Integrated assessment for establishing an oil environmental vulnerability map: Case study for the Santos Basin region, Brazil

The growth of maritime transport and oil exploitation activities may increase the risk of oil spills. Thus, plans and actions to prevent or mitigate impacts are needed to minimize the effects caused by oil. However, tools used worldwide to support contingency plans have not been integrated, thus leading to failure in establishing priority areas. This investigation aimed to develop indices of environmental vulnerability to oil (IEVO), by combining information about environmental sensibility to oil and results of numerical modeling of spilled oil. To achieve that, a case study concerning to oil spills scenarios in a subtropical coastal area was designed, and IEVOs were calculated and presented in maps, in order to make the information about the areas' vulnerability more easily visualized. For summer, the extension of coastline potentially affected by oil was approximately 150. km, and most of the coastline presented medium to high vulnerability. For winter, 230. km coastline would be affected, from which 75% were classified as medium to high vulnerability. Thus, IEVO maps allowed a rapid and clearer interpretation of the vulnerability of the mapped region, facilitating the planning process and the actions in response to an oil spill. © 2013 Elsevier Ltd.

Bayesian predictive modeling and comparison of oil samples

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

Valorization of scrap tires pyrolysis oil (STPO) through a 2-stage hydrotreating-hydrocracking strategy. Process variables and kinetic modeling

232 p.

Extraction of volatile oil from aromatic plants with supercritical carbon dioxide: experiments and modeling

An overview of the studies carried out in our laboratories on supercritical fluid extraction (SFE) of volatile oils from seven aromatic plants: pennyroyal (Mentha pulegium L.), fennel seeds (Foeniculum vulgare Mill.), coriander (Coriandrum sativum L.), savory (Satureja fruticosa Beguinot), winter savory (Satureja montana L.), cotton lavender (Santolina chamaecyparisus) and thyme (Thymus vulgaris), is presented. A flow apparatus with a 1 L extractor and two 0.27 L separators was built to perform studies at temperatures ranging from 298 to 353 K and pressures up to 30.0 MPa. The best compromise between yield and composition compared with hydrodistillation (HD) was achieved selecting the optimum experimental conditions of extraction and fractionation. The major differences between HD and SFE oils is the presence of a small percentage of cuticular waxes and the relative amount of thymoquinone, an oxygenated monoterpene with important biological properties, which is present in the oils from thyme and winter savory. On the other hand, the modeling of our data on supercritical extraction of volatile oil from pennyroyal is discussed using Sovova's models. These models have been applied successfully to the other volatile oil extractions. Furthermore, other experimental studies involving supercritical CO2 carried out in our laboratories are also mentioned.

Mathematical modeling of the ester oil-refrigerant R134A mixture two-phase flow with foam formation through a small diameter tube

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Drag reduction phenomenon in viscous oil-water dispersed pipe flow: Experimental investigation and phenomenological modeling

An experimental study on drag-reduction phenomenon in dispersed oil-water flow has been performed in a 26-mm-i.d. Twelve meter long horizontal glass pipe. The flow was characterized using a novel wire-mesh sensor based on capacitance measurements and high-speed video recording. New two-phase pressure gradient, volume fraction, and phase distribution data have been used in the analysis. Drag reduction and slip ratio were detected at oil volume fractions between 10 and 45% and high mixture Reynolds numbers, and with water as the dominant phase. Phase-fraction distribution diagrams and cross-sectional imaging of the flow suggested the presence of a higher amount of water near to the pipe wall. Based on that, a phenomenology for explaining drag reduction in dispersed flow in a flow situation where slip ratio is significant is proposed. A simple phenomenological model is developed and the agreement between model predictions and data, including data from the literature, is encouraging. (c) 2011 American Institute of Chemical Engineers AIChE J, 2012

Modeling for the world crude oil and natural gas markets

Crude oil and natural gas have been essential energy sources and play a crucial role in the world economy. Changes in energy prices significantly impact economic growth. This study builds an econometric model to illustrate the substitute relation between crude oil and natural gas markets. Additionally, the determination of the oil and natural gas prices are endogenized, assuming imperfect competition to reflect a real market strategy. Our empirical results show that the overall performance of this system is acceptable, and the model can be applied to policy analysis for determining monetary or energy policy by introducing this model to the more comprehensive system.

Three dimensional modeling of contaminants transportation (oil spill) in Caspian Sea

Nowadays, Caspian Sea is in focus of more attentions than past because of its individualistic as the biggest lake in the world and the existing of very large oil and gas resources within it. Very large scale of oil pollution caused by development of oil exploration and excavation activities not only make problem for coastal facilities but also make severe damage on environment. In the first stage of this research, the location and quality of oil resources in offshore and onshore have been determined and then affected depletion factors on oil spill such as evaporation, emulsification, dissolution, sedimentation and so on have been studied. In second stage, sea hydrodynamics model is offered and tested by determination of governing hydrodynamic equations on sea currents and on pollution transportation in sea surface and by finding out main parameters in these equations such as Coriolis, bottom friction, wind and etc. this model has been calculated by using cell vertex finite volume method in an unstructured mesh domain. According to checked model; sea currents of Caspian Sea in different seasons of the year have been determined and in final stage different scenarios of oil spill movement in Caspian sea on various conditions have been investigated by modeling of three dimensional oil spill movement on surface (affected by sea currents) and on depth (affected by buoyancy, drag and gravity forces) by applying main above mentioned depletion factors.

Coastal zone oil spill modeling

This work presents the development and application of a three-dimensional oil spill model for predicting the movement of an oil slick in the coastal waters of Singapore. In the model, the oil slick is divided into a number of small elements for simulating of the oil processes of spreading, advection, turbulent diffusion. This model is capable of predicting the horizontal movement of surface oil slick. Satellite images and field observations of oil slicks on the surface in the Singapore Straits are used to validate the newly developed model. Compared with the observations, the numerical results of the oil spill model show good conformity. In this study, the 3d model was generated using the geometrical data of Singapore Straits waters by GAMBIT which is a pre-processor of FLUENT programmed.

Modeling of Convection and Macrosegregation through Appropriate Consideration of Multiphase/Multiscale Phenomena during Alloy Solidification

Solidification processes are complex in nature, involving multiple phases and several length scales. The properties of solidified products are dictated by the microstructure, the mactostructure, and various defects present in the casting. These, in turn, are governed by the multiphase transport phenomena Occurring at different length scales. In order to control and improve the quality of cast products, it is important to have a thorough understanding of various physical and physicochemical phenomena Occurring at various length scales. preferably through predictive models and controlled experiments. In this context, the modeling of transport phenomena during alloy solidification has evolved over the last few decades due to the complex multiscale nature of the problem. Despite this, a model accounting for all the important length scales directly is computationally prohibitive. Thus, in the past, single-phase continuum models have often been employed with respect to a single length scale to model solidification processing. However, continuous development in understanding the physics of solidification at various length scales oil one hand and the phenomenal growth of computational power oil the other have allowed researchers to use increasingly complex multiphase/multiscale models in recent. times. These models have allowed greater understanding of the coupled micro/macro nature of the process and have made it possible to predict solute segregation and microstructure evolution at different length scales. In this paper, a brief overview of the current status of modeling of convection and macrosegregation in alloy solidification processing is presented.

Modeling of Freezing Phenomena Induced by Chemical Reactions

Spatial variations in the concentration of a reactive solute in solution are often encountered in a catalyst particle, and this leads to variation in the freezing point of the solution. Depending on the operating temperature, this can result in freezing of the solvent oil a portion of catalyst, rendering that part of the active area ineffective Freezing call occur by formation of a sharp front or it mush that separates the solid and fluid phases. In this paper, we model the extent of reduction in the active area due to freezing. Assuming that the freezing point decreases linearly with solute concentration, conditions for freezing to occur have been derived. At steady state, the ineffective fraction of catalyst pellet is found to be the same irrespective of the mode of freezing. Progress of freezing is determined by both the heat of reaction and the latent heat of fusion Unlike in freezing of alloys where the latter plays a dominant role, the exothermicity of the reaction has a significant effect on freezing in the presence of chemical reactions. A dimensionless group analogous to the Stefan number could be defined to capture the combined effect of both of these.

Combined Atomic Force Microscopy and Modeling Study of The Evolution of Octadecylamine Films on a Mica Surface

The time evolution of the film thickness and domain formation of octadecylamine molecules adsorbed oil a mica surface is investigated Using atomic force microscopy. The adsorbed Film thickness is determined by measuring the height profile across the mica-amine interface of a mica surface partially immersed in a 15 mM solution of octadecylamine in chloroform. Using this novel procedure, adsorption of amine on mica is found to occur in three distinct stages, with morphologically distinct domain Formation and growth occurring during each stage. In the first stage, where adsorption is primarily in the thin-film regime, all average Film thickness of 0.2 (+/- 0.3) nm is formed for exposure times below 30 s and 0.8 (+/- 0.2) nm for 60 s of immersion time. During this stage, large sample spanning domains are observed. The second stage, which occurs between 60-300 s, is associated with it regime of rapid film growth, and the film thickness increases from about 0.8 to 25 nm during this stage. Once the thick-film regime is established, further exposure to the amine solution results in all increase in the domain area, and it regime of lateral domain growth is observed. In this stage, the domain area coverage grows from 38 to 75%, and the FTIR spectra reveal an increased level of crystallinity in the film. Using it diffusion-controlled model and it two-step Langmuir isotherm, the time evolution of the film growth is quantitatively captured. The model predicts the time at which the thin to thick film transition occurs as well its the time required for complete film growth at longer times. The Ward-Tordai equation is also solved to determine the model parameters in the monolayer (thin-film) regime, which occurs during the initial stages of film growth.

Copolyesters from Soybean Oil for Use as Resorbable Biomaterials

A family of soybean oil (SO) based biodegradable cross-linked copolyesters sourced from renewable resources was developed for use as resorbable biomaterials. The polyesters were prepared by a melt condensation of epoxidized soybean oil polyol and sebacic acid with citric acid (CA) as a cross-linker. D-Mannitol (M) was added as an additional reactant to improve mechanical properties. Differential scanning calorimetry revealed that the polyester synthesized using only CA as the cross-linker was semicrystalline and elastomeric at physiological temperature. The polymers were hydrophobic in nature. The water wettability, elongation at break and the degradation rate of the polyesters decreased with increase in M content or curing time. Modeling of release kinetics of dyes showed a diffusion controlled mechanism underlies the observed sustained release from these polymers. The polyesters supported attachment and proliferation of human stem cells and were thus cytocompatible. Porous scaffolds induced osteogenic differentiation of the stern cells suggesting that these polymers are well suited for bone tissue engineering. Thus, this family of polyesters offers a low cost and green alternative as biocompatible, bioresobable polymers for potential use as resorbable biomaterials for tissue engineering and controlled release.