Embodied energy in cement stabilised rammed earth walls

Rammed earth walls are low carbon emission and energy efficient alternatives to load bearing walls. Large numbers of rammed earth buildings have been constructed in the recent past across the globe. This paper is focused on embodied energy in cement stabilised rammed earth (CSRE) walls. Influence of soil grading, density and cement content on compaction energy input has been monitored. A comparison between energy content of cement and energy in transportation of materials, with that of the actual energy input during rammed earth compaction in the actual field conditions and the laboratory has been made. Major conclusions of the investigations are (a) compaction energy increases with increase in clay fraction of the soil mix and it is sensitive to density of the CSRE wall, (b) compaction energy varies between 0.033 MJ/m(3) and 0.36 MJ/m(3) for the range of densities and cement contents attempted, (c) energy expenditure in the compaction process is negligible when compared to energy content of the cement and (d) total embodied energy in CSRE walls increases linearly with the increase in cement content and is in the range of 0.4-0.5 GJ/m(3) for cement content in the rage of 6-8%. (C) 2009 Elsevier B.V. All rights reserved.

Energy efficiency in India: Assessing the policy regimes and their impacts

In the recent years. India has emerged as one of the fast growing economies of the world necessitating equally rapid increase in modern energy consumption. With an imminent global climate change threat, India will have difficulties in continuing with this rising energy use levels towards achieving high economic growth. It will have to follow an energy-efficient pathway in attaining this goal. In this context, an attempt is made to present India's achievements on the energy efficiency front by tracing the evolution of policies and their impacts. The results indicate that India has made substantial progress in improving energy efficiency which is evident from the reductions achieved in energy intensities of GDP to the tune of 88% during 1980-2007. Similar reductions have been observed both with respect to overall Indian economy and the major sectors of the economy. In terms of energy intensity of GDP, India occupies a relatively high position of nine among the top 30 energy consuming countries of the world. (C) 2009 Elsevier Ltd. All rights reserved.

Dual-Stage Power Management Algorithms for Energy Harvesting Sensors

In this paper, we propose power management algorithms for maximizing the utility of energy harvesting sensors (EHS) that operate purely on the basis of energy harvested from the environment. In particular, we consider communication (i.e., transmission and reception) power management issues for EHS under an energy neutrality constraint. We also consider the fixed power loss effects of the circuitry, the battery inefficiency and its storage capacity, in the design of the algorithms. We propose a two-stage structure that exploits the inherent difference in the timescales at which the energy harvesting and channel fading processes evolve, without loss of optimality of the resulting solution. The outer stage schedules the power that can be used by an inner stage algorithm, so as to maximize the long term average utility and at the same time maintain energy neutrality. The inner stage optimizes the communication parameters to achieve maximum utility in the short-term, subject to the power constraint imposed by the outer stage. We optimize the algorithms for different transmission schemes such as the truncated channel inversion and retransmission strategies. The performance of the algorithms is illustrated via simulations using solar irradiance data, and for the case of Rayleigh fading channels. The results demonstrate the significant performance benefits that can be obtained using the proposed power management algorithms compared to the energy efficient (optimum when there is no storage) and the uniform power consumption (optimum when the battery has infinite capacity and is perfectly efficient) approaches.

Training for Antenna Selection in Time-Varying Channels: Optimal Selection, Energy Allocation, and Energy Efficiency Evaluation

Single receive antenna selection (AS) is a popular method for obtaining diversity benefits without the additional costs of multiple radio receiver chains. Since only one antenna receives at any time, the transmitter sends a pilot multiple times to enable the receiver to estimate the channel gains of its N antennas to the transmitter and select an antenna. In time-varying channels, the channel estimates of different antennas are outdated to different extents. We analyze the symbol error probability (SEP) in time-varying channels of the N-pilot and (N+1)-pilot AS training schemes. In the former, the transmitter sends one pilot for each receive antenna. In the latter, the transmitter sends one additional pilot that helps sample the channel fading process of the selected antenna twice. We present several new results about the SEP, optimal energy allocation across pilots and data, and optimal selection rule in time-varying channels for the two schemes. We show that due to the unique nature of AS, the (N+1)-pilot scheme, despite its longer training duration, is much more energy-efficient than the conventional N-pilot scheme. An extension to a practical scenario where all data symbols of a packet are received by the same antenna is also investigated.

Balanced Excitatory and Inhibitory Synaptic Currents Promote Efficient Coding and Metabolic Efficiency

A balance between excitatory and inhibitory synaptic currents is thought to be important for several aspects of information processing in cortical neurons in vivo, including gain control, bandwidth and receptive field structure. These factors will affect the firing rate of cortical neurons and their reliability, with consequences for their information coding and energy consumption. Yet how balanced synaptic currents contribute to the coding efficiency and energy efficiency of cortical neurons remains unclear. We used single compartment computational models with stochastic voltage-gated ion channels to determine whether synaptic regimes that produce balanced excitatory and inhibitory currents have specific advantages over other input regimes. Specifically, we compared models with only excitatory synaptic inputs to those with equal excitatory and inhibitory conductances, and stronger inhibitory than excitatory conductances (i.e. approximately balanced synaptic currents). Using these models, we show that balanced synaptic currents evoke fewer spikes per second than excitatory inputs alone or equal excitatory and inhibitory conductances. However, spikes evoked by balanced synaptic inputs are more informative (bits/spike), so that spike trains evoked by all three regimes have similar information rates (bits/s). Consequently, because spikes dominate the energy consumption of our computational models, approximately balanced synaptic currents are also more energy efficient than other synaptic regimes. Thus, by producing fewer, more informative spikes approximately balanced synaptic currents in cortical neurons can promote both coding efficiency and energy efficiency.

Consequences of Converting Graded to Action Potentials upon Neural Information Coding and Energy Efficiency

Information is encoded in neural circuits using both graded and action potentials, converting between them within single neurons and successive processing layers. This conversion is accompanied by information loss and a drop in energy efficiency. We investigate the biophysical causes of this loss of information and efficiency by comparing spiking neuron models, containing stochastic voltage-gated Na+ and K+ channels, with generator potential and graded potential models lacking voltage-gated Na+ channels. We identify three causes of information loss in the generator potential that are the by-product of action potential generation: (1) the voltage-gated Na+ channels necessary for action potential generation increase intrinsic noise and (2) introduce non-linearities, and (3) the finite duration of the action potential creates a `footprint' in the generator potential that obscures incoming signals. These three processes reduce information rates by similar to 50% in generator potentials, to similar to 3 times that of spike trains. Both generator potentials and graded potentials consume almost an order of magnitude less energy per second than spike trains. Because of the lower information rates of generator potentials they are substantially less energy efficient than graded potentials. However, both are an order of magnitude more efficient than spike trains due to the higher energy costs and low information content of spikes, emphasizing that there is a two-fold cost of converting analogue to digital; information loss and cost inflation.

Algorithmic challenges in green data centers

With data centers being the supporting infrastructure for a wide range of IT services, their efficiency has become a big concern to operators, as well as to society, for both economic and environmental reasons. The goal of this thesis is to design energy-efficient algorithms that reduce energy cost while minimizing compromise to service. We focus on the algorithmic challenges at different levels of energy optimization across the data center stack. The algorithmic challenge at the device level is to improve the energy efficiency of a single computational device via techniques such as job scheduling and speed scaling. We analyze the common speed scaling algorithms in both the worst-case model and stochastic model to answer some fundamental issues in the design of speed scaling algorithms. The algorithmic challenge at the local data center level is to dynamically allocate resources (e.g., servers) and to dispatch the workload in a data center. We develop an online algorithm to make a data center more power-proportional by dynamically adapting the number of active servers. The algorithmic challenge at the global data center level is to dispatch the workload across multiple data centers, considering the geographical diversity of electricity price, availability of renewable energy, and network propagation delay. We propose algorithms to jointly optimize routing and provisioning in an online manner. Motivated by the above online decision problems, we move on to study a general class of online problem named "smoothed online convex optimization", which seeks to minimize the sum of a sequence of convex functions when "smooth" solutions are preferred. This model allows us to bridge different research communities and help us get a more fundamental understanding of general online decision problems.

Budget-Neutral Financing to Unlock Energy Savings Potential: An Analysis of the ESCO Model in Barcelona

24 p.

Diseño electrónico de una red de comunicaciones para monitorización de estructuras

[ES]El Trabajo Fin de Grado “Diseño electrónico de una red de comunicaciones para monitorización de estructuras” consiste en el desarrollo de un sistema de comunicación orientado al despliegue y gestión de una red con un alto número de sensores para monitorización de estructuras a bordo de una aeronave. El objetivo principal es hacer viable la utilización de dicha red, partiendo de la premisa de crear una alternativa con mayor eficiencia energética que los sistemas actualmente disponibles para tal fin.

Energy demands of diverse spiking cells from the neocortex, hippocampus, and thalamus

It has long been known that neurons in the brain are not physiologically homogeneous. In response to current stimulus, they can fire several distinct patterns of action potentials that are associated with different physiological classes ranging from regular-spiking cells, fast-spiking cells, intrinsically bursting cells, and low-threshold cells. In this work we show that the high degree of variability in firing characteristics of action potentials among these cells is accompanied with a significant variability in the energy demands required to restore the concentration gradients after an action potential. The values of the metabolic energy were calculated for a wide range of cell temperatures and stimulus intensities following two different approaches. The first one is based on the amount of Na+ load crossing the membrane during a single action potential, while the second one focuses on the electrochemical energy functions deduced from the dynamics of the computational neuron models. The results show that the thalamocortical relay neuron is the most energy-efficient cell consuming between 7 and 18 nJ/cm(2) for each spike generated, while both the regular and fast spiking cells from somatosensory cortex and the intrinsically-bursting cell from a cat visual cortex are the least energy-efficient, and can consume up to 100 nJ/cm(2) per spike. The lowest values of these energy demands were achieved at higher temperatures and high external stimuli.

Applying quality control in building energy modelling: Comparative simulation of a high performance building

Quality control is considered from the simulator's perspective through comparative simulation of an ultra energy-efficient building with EE4-DOE2.1E and EnergyPlus. The University of Calgary's Leadership in Energy and Environmental Design Platinum Child Development Centre, with a 66% certified energy cost reduction rating, was the case study building. A Natural Resources Canada incentive program required use of EE4 interface with DOE2.1E simulation engine for energy modelling. As DOE2.1E lacks specific features to simulate advanced systems such as radiant cooling in the CDC, an EnergyPlus model was developed to further evaluate these features. The EE4-DOE2.1E model was used for quality control during development of the base EnergyPlus model and simulation results were compared. Advanced energy systems then added to the EnergyPlus model generated small difference in estimated total annual energy use. The comparative simulation process helped identify the main input errors in the draft EnergyPlus model. The comparative use of less complex simulation programs is recommended for quality control when producing more complex models. © 2009 International Building Performance Simulation Association (IBPSA).

A conceptual framework for future-proofing the energy performance of buildings

This paper presents a review undertaken to understand the concept of 'future-proofing' the energy performance of buildings. The long lifecycles of the building stock, the impacts of climate change and the requirements for low carbon development underline the need for long-term thinking from the early design stages. 'Future-proofing' is an emerging research agenda with currently no widely accepted definition amongst scholars and building professionals. In this paper, it refers to design processes that accommodate explicitly full lifecycle perspectives and energy trends and drivers by at least 2050, when selecting energy efficient measures and low carbon technologies. A knowledge map is introduced, which explores the key axes (or attributes) for achieving a 'future-proofed' energy design; namely, coverage of sustainability issues, lifecycle thinking, and accommodating risks and uncertainties that affect the energy consumption. It is concluded that further research is needed so that established building energy assessment methods are refined to better incorporate future-proofing. The study follows an interdisciplinary approach and is targeted at design teams with aspirations to achieve resilient and flexible low-energy buildings over the long-term. © 2012 Elsevier Ltd.

Heterogeneous reconfigurable system for adaptive particle filters in real-time applications

This paper presents a heterogeneous reconfigurable system for real-time applications applying particle filters. The system consists of an FPGA and a multi-threaded CPU. We propose a method to adapt the number of particles dynamically and utilise the run-time reconfigurability of the FPGA for reduced power and energy consumption. An application is developed which involves simultaneous mobile robot localisation and people tracking. It shows that the proposed adaptive particle filter can reduce up to 99% of computation time. Using run-time reconfiguration, we achieve 34% reduction in idle power and save 26-34% of system energy. Our proposed system is up to 7.39 times faster and 3.65 times more energy efficient than the Intel Xeon X5650 CPU with 12 threads, and 1.3 times faster and 2.13 times more energy efficient than an NVIDIA Tesla C2070 GPU. © 2013 Springer-Verlag.

Energy performance certification as a signal of workplace quality

Energy performance labelling and certification have been introduced widely to address market failures affecting the uptake of energy efficient technologies, by providing a signal to support decision making during contracting processes. The UK has recently introduced the Energy Performance Certificate (EPC) as a signal of building energy performance. The aims of this article are: to evaluate how valid EPC's are signals of occupier satisfaction with office facilities; and to understand whether occupant attitudes towards environmental issues have affected commercial office rental values. This was achieved by surveying occupant satisfaction with their workplaces holistically using a novel multi-item rating scale which gathered 204 responses. Responses to this satisfaction scale were matched with the corresponding EPC and rental value of occupier's workplaces. The satisfaction scale was found to be both a reliable and valid measure. The analysis found that EPC asset rating correlates significantly with occupant satisfaction with all facility attributes. Therefore, EPC ratings may be considered valid signals of overall facility satisfaction within the survey sample. Rental value was found to correlate significantly only with facility aesthetics. No evidence suggests rental value has been affected by occupants' perceptions towards the environmental impact of facilities. © 2013 The Authors.

无线传感器网络中一种启发式最小连通支配集算法

针对最小连通配集问题设计了一种具有较高能量效率的启发式算法。算法首先把网络中所有的节点作为最小连通支配集的一个初始解,然后利用启发式修剪策略剔除冗余节点从而减小最小连通支配集的大小,直到没有冗余节点存在。文中将算法分成集中式和分布式两种情况进行了详细讨论。仿真结果表明,由于实现简便,该算法与其他已有算法相比较,在算法复杂性和算法稳定运行时间上有一定的优势。