artificial neural network model is suitable for mapping the complicated nonlinear relationship between contractors’ attributes and their corresponding pre-qualification (disqualification) decisions. The artificial neural network model can be concluded as an ideal alternative for performing the contractor pre-qualification task.

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Despite the general evolution and broadening of the scope of the concept of infrastructure in many other sectors, the energy sector has maintained the same narrow boundaries for over 80 years. Energy infrastructure is still generally restricted in meaning to the transmission and distribution networks of electricity and, to some extent, gas. This is especially true in the urban development context. This early 20th century system is struggling to meet community expectations that the industry itself created and fostered for many decades. The relentless growth in demand and changing political, economic and environmental challenges require a shift from the traditional ‘predict and provide’ approach to infrastructure which is no longer economically or environmentally viable. Market deregulation and a raft of demand and supply side management strategies have failed to curb society’s addiction to the commodity of electricity. None of these responses has addressed the fundamental problem. This chapter presents an argument for the need for a new paradigm. Going beyond peripheral energy efficiency measures and the substitution of fossil fuels with renewables, it outlines a new approach to the provision of energy services in the context of 21st century urban environments.