942 resultados para Force and energy.
Co-optimisation of indoor environmental quality and energy consumption within urban office buildings
Resumo:
This study aimed to develop a multi-component model that can be used to maximise indoor environmental quality inside mechanically ventilated office buildings, while minimising energy usage. The integrated model, which was developed and validated from fieldwork data, was employed to assess the potential improvement of indoor air quality and energy saving under different ventilation conditions in typical air-conditioned office buildings in the subtropical city of Brisbane, Australia. When operating the ventilation system under predicted optimal conditions of indoor environmental quality and energy conservation and using outdoor air filtration, average indoor particle number (PN) concentration decreased by as much as 77%, while indoor CO2 concentration and energy consumption were not significantly different compared to the normal summer time operating conditions. Benefits of operating the system with this algorithm were most pronounced during the Brisbane’s mild winter. In terms of indoor air quality, average indoor PN and CO2 concentrations decreased by 48% and 24%, respectively, while potential energy savings due to free cooling went as high as 108% of the normal winter time operating conditions. The application of such a model to the operation of ventilation systems can help to significantly improve indoor air quality and energy conservation in air-conditioned office buildings.
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Although a number of studies have examined the role of gastric emptying (GE) in obesity, the influences of habitual physical activity level, body composition and energy expenditure (EE) on GE have received very little consideration. In this study, we have compared GE in active and inactive males, and we have characterised relationships with body composition (fat and fat free mass) and EE. Forty-four males (Active: n=22, Inactive: n=22; range BMI 21-36kg/m2; range percent fat mass 9-42%) were studied, with GE of a standardised (1676 kJ) pancake meal being assessed by 13C-octanoic acid breath test, body composition by air displacement plethysmography, resting metabolic rate (RMR) by indirect calorimetry and activity EE (AEE) by accelerometry. Results showed that GE was faster in active compared to inactive males (mean ±SD half time (t1/2): Active: 157±18 and Inactive: 179±21 min, p<0.001). When data from both groups were pooled, GE t1/2 was associated with percent fat mass (r=0.39, p<0.01) and AEE (r =-0.46, p<0.01). After controlling for habitual physical activity status, the association between AEE and GE remained, but not that for percent fat mass and GE. BMI and RMR were not associated with GE. In summary, faster GE is considered to be a marker of a habitually active lifestyle in males, and is associated with a higher AEE and lower percent fat mass. The possibility that GE contributes to a gross physiological regulation (or dysregulation) of food intake with physical activity level deserves further investigation.
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Pumping systems are widely used in many applications, including municipal water/wastewater services, domestic, commercial and agricultural services, and industrial processes. They are a very significant energy user and consume nearly 20% of the world’s electrical energy demand. Therefore, improving the energy efficiency of pumping systems can provide great benefits in terms of energy, environment, and cost reduction. In this entry, an overview of pump classification with pros and cons of each type of pump is presented. The procedures used to design pumping systems are also outlined. This is then followed by a discussion on the opportunities for improving the energy efficiency of pumping systems during every stage of design, selection, operation, and maintenance.
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Conductance measurements of junctions between a high- superconductor and a metallic oxide have been carried out along the a-b plane to examine the tunnel-junction spectra. For these measurements, in situ films have been grown on c-axis oriented thin films using the pulsed laser deposition technique. Two distinctive energy gaps have been observed along with conductance peaks around zero bias. The analysis of zero-bias conductance and energy gap data suggests the presence of midgap states located at the centre of a finite energy gap. The results obtained are also in accordance with the d-wave nature of high- superconductors.
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The dissipation rate of turbulent kinetic energy (epsilon) is a key parameter for mixing in surface aerators. In particular, determination epsilon across the impeller stream, where the most intensive mixing takes place, is essential to ascertain that an appropriate degree of mixing is achieved. Present work by using commercial software VisiMix (R) calculates the energy dissipation rate in geometrically similar unbaffled surface aeration systems in order to scale-up the oxygen transfer process. It is found that in geometrically similar system, oxygen transfer rate is uniquely correlated with dissipation rate of energy. Simulation or scale-up equation governing oxygen transfer rate and dissipation rate of energy has been developed in the present work.
Resumo:
The dissipation rate of turbulent kinetic energy(e)is a key parameter for mixing in surface aerators. In particular, determination e across the impeller stream, where the most intensive mixing takes place, is essential to ascertain that an appropriate degree of mixing is achieved. Present work by using commercial software VisiMix calculates the energy dissipation rate in geometrically similar unbaffled surface aeration systems in order to scale-up the oxygen transfer process. It is found that in geometrically similar system,oxygen transfer rate is uniquely correlated with dissipation rate of energy. Simulation or scale-up equation governing oxygen transfer rate and dissipation rate of energy has been developed in the present work.
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Analytical expressions for the corrections to duality are obtained for nonsingular potentials, and are found to be small numerically. An alternative consistent way of energy smoothing, developed by Strutinsky, is elucidated. This may be of use even when potential models are not valid.
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The effects of heat stress on dairy production can be separated into 2 distinct causes: those effects that are mediated by the reduced voluntary feed intake associated with heat stress, and the direct physiological and metabolic effects of heat stress. To distinguish between these, and identify their effect on milk protein and casein concentration, mid-lactation Holstein-Friesian cows (n = 24) were housed in temperature-controlled chambers and either subjected to heat stress HS; temperature-humidity index (THI) ~78 or kept in a THI < 70 environment and pair-fed with heat-stressed cows (TN-R) for 7 d. A control group of cows was kept in a THI < 70 environment with ad libitum feeding (TN-AL). A subsequent recovery period (7 d), with THI < 70 and ad libitum feeding followed. Intake accounted for only part of the effects of heat stress. Heat stress reduced the milk protein concentration, casein number, and casein concentration and increased the urea concentration in milk beyond the effects of restriction of intake. Under HS, the proportion in total casein of αS1-casein increased and the proportion of αS2-casein decreased. Because no effect of HS on milk fat or lactose concentration was found, these effects appeared to be the result of specific downregulation of mammary protein synthesis, and not a general reduction in mammary activity. No residual effects were found of HS or TN-R on milk production or composition after THI < 70 and ad libitum intake were restored. Heat-stressed cows had elevated blood concentrations of urea and Ca, compared with TN-R and TN-AL. Cows in TN-R had higher serum nonesterified fatty acid concentrations than cows in HS. It was proposed that HS and TN-R cows may mobilize different tissues as endogenous sources of energy.
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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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We consider a scenario in which a wireless sensor network is formed by randomly deploying n sensors to measure some spatial function over a field, with the objective of computing a function of the measurements and communicating it to an operator station. We restrict ourselves to the class of type-threshold functions (as defined in the work of Giridhar and Kumar, 2005), of which max, min, and indicator functions are important examples: our discussions are couched in terms of the max function. We view the problem as one of message-passing distributed computation over a geometric random graph. The network is assumed to be synchronous, and the sensors synchronously measure values and then collaborate to compute and deliver the function computed with these values to the operator station. Computation algorithms differ in (1) the communication topology assumed and (2) the messages that the nodes need to exchange in order to carry out the computation. The focus of our paper is to establish (in probability) scaling laws for the time and energy complexity of the distributed function computation over random wireless networks, under the assumption of centralized contention-free scheduling of packet transmissions. First, without any constraint on the computation algorithm, we establish scaling laws for the computation time and energy expenditure for one-time maximum computation. We show that for an optimal algorithm, the computation time and energy expenditure scale, respectively, as Theta(radicn/log n) and Theta(n) asymptotically as the number of sensors n rarr infin. Second, we analyze the performance of three specific computation algorithms that may be used in specific practical situations, namely, the tree algorithm, multihop transmission, and the Ripple algorithm (a type of gossip algorithm), and obtain scaling laws for the computation time and energy expenditure as n rarr infin. In particular, we show that the computation time for these algorithms scales as Theta(radicn/lo- g n), Theta(n), and Theta(radicn log n), respectively, whereas the energy expended scales as , Theta(n), Theta(radicn/log n), and Theta(radicn log n), respectively. Finally, simulation results are provided to show that our analysis indeed captures the correct scaling. The simulations also yield estimates of the constant multipliers in the scaling laws. Our analyses throughout assume a centralized optimal scheduler, and hence, our results can be viewed as providing bounds for the performance with practical distributed schedulers.
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In receive antenna selection (AS), only signals from a subset of the antennas are processed at any time by the limited number of radio frequency (RF) chains available at the receiver. Hence, the transmitter needs to send pilots multiple times to enable the receiver to estimate the channel state of all the antennas and select the best subset. Conventionally, the sensitivity of coherent reception to channel estimation errors has been tackled by boosting the energy allocated to all pilots to ensure accurate channel estimates for all antennas. Energy for pilots received by unselected antennas is mostly wasted, especially since the selection process is robust to estimation errors. In this paper, we propose a novel training method uniquely tailored for AS that transmits one extra pilot symbol that generates accurate channel estimates for the antenna subset that actually receives data. Consequently, the transmitter can selectively boost the energy allocated to the extra pilot. We derive closed-form expressions for the proposed scheme's symbol error probability for MPSK and MQAM, and optimize the energy allocated to pilot and data symbols. Through an insightful asymptotic analysis, we show that the optimal solution achieves full diversity and is better than the conventional method.
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The present study evaluates the feasibility of undelimbed Scots pine (Pinus sylvestris L.) for integrated production of pulp and energy in a kraft pulp mill from the technical, economic and environmental points of view, focusing on the potential of bundle harvesting. The feasibility of tree sections for pulp production was tested by conducting an industrial wood-handling experiment, laboratory cooking and bleaching trials, using conventional small-diameter Scots pine pulpwood as a reference. These trials showed that undelimbed Scots pine sections can be processed in favourable conditions as a blend with conventional small-diameter pulpwood without reducing the pulp quality. However, fibre losses at various phases of the process may increase when using undelimbed material. In the economic evaluation, both pulp production and wood procurement costs were considered, using the relative wood paying capability of a kraft pulp mill as a determinant. The calculations were made for three Scots pine first-thinning stands with the breast-height diameter of the removal (6 12 cm) as the main distinctive factor. The supply chains included in the comparison were based on cut-to-length harvesting, whole-tree harvesting and bundle harvesting (whole-tree bundling). With the current ratio of pulp and energy prices, the wood paying capability declines with an increase in the proportion of the energy fraction of the raw material. The supply system based on the cut-to-length method was the most efficient option, resulting in the highest residual value at stump in most cases. A decline in the pulp price and an increase in the energy price improved the competitiveness of the whole-tree systems. With short truck transportation distances and low pulp prices, however, the harvesting of loose whole trees can result in higher residual value at stump in small-diameter stands. While savings in transportation costs did not compensate for the high cutting and compaction costs by the second prototype of the bundle harvester, an increase in transportation distances improved its competitiveness. Since harvesting undelimbed assortments increases nutrient export from the site, which can affect soil productivity, the whole-tree alternatives included in the present study cannot be recommended on infertile peatlands and mineral soils. The harvesting of loose whole trees or bundled whole trees implies a reduction in protective logging residues and an increase in site traffic or payloads. These factors increase the risk of soil damage, especially on peat soils with poor bearing capacity. Within the wood procurement parameters which were examined, the CO2 emissions of the supply systems varied from 13 27 kg m3. Compaction of whole trees into bundles reduced emissions from transportation by 30 39%, but these reductions were insufficient to compensate for the increased emissions from cutting and compaction.
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This dissertation examines the impacts of energy and climate policies on the energy and forest sectors, focusing on the case of Finland. The thesis consists of an introduction article and four separate studies. The dissertation was motivated by the climate concern and the increasing demand of renewable energy. In particular, the renewable energy consumption and greenhouse gas emission reduction targets of the European Union were driving this work. In Finland, both forest and energy sectors are in key roles in achieving these targets. In fact, the separation between forest and energy sector is diminishing as the energy sector is utilizing increasing amounts of wood in energy production and as the forest sector is becoming more and more important energy producer. The objective of this dissertation is to find out and measure the impacts of climate and energy policies on the forest and energy sectors. In climate policy, the focus is on emissions trading, and in energy policy the dissertation focuses on the promotion of renewable forest-based energy use. The dissertation relies on empirical numerical models that are based on microeconomic theory. Numerical partial equilibrium mixed complementarity problem models were constructed to study the markets under scrutiny. The separate studies focus on co-firing of wood biomass and fossil fuels, liquid biofuel production in the pulp and paper industry, and the impacts of climate policy on the pulp and paper sector. The dissertation shows that the policies promoting wood-based energy may have have unexpected negative impacts. When feed-in tariff is imposed together with emissions trading, in some plants the production of renewable electricity might decrease as the emissions price increases. The dissertation also shows that in liquid biofuel production, investment subsidy may cause high direct policy costs and other negative impacts when compared to other policy instruments. The results of the dissertation also indicate that from the climate mitigation perspective, perfect competition is the favored wood market competition structure, at least if the emissions trading system is not global. In conclusion, this dissertation suggests that when promoting the use of wood biomass in energy production, the favored policy instruments are subsidies that promote directly the renewable energy production (i.e. production subsidy, renewables subsidy or feed-in premium). Also, the policy instrument should be designed to be dependent on the emissions price or on the substitute price. In addition, this dissertation shows that when planning policies to promote wood-based renewable energy, the goals of the policy scheme should be clear before decisions are made on the choice of the policy instruments.
Resumo:
Increasing network lifetime is important in wireless sensor/ad-hoc networks. In this paper, we are concerned with algorithms to increase network lifetime and amount of data delivered during the lifetime by deploying multiple mobile base stations in the sensor network field. Specifically, we allow multiple mobile base stations to be deployed along the periphery of the sensor network field and develop algorithms to dynamically choose the locations of these base stations so as to improve network lifetime. We propose energy efficient low-complexity algorithms to determine the locations of the base stations; they include i) Top-K-max algorithm, ii) maximizing the minimum residual energy (Max-Min-RE) algorithm, and iii) minimizing the residual energy difference (MinDiff-RE) algorithm. We show that the proposed base stations placement algorithms provide increased network lifetimes and amount of data delivered during the network lifetime compared to single base station scenario as well as multiple static base stations scenario, and close to those obtained by solving an integer linear program (ILP) to determine the locations of the mobile base stations. We also investigate the lifetime gain when an energy aware routing protocol is employed along with multiple base stations.
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A geometric invariant is associated to the space of fiat connections on a G-bundle over a compact Riemann surface and is related to the energy of harmonic functions.