5 resultados para Forecasts

em Universidade Federal do Rio Grande do Norte(UFRN)


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The world has many types of oil that have a range of values of density and viscosity, these are characteristics to identify whether an oil is light, heavy or even ultraheavy. The occurrence of heavy oil has increased significantly and pointing to a need for greater investment in the exploitation of deposits and therefore new methods to recover that oil. There are economic forecasts that by 2025, the heavy oil will be the main source of fossil energy in the world. One such method is the use of solvent vaporized VAPEX which is known as a recovery method which consists of two horizontal wells parallel to each other, with a gun and another producer, which uses as an injection solvent that is vaporized in order to reduce the viscosity of oil or bitumen, facilitating the flow to the producing well. This method was proposed by Dr. Roger Butler, in 1991. The importance of this study is to analyze how the influence some operational reservoir and parameters are important in the process VAPEX, such as accumulation of oil produced in the recovery factor in flow injection and production rate. Parameters such as flow injection, spacing between wells, type of solvent to be injected, vertical permeability and oil viscosity were addressed in this study. The results showed that the oil viscosity is the parameter that showed statistically significant influence, then the choice of Heptane solvent to be injected showed a greater recovery of oil compared to other solvents chosen, considering the spacing between the wells was shown that for a greater distance between the wells to produce more oil

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The increase in ultraviolet radiation (UV) at surface, the high incidence of non-melanoma skin cancer (NMSC) in coast of Northeast of Brazil (NEB) and reduction of total ozone were the motivation for the present study. The overall objective was to identify and understand the variability of UV or Index Ultraviolet Radiation (UV Index) in the capitals of the east coast of the NEB and adjust stochastic models to time series of UV index aiming make predictions (interpolations) and forecasts / projections (extrapolations) followed by trend analysis. The methodology consisted of applying multivariate analysis (principal component analysis and cluster analysis), Predictive Mean Matching method for filling gaps in the data, autoregressive distributed lag (ADL) and Mann-Kendal. The modeling via the ADL consisted of parameter estimation, diagnostics, residuals analysis and evaluation of the quality of the predictions and forecasts via mean squared error and Pearson correlation coefficient. The research results indicated that the annual variability of UV in the capital of Rio Grande do Norte (Natal) has a feature in the months of September and October that consisting of a stabilization / reduction of UV index because of the greater annual concentration total ozone. The increased amount of aerosol during this period contributes in lesser intensity for this event. The increased amount of aerosol during this period contributes in lesser intensity for this event. The application of cluster analysis on the east coast of the NEB showed that this event also occurs in the capitals of Paraiba (João Pessoa) and Pernambuco (Recife). Extreme events of UV in NEB were analyzed from the city of Natal and were associated with absence of cloud cover and levels below the annual average of total ozone and did not occurring in the entire region because of the uneven spatial distribution of these variables. The ADL (4, 1) model, adjusted with data of the UV index and total ozone to period 2001-2012 made a the projection / extrapolation for the next 30 years (2013-2043) indicating in end of that period an increase to the UV index of one unit (approximately), case total ozone maintain the downward trend observed in study period

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The increasing demand for energy and the environment consequences derived from the use of fossil energy, beyond the future scarcity of the oil that currently is the main power plant of the world, it stimulated the research around the production of biodiesel. In this work the synthesis of biodiesel of cotton in the methyl route was carried through, for had been in such a way used catalyst commercial homogeneous, Na-Methylat and the K-Methylat, aiming to the evaluation of the efficiency of them. An experimental planning 23 was elaborated aiming to evaluate the influence of the variable (molar reason oil/alcohol, % of catalyst and temperature) in the process as well as indicating the excellent point of operation in each case. The biodiesel was analyzed by gaseous chromatography, indicating a conversion of 96,79% when used Na-Methylat® as catalytic, and 95,65% when the K-Methylat® was used. Optimum result found with regard to the conversion was obtained at the following conditions: molar reason oil/alcohol (1:8), temperature of 40°C and 1% of catalyst Na-Methylat, reaching a 96,79% conversion, being, therefore, above of the established for the European norm (96.5%). The analysis of regression showed that the only significant effect for a confidence level of 95%, was of the changeable temperature. The variance analysis evidenced that the considered model is fitted quite to the experimental response, being statistically significant; however it does not serve inside for make forecasts of the intervals established for each variable. The best samples were analyzed by infra-red (IR) that identified the strong bands of axial deformation C=O of methylic ester, characterized through analyses physicochemical that had indicated conformity with the norms of the ANP, that with the thermal and rheological analyses had together evidenced that biodiesel can be used as combustible alternative in substitution to diesel

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Lithium (Li) is a chemical element with atomic number 3 and it is among the lightest known elements in the universe. In general, the Lithium is found in the nature under the form of two stable isotopes, the 6Li and 7Li. This last one is the most dominant and responds for about 93% of the Li found in the Universe. Due to its fragileness this element is largely used in the astrophysics, especially in what refers to the understanding of the physical process that has occurred since the Big Bang going through the evolution of the galaxies and stars. In the primordial nucleosynthesis in the Big Bang moment (BBN), the theoretical calculation forecasts a Li production along with all the light elements such as Deuterium and Beryllium. To the Li the BNB theory reviews a primordial abundance of Log log ǫ(Li) =2.72 dex in a logarithmic scale related to the H. The abundance of Li found on the poor metal stars, or pop II stars type, is called as being the abundance of Li primordial and is the measure as being log ǫ(Li) =2.27 dex. In the ISM (Interstellar medium), that reflects the current value, the abundance of Lithium is log ǫ(Li) = 3.2 dex. This value has great importance for our comprehension on the chemical evolution of the galaxy. The process responsible for the increasing of the primordial value present in the Li is not clearly understood until nowadays. In fact there is a real contribution of Li from the giant stars of little mass and this contribution needs to be well streamed if we want to understand our galaxy. The main objection in this logical sequence is the appearing of some giant stars with little mass of G and K spectral types which atmosphere is highly enriched with Li. Such elevated values are exactly the opposite of what could happen with the typical abundance of giant low mass stars, where convective envelops pass through a mass deepening in which all the Li should be diluted and present abundances around log ǫ(Li) ∼1.4 dex following the model of stellar evolution. In the Literature three suggestions are found that try to reconcile the values of the abundance of Li theoretical and observed in these rich in Li giants, but any of them bring conclusive answers. In the present work, we propose a qualitative study of the evolutionary state of the rich in Li stars in the literature along with the recent discovery of the first star rich in Li observed by the Kepler Satellite. The main objective of this work is to promote a solid discussion about the evolutionary state based on the characteristic obtained from the seismic analysis of the object observed by Kepler. We used evolutionary traces and simulation done with the population synthesis code TRILEGAL intending to evaluate as precisely as possible the evolutionary state of the internal structure of these groups of stars. The results indicate a very short characteristic time when compared to the evolutionary scale related to the enrichment of these stars

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Present day weather forecast models usually cannot provide realistic descriptions of local and particulary extreme weather conditions. However, for lead times of about a small number of days, they provide reliable forecast of the atmospheric circulation that encompasses the subscale processes leading to extremes. Hence, forecasts of extreme events can only be achieved through a combination of dynamical and statistical analysis methods, where a stable and significant statistical model based on prior physical reasoning establishes posterior statistical-dynamical model between the local extremes and the large scale circulation. Here we present the development and application of such a statistical model calibration on the besis of extreme value theory, in order to derive probabilistic forecast for extreme local temperature. The dowscaling applies to NCEP/NCAR re-analysis, in order to derive estimates of daily temperature at Brazilian northeastern region weather stations