837 resultados para Energy consumption.


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The University of Queensland UltraCommuter concept is an ultra- light, low-drag, hybrid-electric sports coupe designed to minimize energy consumption and environmental impact while enhancing the performance, styling, features and convenience that motorists enjoy. This paper presents a detailed simulation study of the vehicle's performance and fuel economy using ADVISOR, including a detailed description of the component models and parameters assumed. Results from the study include predictions of a 0-100 kph acceleration time of ≺9s, and top speed of 170 kph, an electrical energy consumption of ≺67 Wh/km in ZEV mode and a petrol-equivalent fuel consumption of ≺2.5 L/100 km in charge-sustaining HEV mode. Overall, the results of the ADVISOR modelling confirm the UltraCommuter's potential to achieve high performance with high efficiency, and the authors look forward to a confirmation of these estimates following completion of the vehicle.

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This paper presents a new simplified parametric analysis technique for the design of fuel cell and hybrid-electric vehicles. The technique utilizes a comprehensive set of ∼30 parameters to fully characterize the vehicle platform, powertrain components, vehicle performance requirements and driving conditions. It is best applied to the sizing of powertrain components and prediction of energy consumption in a vehicle. This new parametric technique makes a good complement to existing vehicle simulation software packages and therefore represents a potentially valuable tool for the hybrid vehicle designer.

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The prime objective of drying is to enhance shelf life of perishable food materials. As the process is very energy intensive in nature, researchers are trying to minimise energy consumption in the drying process. In order to determine the exact amount of energy needed for drying a food product, understanding the physics of moisture distribution and bond strength of water within the food material is essential. In order understand the critical moisture content, moisture distribution and water bond strength in food material, Thermogravimetric analysis (TGA) can be properly utilised. This work has been conducted to investigate moisture distribution and water bond strength in selected food materials; apple, banana and potato. It was found that moisture distribution and water bond strength influence moisture migration from the food materials. In addition, proportion of different types of water (bound, free, surface water) has been simply identified using TGA. This study provides a better understanding of water contents and its role in drying rate and energy consumption.

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Sustainability has become an important principle to be pursued throughout the life-cycles of project development. Facility managers are in a commanding position to maximise the potential of sustainability. Sustainability endeavours in facility management (FM) practices will not only contribute to reducing energy consumption and waste, but will also help increase organisational productivity, financial returns and standing in the community. At the forefront of sustainable practices, FM professionals can exercise a great deal of influence through operational and strategic management and they should be empowered with the necessary knowledge and capabilities. However, literature studies suggest that there is a gap between the level of awareness and knowledge and the necessary skills required to promote sustainability endeavours in the FM profession. Therefore, it is worthwhile to reflect on people capability issues since it is considered as the key enabler in managing the sustainability agenda as well as being central to the improvement of competency and innovation in an organization. This paper aims to identify the critical factors for enhancing people capabilities in promoting the sustainability agenda in the FM sector. To achieve this objective, a total of 60 factors were identified through a comprehensive literature review and then a questionnaire survey with 52 respondents was conducted to collect the perceived importance of these factors. The survey analysis revealed 23 critical factors as significantly important. These critical factors will serve as the basis for the establishment of a mechanism to equip facility managers with the right knowledge, to continue education and training and to develop new mind-sets to enhance the implementation of sustainability measures in FM practices.

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Custom designed for display on the Cube Installation situated in the new Science and Engineering Centre (SEC) at QUT, the ECOS project is a playful interface that uses real-time weather data to simulate how a five-star energy building operates in climates all over the world. In collaboration with the SEC building managers, the ECOS Project incorporates energy consumption and generation data of the building into an interactive simulation, which is both engaging to users and highly informative, and which invites play and reflection on the roles of green buildings. ECOS focuses on the principle that humans can have both a positive and negative impact on ecosystems with both local and global consequence. The ECOS project draws on the practice of Eco-Visualisation, a term used to encapsulate the important merging of environmental data visualization with the philosophy of sustainability. Holmes (2007) uses the term Eco-Visualisation (EV) to refer to data visualisations that ‘display the real time consumption statistics of key environmental resources for the goal of promoting ecological literacy’. EVs are commonly artifacts of interaction design, information design, interface design and industrial design, but are informed by various intellectual disciplines that have shared interests in sustainability. As a result of surveying a number of projects, Pierce, Odom and Blevis (2008) outline strategies for designing and evaluating effective EVs, including ‘connecting behavior to material impacts of consumption, encouraging playful engagement and exploration with energy, raising public awareness and facilitating discussion, and stimulating critical reflection.’ Consequently, Froehlich (2010) and his colleagues also use the term ‘Eco-feedback technology’ to describe the same field. ‘Green IT’ is another variation which Tomlinson (2010) describes as a ‘field at the juncture of two trends… the growing concern over environmental issues’ and ‘the use of digital tools and techniques for manipulating information.’ The ECOS Project team is guided by these principles, but more importantly, propose an example for how these principles may be achieved. The ECOS Project presents a simplified interface to the very complex domain of thermodynamic and climate modeling. From a mathematical perspective, the simulation can be divided into two models, which interact and compete for balance – the comfort of ECOS’ virtual denizens and the ecological and environmental health of the virtual world. The comfort model is based on the study of psychometrics, and specifically those relating to human comfort. This provides baseline micro-climatic values for what constitutes a comfortable working environment within the QUT SEC buildings. The difference between the ambient outside temperature (as determined by polling the Google Weather API for live weather data) and the internal thermostat of the building (as set by the user) allows us to estimate the energy required to either heat or cool the building. Once the energy requirements can be ascertained, this is then balanced with the ability of the building to produce enough power from green energy sources (solar, wind and gas) to cover its energy requirements. Calculating the relative amount of energy produced by wind and solar can be done by, in the case of solar for example, considering the size of panel and the amount of solar radiation it is receiving at any given time, which in turn can be estimated based on the temperature and conditions returned by the live weather API. Some of these variables can be altered by the user, allowing them to attempt to optimize the health of the building. The variables that can be changed are the budget allocated to green energy sources such as the Solar Panels, Wind Generator and the Air conditioning to control the internal building temperature. These variables influence the energy input and output variables, modeled on the real energy usage statistics drawn from the SEC data provided by the building managers.

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Due to their inherently hypoxic environment, cancer cells often resort to glycolysis, or the anaerobic breakdown of glucose to form ATP to provide for their energy needs, known as the Warburg effect. At the same time, overexpression of the insulin receptor in non-small cell lung cancer (NSCLC) is associated with an increased risk of metastasis and decreased survival. The uptake of glucose into cells is carried out via glucose transporters or GLUTs. Of these, GLUT-4 is essential for insulin-stimulated glucose uptake. Following treatment with the epigenetic targeting agents histone deacetylase inhibitors (HDACi), GLUT-3 and GLUT-4 expression were found to be induced in NSCLC cell lines, with minimal responses in transformed normal human bronchial epithelial cells (HBECs). Similar results for GLUT-4 were observed in cells derived from liver, muscle, kidney and pre-adipocytes. Bioinformatic analysis of the promoter for GLUT-4 indicates that it may also be regulated by several chromatin binding factors or complexes including CTCF, SP1 and SMYD3. Chromatin immunoprecipitation studies demonstrate that the promoter for GLUT-4 is dynamically remodeled in response to HDACi. Overall, these results may have value within the clinical setting as (a) it may be possible to use this to enhance fluorodeoxyglucose (18F) positron emission tomography (FDG-PET) imaging sensitivity; (b) it may be possible to target NSCLC through the use of HDACi and insulin mediated uptake of the metabolic targeting drugs such as 2-deoxyglucose (2-DG); or (c) enhance or sensitize NSCLC to chemotherapy. © 2011 by the authors; licensee MDPI, Basel, Switzerland.

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Technological advances have led to an influx of affordable hardware that supports sensing, computation and communication. This hardware is increasingly deployed in public and private spaces, tracking and aggregating a wealth of real-time environmental data. Although these technologies are the focus of several research areas, there is a lack of research dealing with the problem of making these capabilities accessible to everyday users. This thesis represents a first step towards developing systems that will allow users to leverage the available infrastructure and create custom tailored solutions. It explores how this notion can be utilized in the context of energy monitoring to improve conventional approaches. The project adopted a user-centered design process to inform the development of a flexible system for real-time data stream composition and visualization. This system features an extensible architecture and defines a unified API for heterogeneous data streams. Rather than displaying the data in a predetermined fashion, it makes this information available as building blocks that can be combined and shared. It is based on the insight that individual users have diverse information needs and presentation preferences. Therefore, it allows users to compose rich information displays, incorporating personally relevant data from an extensive information ecosystem. The prototype was evaluated in an exploratory study to observe its natural use in a real-world setting, gathering empirical usage statistics and conducting semi-structured interviews. The results show that a high degree of customization does not warrant sustained usage. Other factors were identified, yielding recommendations for increasing the impact on energy consumption.

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Background Dietary diversity is recognized as a key element of a high quality diet. However, diets that offer a greater variety of energy-dense foods could increase food intake and body weight. The aim of this study was to explore association of diet diversity with obesity in Sri Lankan adults. Methods Six hundred adults aged > 18 years were randomly selected by using multi-stage stratified sample. Dietary intake assessment was undertaken by a 24 hour dietary recall. Three dietary scores, Dietary Diversity Score (DDS), Dietary Diversity Score with Portions (DDSP) and Food Variety Score (FVS) were calculated. Body mass index (BMI) ≥ 25 kg.m-2 is defined as obese and Asian waist circumference cut-offs were used diagnosed abdominal obesity. Results Mean of DDS for men and women were 6.23 and 6.50 (p=0.06), while DDSP was 3.26 and 3.17 respectively (p=0.24). FVS values were significantly different between men and women 9.55 and 10.24 (p=0.002). Dietary diversity among Sri Lankan adults was significantly associated with gender, residency, ethnicity, education level but not with diabetes status. As dietary scores increased, the percentage consumption was increased in most of food groups except starches. Obese and abdominal obese adults had the highest DDS compared to non obese groups (p<0.05). With increased dietary diversity the level of BMI, waist circumference and energy consumption was significantly increased in this population. Conclusion Our data suggests that dietary diversity is positively associated with several socio-demographic characteristics and obesity among Sri Lankan adults. Although high dietary diversity is widely recommended, public health messages should emphasize to improve dietary diversity in selective food items.

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Electricity network investment and asset management require accurate estimation of future demand in energy consumption within specified service areas. For this purpose, simple models are typically developed to predict future trends in electricity consumption using various methods and assumptions. This paper presents a statistical model to predict electricity consumption in the residential sector at the Census Collection District (CCD) level over the state of New South Wales, Australia, based on spatial building and household characteristics. Residential household demographic and building data from the Australian Bureau of Statistics (ABS) and actual electricity consumption data from electricity companies are merged for 74 % of the 12,000 CCDs in the state. Eighty percent of the merged dataset is randomly set aside to establish the model using regression analysis, and the remaining 20 % is used to independently test the accuracy of model prediction against actual consumption. In 90 % of the cases, the predicted consumption is shown to be within 5 kWh per dwelling per day from actual values, with an overall state accuracy of -1.15 %. Given a future scenario with a shift in climate zone and a growth in population, the model is used to identify the geographical or service areas that are most likely to have increased electricity consumption. Such geographical representation can be of great benefit when assessing alternatives to the centralised generation of energy; having such a model gives a quantifiable method to selecting the 'most' appropriate system when a review or upgrade of the network infrastructure is required.

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The built environment has a profound impact on our natural environment, economy, health and productivity. As the majority of the people spent most of their time inside buildings, the environment in which they perform their daily activities will have an impact on their health and productivity. Studies have been conducted about the negative impacts of presence of non-favorable conditions to human health and well being. The term "Sick Building Syndrome" (SBS) is used to describe situations in which building occupants experience acute health and comfort problems that appear to be linked to their time spent in a building. Sustainable infrastructure rating systems have requirements intended to improve occupant productivity and health.While the impact of Sustainable Infrastructure in energy consumption and waste/water reduction can be measured using available tools, the impact on productivity remained as an assumption that is not clearly measured. The purpose of this research is to develop a framework to assess whether the impacts of the incorporation of features intended to improve occupants’ performance and health such as: increased ventilation, lightning and thermal comfort serve their intended purpose.

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The US National Institute of Standards and Technology (NIST) showed that, in 2004, owners and operations managers bore two thirds of the total industry cost burden from inadequate interoperability in construction projects from inception to operation, amounting to USD10.6 billion. Building Information Modelling (BIM) and similar tools were identified by Engineers Australia in 2005 as potential instruments to significantly reduce this sum, which in Australia could amount to total industry-wide cost burden of AUD12 billion. Public sector road authorities in Australia have a key responsibility in driving initiatives to reduce greenhouse gas emissions from the construction and operations of transport infrastructure. However, as previous research has shown the Environmental Impact Assessment process, typically used for project approvals and permitting based on project designs available at the consent stage, lacks Key Performance Indicators (KPIs) that include long-term impact factors and transfer of information throughout the project life cycle. In the building construction industry, BIM is widely used to model sustainability KPIs such as energy consumption, and integrated with facility management systems. This paper proposes that a similar use of BIM in early design phases of transport infrastructure could provide: (i) productivity gains through improved interoperability and documentation; (ii) the opportunity to carry out detailed cost-benefit analyses leading to significant operational cost savings; (iii) coordinated planning of street and highway lighting with other energy and environmental considerations; iv) measurable KPIs that include long-term impact factors which are transferable throughout the project life cycle; and (v) the opportunity for integrating design documentation with sustainability whole-of-life targets.

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This thesis introduces advanced Demand Response algorithms for residential appliances to provide benefits for both utility and customers. The algorithms are engaged in scheduling appliances appropriately in a critical peak day to alleviate network peak, adverse voltage conditions and wholesale price spikes also reducing the cost of residential energy consumption. Initially, a demand response technique via customer reward is proposed, where the utility controls appliances to achieve network improvement. Then, an improved real-time pricing scheme is introduced and customers are supported by energy management schedulers to actively participate in it. Finally, the demand response algorithm is improved to provide frequency regulation services.

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Objective. To assess the effectiveness of workplace interventions in improving physical activity. Data Source. EBSCO research database (and all subdatabases). Study Inclusion and Exclusion Criteria. Articles were published from 2000 to 2010 in English, had appropriate designs, and measured employees' physical activity, energy consumption, and/or body mass index (BMI) as primary outcomes. Articles that did not meet the inclusion criteria were excluded. Data Extraction. Data extracted included study design, study population, duration, intervention activities, outcomes, and results. Data Synthesis. Data were synthesized into one table. Results of each relevant outcome including p values were combined. Results. Twelve (60%) of 20 selected interventions reported an improvement in physical activity level, steps, or BMI, and there was one slowed step reduction in the intervention group. Among these, 10 were less than 6 months in duration; 9 used pedometers; 6 applied Internet-based approaches; and 5 included activities targeting social and environmental levels. Seven of 8 interventions with pre-posttest and quasi-experimental controlled design showed improvement on at least one outcome. However, 7 of 12 randomized controlled trials (RCTs) did not prove effective in any outcome. Conclusion. Interventions that had less rigorous research designs, used pedometers, applied Internet-based approaches, and included activities at social and environmental levels were more likely to report being effective than those without these characteristics.

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The ISSCT Engineering Workshop 2008 in Brazil was well attended with 62 participants including 39 overseas visitors from 15 countries. The workshop addressed the theme Design, manufacturing and maintenance of sugar mill equipment. From the technical sessions, the following conclusions were drawn: • Several speakers articulated a shared vision of the future of the Brazilian sugar industry. This shared vision gives considerable confidence that the vision can become a reality. • There is an increased focus on energy products. As a result, the reduction of factory energy consumption in order to maximise the energy available for products is also a focus. • New equipment and products are being developed with reduced power consumption, lower capital and maintenance costs, and better performance. • Methods presented for reducing maintenance costs included the use of a maintenance management system, condition monitoring and material selection. The workshop was held in conjunction with Piracicaba’s annual SIMTEC exhibition for the sugar and alcohol industries that provides a forum for technical presentations and discussion, and showcases products and services from manufacturers and service providers. In return for holding the workshop in conjunction with SIMTEC, SIMTEC provided sponsorship for the workshop, including paying travel and accommodation costs for two invited speakers, and organisation for the workshop. The ISSCT and SIMTEC technical programs were arranged so that their technical sessions did not clash, and the ISSCT program was extended a day to provide an opportunity for ISSCT participants to attend the SIMTEC exhibition. Informal feedback from workshop participants suggested that the arrangement between ISSCT and SIMTEC worked well. Site visits to two manufacturing facilities and two sugar mills were arranged as part of the workshop.

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In the past few years, there has been a steady increase in the attention, importance and focus of green initiatives related to data centers. While various energy aware measures have been developed for data centers, the requirement of improving the performance efficiency of application assignment at the same time has yet to be fulfilled. For instance, many energy aware measures applied to data centers maintain a trade-off between energy consumption and Quality of Service (QoS). To address this problem, this paper presents a novel concept of profiling to facilitate offline optimization for a deterministic application assignment to virtual machines. Then, a profile-based model is established for obtaining near-optimal allocations of applications to virtual machines with consideration of three major objectives: energy cost, CPU utilization efficiency and application completion time. From this model, a profile-based and scalable matching algorithm is developed to solve the profile-based model. The assignment efficiency of our algorithm is then compared with that of the Hungarian algorithm, which does not scale well though giving the optimal solution.