8 resultados para Artificial lift method

em Biblioteca Digital da Produção Intelectual da Universidade de São Paulo


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The use of the core-annular flow pattern, where a thin fluid surrounds a very viscous one, has been suggested as an attractive artificial-lift method for heavy oils in the current Brazilian ultra-deepwater production scenario. This paper reports the pressure drop measurements and the core-annular flow observed in a 2 7/8-inch and 300 meter deep pilot-scale well conveying a mixture of heavy crude oil (2000 mPa.s and 950 kg/m3 at 35 C) and water at several combinations of the individual flow rates. The two-phase pressure drop data are compared with those of single-phase oil flow to assess the gains due to water injection. Another issue is the handling of the core-annular flow once it has been established. High-frequency pressure-gradient signals were collected and a treatment based on the Gabor transform together with neural networks is proposed as a promising solution for monitoring and control. The preliminary results are encouraging. The pilot-scale tests, including long-term experiments, were conducted in order to investigate the applicability of using water to transport heavy oils in actual wells. It represents an important step towards the full scale application of the proposed artificial-lift technology. The registered improvements in terms of oil production rate and pressure drop reductions are remarkable.

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In this paper is presented a multilayer perceptron neural network combined with the Nelder-Mead Simplex method to detect damage in multiple support beams. The input parameters are based on natural frequencies and modal flexibility. It was considered that only a number of modes were available and that only vertical degrees of freedom were measured. The reliability of the proposed methodology is assessed from the generation of random damages scenarios and the definition of three types of errors, which can be found during the damage identification process. Results show that the methodology can reliably determine the damage scenarios. However, its application to large beams may be limited by the high computational cost of training the neural network.

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This paper presents an optimum user-steered boundary tracking approach for image segmentation, which simulates the behavior of water flowing through a riverbed. The riverbed approach was devised using the image foresting transform with a never-exploited connectivity function. We analyze its properties in the derived image graphs and discuss its theoretical relation with other popular methods such as live wire and graph cuts. Several experiments show that riverbed can significantly reduce the number of user interactions (anchor points), as compared to live wire for objects with complex shapes. This paper also includes a discussion about how to combine different methods in order to take advantage of their complementary strengths.

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A new concept for in vitro visual evaluation of sun protection factor (SPF) of cosmetic formulations based on a supramolecular ultraviolet (UV) dosimeter was clearly demonstrated. The method closely parallels the method validated for in vivo evaluation and relies on the determination of the slightest perceptible bleaching of an iron-complex dye/nanocrystallinetitanium dioxide interface (UV dosimeter) in combination with an artificial skin substrate simulating the actual human skin in the presence and absence of a cosmetic formulation. The successful evaluation of SPF was ensured by the similarity of the erythema response of our dosimeter and human skin to UV light irradiation. A good linear correlation of in vitro and in vivo data up to SPF 40 confirmed the effectiveness of such a simple, cheap, and fast method. In short, here we unravel a convenient and accessible visual FPS evaluation method that can help improving the control on cosmetic products contributing to the reduction of skin cancer, one of the critical public health issues nowadays. (C) 2011 Wiley Periodicals, Inc. and the American Pharmacists Association J Pharm Sci 101:726732, 2012

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A simple and fast method for the determination of Ca, Cu, Fe, Mg, Mn, Se and Zn in bovine semen by quadrupole inductively coupled plasma spectrometry (q-ICP-MS) is described. Prior to analysis, samples (200 mu L) were diluted 1:50 in a solution containing 0.01% v/v Triton (R) X-100 and 0.5% v/v nitric acid and directly analyzed by ICP-MS. The limits of detection of the method are 0.3, 0.03, 0.2, 0.04, 0.04, 0.03 and 0.03 mu g L-1 for Ca-44, Cu-63, Fe-57, Mg-24, Zn-64, Se-82 and Mn-55, respectively. For purposes of comparison and method validation, four ordinary bovine semen samples were directly analyzed by ICP-MS and by flame atomic absorption spectrometry (FAAS) or graphite furnace atomic absorption spectrometry (GF AAS), with no statistical difference between the techniques at the 95% level when applying the t-test. Then, the proposed method was applied in the determinations of Ca, Cu, Fe, Mg, Mn, Se and Zn in collected samples of bovine semen from different breeds, which are used in reproduction programs and artificial insemination.

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A chaotic encryption algorithm is proposed based on the "Life-like" cellular automata (CA), which acts as a pseudo-random generator (PRNG). The paper main focus is to use chaos theory to cryptography. Thus, CA was explored to look for this "chaos" property. This way, the manuscript is more concerning on tests like: Lyapunov exponent, Entropy and Hamming distance to measure the chaos in CA, as well as statistic analysis like DIEHARD and ENT suites. Our results achieved higher randomness quality than others ciphers in literature. These results reinforce the supposition of a strong relationship between chaos and the randomness quality. Thus, the "chaos" property of CA is a good reason to be employed in cryptography, furthermore, for its simplicity, low cost of implementation and respectable encryption power. (C) 2012 Elsevier Ltd. All rights reserved.

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Abstract Background Accurate malaria diagnosis is mandatory for the treatment and management of severe cases. Moreover, individuals with asymptomatic malaria are not usually screened by health care facilities, which further complicates disease control efforts. The present study compared the performances of a malaria rapid diagnosis test (RDT), the thick blood smear method and nested PCR for the diagnosis of symptomatic malaria in the Brazilian Amazon. In addition, an innovative computational approach was tested for the diagnosis of asymptomatic malaria. Methods The study was divided in two parts. For the first part, passive case detection was performed in 311 individuals with malaria-related symptoms from a recently urbanized community in the Brazilian Amazon. A cross-sectional investigation compared the diagnostic performance of the RDT Optimal-IT, nested PCR and light microscopy. The second part of the study involved active case detection of asymptomatic malaria in 380 individuals from riverine communities in Rondônia, Brazil. The performances of microscopy, nested PCR and an expert computational system based on artificial neural networks (MalDANN) using epidemiological data were compared. Results Nested PCR was shown to be the gold standard for diagnosis of both symptomatic and asymptomatic malaria because it detected the major number of cases and presented the maximum specificity. Surprisingly, the RDT was superior to microscopy in the diagnosis of cases with low parasitaemia. Nevertheless, RDT could not discriminate the Plasmodium species in 12 cases of mixed infections (Plasmodium vivax + Plasmodium falciparum). Moreover, the microscopy presented low performance in the detection of asymptomatic cases (61.25% of correct diagnoses). The MalDANN system using epidemiological data was worse that the light microscopy (56% of correct diagnoses). However, when information regarding plasma levels of interleukin-10 and interferon-gamma were inputted, the MalDANN performance sensibly increased (80% correct diagnoses). Conclusions An RDT for malaria diagnosis may find a promising use in the Brazilian Amazon integrating a rational diagnostic approach. Despite the low performance of the MalDANN test using solely epidemiological data, an approach based on neural networks may be feasible in cases where simpler methods for discriminating individuals below and above threshold cytokine levels are available.

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A simple and fast method for the determination of Ca, Cu, Fe, Mg, Mn, Se and Zn in bovine semen by quadrupole inductively coupled plasma spectrometry (q-ICP-MS) is described. Prior to analysis, samples (200 µL) were diluted 1:50 in a solution containing 0.01% v/v Triton® X-100 and 0.5% v/v nitric acid and directly analyzed by ICP-MS. The limits of detection of the method are 0.3, 0.03, 0.2, 0.04, 0.04, 0.03 and 0.03 µg L-1 for 44Ca, 63Cu, 57Fe, 24Mg, 64Zn, 82Se and 55Mn, respectively. For purposes of comparison and method validation, four ordinary bovine semen samples were directly analyzed by ICP-MS and by flame atomic absorption spectrometry (FAAS) or graphite furnace atomic absorption spectrometry (GF AAS), with no statistical difference between the techniques at the 95% level when applying the t-test. Then, the proposed method was applied in the determinations of Ca, Cu, Fe, Mg, Mn, Se and Zn in collected samples of bovine semen from different breeds, which are used in reproduction programs and artificial insemination.