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Storage capacity is a key aspect when validating potential CO2 sequestration sites. Most CO2 storage projects, for obvious reasons, target conventional aquifers (e.g., saline aquifers, depleted hydrocarbon fields) with good reservoir properties and ample subsurface data. However, non-geological factors, such as proximity to the CO2 source, may require storing CO2 in geologically “less-than-ideal” sites. We here present a first-order CO2 storage resource estimate of such an unconventional storage unit, a naturally fractured, compartmentalized and underpressured siliciclastic aquifer located at 670–1,000 m below Longyearbyen, Arctic Norway. Water injection tests confirm the injectivity of the reservoir. Capacity calculations, based on the US DOE guidelines for CO2 storage resource estimation, were implemented in a stochastic volumetric workflow. All available data were used to specify input parameters and their probability distributions. The areal extent of the compartmentalized reservoir is poorly constrained, encouraging a scenario-based approach. Other high-impact parameters influencing storage resource estimates include CO2 saturation, CO2 density and the storage efficiency factor. The hydrodynamic effects of storing CO2 in a compartmentalized aquifer are accounted for by calculating probable storage efficiency factors (0.04–0.79 %) in a fully closed system. The results are ultimately linked to the chosen scenario, with two orders of magnitude difference between scenarios. The fracture network contributes with up to 2 % to the final volumes. The derived workflow validates CO2 storage sites based on initial feasibility assessments, and may be applied to aid decision making at other unconventional CO2 storage sites with significant data uncertainty.

Artículos en revistas No disponible / Not available info:eu-repo/semantics/publishedVersion

Electronic engine controls based on real time diagnosis of combustion process can significantly help incompling with the stricter and stricter regulations on pollutants emissions and fuel consumption.Themost important parameter for hee valuation of combustion quality in internal combustion engine sisthein-cylinder pressure, butits direct measurement is very expensive and involves an intrusive approach to the cylinder.Previous researches demonstrated the direct relationship existing between in-cylinder pressure and engine crankshaft speed and several authors triedtore construct the pressure cycle on the basis of the engine speed signal. In this paper we propose the use of a Multi-Layer Percept ronneural network to model the relationship between the engine crank shaft speed and some parameters derived from the in-cylinder pressure cycle.This allows to have an on-intrusive estimation of cylinder pressure and are altime evaluation of combustion quality. Thestructureofthemodel and thetrainingprocedureisoutlinedinthepaper.Apossiblecombustioncontroller usingtheinformationextractedfromthecrankshaftspeedinformationisalsoproposed. The application of the neural network model is demonstrated on a single-cylinder spark ignition engine tested in a wider ange of speeds and loads.Results confirm tha ta good estimation of some combustion pressure parameters can be obtained by means of a suitable processing of crank shaft speed signal.

Most households in sub-Saharan Africa rely on wood-based cooking fuels and their number is expected to rise. Despite this, national and subnational energy policies often neglect biomass cooking fuels. A Formative Scenario Analysis process is applied to show how the cooking fuel sector in Kilimanjaro Region (Tanzania) and Kitui County (Kenya) might evolve by 2030. In order to provide relevant knowledge for potential energy policies, this paper aims to identify the main drivers impacting the cooking fuel sector, and to assess and explore current and future demand and supply potential of biomass cooking fuels. Our results show that policies have the potential to substantially impact the future mix of cooking fuels and to foster or hamper the use of efficient cooking fuel technologies. Half of Kilimanjaro Region’s households could be supplied with biogas; in Kitui County, wood-based cooking fuels is likely to remain dominant but improving the efficiency of the technologies would reduce the demand for wood considerably. Hence, we argue that energy policies should explicitly consider biomass cooking fuels and endeavour to make this sector more sustainable and that priority should be given to increasing the sustainability of the biomass cooking fuel sector. Key leverage points to do so are improving the access to improved biomass technologies and capacity building.

The particle flowpattern and granule segregation in tapered fluidized beds have been studied using two techniques. The first technique is to fluidize beds of varying total mass and granule fractions, then defluidize them suddenly to "freeze" the composition, section the bed in layers, and determine the composition of each layer by sieving. The second technique is to track a radioactive particle mimicking a granule as it moves in the bed. The results show that the segregation behaviour of granules is complex, their behaviour changing from flotsam at low granule concentrations to slightly jetsam at higher concentrations. The flow in the tapered bed is very different from what is expected based on relations derived for cylindrical beds. In the tapered bed a central region of high bubble activity and upward flow was a dominant feature. This "gulf streaming" became more pronounced as the total bed mass, and therefore the bed height, was increased, resulting in a bed turn-over time almost independent of the total bed mass. Quantitative data are given for upward and downward particle velocities and flows, bed turnover times, and axial granule concentration profiles. (c) 2006 Elsevier Ltd. All rights reserved.

Gasoline direct injection (GDI) combustion with un-throttled lean stratified operation allows to reduce engine toxic emissions and achieve significant benefits in terms of fuel consumption. However, use of gasoline stratified charges can lead to several problems, such as a high cycle-to-cycle variability and increased particle emissions. Use of multiple injection strategies allows to mitigate these problems, but it requires the injection of small fuel amounts forcing the traditional solenoid injectors to work in their "ballistic" region, where the correlation between coil energizing time and injected fuel amount becomes highly not linear. In the present work a closed-loop control system able to manage the delivery of small quantities of fuel has been introduced. The control system is based on a particular feature found on the coil voltage command signal during the de-energizing phase. On the basis of this feature, the injector needle closing time and then, in turn, the actual amount of fuel injected can be calculated. Results showed that the proposed control system, through a proper management of ballistic injections, has the potential to increase the minimum fuel injection capabilities of GDI solenoid injectors.

Artículos en revistas The electricity consumption in the buildings sector has been steadily increasing during the last decade, up to the point that energy efficiency in this sector has become a major problem for governments, utilities, customers, and the environment. The foreseen high penetration of distributed micro-generation facilities based on renewables can help to reduce the environmental footprint of buildings and households, although the complexity of managing effectively the electric grid increases dramatically under these conditions. The IEEE 2030 standard for interoperability in the Smart Grid remarks upon the importance of well-defined data models in such complex scenarios and puts emphasis on the benefits of ontologies and OWL (Web Ontology Language) for this purpose. This paper presents an OWL-based ontology that formally defines the vocabulary and taxonomy and captures the engineering and business semantics of this domain of knowledge (i.e., energy efficiency in the so-called nZEN - nearly Zero-Energy Neighborhoods). This ontology has been defined under the scope of the EU (European Union) research project ENERsip. The paper also highlights the main benefits the ontology brought to all the phases of the project life cycle, as well as how future work can make the most out of it. info:eu-repo/semantics/publishedVersion

This paper estimates the level of transient and persistent efficiency in the use of electricity in Swiss households using the newly developed generalized true random effects model (GTREM). An unbalanced panel dataset of 1994 Swiss households from 2010 to 2014 collected via a household survey is used to estimate an electricity demand frontier function. We further investigate whether energy and investment literacy have an influence on the household electricity consumption. The results show significant inefficiencies in the use of electricity among Swiss households, both transient (11%) and persistent (22%). We note that the high persistent inefficiency is indicative of structural problems faced by households and systematic behavioral shortcomings in residential electricity consumption. These results indicate a considerable potential for electricity savings and thus reaching the reduction targets defined by the Swiss federal council as part of the Energy Strategy 2050, wherein end-use efficiency improvement is one of the main pillars. The results support a positive role of energy and, in particular, investment literacy in reducing household electricity consumption. Policies targeting an improvement of these attributes could help to enhance efficiency in the use of energy within households.