886 resultados para Primary energy source uncertainty
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Energy shocks like the Fukushima accident can have important political consequences. This article examines their impact on collaboration patterns between collective actors in policy processes. It argues that external shocks create both behavioral uncertainty, meaning that actors do not know about other actors' preferences, and policy uncertainty on the choice and consequences of policy instruments. The context of uncertainty interacts with classical drivers of actor collaboration in policy processes. The analysis is based on a dataset comprising interview and survey data on political actors in two subsequent policy processes in Switzerland and Exponential Random Graph Models for network data. Results first show that under uncertainty, collaboration of actors in policy processes is less based on similar preferences than in stable contexts, but trust and knowledge of other actors are more important. Second, under uncertainty, scientific actors are not preferred collaboration partners.
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Uncertainty has been found to be a major component of the cancer experience and can dramatically affect psychosocial adaptation and outcomes of a patient's disease state (McCormick, 2002). Patients with a diagnosis of Carcinoma of Unknown Primary (CUP) may experience higher levels of uncertainty due to the unpredictability of current and future symptoms, limited treatment options and an undetermined life expectancy. To date, only one study has touched upon uncertainty and its' effects on those with CUP but no information exists concerning the effects of uncertainty regarding diagnosis and treatment on the distress level and psychosocial adjustment of this population (Parker & Lenzi, 2003). ^ Mishel's Uncertainty in Illness Theory (1984) proposes that uncertainty is preceded by three variables, one of which being Structure Providers. Structure Providers include credible authority, the degree of trust and confidence the patient has with their doctor, education and social support. It was the goal of this study to examine the relationship between uncertainty and Structure Providers to support the following hypotheses: (1) There will be a negative association between credible authority and uncertainty, (2) There will be a negative association between education level and uncertainty, and (3) There will be a negative association between social support and uncertainty. ^ This cross-sectional analysis utilized data from 219 patients following their initial consultation with their oncologist. Data included the Mishel Uncertainty in Illness Scale (MUIS) which was used to determine patients' uncertainty levels, the Medical Outcomes Study-Social Support Scale (MOSS-SSS) to assess patients, levels of social support, the Patient Satisfaction Questionnaire (PSQ-18) and the Cancer Diagnostic Interview Scale (CDIS) to measure credible authority and general demographic information to assess age, education, marital status and ethnicity. ^ In this study we found that uncertainty levels were generally higher in this sample as compared to other types of cancer populations. And while our results seemed to support most of our hypothesis, we were only able to show significant associations between two. The analyses indicated that credible authority measured by both the CDIS and the PSQ was a significant predictor of uncertainty as was social support measured by the MOSS-SS. Education has shown to have an inconsistent pattern of effect in relation to uncertainty and in the current study there was not enough data to significantly support our hypothesis. ^ The results of this study generally support Mishel's Theory of Uncertainty in Illness and highlight the importance of taking into consideration patients, psychosocial factors as well as employing proper communication practices between physicians and their patients.^
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Due to the ongoing effects of climate change, phytoplankton are likely to experience enhanced irradiance, more reduced nitrogen, and increased water acidity in the future ocean. Here, we used Thalassiosira pseudonana as a model organism to examine how phytoplankton adjust energy production and expenditure to cope with these multiple, interrelated environmental factors. Following acclimation to a matrix of irradiance, nitrogen source, and CO2 levels, the diatom's energy production and expenditures were quantified and incorporated into an energetic budget to predict how photosynthesis was affected by growth conditions. Increased light intensity and a shift from inline image to inline image led to increased energy generation, through higher rates of light capture at high light and greater investment in photosynthetic proteins when grown on inline image. Secondary energetic expenditures were adjusted modestly at different culture conditions, except that inline image utilization was systematically reduced by increasing pCO2. The subsequent changes in element stoichiometry, biochemical composition, and release of dissolved organic compounds may have important implications for marine biogeochemical cycles. The predicted effects of changing environmental conditions on photosynthesis, made using an energetic budget, were in good agreement with observations at low light, when energy is clearly limiting, but the energetic budget over-predicts the response to inline image at high light, which might be due to relief of energetic limitations and/or increased percentage of inactive photosystem II at high light. Taken together, our study demonstrates that energetic budgets offered significant insight into the response of phytoplankton energy metabolism to the changing environment and did a reasonable job predicting them.
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We study a cognitive radio scenario in which the network of sec- ondary users wishes to identify which primary user, if any, is trans- mitting. To achieve this, the nodes will rely on some form of location information. In our previous work we proposed two fully distributed algorithms for this task, with and without a pre-detection step, using propagation parameters as the only source of location information. In a real distributed deployment, each node must estimate its own po- sition and/or propagation parameters. Hence, in this work we study the effect of uncertainty, or error in these estimates on the proposed distributed identification algorithms. We show that the pre-detection step significantly increases robustness against uncertainty in nodes' locations.
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This work is related to the improvement of the dynamic performance of the Buck converter by means of introducing an additional power path that virtually increase s the output capacitance during transients, thus improving the output impedance of the converter. It is well known that in VRM applications, with wide load steps, voltage overshoots and undershoots ma y lead to undesired performance of the load. To solve this problem, high-bandwidth high-switching frequency power converter s can be applied to reduce the transient time or a big output capacitor can be applied to reduce the output impedance. The first solution can degrade the efficiency by increasing switching losses of the MOSFETS, and the second solution is penalizing the cost and size of the output filter. The additional energy path, as presented here, is introduced with the Output Impedance Correction Circuit (OICC) based on the Controlled Current Source (CCS). The OICC is using CCS to inject or extract a current n - 1 times larger than the output capacitor current, thus virtually increasing n times the value of the output capacitance during the transients. This feature allows the usage of a low frequency Buck converter with smaller capacitor but satisfying the dynamic requirements.
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Una apropiada evaluación de los márgenes de seguridad de una instalación nuclear, por ejemplo, una central nuclear, tiene en cuenta todas las incertidumbres que afectan a los cálculos de diseño, funcionanmiento y respuesta ante accidentes de dicha instalación. Una fuente de incertidumbre son los datos nucleares, que afectan a los cálculos neutrónicos, de quemado de combustible o activación de materiales. Estos cálculos permiten la evaluación de las funciones respuesta esenciales para el funcionamiento correcto durante operación, y también durante accidente. Ejemplos de esas respuestas son el factor de multiplicación neutrónica o el calor residual después del disparo del reactor. Por tanto, es necesario evaluar el impacto de dichas incertidumbres en estos cálculos. Para poder realizar los cálculos de propagación de incertidumbres, es necesario implementar metodologías que sean capaces de evaluar el impacto de las incertidumbres de estos datos nucleares. Pero también es necesario conocer los datos de incertidumbres disponibles para ser capaces de manejarlos. Actualmente, se están invirtiendo grandes esfuerzos en mejorar la capacidad de analizar, manejar y producir datos de incertidumbres, en especial para isótopos importantes en reactores avanzados. A su vez, nuevos programas/códigos están siendo desarrollados e implementados para poder usar dichos datos y analizar su impacto. Todos estos puntos son parte de los objetivos del proyecto europeo ANDES, el cual ha dado el marco de trabajo para el desarrollo de esta tesis doctoral. Por tanto, primero se ha llevado a cabo una revisión del estado del arte de los datos nucleares y sus incertidumbres, centrándose en los tres tipos de datos: de decaimiento, de rendimientos de fisión y de secciones eficaces. A su vez, se ha realizado una revisión del estado del arte de las metodologías para la propagación de incertidumbre de estos datos nucleares. Dentro del Departamento de Ingeniería Nuclear (DIN) se propuso una metodología para la propagación de incertidumbres en cálculos de evolución isotópica, el Método Híbrido. Esta metodología se ha tomado como punto de partida para esta tesis, implementando y desarrollando dicha metodología, así como extendiendo sus capacidades. Se han analizado sus ventajas, inconvenientes y limitaciones. El Método Híbrido se utiliza en conjunto con el código de evolución isotópica ACAB, y se basa en el muestreo por Monte Carlo de los datos nucleares con incertidumbre. En esta metodología, se presentan diferentes aproximaciones según la estructura de grupos de energía de las secciones eficaces: en un grupo, en un grupo con muestreo correlacionado y en multigrupos. Se han desarrollado diferentes secuencias para usar distintas librerías de datos nucleares almacenadas en diferentes formatos: ENDF-6 (para las librerías evaluadas), COVERX (para las librerías en multigrupos de SCALE) y EAF (para las librerías de activación). Gracias a la revisión del estado del arte de los datos nucleares de los rendimientos de fisión se ha identificado la falta de una información sobre sus incertidumbres, en concreto, de matrices de covarianza completas. Además, visto el renovado interés por parte de la comunidad internacional, a través del grupo de trabajo internacional de cooperación para evaluación de datos nucleares (WPEC) dedicado a la evaluación de las necesidades de mejora de datos nucleares mediante el subgrupo 37 (SG37), se ha llevado a cabo una revisión de las metodologías para generar datos de covarianza. Se ha seleccionando la actualización Bayesiana/GLS para su implementación, y de esta forma, dar una respuesta a dicha falta de matrices completas para rendimientos de fisión. Una vez que el Método Híbrido ha sido implementado, desarrollado y extendido, junto con la capacidad de generar matrices de covarianza completas para los rendimientos de fisión, se han estudiado diferentes aplicaciones nucleares. Primero, se estudia el calor residual tras un pulso de fisión, debido a su importancia para cualquier evento después de la parada/disparo del reactor. Además, se trata de un ejercicio claro para ver la importancia de las incertidumbres de datos de decaimiento y de rendimientos de fisión junto con las nuevas matrices completas de covarianza. Se han estudiado dos ciclos de combustible de reactores avanzados: el de la instalación europea para transmutación industrial (EFIT) y el del reactor rápido de sodio europeo (ESFR), en los cuales se han analizado el impacto de las incertidumbres de los datos nucleares en la composición isotópica, calor residual y radiotoxicidad. Se han utilizado diferentes librerías de datos nucleares en los estudios antreriores, comparando de esta forma el impacto de sus incertidumbres. A su vez, mediante dichos estudios, se han comparando las distintas aproximaciones del Método Híbrido y otras metodologías para la porpagación de incertidumbres de datos nucleares: Total Monte Carlo (TMC), desarrollada en NRG por A.J. Koning y D. Rochman, y NUDUNA, desarrollada en AREVA GmbH por O. Buss y A. Hoefer. Estas comparaciones demostrarán las ventajas del Método Híbrido, además de revelar sus limitaciones y su rango de aplicación. ABSTRACT For an adequate assessment of safety margins of nuclear facilities, e.g. nuclear power plants, it is necessary to consider all possible uncertainties that affect their design, performance and possible accidents. Nuclear data are a source of uncertainty that are involved in neutronics, fuel depletion and activation calculations. These calculations can predict critical response functions during operation and in the event of accident, such as decay heat and neutron multiplication factor. Thus, the impact of nuclear data uncertainties on these response functions needs to be addressed for a proper evaluation of the safety margins. Methodologies for performing uncertainty propagation calculations need to be implemented in order to analyse the impact of nuclear data uncertainties. Nevertheless, it is necessary to understand the current status of nuclear data and their uncertainties, in order to be able to handle this type of data. Great eórts are underway to enhance the European capability to analyse/process/produce covariance data, especially for isotopes which are of importance for advanced reactors. At the same time, new methodologies/codes are being developed and implemented for using and evaluating the impact of uncertainty data. These were the objectives of the European ANDES (Accurate Nuclear Data for nuclear Energy Sustainability) project, which provided a framework for the development of this PhD Thesis. Accordingly, first a review of the state-of-the-art of nuclear data and their uncertainties is conducted, focusing on the three kinds of data: decay, fission yields and cross sections. A review of the current methodologies for propagating nuclear data uncertainties is also performed. The Nuclear Engineering Department of UPM has proposed a methodology for propagating uncertainties in depletion calculations, the Hybrid Method, which has been taken as the starting point of this thesis. This methodology has been implemented, developed and extended, and its advantages, drawbacks and limitations have been analysed. It is used in conjunction with the ACAB depletion code, and is based on Monte Carlo sampling of variables with uncertainties. Different approaches are presented depending on cross section energy-structure: one-group, one-group with correlated sampling and multi-group. Differences and applicability criteria are presented. Sequences have been developed for using different nuclear data libraries in different storing-formats: ENDF-6 (for evaluated libraries) and COVERX (for multi-group libraries of SCALE), as well as EAF format (for activation libraries). A revision of the state-of-the-art of fission yield data shows inconsistencies in uncertainty data, specifically with regard to complete covariance matrices. Furthermore, the international community has expressed a renewed interest in the issue through the Working Party on International Nuclear Data Evaluation Co-operation (WPEC) with the Subgroup (SG37), which is dedicated to assessing the need to have complete nuclear data. This gives rise to this review of the state-of-the-art of methodologies for generating covariance data for fission yields. Bayesian/generalised least square (GLS) updating sequence has been selected and implemented to answer to this need. Once the Hybrid Method has been implemented, developed and extended, along with fission yield covariance generation capability, different applications are studied. The Fission Pulse Decay Heat problem is tackled first because of its importance during events after shutdown and because it is a clean exercise for showing the impact and importance of decay and fission yield data uncertainties in conjunction with the new covariance data. Two fuel cycles of advanced reactors are studied: the European Facility for Industrial Transmutation (EFIT) and the European Sodium Fast Reactor (ESFR), and response function uncertainties such as isotopic composition, decay heat and radiotoxicity are addressed. Different nuclear data libraries are used and compared. These applications serve as frameworks for comparing the different approaches of the Hybrid Method, and also for comparing with other methodologies: Total Monte Carlo (TMC), developed at NRG by A.J. Koning and D. Rochman, and NUDUNA, developed at AREVA GmbH by O. Buss and A. Hoefer. These comparisons reveal the advantages, limitations and the range of application of the Hybrid Method.
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The proline (Pro) concentration increases greatly in the growing region of maize (Zea mays L.) primary roots at low water potentials (ψw), largely as a result of an increased net rate of Pro deposition. Labeled glutamate (Glu), ornithine (Orn), or Pro was supplied specifically to the root tip of intact seedlings in solution culture at high and low ψw to assess the relative importance of Pro synthesis, catabolism, utilization, and transport in root-tip Pro deposition. Labeling with [3H]Glu indicated that Pro synthesis from Glu did not increase substantially at low ψw and accounted for only a small fraction of the Pro deposition. Labeling with [14C]Orn showed that Pro synthesis from Orn also could not be a substantial contributor to Pro deposition. Labeling with [3H]Pro indicated that neither Pro catabolism nor utilization in the root tip was decreased at low ψw. Pro catabolism occurred at least as rapidly as Pro synthesis from Glu. There was, however, an increase in Pro uptake at low ψw, which suggests increased Pro transport. Taken together, the data indicate that increased transport of Pro to the root tip serves as the source of low-ψw-induced Pro accumulation. The possible significance of Pro catabolism in sustaining root growth at low ψw is also discussed.
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This paper assesses the impact of decarbonisation of the energy sector on employment in Europe. Setting the stage for such an assessment, the paper provides an analysis of possible pathways to decarbonise Europe’s energy system, taking into account EU greenhouse gas emissions reduction targets for 2020 and 2050. It pays particular attention to various low-carbon technologies that could be deployed in different regions of the EU. It concludes that efficiency and renewables play a major role in any decarbonisation scenario and that the power sector is the main enabler for the transition to a low-carbon economy in Europe, despite rising electricity demand. The extent of the decline in the share of fossil fuels will largely depend on the existence of carbon capture and storage (CCS), which remains a major source of uncertainty.
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Summary. For more than two decades, the development of renewable energy sources (RES) has been an important aim of EU energy policy. It accelerated with the adoption of a 1997 White Paper and the setting a decade later of a 20% renewable energy target, to be reached by 2020. The EU counts on renewable energy for multiple purposes: to diversify its energy supply; to increase its security of supply; and to create new industries, jobs, economic growth and export opportunities, while at the same time reducing greenhouse gas (GHG) emissions. Many expectations rest on its development. Fossil fuels have been critical to the development of industrial nations, including EU Member States, which are now deeply reliant upon coal, oil and gas for nearly every aspect of their existence. Faced with some hard truths, however, the Member States have begun to shelve fossil fuel. These hard truths are as follows: firstly, fossil fuels are a finite resource, sometimes difficult to extract. This means that, at some point, fossil fuels are going to be more difficult to access in Europe or too expensive to use.1 The problem is that you cannot just stop using fossil fuels when they become too expensive; the existing infrastructure is profoundly reliant on fossil fuels. It is thus almost normal that a fierce resistance to change exists. Secondly, fossil fuels contribute to climate change. They emit GHG, which contribute greatly to climate change. As a consequence, their use needs to be drastically reduced. Thirdly, Member States are currently suffering a decline in their own fossil fuel production. This increases their dependence on increasingly costly fossil fuel imports from increasingly unstable countries. This problem is compounded by global developments: the growing share of emerging economies in global energy demand (in particular China and India but also the Middle East) and the development of unconventional oil and gas production in the United States. All these elements endanger the competitiveness of Member States’ economies and their security of supply. Therefore, new indigenous sources of energy and a diversification of energy suppliers and routes to convey energy need to be found. To solve all these challenges, in 2008 the EU put in place a strategy based on three objectives: sustainability (reduction of GHG), competitiveness and security of supply. The adoption of a renewable energy policy was considered essential for reaching these three strategic objectives. The adoption of the 20% renewable energy target has undeniably had a positive effect in the EU on the growth in renewables, with the result that renewable energy sources are steadily increasing their presence in the EU energy mix. They are now, it can be said, an integral part of the EU energy system. However, the necessity of reaching this 20% renewable energy target in 2020, combined with other circumstances, has also engendered in many Member States a certain number of difficulties, creating uncertainties for investors and postponing benefits for consumers. The electricity sector is the clearest example of this downside. Subsidies have become extremely abundant and vary from one Member State to another, compromising both fair competition and single market. Networks encountered many difficulties to develop and adapt. With technological progress these subsidies have also become quite excessive. The growing impact of renewable electricity fluctuations has made some traditional power plants unprofitable and created disincentives for new investments. The EU does clearly need to reassess its strategy. If it repeats the 2008 measures it will risk to provoke increased instability and costs.
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"November 1978."
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Contrast sensitivity improves with the area of a sine-wave grating, but why? Here we assess this phenomenon against contemporary models involving spatial summation, probability summation, uncertainty, and stochastic noise. Using a two-interval forced-choice procedure we measured contrast sensitivity for circular patches of sine-wave gratings with various diameters that were blocked or interleaved across trials to produce low and high extrinsic uncertainty, respectively. Summation curves were steep initially, becoming shallower thereafter. For the smaller stimuli, sensitivity was slightly worse for the interleaved design than for the blocked design. Neither area nor blocking affected the slope of the psychometric function. We derived model predictions for noisy mechanisms and extrinsic uncertainty that was either low or high. The contrast transducer was either linear (c1.0) or nonlinear (c2.0), and pooling was either linear or a MAX operation. There was either no intrinsic uncertainty, or it was fixed or proportional to stimulus size. Of these 10 canonical models, only the nonlinear transducer with linear pooling (the noisy energy model) described the main forms of the data for both experimental designs. We also show how a cross-correlator can be modified to fit our results and provide a contemporary presentation of the relation between summation and the slope of the psychometric function.
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To fully utilize second-life batteries on the grid system, a hybrid battery scheme needs to be considered for several reasons: the uncertainty over using a single source supply chain for second-life batteries, the differences in evolving battery chemistry and battery configuration by different suppliers to strive for greater power levels, and the uncertainty of degradation within a second-life battery. Therefore, these hybrid battery systems could have widely different module voltage, capacity, and initial state of charge and state of health. In order to suitably integrate and control these widely different batteries, a suitable multimodular converter topology and an associated control structure are required. This paper addresses these issues proposing a modular boost-multilevel buck converter based topology to integrate these hybrid second-life batteries to a grid-tie inverter. Thereafter, a suitable module-based distributed control architecture is introduced to independently utilize each converter module according to its characteristics. The proposed converter and control architecture are found to be flexible enough to integrate widely different batteries to an inverter dc link. Modeling, analysis, and experimental validation are performed on a single-phase modular hybrid battery energy storage system prototype to understand the operation of the control strategy with different hybrid battery configurations.
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Distributed source coding (DSC) has recently been considered as an efficient approach to data compression in wireless sensor networks (WSN). Using this coding method multiple sensor nodes compress their correlated observations without inter-node communications. Therefore energy and bandwidth can be efficiently saved. In this paper, we investigate a randombinning based DSC scheme for remote source estimation in WSN and its performance of estimated signal to distortion ratio (SDR). With the introduction of a detailed power consumption model for wireless sensor communications, we quantitatively analyze the overall network energy consumption of the DSC scheme. We further propose a novel energy-aware transmission protocol for the DSC scheme, which flexibly optimizes the DSC performance in terms of either SDR or energy consumption, by adapting the source coding and transmission parameters to the network conditions. Simulations validate the energy efficiency of the proposed adaptive transmission protocol. © 2007 IEEE.