853 resultados para Energy consumption survey
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In a system with energy harvesting (EH) nodes, the design focus shifts from minimizing energy consumption by infrequently transmitting less information to making the best use of available energy to efficiently deliver data while adhering to the fundamental energy neutrality constraint. We address the problem of maximizing the throughput of a system consisting of rate-adaptive EH nodes that transmit to a destination. Unlike related literature, we focus on the practically important discrete-rate adaptation model. First, for a single EH node, we propose a discrete-rate adaptation rule and prove its optimality for a general class of stationary and ergodic EH and fading processes. We then study a general system with multiple EH nodes in which one is opportunistically selected to transmit. We first derive a novel and throughput-optimal joint selection and rate adaptation rule (TOJSRA) when the nodes are subject to a weaker average power constraint. We then propose a novel rule for a multi-EH node system that is based on TOJSRA, and we prove its optimality for stationary and ergodic EH and fading processes. We also model the various energy overheads of the EH nodes and characterize their effect on the adaptation policy and the system throughput.
Quick, Decentralized, Energy-Efficient One-Shot Max Function Computation Using Timer-Based Selection
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In several wireless sensor networks, it is of interest to determine the maximum of the sensor readings and identify the sensor responsible for it. We propose a novel, decentralized, scalable, energy-efficient, timer-based, one-shot max function computation (TMC) algorithm. In it, the sensor nodes do not transmit their readings in a centrally pre-defined sequence. Instead, the nodes are grouped into clusters, and computation occurs over two contention stages. First, the nodes in each cluster contend with each other using the timer scheme to transmit their reading to their cluster-heads. Thereafter, the cluster-heads use the timer scheme to transmit the highest sensor reading in their cluster to the fusion node. One new challenge is that the use of the timer scheme leads to collisions, which can make the algorithm fail. We optimize the algorithm to minimize the average time required to determine the maximum subject to a constraint on the probability that it fails to find the maximum. TMC significantly lowers average function computation time, average number of transmissions, and average energy consumption compared to approaches proposed in the literature.
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Minimizing energy consumption is of utmost importance in an energy starved system with relaxed performance requirements. This brief presents a digital energy sensing method that requires neither a constant voltage reference nor a time reference. An energy minimizing loop uses this to find the minimum energy point and sets the supply voltage between 0.2 and 0.5 V. Energy savings up to 1275% over existing minimum energy tracking techniques in the literature is achieved.
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Multicast in wireless sensor networks (WSNs) is an efficient way to spread the same data to multiple sensor nodes. It becomes more effective due to the broadcast nature of wireless link, where a message transmitted from one source is inherently received by all one-hop receivers, and therefore, there is no need to transmit the message one by one. Reliable multicast in WSNs is desirable for critical tasks like code updation and query based data collection. The erroneous nature of wireless medium coupled with limited resource of sensor nodes, makes the design of reliable multicast protocol a challenging task. In this work, we propose a time division multiple access (TDMA) based energy aware media access and control (TEA-MAC) protocol for reliable multicast in WSNs. The TDMA eliminates collisions, overhearing and idle listening, which are the main sources of reliability degradation and energy consumption. Furthermore, the proposed protocol is parametric in the sense that it can be used to trade-off reliability with energy and delay as per the requirement of the underlying applications. The performance of TEA-MAC has been evaluated by simulating it using Castalia network simulator. Simulation results show that TEA-MAC is able to considerably improve the performance of multicast communication in WSNs.
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In this second of the two-part study, the results of the Tank-to-Wheels study reported in the first part are combined with Well-to-Tank results in this paper to provide a comprehensive Well-to-Wheels energy consumption and greenhouse gas emissions evaluation of automotive fuels in India. The results indicate that liquid fuels derived from petroleum have Well-to-Tank efficiencies in the range of 75-85% with liquefied petroleum gas being the most efficient fuel in the Well-to-Tank stage with 85% efficiency. Electricity has the lowest efficiency of 20% which is mainly attributed due to its dependence on coal and 25.4% losses during transmission and distribution. The complete Well-to-Wheels results show diesel vehicles to be the most efficient among all configurations, specifically the diesel-powered split hybrid electric vehicle. Hydrogen engine configurations are the least efficient due to low efficiency of production of hydrogen from natural gas. Hybridizing electric vehicles reduces the Well-to-Wheels greenhouse gas emissions substantially with split hybrid configuration being the most efficient. Electric vehicles do not offer any significant improvement over gasoline-powered configurations; however a shift towards renewable sources for power generation and reduction in losses during transmission and distribution can make it a feasible option in the future. (C) 2015 Elsevier Ltd. All rights reserved.
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Scalable video coding allows an efficient provision of video services at different quality levels with different energy demands. According to the specific type of service and network scenario, end users and/or operators may decide to choose among different energy versus quality combinations. In order to deal with the resulting trade-off, in this paper we analyze the number of video layers that are worth to be received taking into account the energy constraints. A single-objective optimization is proposed based on dynamically selecting the number of layers, which is able to minimize the energy consumption with the constraint of a minimal quality threshold to be reached. However, this approach cannot reflect the fact that the same increment of energy consumption may result in different increments of visual quality. Thus, a multiobjective optimization is proposed and a utility function is defined in order to weight the energy consumption and the visual quality criteria. Finally, since the optimization solving mechanism is computationally expensive to be implemented in mobile devices, a heuristic algorithm is proposed. This way, significant energy consumption reduction will be achieved while keeping reasonable quality levels.
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[EN]The generation of spikes by neurons is energetically a costly process and the evaluation of the metabolic energy required to maintain the signaling activity of neurons a challenge of practical interest. Neuron models are frequently used to represent the dynamics of real neurons but hardly ever to evaluate the electrochemical energy required to maintain that dynamics. This paper discusses the interpretation of a Hodgkin-Huxley circuit as an energy model for real biological neurons and uses it to evaluate the consumption of metabolic energy in the transmission of information between neurons coupled by electrical synapses, i.e., gap junctions. We show that for a single postsynaptic neuron maximum energy efficiency, measured in bits of mutual information per molecule of adenosine triphosphate (ATP) consumed, requires maximum energy consumption. For groups of parallel postsynaptic neurons we determine values of the synaptic conductance at which the energy efficiency of the transmission presents clear maxima at relatively very low values of metabolic energy consumption. Contrary to what could be expected, the best performance occurs at a low energy cost.
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O principal objetivo da tese está relacionado ao tratamento de águas oleosas através da eletrofloculação utilizando corrente alternada de frequência variável, o qual procurou explorar as potencialidades desta técnica. Com a crescente demanda por petróleo e seus derivados, é cada vez maior a produção dessas águas residuárias que, antes de serem descartadas, precisam ser submetidas a tratamento que satisfaçam aos requisitos legais. O trabalho apresentado descreve o levantamento bibliográfico e os resultados dos ensaios realizados, empregando o tratamento de eletrofloculação com a finalidade de remover as substâncias consideradas poluentes presentes nestes efluentes. O processo de eletrofloculação foi testado tanto para o tratamento em corrente continua quanto em corrente alternada de frequência variável em efluentes sintéticos e reais de alta salinidade, contendo teores elevados de óleos e graxas, turbidez e cor. Eficiências de redução de 99% para óleos e graxas, cor e turbidez foram obtidos utilizando eletrodos de alumínio. O processo de eletrofloculação demonstrou-se bastante vantajoso em função da alta condutividade que permite o tratamento com menor consumo energético. A tecnologia de eletrofloculação com corrente alternada quando comparada com a tecnologia de corrente contínua se mostrou muito eficiente em relação a economia no desgaste de massa de eletrodos, o que, dependendo do tempo de aplicação da corrente elétrica nas mesmas condições de estudo, houve redução de mais da metade do consumo.
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Network information theory and channels with memory are two important but difficult frontiers of information theory. In this two-parted dissertation, we study these two areas, each comprising one part. For the first area we study the so-called entropy vectors via finite group theory, and the network codes constructed from finite groups. In particular, we identify the smallest finite group that violates the Ingleton inequality, an inequality respected by all linear network codes, but not satisfied by all entropy vectors. Based on the analysis of this group we generalize it to several families of Ingleton-violating groups, which may be used to design good network codes. Regarding that aspect, we study the network codes constructed with finite groups, and especially show that linear network codes are embedded in the group network codes constructed with these Ingleton-violating families. Furthermore, such codes are strictly more powerful than linear network codes, as they are able to violate the Ingleton inequality while linear network codes cannot. For the second area, we study the impact of memory to the channel capacity through a novel communication system: the energy harvesting channel. Different from traditional communication systems, the transmitter of an energy harvesting channel is powered by an exogenous energy harvesting device and a finite-sized battery. As a consequence, each time the system can only transmit a symbol whose energy consumption is no more than the energy currently available. This new type of power supply introduces an unprecedented input constraint for the channel, which is random, instantaneous, and has memory. Furthermore, naturally, the energy harvesting process is observed causally at the transmitter, but no such information is provided to the receiver. Both of these features pose great challenges for the analysis of the channel capacity. In this work we use techniques from channels with side information, and finite state channels, to obtain lower and upper bounds of the energy harvesting channel. In particular, we study the stationarity and ergodicity conditions of a surrogate channel to compute and optimize the achievable rates for the original channel. In addition, for practical code design of the system we study the pairwise error probabilities of the input sequences.
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468 p.
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Fish bioenergetics models estimate relationships between energy budgets and environmental and physiological variables. This study presents a generic rockfish (Sebastes) bioenergetics model and estimates energy consumption by northern California blue rockf ish (S. mystinus) under average (baseline) and El Niño conditions. Compared to males, female S. mystinus required more energy because they were larger and had greater reproductive costs. When El Niño conditions (warmer temperatures; lower growth, condition, and fecundity) were experienced every 3−7 years, energy consumption decreased on an individual and a per-recruit basis in relation to baseline conditions, but the decrease was minor (<4% at the individual scale, <7% at the per-recruit scale) compared to decreases in female egg production (12−19% at the individual scale, 15−23% at the per-recruit scale). When mortality in per-recruit models was increased by adding fishing, energy consumption in El Niño models grew more similar to that seen in the baseline model. However, egg production decreased significantly — an effect exacerbated by the frequency of El Niño events. Sensitivity analyses showed that energy consumption estimates were most sensitive to respiration parameters, energy density, and female fecundity, and that estimated consumption increased as parameter uncertainty increased. This model provides a means of understanding rockfish trophic ecology in the context of community structure and environmental change by synthesizing metabolic, demographic, and environmental information. Future research should focus on acquiring such information so that models like the bioenergetics model can be used to estimate the effect of climate change, community shifts, and different harvesting strategies on rockfish energy demands.
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Attempts were made to quantify the environmental impacts of the basement walls of two commercial buildings in London. Four different retaining wall options were designed based on steel and concrete systems for each of the sites. It was considered that excavation would take place with the aid of a one or two anchors system. Evaluation of embodied energy (EE) and CO2 emissions for each of the wall designs and anchoring systems were compared. Results show that there are notable differences in EE between different wall designs. Using the averaged set of Embodied Energy Intensity (EEI) values, the use of recycled steel over virgin steel would reduce the EE of the wall significantly. The difference in anchor designs is relatively insignificant, and therefore the practicality of the design for the specific site should be the deciding factor for anchor types. Generally, the scale of environmental impacts due to constructions is large compared to other aspects in life as demonstrated with the comparisons to car emissions and household energy consumption. Copyright ASCE 2008.
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A mathematical model is developed to predict the energy consumption of a heavy vehicle. It includes the important factors of heavy-vehicle energy consumption, namely engine and drivetrain performances, losses due to accessories, aerodynamic drag, rolling resistance, road gradients, and driver behaviour. Novel low-cost testing methods were developed to determine engine and drivetrain characteristics. A simple drive cycle was used to validate the model. The model is able to predict the fuel use for a 371 tractor-semitrailer vehicle over a 4 km drive cycle within 1 per cent. This paper demonstrates that accurate and reliable vehicle benchmarking and model parameter measurement can be achieved without expensive equipment overheads, e.g. engine and chassis dynamometers.
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The embodied energy (EE) and gas emissions of four design alternatives for an embankment retaining wall system are analyzed for a hypothetical highway construction project. The airborne emissions considered are carbon dioxide (CO 2), methane (CH 4), nitrous oxide (N 2O), sulphur oxides (SO X), and nitrogen oxides (NO X). The process stages considered in this study are the initial materials production, transportation of construction machineries and materials, machinery operation during installation, and machinery depreciations. The objectives are (1) to determine whether there are statistically significant differences among the structural alternatives; (2) to understand the relative proportions of impacts for the process stages within each design; (3) to contextualize the impacts to other aspects in life by comparing the computed EE values to household energy consumption and car emission values; and (4) to examine the validity of the adopted EE as an environmental impact indicator through comparison with the amount of gas emissions. For the project considered in this study, the calculated results indicate that propped steel sheet pile wall and minipile wall systems have less embodied energy and gas emissions than cantilever steel tubular wall and secant concrete pile wall systems. The difference in CO 2 emission for the retaining wall of 100 m length between the most and least environmentally preferable wall design is equivalent to an average 2.0 L family car being driven for 6.2 million miles (or 62 cars with a mileage of 10,000 miles/year for 10 years). The impacts in construction are generally notable and careful consideration and optimization of designs will reduce such impacts. The use of recycled steel or steel pile as reinforcement bar is effective in reducing the environmental impact. The embodied energy value of a given design is correlated to the amount of gas emissions. © 2011 American Society of Civil Engineers.
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Reducing energy consumption is a major challenge for "energy-intensive" industries such as papermaking. A commercially viable energy saving solution is to employ data-based optimization techniques to obtain a set of "optimized" operational settings that satisfy certain performance indices. The difficulties of this are: 1) the problems of this type are inherently multicriteria in the sense that improving one performance index might result in compromising the other important measures; 2) practical systems often exhibit unknown complex dynamics and several interconnections which make the modeling task difficult; and 3) as the models are acquired from the existing historical data, they are valid only locally and extrapolations incorporate risk of increasing process variability. To overcome these difficulties, this paper presents a new decision support system for robust multiobjective optimization of interconnected processes. The plant is first divided into serially connected units to model the process, product quality, energy consumption, and corresponding uncertainty measures. Then multiobjective gradient descent algorithm is used to solve the problem in line with user's preference information. Finally, the optimization results are visualized for analysis and decision making. In practice, if further iterations of the optimization algorithm are considered, validity of the local models must be checked prior to proceeding to further iterations. The method is implemented by a MATLAB-based interactive tool DataExplorer supporting a range of data analysis, modeling, and multiobjective optimization techniques. The proposed approach was tested in two U.K.-based commercial paper mills where the aim was reducing steam consumption and increasing productivity while maintaining the product quality by optimization of vacuum pressures in forming and press sections. The experimental results demonstrate the effectiveness of the method.