809 resultados para Oil pipes


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Commercially viable carbon–neutral biodiesel production from microalgae has potential for replacing depleting petroleum diesel. The process of biodiesel production from microalgae involves harvesting, drying and extraction of lipids which are energy- and cost-intensive processes. The development of effective large-scale lipid extraction processes which overcome the complexity of microalgae cell structure is considered one of the most vital requirements for commercial production. Thus the aim of this work was to investigate suitable extraction methods with optimised conditions to progress opportunities for sustainable microalgal biodiesel production. In this study, the green microalgal species consortium, Tarong polyculture was used to investigate lipid extraction with hexane (solvent) under high pressure and variable temperature and biomass moisture conditions using an Accelerated Solvent Extraction (ASE) method. The performance of high pressure solvent extraction was examined over a range of different process and sample conditions (dry biomass to water ratios (DBWRs): 100%, 75%, 50% and 25% and temperatures from 70 to 120 ºC, process time 5–15 min). Maximum total lipid yields were achieved at 50% and 75% sample dryness at temperatures of 90–120 ºC. We show that individual fatty acids (Palmitic acid C16:0; Stearic acid C18:0; Oleic acid C18:1; Linolenic acid C18:3) extraction optima are influenced by temperature and sample dryness, consequently affecting microalgal biodiesel quality parameters. Higher heating values and kinematic viscosity were compliant with biodiesel quality standards under all extraction conditions used. Our results indicate that biodiesel quality can be positively manipulated by selecting process extraction conditions that favour extraction of saturated and mono-unsaturated fatty acids over optimal extraction conditions for polyunsaturated fatty acids, yielding positive effects on cetane number and iodine values. Exceeding biodiesel standards for these two parameters opens blending opportunities with biodiesels that fall outside the minimal cetane and maximal iodine values.

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Few would disagree that the upstream oil & gas industry has become more technology-intensive over the years. But how does innovation happen in the industry? Specifically, what ideas and inputs flow from which parts of the sector׳s value network, and where do these inputs go? And how do firms and organizations from different countries contribute differently to this process? This paper puts forward the results of a survey designed to shed light on these questions. Carried out in collaboration with the Society of Petroleum Engineers (SPE), the survey was sent to 469 executives and senior managers who played a significant role with regard to R&D and/or technology deployment in their respective business units. A total of 199 responses were received from a broad range of organizations and countries around the world. Several interesting themes and trends emerge from the results, including: (1) service companies tend to file considerably more patents per innovation than other types of organization; (2) over 63% of the deployed innovations reported in the survey originated in service companies; (3) neither universities nor government-led research organizations were considered to be valuable sources of new information and knowledge in the industry׳s R&D initiatives, and; (4) despite the increasing degree of globalization in the marketplace, the USA still plays an extremely dominant role in the industry׳s overall R&D and technology deployment activities. By providing a detailed and objective snapshot of how innovation happens in the upstream oil & gas sector, this paper provides a valuable foundation for future investigations and discussions aimed at improving how R&D and technology deployment are managed within the industry. The methodology did result in a coverage bias within the survey, however, and the limitations arising from this are explored.

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Frequency Domain Spectroscopy (FDS) is successfully being used to assess the insulation condition of oil filled power transformers. However, it has to date only been implemented on de-energized transformers, which requires the transformers to be shut down for an extended period which can result in significant costs. To solve this issue, a method of implementing FDS under energized condition is proposed here. A chirp excitation waveform is used to replace the conventional sinusoidal waveform to reduce the measurement time in this method. Investigation of the dielectric response under the influence of a high voltage stress at power frequency is reported based on experimental results. To further understand the insulation ageing process, the geometric capacitance effect is removed to enhance the detection of the ageing signature. This enhancement enables the imaginary part of admittance to be used as a new indicator to assess the ageing status of the insulation.

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The upstream oil & gas industry has been contending with massive data sets and monolithic files for many years, but “Big Data”—that is, the ability to apply more sophisticated types of analytical tools to information in a way that extracts new insights or creates new forms of value—is a relatively new concept that has the potential to significantly re-shape the industry. Despite the impressive amount of value that is being realized by Big Data technologies in other parts of the marketplace, however, much of the data collected within the oil & gas sector tends to be discarded, ignored, or analyzed in a very cursory way. This paper examines existing data management practices in the upstream oil & gas industry, and compares them to practices and philosophies that have emerged in organizations that are leading the Big Data revolution. The comparison shows that, in companies that are leading the Big Data revolution, data is regarded as a valuable asset. The presented evidence also shows, however, that this is usually not true within the oil & gas industry insofar as data is frequently regarded there as descriptive information about a physical asset rather than something that is valuable in and of itself. The paper then discusses how upstream oil & gas companies could potentially extract more value from data, and concludes with a series of specific technical and management-related recommendations to this end.

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The upstream oil and gas industry has been contending with massive data sets and monolithic files for many years, but “Big Data” is a relatively new concept that has the potential to significantly re-shape the industry. Despite the impressive amount of value that is being realized by Big Data technologies in other parts of the marketplace, however, much of the data collected within the oil and gas sector tends to be discarded, ignored, or analyzed in a very cursory way. This viewpoint examines existing data management practices in the upstream oil and gas industry, and compares them to practices and philosophies that have emerged in organizations that are leading the way in Big Data. The comparison shows that, in companies that are widely considered to be leaders in Big Data analytics, data is regarded as a valuable asset—but this is usually not true within the oil and gas industry insofar as data is frequently regarded there as descriptive information about a physical asset rather than something that is valuable in and of itself. The paper then discusses how the industry could potentially extract more value from data, and concludes with a series of policy-related questions to this end.

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The research introduces a promising technique for monitoring the degradation status of oil-paper insulation systems of large power transformers in an online mode and innovative enhancements are also made on the existing offline measurements, which afford more direct understanding of the insulation degradation process. Further, these techniques benefit from a quick measurement owing to the chirp waveform signal application. The techniques are improved and developed on the basis of measuring the impedance response of insulation systems. The feasibility and validity of the techniques was supported by the extensive simulation works as well as experimental investigations.

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A series of macro–mesoporous TiO2/Al2O3 nanocomposites with different morphologies were synthesized. The materials were calcined at 723 K and were characterized by X-ray diffraction (XRD), Scanning electron microscopy (SEM), Transmission electron microscope (TEM), N2 adsorption/desorption, Infrared Emission Spectroscopy (IES), X-ray photoelectron spectroscopy (XPS) and UV–visible spectroscopy (UV–visible). A modified approach was proposed for the synthesis of 1D (fibrous) nanocomposite with higher Ti/Al molar ratio (2:1) at lower temperature (<100 °C), which makes it possible to synthesize such materials on industrial scale. The performance–morphology relationship of as-synthesized TiO2/Al2O3 nanocomposites was investigated by the photocatalytic degradation of a model organic pollutant under UV irradiation. The samples with 1D (fibrous) morphology exhibited superior catalytic performance than the samples without, such as titania microspheres.

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This paper examines the feasibility of using vertical light pipes to naturally illuminate the central core of a multilevel building not reached by window light. The challenges addressed were finding a method to extract and distribute equal amounts of light at each level and designing collectors to improve the effectiveness of vertical light pipes in delivering low elevation sunlight to the interior. Extraction was achieved by inserting partially reflecting cones within transparent sections of the pipes at each floor level. Theory was formulated to estimate the partial reflectance necessary to provide equal light extraction at each level. Designs for daylight collectors formed from laser cut panels tilted above the light pipe were developed and the benefits and limitations of static collectors as opposed to collectors that follow the sun azimuth investigated. Performance was assessed with both basic and detailed mathematical simulation and by observations made with a five level model building under clear sky conditions.

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A 60-year-old male experienced a marked unilateral myopic shift of 20 D following attempted removal of intravitreal heavy silicone oil (HSO) used in the treatment of inferior proliferative vitreous retinopathy following retinal detachment. Examination revealed HSO adherent to the corneal endothelium forming a convex interface with the aqueous, obscuring the entire pupil, which required surgical intervention to restore visual acuity. This case highlights the potential ocular complications associated with silicone oil migration into the anterior chamber, which include corneal endothelial decompensation and a significant increase in myopia.

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Five significant problems hinder advances in understanding of the volcanology of kimberlites: (1) kimberlite geology is very model driven; (2) a highly genetic terminology drives deposit or facies interpretation; (3) the effects of alteration on preserved depositional textures have been grossly underestimated; (4) the level of understanding of the physical process significance of preserved textures is limited; and, (5) some inferred processes and deposits are not based on actual, modern volcanological processes. These issues need to be addressed in order to advance understanding of kimberlite volcanological pipe forming processes and deposits. The traditional, steep-sided southern African pipe model (Class I) consists of a steep tapering pipe with a deep root zone, a middle diatreme zone and an upper crater zone (if preserved). Each zone is thought to be dominated by distinctive facies, respectively: hypabyssal kimberlite (HK, descriptively called here massive coherent porphyritic kimberlite), tuffisitic kimberlite breccia (TKB, descriptively here called massive, poorly sorted lapilli tuff) and crater zone facies, which include variably bedded pyroclastic kimberlite and resedimented and reworked volcaniclastic kimberlite (RVK). Porphyritic coherent kimberlite may, however, also be emplaced at different levels in the pipe, as later stage intrusions, as well as dykes in the surrounding country rock. The relationship between HK and TKB is not always clear. Sub-terranean fluidisation as an emplacement process is a largely unsubstantiated hypothesis; modern in-vent volcanological processes should initially be considered to explain observed deposits. Crater zone volcaniclastic deposits can occur within the diatreme zone of some pipes, indicating that the pipe was largely empty at the end of the eruption, and subsequently began to fill-in largely through resedimentation and sourcing of pyroclastic deposits from nearby vents. Classes II and III Canadian kimberlite models have a more factual, descriptive basis, but are still inadequately documented given the recency of their discovery. The diversity amongst kimberlite bodies suggests that a three-model classification is an over-simplification. Every kimberlite is altered to varying degrees, which is an intrinsic consequence of the ultrabasic composition of kimberlite and the in-vent context; few preserve original textures. The effects of syn- to post-emplacement alteration on original textures have not been adequately considered to date, and should be back-stripped to identify original textural elements and configurations. Applying sedimentological textural configurations as a guide to emplacement processes would be useful. The traditional terminology has many connotations about spatial position in pipe and of process. Perhaps the traditional terminology can be retained in the industrial situation as a general lithofacies-mining terminological scheme because it is so entrenched. However, for research purposes a more descriptive lithofacies terminology should be adopted to facilitate detailed understanding of deposit characteristics, important variations in these, and the process origins. For example every deposit of TKB is different in componentry, texture, or depositional structure. However, because so many deposits in many different pipes are called TKB, there is an implication that they are all similar and that similar processes were involved, which is far from clear.

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This study explores the potential use of empty fruit bunch (EFB) residues from palm oil processing residues, as an alternative feedstock for microbial oil production. EFB is a readily available, lignocellulosic biomass that provides cheaper substrates for oil production in comparison to the use of pure sugars. In this study, potential oleaginous microorganisms were selected based on a multi-criteria analysis (MCA) framework which utilised Analytical Hierarchy Process (AHP) with Preference Ranking Organization Method for Enrichment Evaluation (PROMETHEE) aided by Geometrical Analysis for Interactive Aid (GAIA). The MCA framework was used to evaluate several strains of microalgae (Chlorella protothecoides and Chlorella zofingiensis), yeasts (Cryptococcus albidus and Rhodotorula mucilaginosa) and fungi (Aspergillus oryzae and Mucor plumbeus) on glucose, xylose and glycerol. Based on the results of PROMETHEE rankings and GAIA plane, fungal strains A. oryzae and M. plumbeus and yeast strain R. mucilaginosa showed great promise for oil production from lignocellulosic hydrolysates. The study further cultivated A. oryzae, M. plumbeus and R. mucilaginosa on EFB hydrolysates for oil production. EFB was pretreated with dilute sulfuric acid, followed by enzymatic saccharification of solid residue. Hydrolysates tested in this study are detoxified liquid hydrolysates (LH) and enzymatic hydrolysate (EH).

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Statistical comparison of oil samples is an integral part of oil spill identification, which deals with the process of linking an oil spill with its source of origin. In current practice, a frequentist hypothesis test is often used to evaluate evidence in support of a match between a spill and a source sample. As frequentist tests are only able to evaluate evidence against a hypothesis but not in support of it, we argue that this leads to unsound statistical reasoning. Moreover, currently only verbal conclusions on a very coarse scale can be made about the match between two samples, whereas a finer quantitative assessment would often be preferred. To address these issues, we propose a Bayesian predictive approach for evaluating the similarity between the chemical compositions of two oil samples. We derive the underlying statistical model from some basic assumptions on modeling assays in analytical chemistry, and to further facilitate and improve numerical evaluations, we develop analytical expressions for the key elements of Bayesian inference for this model. The approach is illustrated with both simulated and real data and is shown to have appealing properties in comparison with both standard frequentist and Bayesian approaches

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Gac fruits were physically measured and stored under ambient conditions for up to 2 weeks to observe changes in carotenoid contents (lycopene and beta carotene) in its aril. Initial concentrations in the aril of lycopene were from 2.378 mg/g fresh weight (FW) to 3.728 mg/g FW and those of beta carotene were from 0.257 to 0.379 mg/g FW. Carotenoid concentrations in the aril remained stable after 1 week but sharply declined after 2 weeks of storage. Gac oil, pressed from gac aril, has similar concentrations of lycopene and beta carotene (2.436 and 2.592 mg/g, respectively). Oil was treated with 0.02% of butylated hydroxytoluene, or with a stream of nitrogen or untreated then stored in the dark for up to 15 or 19 weeks under different temperatures (5 °C, ambient, 45 and 60 °C). Lycopene and beta carotene in control gac oil degraded following the first-order kinetic model. The degradation rate of lycopene and beta carotene in the treated oil samples were lower than that in the control oil but the first-order kinetic was not always followed. However, both lycopene and beta carotene degraded quickly in gac oil with the first-order kinetic under high temperature conditions (45 and 60 °C) regardless of the treatments used. © 2009 Elsevier Ltd. All rights reserved.