Pirólise de borras oleosas de petroleo utilizando nanomateriais

The oily sludge is a complex mix of hydrocarbons, organic impurities, inorganic and water. One of the major problems currently found in petroleum industry is management (packaging, storage, transport and fate) of waste. The nanomaterials (catalysts) mesoporous and microporous are considered promising for refining and adsorbents process for environment protection. The aim of this work was to study the oily sludge from primary processing (raw and treated) and vacuum residue, with application of thermal analyses technique (pyrolysis), thermal and catalytic pyrolysis with nanomaterials, aiming at production petroleum derived. The sludge and vacuum residue were analyzed using a soxhlet extraction system, elemental analysis, thin layer chromatography, thermogravimetry and pyrolysis coupled in gas chromatography/mass spectrometry (Py GC MS). The catalysts AlMCM-41, AlSBA-15.1 e AlSBA-15.2 were synthesized with molar ratio silicon aluminum of 50 (Si/Al = 50), using tetraethylorthosilicante as source of silicon and pseudobuhemita (AlOOH) as source of aluminum. The analyzes of the catalysts indicate that materials showed hexagonal structure and surface area (783,6 m2/g for AlMCM-41, 600 m2/g for AlSBA-15.1, 377 m2/g for AlSBA-15.2). The extracted oily sludge showed a range 65 to 95% for organic components (oil), 5 to 35% for inorganic components (salts and oxides) and compositions different of derivatives. The AlSBA-15 catalysts showed better performance in analyzes for production petroleum derived, 20% increase in production of kerosene and light gas oil. The energy potential of sludge was high and it can be used as fuel in other cargo processed in refinery

Sistema inteligente para detecção de vazamentos em dutos de petróleo usando transformada Wavelet e redes neurais

This work consists in the use of techniques of signals processing and artificial neural networks to identify leaks in pipes with multiphase flow. In the traditional methods of leak detection exists a great difficulty to mount a profile, that is adjusted to the found in real conditions of the oil transport. These difficult conditions go since the unevenly soil that cause columns or vacuum throughout pipelines until the presence of multiphases like water, gas and oil; plus other components as sand, which use to produce discontinuous flow off and diverse variations. To attenuate these difficulties, the transform wavelet was used to map the signal pressure in different resolution plan allowing the extraction of descriptors that identify leaks patterns and with then to provide training for the neural network to learning of how to classify this pattern and report whenever this characterize leaks. During the tests were used transient and regime signals and pipelines with punctures with size variations from ½' to 1' of diameter to simulate leaks and between Upanema and Estreito B, of the UN-RNCE of the Petrobras, where it was possible to detect leaks. The results show that the proposed descriptors considered, based in statistical methods applied in domain transform, are sufficient to identify leaks patterns and make it possible to train the neural classifier to indicate the occurrence of pipeline leaks

Avaliação oxidativa do biodiesel de pinhão manso em diferentes processos de purificação

The objective of this study was to analyze the oxidative stability of biodiesel from jatropha obtained from different purification processes, three wet processes with different drying (in a vacuum oven, conventional oven and in anhydrous sodium sulfate) and dry (purification with magnesium silicate adsorbent). Raw materials of different qualities (jatropha crop ancient and recent crop) were used. The Jatropha oil was extracted by mechanical extraction and refined. The Jatropha biodiesel was obtained by the transesterification reaction in ethyl route using alkaline catalysis. The biodiesel samples were characterized by analysis of water content, carbon residue, Absorption Spectroscopy in the Infrared Region and Thermogravimetry. Thermogravimetric curves of purified PUsv* PUsq* and had higher initial decomposition temperatures, indicating that the most stable, followed by samples PU* and PUSC*. Besides the sample SP* is a smaller initial temperature, confirming the sample without purification to be less thermally stable. The percentage mass loss of the purified samples showed conversion of about 98.5%. The results of analyzes carbon residue and infrared suggested that contamination by impurities is the main factor for decreased oxidative stability of biodiesel. The oxidative stability was assessed from periodic monitoring, using the techniques of Rancimat, peroxide index, acid value and Pressurized Differential Scanning Calorimetry. Samples of biodiesel from jatropha which showed better oxidative stability were of the best quality raw material and wet scrubbing: PUsq* with dry chemical, using anhydrous sodium sulfate and PUsv* with vacuum drying, which had oxidative stability 6 hours in Rancimat time 0 days, within the limits established by the Technical Regulation No. 4/2012 of the ANP, without the addition of antioxidant, suggesting that these procedures the least influence on the oxidative stability of biodiesel