79 resultados para Energy consumption -- Computer simulation


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Automatic cost analysis of programs has been traditionally concentrated on a reduced number of resources such as execution steps, time, or memory. However, the increasing relevance of analysis applications such as static debugging and/or certiflcation of user-level properties (including for mobile code) makes it interesting to develop analyses for resource notions that are actually application-dependent. This may include, for example, bytes sent or received by an application, number of files left open, number of SMSs sent or received, number of accesses to a datábase, money spent, energy consumption, etc. We present a fully automated analysis for inferring upper bounds on the usage that a Java bytecode program makes of a set of application programmer-deflnable resources. In our context, a resource is defined by programmer-provided annotations which state the basic consumption that certain program elements make of that resource. From these deflnitions our analysis derives functions which return an upper bound on the usage that the whole program (and individual blocks) make of that resource for any given set of input data sizes. The analysis proposed is independent of the particular resource. We also present some experimental results from a prototype implementation of the approach covering a signiflcant set of interesting resources.

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Energy consumption in data centers is nowadays a critical objective because of its dramatic environmental and economic impact. Over the last years, several approaches have been proposed to tackle the energy/cost optimization problem, but most of them have failed on providing an analytical model to target both the static and dynamic optimization domains for complex heterogeneous data centers. This paper proposes and solves an optimization problem for the energy-driven configuration of a heterogeneous data center. It also advances in the proposition of a new mechanism for task allocation and distribution of workload. The combination of both approaches outperforms previous published results in the field of energy minimization in heterogeneous data centers and scopes a promising area of research.

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In recent future, wireless sensor networks ({WSNs}) will experience a broad high-scale deployment (millions of nodes in the national area) with multiple information sources per node, and with very specific requirements for signal processing. In parallel, the broad range deployment of {WSNs} facilitates the definition and execution of ambitious studies, with a large input data set and high computational complexity. These computation resources, very often heterogeneous and driven on-demand, can only be satisfied by high-performance Data Centers ({DCs}). The high economical and environmental impact of the energy consumption in {DCs} requires aggressive energy optimization policies. These policies have been already detected but not successfully proposed. In this context, this paper shows the following on-going research lines and obtained results. In the field of {WSNs}: energy optimization in the processing nodes from different abstraction levels, including reconfigurable application specific architectures, efficient customization of the memory hierarchy, energy-aware management of the wireless interface, and design automation for signal processing applications. In the field of {DCs}: energy-optimal workload assignment policies in heterogeneous {DCs}, resource management policies with energy consciousness, and efficient cooling mechanisms that will cooperate in the minimization of the electricity bill of the DCs that process the data provided by the WSNs.

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Irradiation with swift heavy ions (SHI), roughly defined as those having atomic masses larger than 15 and energies exceeding 1 MeV/amu, may lead to significant modification of the irradiated material in a nanometric region around the (straight) ion trajectory (latent tracks). In the case of amorphous silica, SHI irradiation originates nano-tracks of higher density than the virgin material (densification). As a result, the refractive index is increased with respect to that of the surroundings. Moreover, track overlapping leads to continuous amorphous layers that present a significant contrast with respect to the pristine substrate. We have recently demonstrated that SHI irradiation produces a large number of point defects, easily detectable by a number of experimental techniques (work presented in the parallel conference ICDIM). The mechanisms of energy transfer from SHI to the target material have their origin in the high electronic excitation induced in the solid. A number of phenomenological approaches have been employed to describe these mechanisms: coulomb explosion, thermal spike, non-radiative exciton decay, bond weakening. However, a detailed microscopic description is missing due to the difficulty of modeling the time evolution of the electronic excitation. In this work we have employed molecular dynamics (MD) calculations to determine whether the irradiation effects are related to the thermal phenomena described by MD (in the ps domain) or to electronic phenomena (sub-ps domain), e.g., exciton localization. We have carried out simulations of up to 100 ps with large boxes (30x30x8 nm3) using a home-modified version of MDCASK that allows us to define a central hot cylinder (ion track) from which heat flows to the surrounding cold bath (unirradiated sample). We observed that once the cylinder has cooled down, the Si and O coordination numbers are 4 and 2, respectively, as in virgin silica. On the other hand, the density of the (cold) cylinder increases with respect to that of silica and, furthermore, the silica network ring size decreases. Both effects are in agreement with the observed densification. In conclusion, purely thermal effects do not explain the generation of point defects upon irradiation, but they do account for the silica densification.

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Kinetic Monte Carlo (KMC) is a widely used technique to simulate the evolution of radiation damage inside solids. Despite de fact that this technique was developed several decades ago, there is not an established and easy to access simulating tool for researchers interested in this field, unlike in the case of molecular dynamics or density functional theory calculations. In fact, scientists must develop their own tools or use unmaintained ones in order to perform these types of simulations. To fulfil this need, we have developed MMonCa, the Modular Monte Carlo simulator. MMonCa has been developed using professional C++ programming techniques and has been built on top of an interpreted language to allow having a powerful yet flexible, robust but customizable and easy to access modern simulator. Both non lattice and Lattice KMC modules have been developed. We will present in this conference, for the first time, the MMonCa simulator. Along with other (more detailed) contributions in this meeting, the versatility of MMonCa to study a number of problems in different materials (particularly, Fe and W) subject to a wide range of conditions will be shown. Regarding KMC simulations, we have studied neutron-generated cascade evolution in Fe (as a model material). Starting with a Frenkel pair distribution we have followed the defect evolution up to 450 K. Comparison with previous simulations and experiments shows excellent agreement. Furthermore, we have studied a more complex system (He-irradiated W:C) using a previous parametrization [1]. He-irradiation at 4 K followed by isochronal annealing steps up to 500 K has been simulated with MMonCa. The He energy was 400 eV or 3 keV. In the first case, no damage is associated to the He implantation, whereas in the second one, a significant Frenkel pair concentration (evolving into complex clusters) is associated to the He ions. We have been able to explain He desorption both in the absence and in the presence of Frenkel pairs and we have also applied MMonCa to high He doses and fluxes at elevated temperatures. He migration and trapping dominate the kinetics of He desorption. These processes will be discussed and compared to experimental results. [1] C.S. Becquart et al. J. Nucl. Mater. 403 (2010) 75

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Helium retention in irradiated tungsten leads to swelling, pore formation, sample exfoliation and embrittlement with deleterious consequences in many applications. In particular, the use of tungsten in future nuclear fusion plants is proposed due to its good refractory properties. However, serious concerns about tungsten survivability stems from the fact that it must withstand severe irradiation conditions. In magnetic fusion as well as in inertial fusion (particularly with direct drive targets), tungsten components will be exposed to low and high energy ion (helium) irradiation, respectively. A common feature is that the most detrimental situations will take place in pulsed mode, i.e., high flux irradiation. There is increasing evidence on a correlation between a high helium flux and an enhancement of detrimental effects on tungsten. Nevertheless, the nature of these effects is not well understood due to the subtleties imposed by the exact temperature profile evolution, ion energy, pulse duration, existence of impurities and simultaneous irradiation with other species. Physically based Kinetic Monte Carlo is the technique of choice to simulate the evolution of radiation-induced damage inside solids in large temporal and space scales. We have used the recently developed code MMonCa (Modular Monte Carlo simulator), presented in this conference for the first time, to study He retention (and in general defect evolution) in tungsten samples irradiated with high intensity helium pulses. The code simulates the interactions among a large variety of defects and impurities (He and C) during the irradiation stage and the subsequent annealing steps. In addition, it allows us to vary the sample temperature to follow the severe thermo-mechanical effects of the pulses. In this work we will describe the helium kinetics for different irradiation conditions. A competition is established between fast helium cluster migration and trapping at large defects, being the temperature a determinant factor. In fact, high temperatures (induced by the pulses) are responsible for large vacancy cluster formation and subsequent additional trapping with respect to low flux irradiation.

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Polysilicon cost impacts significantly on the photovoltaics (PV) cost and on the energy payback time. Nowadays, the besetting production process is the so called Siemens process, polysilicon deposition by chemical vapor deposition (CVD) from Trichlorosilane. Polysilicon purification level for PV is to a certain extent less demanding that for microelectronics. At the Instituto de Energía Solar (IES) research on this subject is performed through a Siemens process-type laboratory reactor. Through the laboratory CVD prototype at the IES laboratories, valuable information about the phenomena involved in the polysilicon deposition process and the operating conditions is obtained. Polysilicon deposition by CVD is a complex process due to the big number of parameters involved. A study on the influence of temperature and inlet gas mixture composition on the polysilicon deposition growth rate, based on experimental experience, is shown. Moreover, CVD process accounts for the largest contribution to the energy consumption of the polysilicon production. In addition, radiation phenomenon is the major responsible for low energetic efficiency of the whole process. This work presents a model of radiation heat loss, and the theoretical calculations are confirmed experimentally through a prototype reactor at our disposal, yielding a valuable know-how for energy consumption reduction at industrial Siemens reactors.

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Young trees transplanted from nursery into open field require a minimum amount of soil moisture to successfully root in their new location, especially in dry-climate areas. One possibility is to obtain the required water from air moisture. This can be achieved by reducing the temperature of a surface below the air dew point temperature, inducing water vapor condensation on the surface. The temperature of a surface can be reduced by applying the thermoelectric effect, with Peltier modules powered by electricity. Here, we present a system that generates electricity with a solar photovoltaic module, stores it in a battery, and finally, uses the electricity at the moment in which air humidity and temperature are optimal to maximize water condensation while minimizing energy consumption. Also, a method to reduce the evaporation of the condensed water is proposed. The objective of the system is to sustain young plants in drier periods, rather than exclusively irrigating young plants to boost their growth.

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Con la finalidad de ayudar a la creación y desarrollo de modelos de predicción y simulación que permitan al ciudadano/administraciones publicas gestionar el consumo energético de forma más eficiente y respetuosa con el medio ambiente, se ha implementado un sistema de gestión de datos de indicadores energéticos. En 2007 la UE creó una directiva conocida como "20/20/20" en la que la Unión Europea se compromete a ahorrar un 20% del consumo anual de energía primaria desde esa fecha a 2020. En 2009 la Comisión Europea ha llegado a la conclusión de que con las medidas propuestas en dicha directiva no se podría alcanzar el objetivo de reducción del 20% del consumo energético previsto para el 2020, quedándose en menos de la mitad. Para dar un nuevo impulso a la eficiencia energética se redacta una propuesta de directiva: 2011/0172(COD). En esta directiva se obliga a los estados miembros a potenciar y ampliar la información estadística agregada sobre sus clientes finales (los perfiles de carga, la segmentación de los clientes, su ubicación geográfica, etc ). La Unión Europea plantea que incrementar el volumen y la accesibilidad de los datos de consumo energético, ayudará de forma significativa a alcanzar los objetivos. En este marco, parece lógico afirmar que un banco de datos de indicadores energéticos universalmente accesible puede contribuir de un modo efectivo al aumento de la eficiencia energética. Como aplicativo de este PFC se ha desarrollado una aplicación que permite la definición y almacenamiento de indicadores energéticos, en la que los diferentes sistemas, propietarios o abiertos, pueden volcar y extraer datos de una forma poco costosa. Se ha pretendido realizar una aplicación lo más abierta posible, tanto desde el punto de vista de la funcionalidad, permitiendo la definición del propio indicador a través del sistema, como desde el punto de vista de la implementación, usando únicamente código abierto para el desarrollo de la misma. ABSTRACT. In order to assist in the creation and development of forecasting and simulation models that enable citizens / public authorities manage energy consumption more efficient and environmentally friendly, we have implemented a data management system of energy indicators. In 2007 the EU created a policy known as " 20/20/20 " in which the European Union is committed to saving 20 % of the annual primary energy consumption from that date to 2020 . In 2009 the European Commission has concluded that the measures proposed in the directive could not achieve the goal of 20% reduction in energy consumption expected for 2020 , staying in less than half. To give new impetus to energy efficiency is drawn up a draft directive : 2011/0172 ( COD ) . This directive obliges member states to strengthen and expand aggregate statistical information on their final customers ( load profiles , customer segmentation , geographic location, etc. ) . The European Union argues that increasing the volume and accessibility ofenergy data , will significantly help to achieve the objectives . In this context , it seems logical to say that a database of universally accessible energy indicators can contribute in an effective way to increase energy efficiency. As of this PFC application has developed an application that allows the definition and storage of energy indicators , in which different systems, proprietary or open, can tip and extract data from an inexpensive way. We have tried to make an application as open as possible , both from the point of view of functionality , allowing the definition of the indicator itself through the system , and from the point of view of implementation, using only open source development thereof.

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High-Performance Computing, Cloud computing and next-generation applications such e-Health or Smart Cities have dramatically increased the computational demand of Data Centers. The huge energy consumption, increasing levels of CO2 and the economic costs of these facilities represent a challenge for industry and researchers alike. Recent research trends propose the usage of holistic optimization techniques to jointly minimize Data Center computational and cooling costs from a multilevel perspective. This paper presents an analysis on the parameters needed to integrate the Data Center in a holistic optimization framework and leverages the usage of Cyber-Physical systems to gather workload, server and environmental data via software techniques and by deploying a non-intrusive Wireless Sensor Net- work (WSN). This solution tackles data sampling, retrieval and storage from a reconfigurable perspective, reducing the amount of data generated for optimization by a 68% without information loss, doubling the lifetime of the WSN nodes and allowing runtime energy minimization techniques in a real scenario.

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Reducing the energy consumption for computation and cooling in servers is a major challenge considering the data center energy costs today. To ensure energy-efficient operation of servers in data centers, the relationship among computa- tional power, temperature, leakage, and cooling power needs to be analyzed. By means of an innovative setup that enables monitoring and controlling the computing and cooling power consumption separately on a commercial enterprise server, this paper studies temperature-leakage-energy tradeoffs, obtaining an empirical model for the leakage component. Using this model, we design a controller that continuously seeks and settles at the optimal fan speed to minimize the energy consumption for a given workload. We run a customized dynamic load-synthesis tool to stress the system. Our proposed cooling controller achieves up to 9% energy savings and 30W reduction in peak power in comparison to the default cooling control scheme.

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Governments are working in new policies to slow down total energy consumption and greenhouse gases (GHG) emissions, promoting the deployment of electric vehicles (EVs) in all countries. In order to facilitate this deployment and help to reduce the final costs of their batteries, additional utilization of EVs when those are parked has been proposed. EVs can be used to minimize the total electricity cost of buildings (named vehicle to building applications, V2B). In this paper an economic evaluation of EVs in the Building Energy Management System is shown. The optimal storage capacity and its equivalent number of EVs are determined. This value is then used for determining the optimal charging schedule to be applied to the batteries. From this schedule, the total expected profit is derived for the case of a real hotel in Spain.

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The Smartcity Málaga project is one of Europe?s largest ecoefficient city initiatives. The project has implemented a field trial in 50 households to study the effects of energy monitoring and management technologies on the residential electricity consumption. This poster presents some lessons learned on energy consumption trends, smart clamps reliability and the suitability of power contracted by users, obtained after six months of data analysis.

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The first step in order to comply with the European Union goals of Near to Zero Energy Buildings is to reduce the energy consumption in buildings. Most of the building consumption is related to the use of active systems to maintain the interior comfort. Passive design strategies contribute to improve the interior comfort conditions, increasing the energy efficiency in buildings and reducing their energy consumption. In this work, an analysis of the passive strategies used in Net Energy Plus Houses has been made. The participating houses of the Solar Decathlon Europe 2012 competition were used as case studies. The passive design strategies of these houses were compared with the annual simulations, and the competition monitored data, especially during the Passive Monitored Period. The analysis included the thermal properties of the building envelope, geometric parameters, ratios and others passive solutions such as Thermal Energy Storage systems, evaporative cooling, night ventilation, solar gains and night sky radiation cooling. The results reflect the impact of passive design strategies on the houses' comfort and efficiency, as well as their influence in helping to achieve the Zero Energy Buildings category.

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The uncertainty associated to the forecast of photovoltaic generation is a major drawback for the widespread introduction of this technology into electricity grids. This uncertainty is a challenge in the design and operation of electrical systems that include photovoltaic generation. Demand-Side Management (DSM) techniques are widely used to modify energy consumption. If local photovoltaic generation is available, DSM techniques can use generation forecast to schedule the local consumption. On the other hand, local storage systems can be used to separate electricity availability from instantaneous generation; therefore, the effects of forecast error in the electrical system are reduced. The effects of uncertainty associated to the forecast of photovoltaic generation in a residential electrical system equipped with DSM techniques and a local storage system are analyzed in this paper. The study has been performed in a solar house that is able to displace a residential user?s load pattern, manage local storage and estimate forecasts of electricity generation. A series of real experiments and simulations have carried out on the house. The results of this experiments show that the use of Demand Side Management (DSM) and local storage reduces to 2% the uncertainty on the energy exchanged with the grid. In the case that the photovoltaic system would operate as a pure electricity generator feeding all generated electricity into grid, the uncertainty would raise to around 40%.