21 resultados para Índice de penetração
Resumo:
Satellites signals present disturbances (scintillations), due to presence of irregularities in the ionospheric plasma. In the present work, we dedicate to the study of the attenuation of these scintillations that is, an improvement in the signal, during the main magnetic storm phase during the period of October 2006 to February 2007. Using amplitude of scintillation 1.5GHz (L1) data of the net of satellites GPS, in the ionospheric station of Natal (5.84o S, 35.20o O, -20o dip) and geomagnetic indices, during the minimum solar cycle (referred to as cycle 23), demonstrating its anti-correlation between magnetic activity (Kp) and index of scintillation (
Resumo:
The piles are one of the most important types of solution adopted for the foundation of buildings. They are responsible for transmitting to the soil in deepe r and resistant layers loads from structures. The interaction of the foundation element with the soil is a very important variable, making indispensable your domain in order to determine the strength of the assembly and establish design criteria for each c ase of application of the pile. In this research analyzes were performed f rom experiments load tests for precast concrete piles and inve stigations of soil of type SPT, a study was performed for obtaining the ultimate load capacity of the foundation through methods extrapolation of load - settlement curve , semi - empirical and theoretic . After that, were realized comparisons between the different methods used for two types of soil a granular behavior and other cohesive. For obtaining soil paramet ers to be used i n the methods were established empirical correlations with the standard penetration number (NSPT). The charge - settlement curves of the piles are also analyzed. In the face of established comparisons was indicated the most reliable semiempirical method Déco urt - Quaresma as the most reliable for estimating the tensile strength for granular and cohesive soils. Meanwhile, among the methods studied extrapolation is recommended method of Van der Veen as the most appropriate for predicting the tensile strength.
Resumo:
To contribute in the performance of policies and strategies formulated by development agencies, indexes have been created in anticipation of expressing the multiple dimensions of water resources in an easily interpretable form. Use of Hydro Poverty Index ( WPI) is spreading worldwide , with the same formed by the combination of sub - indices Resource, access, capacity , use and environment. S ome critics a s to its formation have emerged, a mong them stands out the allo cation of weights of sub - indexes , made by an arbitrary process attributing subjectivity to the selection criteria. By involving statistical analysis, when considering the characteristics of the variables generated by the Principal Component Analysis (PCA), it turns out that it is able to solve this problem. The objective of this study is to compare the results of the original WPI with content generated by Principal Com ponent Analysis (PCA) for the indicati on of the weights of sub - indec es applicable in the Seridó River hydrographic Basin . We conclude that the use of Principal Component Analysis in the allocation of weights of Water Poverty Index has identified the sub - indices Resources, Access and Environment are the most representative for the river basin Seridó , and that this new index, WPI' , presented the most comprehensive ranges of values , allowing more easily identify disparities among municipalities. In addition, t he evaluation of the sub - indec es in the study area has great potential to inform the decision - maker in the management of water resources, the most critical locations and deserve greater investments in the aspects analyzed, as the index itself can not cap ture this information.
Resumo:
To identify the relationship between GPS scintillation in Natal-RN (Brazil) and geomagnetic disturbances of any intensities and variations, this work made analysis of the ionospheric behavior and magnetic indexes (Dst , AE and Bz of the interplanetary magnetic field) concerning to different periods of the solar cycle between 2000 and 2014. Part of the data of this research originated at the UFRN observatory, from a GEC Plessey board connected to an ANP -C 114 antenna, modified by Cornell University’s Space group Plasma Physics in order to operate the ScintMon, a GPS monitoring program. This study, therefore, found several cases of inhibited scintillations after the main phase of magnetic storms, a fact that, along with others, corroborated with categorization of Aarons (1991) and models of disturbed dynamo (according to Bonelli, 2008) and over-shielding penetration, defended by Kelley et al. (1979) and Abdu (2011) [4]. In addition to these findings, different morphologies were noted in such disruptions in the GPS signal in accordance with previous magnetic activities. It also found a moderate relationship (R2 = 0.52) between the Dst rate (concerning to specific time) and the average of S4 through a polynomial function. This finding therefore, corroborating Ilma et al. (2012) [17], is an important evidence that the scintillation GPS are not directly controlled by magnetic induction of storms. Completing this work, this relation did show itself as a way of partial predicting of scintillations.
Resumo:
Forecast is the basis for making strategic, tactical and operational business decisions. In financial economics, several techniques have been used to predict the behavior of assets over the past decades.Thus, there are several methods to assist in the task of time series forecasting, however, conventional modeling techniques such as statistical models and those based on theoretical mathematical models have produced unsatisfactory predictions, increasing the number of studies in more advanced methods of prediction. Among these, the Artificial Neural Networks (ANN) are a relatively new and promising method for predicting business that shows a technique that has caused much interest in the financial environment and has been used successfully in a wide variety of financial modeling systems applications, in many cases proving its superiority over the statistical models ARIMA-GARCH. In this context, this study aimed to examine whether the ANNs are a more appropriate method for predicting the behavior of Indices in Capital Markets than the traditional methods of time series analysis. For this purpose we developed an quantitative study, from financial economic indices, and developed two models of RNA-type feedfoward supervised learning, whose structures consisted of 20 data in the input layer, 90 neurons in one hidden layer and one given as the output layer (Ibovespa). These models used backpropagation, an input activation function based on the tangent sigmoid and a linear output function. Since the aim of analyzing the adherence of the Method of Artificial Neural Networks to carry out predictions of the Ibovespa, we chose to perform this analysis by comparing results between this and Time Series Predictive Model GARCH, developing a GARCH model (1.1).Once applied both methods (ANN and GARCH) we conducted the results' analysis by comparing the results of the forecast with the historical data and by studying the forecast errors by the MSE, RMSE, MAE, Standard Deviation, the Theil's U and forecasting encompassing tests. It was found that the models developed by means of ANNs had lower MSE, RMSE and MAE than the GARCH (1,1) model and Theil U test indicated that the three models have smaller errors than those of a naïve forecast. Although the ANN based on returns have lower precision indicator values than those of ANN based on prices, the forecast encompassing test rejected the hypothesis that this model is better than that, indicating that the ANN models have a similar level of accuracy . It was concluded that for the data series studied the ANN models show a more appropriate Ibovespa forecasting than the traditional models of time series, represented by the GARCH model
Resumo:
The main objective is to analyze the abrasive wear resistance to the low stress of the elements that make up the organs of road machinery that are exposed directly to contact with abrasives. These samples were analyzed after these elements are coated superficially by the process of welding electrode coated with (SAER) and the manual process of coating type LVOF thermal spraying. As well, is to provide suggestions for a better recovery and return of these elements, which are reducing costs and avoiding downtime in the fronts of service. The samples were made from a substrate of carbon ABNT 1045 tempered steel, following the same specifications and composition of metals and alloys of constituents was followed the standard governing the dimensions of these samples and in accordance with the corresponding size. The results were evaluated by testing the hardness, abrasion resistance to wear by the low stress and the loss of volume involving the microstructure of coatings analyzed