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Abstract: In Brazil, as in many other countries, the fuel quality control is made according to standard assays, which depend on some of the fuel properties, such as specific gravity, Reid vapor pressure and distillation curve. These properties are intimately related to the fuel composition and their prediction relies on the knowledge of its components characteristics. In Brazil, 25% (v/v) of anhydrous ethanol is added to the mixture of hydrocarbons that is usually called gasoline, according to the local regulations. In this work, the composition of the gasoline was obtained by gas chromatography as a small series of pseudo-components. Given the gasoline composition, its volatility properties and specific gravity were calculated using the Peng–Robinson equation of state with the Fisher–Gmehling mixing rule. The model provided excellent predictions for specific gravity, Reid vapor pressure and most of the distillation curve. However, important deviations are observed at the end of the distillation curve (90+%). These deviations are due to chemical alterations of the fuel caused by the high temperatures occurring at the end of the distillation curve. The model, as proposed, is efficient to forecast the fuel properties; as a consequence, it can be applied as a tool in the study of gasoline formulations and as an alternative tool in quality control. [Copyright &y& Elsevier]

This paper tests different control strategies based on classic proportional integral derivative (PID) and advanced dynamic matrix control (DMC) algorithms for an intermittently stirred, forcefully aerated solid-state fermentation bioreactor. The study was done using a distributed parameter model to reproduce the main operating features of this type of bioreactor. There is predicted to be a remarkable improvement in the bioreactor productivity when control strategies are implemented. For this type of bioreactor, the temperature and water content of the substrate bed can be controlled by saturating the air at the air inlet but manipulating its temperature, coupled with a strategy of water replenishment when the water content of the bed falls below a threshold. Dynamic matrix control is superior to PID control; however, a specific convolution matrix for different stages of the fermentation is necessary due to the changing behavior of the system. This work shows the benefit of mathematical modeling, since the many different operating conditions investigated via simulations would not have been economically feasible to undertake experimentally with a large-scale bioreactor. The results obtained provide an excellent starting point for such large-scale experimental work. [Copyright &y& Elsevier]

Abstract Oil production employing gas lift techniques enable the production of no natural flow wells and supply the energy lost in the reservoir caused by the field depletion, keeping the production in brown fields feasible. The multiphase flow conditions and the long pipes used to transport the fluids from the reservoir to the surface facilities, especially in deep and ultra-deepwater cases, may create unstable flow situations. Several publications in process control have discussed this problem since the 1980s, but the potential multivariable actions on the choke valve and gas lift flow have not been explored so far. In this paper the operating oil production system is treated through a nonlinear predictive control strategy. The strategy evaluation in a rigorous model (OLGA) shows the association between predictive capability and the integrated actuation in the manipulated variables results in an oil production increase and a partial or entire suppression of the instabilities in the multiphase flow. Furthermore, the rate of acting required on the valves is lower in the multivariable approach, allowing the use of slow choke valves as a final control element. [ABSTRACT FROM AUTHOR]

This work describes a simplified dynamic model for control and real time applications in offshore deepwater and ultra-deepwater petroleum production systems. Literature about simplified dynamical models, capable of cover the global architecture of an offshore multiphase production system, is scarce. Hence, the proposed model integrates and adapts partial models available in the literature in order to generate a single model of the whole system. The model, designed to represent slugs generated by the casing heading and terrain/riser concomitantly, was evaluated by comparison with a traditional commercial simulator and was also implemented in two actual production systems. As a result, the model showed the capability of capturing complex dynamical behaviors, such as limit cycles, demonstrated to be numerically more stable than similar models in literature, fast enough to be used in real time applications and proved to be adherent to the commercial simulator and actual operating data from Petrobras production systems. [ABSTRACT FROM AUTHOR]

Abstract: In this paper, a thermodynamic optimization procedure for FCC riser units has been developed. The formulation uses a 2D fluid flow and kinetic model to provide the necessary information for the optimization process. The thermodynamic analysis is based on the unit entropy generation minimization, i.e., the minimization of the destroyed exergy in the system. This kind of analysis has been widely used in power generation plants, with large benefits. It was verified that for any given catalyst mass flow rate, there exists an optimum value for the catalyst to oil mass flow rate ratio, COR, for maximum mass flow rate production of gasoline, or any other desired product. Next, the objective function (net exergy production rate) was maximized through the minimization of the destroyed exergy inside the FCC unit. The optimization was conducted with respect to the catalyst to oil ratio (COR). It is important to stress that all optima are sharp, i.e., for example with H/D =50, the variation of is greater than 50%, calculated from for 5