863 resultados para energy-cost
Resumo:
Construction is an information intensive industry in which the accuracy and timeliness of information is paramount. It observed that the main communication issue in construction is to provide a method to exchange data between the site operation, the site office and the head office. The information needs under consideration are time critical to assist in maintaining or improving the efficiency at the jobsite. Without appropriate computing support this may increase the difficulty of problem solving. Many researchers focus their research on the usage of mobile computing devices in the construction industry and they believe that mobile computers have the potential to solve some construction problems that leads to reduce overall productivity. However, to date very limited observation has been conducted in terms of the deployment of mobile computers for construction workers on-site. By providing field workers with accurate, reliable and timely information at the location where it is needed, it will support the effectiveness and efficiency at the job site. Bringing a new technology into construction industry is not only need a better understanding of the application, but also need a proper preparation of the allocation of the resources such as people, and investment. With this in mind, an accurate analysis is needed to provide clearly idea of the overall costs and benefits of the new technology. A cost benefit analysis is a method of evaluating the relative merits of a proposed investment project in order to achieve efficient allocation of resources. It is a way of identifying, portraying and assessing the factors which need to be considered in making rational economic choices. In principle, a cost benefit analysis is a rigorous, quantitative and data-intensive procedure, which requires identification all potential effects, categorisation of these effects as costs and benefits, quantitative estimation of the extent of each cost and benefit associated with an action, translation of these into a common metric such as dollars, discounting of future costs and benefits into the terms of a given year, and summary of all cost and benefit to see which is greater. Even though many cost benefit analysis methodologies are available for a general assessment, there is no specific methodology can be applied for analysing the cost and benefit of the application of mobile computing devices in the construction site. Hence, the proposed methodology in this document is predominantly adapted from Baker et al. (2000), Department of Finance (1995), and Office of Investment Management (2005). The methodology is divided into four main stages and then detailed into ten steps. The methodology is provided for the CRC CI 2002-057-C Project: Enabling Team Collaboration with Pervasive and Mobile Computing and can be seen in detail in Section 3.
Resumo:
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.
Resumo:
n design of bridge structures, it is common to adopt a 100 year design life. However, analysis of a number of case study bridges in Australia has indicated that the actual design life can be significantly reduced due to premature deterioration resulting from exposure to aggressive environments. A closer analysis of the cost of rehabilitation of these structures has raised some interesting questions. What would be the real service life of a bridge exposed to certain aggressive environments? What is the strategy of conducting bridge rehabilitation? And what are the life cycle costs associated with rehabilitation? A research project funded by the CRC for Construction Innovation in Australia is aimed at addressing these issues. This paper presents a concept map for assisting decision makers to appropriately choose the best treatment for bridge rehabilitation affected by premature deterioration through exposure to aggressive environments in Australia. The decision analysis is referred to a whole of life cycle cost analysis by considering appropriate elements of bridge rehabilitation costs. In addition, the results of bridges inspections in Queensland are presented
Resumo:
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.
Resumo:
The quality of office indoor environments is considered to consist of those factors that impact the occupants according to their health and well-being and (by consequence) their productivity. Indoor Environment Quality (IEQ) can be characterized by four indicators: • Indoor air quality indicators • Thermal comfort indicators • Lighting indicators • Noise indicators. Within each indicator, there are specific metrics that can be utilized in determining an acceptable quality of an indoor environment based on existing knowledge and best practice. Examples of these metrics are: indoor air levels of pollutants or odorants; operative temperature and its control; radiant asymmetry; task lighting; glare; ambient noise. The way in which these metrics impact occupants is not fully understood, especially when multiple metrics may interact in their impacts. It can be estimated that the potential cost of lost productivity from poor IEQ may be much in excess of other operating costs of a building. However, the relative productivity impacts of each of the four indicators is largely unknown. The CRC Project ‘Regenerating Construction to Enhance Sustainability’ has a focus on IEQ impacts before and after building refurbishment. This paper provides an overview of IEQ impacts and criteria and the implementation of a CRC project that is currently researching these factors during the refurbishment of a Melbourne office building. IEQ measurements and their impacts will be reported in a future paper
Resumo:
The quality of office indoor environments is considered to consist of those factors that impact occupants according to their health and well-being and (by consequence) their productivity. Indoor Environment Quality (IEQ) can be characterized by four indicators: • Indoor air quality indicators • Thermal comfort indicators • Lighting indicators • Noise indicators. Within each indicator, there are specific metrics that can be utilized in determining an acceptable quality of an indoor environment based on existing knowledge and best practice. Examples of these metrics are: indoor air levels of pollutants or odorants; operative temperature and its control; radiant asymmetry; task lighting; glare; ambient noise. The way in which these metrics impact occupants is not fully understood, especially when multiple metrics may interact in their impacts. While the potential cost of lost productivity from poor IEQ has been estimated to exceed building operation costs, the level of impact and the relative significance of the above four indicators are largely unknown. However, they are key factors in the sustainable operation or refurbishment of office buildings. This paper presents a methodology for assessing indoor environment quality (IEQ) in office buildings, and indicators with related metrics for high performance and occupant comfort. These are intended for integration into the specification of sustainable office buildings as key factors to ensure a high degree of occupant habitability, without this being impaired by other sustainability factors. The assessment methodology was applied in a case study on IEQ in Australia’s first ‘six star’ sustainable office building, Council House 2 (CH2), located in the centre of Melbourne. The CH2 building was designed and built with specific focus on sustainability and the provision of a high quality indoor environment for occupants. Actual IEQ performance was assessed in this study by field assessment after construction and occupancy. For comparison, the methodology was applied to a 30 year old conventional building adjacent to CH2 which housed the same or similar occupants and activities. The impact of IEQ on occupant productivity will be reported in a separate future paper
Resumo:
This paper will summarise the findings from a study that explored the link between dwelling design, or type, and energy efficiencies in sub-tropical climates. An increasing number of government and private sector development companies are initiating projects that aim to deliver enhanced environmental outcomes at both sub-divisional and dwelling levels. The study used AccuRate, a new thermal modelling tool developed by CSIRO that responds to the need to improve ventilation modelling. The study found that dwellings developed in conjunction with the Departments of Housing and Public Works have set the benchmark. It provides a snapshot of the energy efficiency of a range of dwelling types found in recent subdivisions. However, the trend toward increasing urban densities may reduce the likelihood that cooling breezes will be available to cool dwellings. The findings are relevant to regulators, designers and industry in all states interested in reducing the energy used to cool dwellings in summer.
Resumo:
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’.
Resumo:
This report summarises the findings from the Sustainable Subdivisions: Energy-Efficient Design project. As new energy-efficiency regulations are developed, there will be a significant demand for information on available assessment tools for rating energy-efficient dwellings, and subdivisional issues such as orientation and solar access will become increasingly important. There will also be increased pressure for products that deliver energy efficiency, such as solar technology, glazing systems, insulation and low-energy building products and materials. The objectives of the Sustainable Subdivisions: Energy-Efficient Design project were to:
Resumo:
There is evidence that many heating, ventilating & air conditioning (HVAC) systems, installed in larger buildings, have more capacity than is ever required to keep the occupants comfortable. This paper explores the reasons why this can occur, by examining a typical brief/design/documentation process. Over-sized HVAC systems cost more to install and operate and may not be able to control thermal comfort as well as a “right-sized” system. These impacts are evaluated, where data exists. Finally, some suggestions are developed to minimise both the extent of, and the negative impacts of, HVAC system over-sizing, for example: • Challenge “rules of thumb” and/or brief requirements which may be out of date. • Conduct an accurate load estimate, using AIRAH design data, specific to project location, and then resist the temptation to apply “safety factors • Use a load estimation program that accounts for thermal storage and diversification of peak loads for each zone and air handling system. • Select chiller sizes and staged or variable speed pumps and fans to ensure good part load performance. • Allow for unknown future tenancies by designing flexibility into the system, not by over-sizing. For example, generous sizing of distribution pipework and ductwork will allow available capacity to be redistributed. • Provide an auxiliary tenant condenser water loop to handle high load areas. • Consider using an Integrated Design Process, build an integrated load and energy use simulation model and test different operational scenarios • Use comprehensive Life Cycle Cost analysis for selection of the most optimal design solutions. This paper is an interim report on the findings of CRC-CI project 2002-051-B, Right-Sizing HVAC Systems, which is due for completion in January 2006.
Resumo:
In this paper, the placement of sectionalizers, as well as, a cross-connection is optimally determined so that the objective function is minimized. The objective function employed in this paper consists of two main parts, the switch cost and the reliability cost. The switch cost is composed of the cost of sectionalizers and cross-connection and the reliability cost is assumed to be proportional to a reliability index, SAIDI. To optimize the allocation of sectionalizers and cross-connection problem realistically, the cost related to each element is considered as discrete. In consequence of binary variables for the availability of sectionalizers, the problem is extremely discrete. Therefore, the probability of local minimum risk is high and a heuristic-based optimization method is needed. A Discrete Particle Swarm Optimization (DPSO) is employed in this paper to deal with this discrete problem. Finally, a testing distribution system is used to validate the proposed method.
Resumo:
Routine postsurgery assessment of primary total hip arthroplasty (THA) is recommended in many countries. Whether the benefits of this activity are justified by the costs is not known. We used a decision-analytic Markov model to compare the costs and health outcomes of 3 different follow-up strategies after primary THA. If there is no routine follow-up of patients for 7 years after primary THA, there would be cost savings between AU$6.5 and $11.9 million and gains of between 1.8 and 8.8 quality-adjusted life years. Policy makers should investigate less resource-intensive alternatives to common routine postsurgical assessment.
Resumo:
This thesis is a documented energy audit and long term study of energy and water reduction in a ghee factory. Global production of ghee exceeds 4 million tonnes annually. The factory in this study refines dairy products by non-traditional centrifugal separation and produces 99.9% pure, canned, crystallised Anhydrous Milk Fat (Ghee). Ghee is traditionally made by batch processing methods. The traditional method is less efficient, than centrifugal separation. An in depth systematic investigation was conducted of each item of major equipment including; ammonia refrigeration, a steam boiler, canning equipment, pumps, heat exchangers and compressed air were all fine-tuned. Continuous monitoring of electrical usage showed that not every initiative worked, others had pay back periods of less than a year. In 1994-95 energy consumption was 6,582GJ and in 2003-04 it was 5,552GJ down 16% for a similar output. A significant reduction in water usage was achieved by reducing the airflow in the refrigeration evaporative condensers to match the refrigeration load. Water usage has fallen 68% from18ML in 1994-95 to 5.78ML in 2003-04. The methods reported in this thesis could be applied to other industries, which have similar equipment, and other ghee manufacturers.
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Damage localization induced by strain softening can be predicted by the direct minimization of a global energy function. This article concerns the computational strategy for implementing this principle for softening materials such as concrete. Instead of using heuristic global optimization techniques, our strategies are a hybrid of local optimization methods with a path-finding approach to ensure a global optimum. With admissible nodal displacements being independent variables, it is easy to deal with the geometric (mesh) constraint conditions. The direct search optimization methods recover the localized solutions for a range of softening lattice models which are representative of quasi-brittle structures