Development of a Continuous Emulsion Copolymerization Process in a Tubular Reactor

This contribution describes the development of a continuous emulsion copolymerization processs for vinyl acetate and n-butyl acrylate in a tubular reactor. Special features of this reactor include the use of oscillatory (pulsed) flow and internals (sieve plates) to prevent polymer fouling and promote good radial mixing, along with a controlled amount of axial mixing. The copolymer system studied (vinyl acetate and butyl acrylate) is strongly prone to composition drift due to very different reactivity ratios. An axially dispersed plug flow model, based on classical free radical copolymerization kinetics, was developed for this process and used successfully to optimize the lateral feeding profile to reduce compositional drift. An energy balance was included in the model equations to predict the effect of temperature variations on the process. The model predictions were validated with experimental data for monomer conversion, copolymer composition, average particle size, and temperature measured along the reactor length.

A novel continuous time representation for the scheduling of pipeline systems with pumping yield rate constraints

Pipeline systems play a key role in the petroleum business. These operational systems provide connection between ports and/or oil fields and refineries (upstream), as well as between these and consumer markets (downstream). The purpose of this work is to propose a novel MINLP formulation based on a continuous time representation for the scheduling of multiproduct pipeline systems that must supply multiple consumer markets. Moreover, it also considers that the pipeline operates intermittently and that the pumping costs depend on the booster stations yield rates, which in turn may generate different flow rates. The proposed continuous time representation is compared with a previously developed discrete time representation [Rejowski, R., Jr., & Pinto, J. M. (2004). Efficient MILP formulations and valid cuts for multiproduct pipeline scheduling. Computers and Chemical Engineering, 28, 1511] in terms of solution quality and computational performance. The influence of the number of time intervals that represents the transfer operation is studied and several configurations for the booster stations are tested. Finally, the proposed formulation is applied to a larger case, in which several booster configurations with different numbers of stages are tested. (C) 2007 Elsevier Ltd. All rights reserved.

A Functional Verification Methodology Based on Parameter Domains for Efficient Input Stimuli Generation and Coverage Modeling

Modern Integrated Circuit (IC) design is characterized by a strong trend of Intellectual Property (IP) core integration into complex system-on-chip (SOC) architectures. These cores require thorough verification of their functionality to avoid erroneous behavior in the final device. Formal verification methods are capable of detecting any design bug. However, due to state explosion, their use remains limited to small circuits. Alternatively, simulation-based verification can explore hardware descriptions of any size, although the corresponding stimulus generation, as well as functional coverage definition, must be carefully planned to guarantee its efficacy. In general, static input space optimization methodologies have shown better efficiency and results than, for instance, Coverage Directed Verification (CDV) techniques, although they act on different facets of the monitored system and are not exclusive. This work presents a constrained-random simulation-based functional verification methodology where, on the basis of the Parameter Domains (PD) formalism, irrelevant and invalid test case scenarios are removed from the input space. To this purpose, a tool to automatically generate PD-based stimuli sources was developed. Additionally, we have developed a second tool to generate functional coverage models that fit exactly to the PD-based input space. Both the input stimuli and coverage model enhancements, resulted in a notable testbench efficiency increase, if compared to testbenches with traditional stimulation and coverage scenarios: 22% simulation time reduction when generating stimuli with our PD-based stimuli sources (still with a conventional coverage model), and 56% simulation time reduction when combining our stimuli sources with their corresponding, automatically generated, coverage models.

Improved generation lifetime model for the electrical characterization of single- and double-gate SOI nMOSFETs

This work proposes a refined technique for the extraction of the generation lifetime in single- and double-gate partially depleted SOI nMOSFETs. The model presented in this paper, based on the drain current switch-off transients, takes into account the influence of the laterally non-uniform channel doping, caused by the presence of the halo implanted region, and the amount of charge controlled by the drain and source junctions on the floating body effect when the channel length is reduced. The obtained results for single- gate (SG) devices are compared with two-dimensional numerical simulations and experimental data, extracted for devices fabricated in a 0.1 mu m SOI CMOS technology, showing excellent agreement. The improved model to determine the generation lifetime in double-gate (DG) devices beyond the considerations previously presented also consider the influence of the silicon layer thickness on the drain current transient. The extracted data through the improved model for DG devices were compared with measurements and two-dimensional numerical simulations of the SG devices also presenting a good adjustment with the channel length reduction and the same tendency with the silicon layer thickness variation.

A Separation Principle for the Continuous-Time LQ-Problem With Markovian Jump Parameters

In this paper, we devise a separation principle for the finite horizon quadratic optimal control problem of continuous-time Markovian jump linear systems driven by a Wiener process and with partial observations. We assume that the output variable and the jump parameters are available to the controller. It is desired to design a dynamic Markovian jump controller such that the closed loop system minimizes the quadratic functional cost of the system over a finite horizon period of time. As in the case with no jumps, we show that an optimal controller can be obtained from two coupled Riccati differential equations, one associated to the optimal control problem when the state variable is available, and the other one associated to the optimal filtering problem. This is a separation principle for the finite horizon quadratic optimal control problem for continuous-time Markovian jump linear systems. For the case in which the matrices are all time-invariant we analyze the asymptotic behavior of the solution of the derived interconnected Riccati differential equations to the solution of the associated set of coupled algebraic Riccati equations as well as the mean square stabilizing property of this limiting solution. When there is only one mode of operation our results coincide with the traditional ones for the LQG control of continuous-time linear systems.

The Policy Iteration Algorithm for Average Continuous Control of Piecewise Deterministic Markov Processes

The main goal of this paper is to apply the so-called policy iteration algorithm (PIA) for the long run average continuous control problem of piecewise deterministic Markov processes (PDMP`s) taking values in a general Borel space and with compact action space depending on the state variable. In order to do that we first derive some important properties for a pseudo-Poisson equation associated to the problem. In the sequence it is shown that the convergence of the PIA to a solution satisfying the optimality equation holds under some classical hypotheses and that this optimal solution yields to an optimal control strategy for the average control problem for the continuous-time PDMP in a feedback form.

Generation of self-similar Gaussian time series by means of the DWT and DWPT variance maps

Due to the several kinds of services that use the Internet and data networks infra-structures, the present networks are characterized by the diversity of types of traffic that have statistical properties as complex temporal correlation and non-gaussian distribution. The networks complex temporal correlation may be characterized by the Short Range Dependence (SRD) and the Long Range Dependence - (LRD). Models as the fGN (Fractional Gaussian Noise) may capture the LRD but not the SRD. This work presents two methods for traffic generation that synthesize approximate realizations of the self-similar fGN with SRD random process. The first one employs the IDWT (Inverse Discrete Wavelet Transform) and the second the IDWPT (Inverse Discrete Wavelet Packet Transform). It has been developed the variance map concept that allows to associate the LRD and SRD behaviors directly to the wavelet transform coefficients. The developed methods are extremely flexible and allow the generation of Gaussian time series with complex statistical behaviors.

THE VANISHING DISCOUNT APPROACH FOR THE AVERAGE CONTINUOUS CONTROL OF PIECEWISE DETERMINISTIC MARKOV PROCESSES

This work is concerned with the existence of an optimal control strategy for the long-run average continuous control problem of piecewise-deterministic Markov processes (PDMPs). In Costa and Dufour (2008), sufficient conditions were derived to ensure the existence of an optimal control by using the vanishing discount approach. These conditions were mainly expressed in terms of the relative difference of the alpha-discount value functions. The main goal of this paper is to derive tractable conditions directly related to the primitive data of the PDMP to ensure the existence of an optimal control. The present work can be seen as a continuation of the results derived in Costa and Dufour (2008). Our main assumptions are written in terms of some integro-differential inequalities related to the so-called expected growth condition, and geometric convergence of the post-jump location kernel associated to the PDMP. An example based on the capacity expansion problem is presented, illustrating the possible applications of the results developed in the paper.

On the Filtering Problem for Continuous-Time Markov Jump Linear Systems with no Observation of the Markov Chain

We consider in this paper the optimal stationary dynamic linear filtering problem for continuous-time linear systems subject to Markovian jumps in the parameters (LSMJP) and additive noise (Wiener process). It is assumed that only an output of the system is available and therefore the values of the jump parameter are not accessible. It is a well known fact that in this setting the optimal nonlinear filter is infinite dimensional, which makes the linear filtering a natural numerically, treatable choice. The goal is to design a dynamic linear filter such that the closed loop system is mean square stable and minimizes the stationary expected value of the mean square estimation error. It is shown that an explicit analytical solution to this optimal filtering problem is obtained from the stationary solution associated to a certain Riccati equation. It is also shown that the problem can be formulated using a linear matrix inequalities (LMI) approach, which can be extended to consider convex polytopic uncertainties on the parameters of the possible modes of operation of the system and on the transition rate matrix of the Markov process. As far as the authors are aware of this is the first time that this stationary filtering problem (exact and robust versions) for LSMJP with no knowledge of the Markov jump parameters is considered in the literature. Finally, we illustrate the results with an example.

Adequacy of Cold Rolling Models to Upgrade Set-up Generation Systems

This paper presents two strategies for the upgrade of set-up generation systems for tandem cold mills. Even though these mills have been modernized mainly due to quality requests, their upgrades may be made intending to replace pre-calculated reference tables. In this case, Bryant and Osborn mill model without adaptive technique is proposed. As a more demanding modernization, Bland and Ford model including adaptation is recommended, although it requires a more complex computational hardware. Advantages and disadvantages of these two systems are compared and discussed and experimental results obtained from an industrial cold mill are shown.

Singular Perturbation for the Discounted Continuous Control of Piecewise Deterministic Markov Processes

This paper deals with the expected discounted continuous control of piecewise deterministic Markov processes (PDMP`s) using a singular perturbation approach for dealing with rapidly oscillating parameters. The state space of the PDMP is written as the product of a finite set and a subset of the Euclidean space a""e (n) . The discrete part of the state, called the regime, characterizes the mode of operation of the physical system under consideration, and is supposed to have a fast (associated to a small parameter epsilon > 0) and a slow behavior. By using a similar approach as developed in Yin and Zhang (Continuous-Time Markov Chains and Applications: A Singular Perturbation Approach, Applications of Mathematics, vol. 37, Springer, New York, 1998, Chaps. 1 and 3) the idea in this paper is to reduce the number of regimes by considering an averaged model in which the regimes within the same class are aggregated through the quasi-stationary distribution so that the different states in this class are replaced by a single one. The main goal is to show that the value function of the control problem for the system driven by the perturbed Markov chain converges to the value function of this limit control problem as epsilon goes to zero. This convergence is obtained by, roughly speaking, showing that the infimum and supremum limits of the value functions satisfy two optimality inequalities as epsilon goes to zero. This enables us to show the result by invoking a uniqueness argument, without needing any kind of Lipschitz continuity condition.

Supercritical steam cycles and biomass integrated gasification combined cycles for sugarcane mills

Back in 1970s and 1980s, cogeneration plants in sugarcane mills were primarily designed to consume all bagasse, and produce steam and electricity to the process. The plants used medium pressure steam boilers (21 bar and 300 degrees C) and backpressure steam turbines. Some plants needed also an additional fuel, as the boilers were very inefficient. In those times, sugarcane bagasse did not have an economic value, and it was considered a problem by most mills. During the 1990s and the beginning of the 2000s, sugarcane industry faced an open market perspective, thus, there was a great necessity to reduce costs in the production processes. In addition, the economic value of by-products (bagasse, molasses, etc.) increased, and there was a possibility of selling electricity to the grid. This new scenario led to a search for more advanced cogeneration systems, based mainly on higher steam parameters (40-80 bar and 400-500 degrees C). In the future, some authors suggest that biomass integrated gasification combined cycles are the best alternative to cogeneration plants in sugarcane mills. These systems might attain 35-40% efficiency for the power conversion. However, supercritical steam cycles might also attain these efficiency values, what makes them an alternative to gasification-based systems. This paper presents a comparative thermoeconomic study of these systems for sugarcane mills. The configurations studied are based on real systems that could be adapted to biomass use. Different steam consumptions in the process are considered, in order to better integrate these configurations in the mill. (C) 2009 Elsevier Ltd. All rights reserved.

Electron beam induced second-harmonic generation in Er(3+) doped PbO-GeO(2) glasses containing silver nanoparticles

Electron beam induced second harmonic generation (SHG) is studied in Er(3+) doped PbO-GeO(2) glasses containing silver nanoparticles with concentrations that are controlled by the heat-treatment of the samples. The SHG is observed at T = 4.2 K using a p-polarized laser beam at 1064 nm. Enhancement of the SHG is observed in the samples that are submitted to electron beam incidence. The highest value of the nonlinear susceptibility, 2.08 pm/V, is achieved for the sample heat-treated during 72 h and submitted to an electron beam current of 15 nA. The samples that were not exposed to the electron beam present a susceptibility of a parts per thousand 0.5 pm/V.

Nutritional Aspects of Second Generation Soy Foods

Samples of 15 second generation soy-based products (n = 3), commercially available, were analyzed for their protein and isoflavone contents and in vitro antioxidant activity, by means of the Folin-Ciocalteu reducing ability, DPPH radical scavenging capacity, and oxygen radical absorbance capacity. Isoflavone identification and quantification were performed by high-performance liquid chromatography. Products containing soy and/or soy-based ingredients represent important sources of protein in addition to the low fat amounts. However, a large variation in isoflavone content and in vitro antioxidant capacity was observed. The isoflavone content varied from 2.4 to 18.1 mg/100 g (FW), and soy kibe and soy sausage presented the highest amounts. Chocolate had the highest antioxidant capacity, but this fact was probably associated with the addition of cocoa liquor, a well-known source of polyphenolics. This study showed that the soy-based foods do not present a significant content of isoflavones when compared with the grain, and their in vitro antioxidant capacity is not related with these compounds but rather to the presence of other phenolics and synthetic antioxidants, such as sodium erythorbate. However, they may represent alternative sources and provide soy protein, isoflavones, and vegetable fat for those who are not ready to eat traditional soy foods.

Effect of Simvastatin on the Generation of Autoantibodies Against Oxidized LDL and Progression of Atherosclerosis in Rabbits

Oxidized Low-Density Lipoproteins (oxLDL) and autoantibodies against oxLDL are important in the development of atherosclerotic lesions. Statins are efficacious in the control of dyslipidemia and prevention of atherosclerosis; however, many questions concerning the mechanism of action of such drugs remain unknown. This work investigated the effect of simvastatin on generation of autoantibodies against oxLDL and development of atherosclerosis in rabbits. The animals were divided into three groups: control, hypercholesterolemic, and hypercholesterolemic simvastatin (3.0 mg simvastatin/ kg body weight). Concentrations of autoantibodies against oxLDL were determined on days 0,30 and 60 of the experiment and the atherosclerotic lesions were evaluated at the end of the study. Simvastatin reduced intimal proliferation in the thoracic region, prevented arterial calcification and inhibited the generation of autoantibodies against oxLDL. In conclusion, daily administration of simvastatin slows down atherosclerotic lesion development in rabbits with induced hypercholesterolemia and inhibition on generation of autoantibodies against oxLDL contributes to the cardioprotective effect observed.