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A phased approach for generation of linear reaction schemes, i.e., schemes where each reaction has only one reactant and one product as principal species, is proposed in this work. Exhaustive generation of all stoichiometric consistent chemical reactions and enumeration of all possible reaction schemes (based on mass flux analysis), is considered. A graph approach is used for representation of the reaction schemes, and a network model used to elucidate the structure of alternative models at a given level of complexity. After the selection of plausible model structures, determination of possible model parameters is performed in a later step, through regression of the experimental data available. We consider the application to a relevant case study, capable of evidencing the gains and advantages resulting from this systematic analysis.

Model-based optimal design of experiments (M-bODE) is a crucial step in model parametrization since it encloses a framework that maximizes the amount of information extracted from a battery of lab experiments. We address the design of M-bODE for dynamic models considering a continuous representation of the design. We use Semidefinite Programming (SDP) to derive robust minmax formulations for nonlinear models, and extend the formulations to other criteria. The approaches are demonstrated for a CSTR where a two-step reaction occurs.

Publisher Summary This chapter discusses the optimization of batch polymerization systems, using a feasible path approach, with roots on Model Predictive Control (MPC) theory. The approach allows the reuse of many concepts previously developed for nonlinear MPC of continuous plants. It also provides an efficient and well integrated methodology for the optimal supervision of discontinuous chemical processes. The application of this technique in the optimization of the batch-suspension polymerization of vinyl chloride is also described. The chapter discusses its application to the optimization and nonlinear control of the batch-suspension polymerization of vinyl chloride (VCM). This system involves four phases––monomer, polymer, aqueous, and gas––and a heterogeneous reaction. Various kinetic models have been proposed to describe the process, with significant differences at the level of complexity and detail given to various chemical and physical phenomena taking place. The results obtained with a batch-suspension polymerization reactor clearly illustrate the advantages and possible improvements in the operation of discontinuous processes, associated with a more generalized use of theses methodologies.

In this work, experimental data on the gas solubility of hydrofluorocarbons (CHF3, CH2F2 and CH3F) in four room-temperature ionic liquids (RTILs) were determined within the temperature range 288 K to 308 K and at atmospheric pressure. The RTILs used were 1-ethyl-3-methylimidazolium bis(trifluoromethanesulfonyl)imide([C2mim][NTf2]), (trihexyl)tetradecyl-phosphoniumbis(trifluoro-methylsulfonyl)imide ([P6,6,6,14][NTf2]), and N-methyl-2-hydroxyethylammoniumpropionate ([m-2-HEA][Pr]) and pentanoate ([m-2-HEA][P]). Two modelling approaches, which we denote as predictive and correlative, were compared. In the former, the cubic plus association equation of state (CPA EoS) is used as a predictive model to estimate the solubilities using only pure components physical properties. In the latter, the regular-solution theory is the basis to build an empirical model whose parameters are obtained through least-squares fitting of experimental values.

A nonlinear model predictive control algorithm is implemented on-line to control the liquid level and temperature in a pilot plant CSTR, where an irreversible exothermic chemical reaction is simulated experimentally by steam injection. The dynamic behavior of the pilot plant reactor is represented using a mechanistic, first principle model and a comparison between off-line simulation and experimental data is presented. Several sources of model mismatch and unmeasured disturbances are identified that affect the quality of the model in representing the reactor dynamics. Despite these mismatches and disturbances, the closed loop system is able to track setpoint changes and reject disturbances quite well. In particular, the NMPC controller is demonstrated for different tuning parameters and under conditions of constraint saturation at unstable points. http://www.sciencedirect.com/science/article/B6V2H-43K2P7T-5/1/342536dc21267c866ea2f015c70c30ec

We consider the integration of biodiesel and bioethanol production processes with an existing oilseed processing industry to expand the value chain associated with the original raw materials, with multiple advantages from the economic and sustainability perspectives. This process integration task provides several opportunities for the application of systematic decision making methodologies. However, to be implemented in a significant extension, it also places many demands at the levels of the development of accurate models for the thermodynamic and kinetic description of the operations considered, and optimization based design methods for the units to be included in the processing structure. An overview of recent developments in each of these levels is considered in the first part of this work. This is followed with the presentation of an optimal design methodology for the specification of a “De Smet” horizontal solid-liquid extractor, commonly used by the industry to leach out the oil from the flakes. A comparison of the performance of the optimal design with a reference unit is given.

While the design of products and processes involving ionic liquids (ILs) requires knowledge of the thermophysical properties for these compounds, the massive number of possible distinct ILs precludes their detailed experimental characterization. To overcome this limitation, chemists and engineers must rely on predictive models that are able to generate reliable values for these properties, from the knowledge of the structure of the IL. A large body of literature was developed in the last decade for this purpose, aiming at developing predictive models for thermophysical and transport properties of ILs. A critical review of those models is reported here. The modelling approaches are discussed and suggestions relative to the current best methodologies for the prediction of each property are presented. Since most of the these works date from the last 5 years, this field can still be considered to be in its infancy. Consequently, this work also aims at highlighting major gaps in both existing data and modelling approaches, identifying unbeaten tracks and promising paths for further development in this area.

The main goal of this work is to investigate the performance of a Receding Horizon Model Predictive Control scheme applied to a real plant. Nonlinear Model Predictive Control (MPC) algorithms have been described in the literature with great success when applied in simulation studies. However, simulation results do not always reflect the process realities, and they are often inadequate to guarantee that such sophisticated control algorithms can be applied in real plants. In this work, a linearized MPC control design has been experimentally used for temperature and level control in a CSTR. The process is unstable in open-loop, the variables are not all measured, while the process parameters are not very well known and can change with time. The experimental control tests were carried out in an industrial scale pilot plant where a pseudo zero order exothermic chemical reaction is partially simulated. The rate of heat generated by reaction is calculated and converted into an equivalent steam flowrate, which is injected in the mixture. A significant improvement in the controller performance is obtained with the MPC strategy, when compared with the previously existing PI based controller structure. The possibility of implementing the MPC in the corresponding industrial environment is outlined.

Over the last decade ionic liquids appeared as potential entrainers for extractive distillation processes. However experimental vapor-liquid equilibrium data for ionic liquid containing systems is still scarce since most conventional equilibrium cells are not adequate for these systems. To overcome that limitation a new isobaric microebulliometer, operating at pressures ranging from 0.05 to 0.1 MPa and requiring a sample volume lower than 8 mL was developed and validated in this work. The new apparatus was used to determine isobaric VLE data at pressures of 0.05, 0.07 and 0.1 MPa for eight binary mixtures of 1-ethyl-3-methylimidazolium chloride ([C(2)mim][Cl]), 1-butyl-3-methylimidazolium chloride ([C(4)mim][Cl]), 1-hexyl-3-methylimidazolium chloride ([C(6)mim][Cl]), and choline chloride ([N-111(2OH)[Cl]) with water and ethanol. The experimental data here measured were correlated with the NRTL model. (C) 2013 Elsevier B.V. All rights reserved.

W3DS clients should be able to request 3D scenes, either using the getscene or gettile operations, and directly display them without any additional manipulation or geographic positional correction. In this paper we will discuss how tiles should be served to W3DS clients, since 3D tiles are more difficult to manage than 2D tiles. While 2D tiles just need to be placed side by side, 3D tiles also have to fit along the z axis. The volume and complexity of 3D information requires more complicated logic on the client side. Clients can decide that geographic features far away from the viewer can have less detail than those near the observer. For that reason, 3D clients may want to join together tiles of different resolutions. We will show an algorithm to perfectly slice 3D terrain models using the GDAL and CGAL libraries. It can be used in existing W3DS services to improve the quality of visualisations.

In this paper we describe an open source implementing of the Web 3D Service (W3DS) based on the OGC’s draft proposal. The implementation was developed on top of the open source java-based map server GeoServer, as a community module. With an open source implementation available, test beds can be promoted to better know the strengths and limitations of the current proposal. Without practical interoperability assessments demonstrated, W3DS barely become a 3D standard in urban management applications.

This paper introduces a mathematical programming approach to systematically find optimal designs of experiments for linear algebraic models. The method assumes that we have a fully specified parametric model with unknown parameters and the design criterion is convex. To address the problem we use a semi-definite programming formulation, originally developed by Vandenberghe and Boyd (1999) , and propose a new global optimization based framework to determine D-optimal designs. The approaches are applied to an empirical response surface model to design an experimental design, and the mixture components are the composition of the solvent.

This paper deals with the experimental implementation of an automatic scheme for fault detection and identification (FDI). It also provides redundant signals for performing an efficient control in case of a faulty situation, improving safety and reliability of plant operations. Two approaches for on-line parameter estimation are tested: a variant of Recursive Least Squares (RLS) algorithm for linear or linearized models and the GREG algorithm (Stewart et al. , 1992), suitable for more general nonlinear models. The fault detection method is based on a statistical analysis of the deviation of the process parameters. Simultaneously, an Extended Kalman Filter (EKF) enables the fault identification to be performed, reducing false alarms and providing estimates of process variables for alternative control purposes. Applications take place in a industrial-scale pilot plant. The good performance obtained highlighted the strategy employed when sensor faults were introduced artificially on control loops.

Previous experience with predictive control algorithms has shown that the way the optimization problems are formulated and solved has a big impact in the success of the control strategy. Here a multiple shooting formulation is proposed, where a process model is integrated separately inside each sampling interval, and the corresponding equality constraints are added directly to the optimization problem. It is shown that the resulting formulation provides a more reliable framework for the solution of predictive control problems, both in the linear and nonlinear cases. This strategy is compared with the original nonlinear Newton-type (state space) algorithm, on a number of process models with challenging features, including the reactor model from the Tennessee Eastman problem.

Background Registries have a major role in patient follow-up, prospectively collecting real life data, they help us to better understand rare diseases like scleroderma. These atabases allow standardization of daily clinical practice, introducing decision support tools and improving quality and health outcomes. They also allow drug and device surveillance; scientific societies, academia and regulatory authorities can analyze their selected core set of data. Methods Our web-based registry - RIDAI (Informatic Registry of Autoimmune Diseases; www.ridai.org), was created in 2003 by the Portuguese Society Internal Medicine to support all Autoimmunity Clinics in Portugal; currently collecting data from 40 centres, with 4825 patients with different diseases. It has been constantly developped to comprise all the updated tools to measure important domains in autoimmune diseases. Demographic and clinical data were collected and analysed in Microsoft Excel 2013. Results Short presentation and demonstration of RIDAI, online since 2013. The scleroderma cohort has 326 patients, 227 limited and 99 diffuse subtypes, 43 (13.2%) males, mean age 56.4 (range 3–90), longest follow-up since 1993. Comorbidities are highly prevalent in our cohort: dyslipidemia in 46 patients, hypertension in 40, peripheral vascular disease in 22, osteoporosis in 20, heart failure in 13, diabetes in 10 and coronary heart disease in 3 patients. Most frequently used tools include Modified Rodnan Skin Score (mRSS), Visual Analogic Scale (VAS), Joint Count, EUSTAR Systemic Sclerosis Activity Scale (EUSTAR SSAS), the UCLA Scleroderma Clinical Trials Consortium Gastrointestinal Scale (SCTC GIT), Health Assessment Questionaire (HAQ) and Short Form-36 (SF-36). MRSS has a mean value of 9.1. Patient VAS has a mean 39.6; physician VAS mean 38.6. Painful Joint Count has a mean value of 3.0; tender Joint Count mean 1.6. The EUSTAR SSAS has a mean value of 1.27. SCTC GIT mean value is 0.52. HAQ mean value is 1.0; SF-36 mean is 103.9. Biological disease modifying drugs were prescribed off-label in 10 patients, for severe skin and joint disease. Conclusions The RIDAI is the largest portuguese scleroderma registry. It9s a versatile application and can be articulated with other platforms, with direct contribution to international multicentric studies. The presentation of the first 326 patients illustrates the complexity and heterogeneity of systemic sclerosis and of this cohort of patients. Treating to target and using standardized monitoring tools, Portuguese Internal Medicine physicians confirm good treatment performance, with a positive impact on indexes, specially mean mRSS and quality of life (HAQ, SF-36); enabling comparision with best practices. Disclosure of Interest None declared

This study extends the multistep, Newton-type formulation [Li and Biegler (1989) Chem. Eng. Res, Des., 67, 562–577]for nonlinear constrained process control. The computation of the control law is based on an augmented performance index, which improves the performance of the method over the original formulation. A number of modifications are also introduced in the computational algorithm to extend the range of problems, eliminate steady-state offsets, and extend the output predictive horizon to infinity. We show that the global stability properties of the original Newton controller are preserved by the present modifications. Moreover in the absence of active constraints, the method behaves as an extension of the linear quadratic regulator for, exhibiting therefore excellent stability properties for a large range of tuning parameters. The capabilities of the method are illustrated by application to various process examples.

This work considers the catalyst deactivation phenomena in ethyl tert-butyl ether (ETBE) reactors, and the estimation of the corresponding kinetic parameters from industrial plant data. For this purpose a simulation model of these units is developed, and used to build a parameter estimation problem constrained by partial differential equations. Good agreement between the model predictions and the available industrial data is achieved, enabling the use of the resulting model in several process related tasks.

Effects of hard constraints in the stability of model-predictive control (MPC) are reviewed. Assuming a fixed active set, the optimal solution can be expressed in a general state-feedback closed form, which corresponds to a piecewise linear controller for the linear model case. Changes in the original unconstrained solution by the active constraints and other effects related to the loss of degrees of freedom are depicted in this analysis. In addition to modifications in the unconstrained feedback gain, we show that the presence of active output constraints can introduce extra feedback terms in the predictive controller. This can lead to instability of the constrained closed-loop system with certain active sets, independent of the choice of tuning parameters. To cope with these problems and extent the constraint handling capabilities of MPC, we introduce the consideration of soft constraints. We compare the use of the l 2 -(quadratic), l 1 -(exact), and l∞-norm penalty formulations. The analysis reveals a strong similarity between the control laws, which allows a direct extrapolation of the unconstrained tuning guidelines to the constrained case. In particular, the exact penalty treatment has identical stability characteristics to the correspondent unconstrained case and therefore seems well suited for general soft constraint handling, even with nonlinear models. These extensions are included in the previously developed Newton control framework, allowing the use of the approach within a consistent framework for both linear and nonlinear process models, increasing the scope of applications of the method. Process examples illustrate the capabilities of the proposed approaches

Trust region concepts originating from nonlinear programming are applied to the nonlinear Newton-type control framework. This extension is well suited to deal with the ill-conditioning of the predictive equations and is also able to provide a significant acceleration in the rate of convergence of the original algorithm. The approach is illustrated by application to a number of challenging process examples, including open loop instabilities, sign changes in the process gains, and input multiplicities.

This paper addresses the optimal design of drug delivery matrices employing Dynamic Optimization (DO), using the scaffold matrix dimensions, the concentration of the crosslinking agent and initial drug concentration as decision variables to reach a target profile within a given time horizon. The conceptual approach is demonstrated via the design of chitosan based matrices previously cross-linked with genipin in immobilized liposomes, used to encapsulate a drug. The kinetic model employed was derived from data obtained in lab assays. The PDE model describing the diffusion mechanism is discretized with Finite Differences, and the resulting ODEs together with a description of the degradation rate are handled via a simultaneous approach, with a discretization scheme based on orthogonal collocation in Finite Elements in time. The results obtained illustrate the adequacy of this type of methodologies for drug delivery design.

This paper presents a general approach for the design/selection of single molecular structures with prescribed functionality, based on mathematical programming techniques. The strategy relies on an efficient decomposition of the design problem into two levels, relative to the identification of structurally feasible candidate molecules that satisfy the property constraints, and their ranking regarding a set of performance objectives that include both operational and safety aspects. Group contribution methods and correlations are employed to model a significant fraction of the physical properties used in the problem formulation. The approach introduced is demonstrated by application to an example commonly found in aromatics industry - the design of extraction agents to promote L/L separations.

In this work, kinetic models were obtained from experimental data in the open literature, for both the alkaline (NaOH) and acid (H2SO4) homogeneous catalysis of the transesterification reaction, used to produce biodiesel from vegetable oils. Two approaches, designated as statistical and empirical, were adopted to obtain these models. For both catalysis types, the kinetic models obtained show average absolute errors of approximately 4%, using both empirical and statistical approaches, well within the precision of the experimental procedures. In the alkaline catalysis, kinetic models fitted better a pseudo 2nd-order reaction, while for the acid catalysis pseudo 1st-order reaction provided a best fit.

Although the control of an FCC plant includes all the hardware components of the process, it is at the FCC reactor-regenerator system that the control is the most critical. This is mainly due to the strong interaction between the reactor and regenerator units. As a result, the reactor-regenerator system presents a highly nonlinear behavior and is therefore a challenge for control tasks. This paper presents a brief introduction to the control of a high-efficiency FCC unit and the implementation of the main regulatory control loops in the reactor-regenerator system of a real Portuguese industrial high- efficiency FCC unit. Moreover, closed-loop dynamic simulations performed with a model previously developed by the same authors, are compared to industrial dynamic data from step tests done in GalpEnergia FCC unit showing that this FCC simulator can realistically represent the closed-loop dynamic behavior of a real industrial operating unit. Therefore, this dynamic model has a great potential to be used as a reference model for advanced model-based control and real-time optimization purposes.

This work considers the use of information indices for optimal model selection and validation of process data. The approach followed assumes the existence of a set of fundamental process models associated with possible, although distinct, operating regions. A 2-phase mathematical programming algorithm for the assessment of structural changes and optimal fitting of local models in data series is proposed. This approach is used to determine the kinetic parameters of the gelation reaction of chitosan with genipin, employing dynamical elastic modulus data.

This paper describes a methodology for the design of free-radical polymer products based on discontinuous operation. This design problem is characterized by considerable complexity, high dimensionality, nonlinear behavior of the physical models, and multi-objective nature. To avoid most of these limitations, a two-step methodology is introduced, where the problem is initially reformulated in terms of some of the decision variables used. In the second phase, the determination of the remaining complicating variables is completed, from the solution obtained during the previous step. The capability of manufacturing innovative products with improved properties is demonstrated with the batch suspension polymerization of vinyl chloride to produce polyvinyl chloride (PVC), which is one of the currently most widely used thermoplastics.

This paper presents a general framework to handle the optimal sizing of singlestage multi-product units incorporating demand uncertainty. This problem consists on the determination of the type, number of units and their capacities, chosen from a set of standard equipment sizes. The objective function is the profit expectation maximization, involving five components: i. revenue; ii. production cost; iii. equipment depreciation cost; iv. storage cost; v. cost due to non fulfillment of the demand target. The multiple dimension integral representation of the expectation is approximated through cubature formulae. With linear process models, an overall MILP problem formulation is obtained. The approach is applied to the design of the furnace section of a ceramic tile industrial plant, where different products are obtained.

This work describes a methodology for the synthesis of networks of multiphasic reactors, specially suited for processes where complex mecanistic models and a large number of unit types are present. The key concept consists on the decomposition and iteration of the original problem between two different representation levels (corresponding to smaller and less nonlinear problems), to avoid some of the numerical difficulties associated with the original one. This strategy was successfully applied to the aniline production phase of Quimigal S.A., allowing a systematic retrofit of this industrial process.

Using a growth medium based on cane blackstrap molasses, we compared ethanol production by two strains of Saccharomyces cerevisiae that were immobilized in polyurethane foam cubes in a fluidised-bed fermenter. One strain (NCYC 1119) was adhesive and extremely flocculent, whilst the other strain was not adhesive and only weakly flocculent. The strong flocs of NCYC 1119 caused blockage of the bed, so that stable operation could not be achieved beyond 15 days. Nevertheless, it was able to produce 40 g L-1 ethanol at a rate up to 16 g L-1 h-1 (D = 0.4 h-1), although this production period was limited to 192 h. In contrast, the non-adhesive strain was only capable of producing 28 g L-1 ethanol at a rate of 11 g L-1 h-1 at the same dilution rate, even though production continued for 576 h. Despite the conversion of sugars to ethanol not being complete during these trials (up to 47 g L-1 was expected), it was clearly demonstrated that the productivity of the adhesive strain was higher than that of the non-adhesive one. However, further work is required to develop this process into a robust, industrial system. http://www.sciencedirect.com/science/article/B6TG1-4K3CKGW-6/1/e0acf7d19e1fcfcc4e0bfeabfc9f39e5

Static bifurcation in a FCC unit is a problem that arises whenever studying the control of a FCC unit. The origin of this behavior is usually due to the exothermicity of the catalyst regeneration reactions and to important phenomena of backmixing in the regenerator. For this reason the geometrical and operational design of the regenerator unit plays an important role in the overall performance and dynamic stability of FCCs. Prior work has focused on model and control problems of different operating FCC units. However, none of these studies have considered a FCC unit with high efficiency regenerator. This paper presents an analysis of the static bifurcation behavior of an UP FCC unit with high efficiency regenerator. The results show that the high efficiency regenerator presents static bifurcation exhibiting multiple steady states, depending on the operating conditions.

This work introduces a strategy for the optimal design of distillation systems based on continuous optimization. The approach is similar to the one proposed earlier by [Lang, Y. -D., & Biegler, L. T. (2002). A distributed stream method for tray optimization. AIChE Journal, 48, 582], avoiding the need of solving extremely large and non-linear discrete optimization problems. When used with complex distillation units, it can identify interesting design configurations not considered by other continuous formulations, and also relieve some of the numerical difficulties associated with the use of distribution functions for the optimal location of feed and side-streams. The method considers a relaxation of the original problem, where the streams are initially split to several trays in the column, not necessarily adjacent. The optimal location of each stream is converged by constraining the optimization problem, using adjustable parameters that control the minimum amount of aggregation allowed. The methodology is illustrated with the application to several industrial case studies, including sets of distillation columns. Models up to 17,000 variables/equations were solved, revealing large economic benefits in the design of new units and optimization of sets of existing ones.

Publisher Summary This chapter analyzes a system for chemical process control and supervision based on real-time Linux. It describes a general system for hierarchical supervision and control of complex chemical plants, using the real-time extensions of the Linux operating system. Distributed control systems (DCS) are widely used throughout the chemical process industries and generally regarded as providing an efficient approach for the control of complex systems. Their ability to successively decompose control problems into more manageable tasks eliminates performance bottlenecks, and provides a reliable framework for process control. Several factors contributed to the success of this application in chemical plants, such as low cost and abundant availability of distributed computing and network equipment, acceptance of key industry standards by major manufacturers, and the growing capability to integrate the control with business and manufacturing layers. The reliability of this approach is particularly suited for use with complex and heterogeneous DCS, where stringent coordination and timing requirements can be crucial. The system has an open modular nature, which can be easily extended and integrated with additional open-source tools. This nature makes it also particularly suitable as a research and educational tool.

Highly nonlinear and open-loop unstable processes pose serious difficulties to the implementation of optimal control solutions, such as Model Predictive Control (MPC). An example of such processes is the Tennessee Eastman model. Here we show that by proper combination of the optimization algorithm with additional intermediate layers of control, most of the ill-conditioning can be avoided, without loss of performance. Simulation results of our control strategy are compared with previously published results. The numerical efficiency of the solution procedure is addressed, and some characteristics of the problem that can be further exploited are also identified.

Publisher Summary This chapter discusses the optimization of batch polymerization systems, using a feasible path approach, with roots on Model Predictive Control (MPC) theory. The approach allows the reuse of many concepts previously developed for nonlinear MPC of continuous plants. It also provides an efficient and well integrated methodology for the optimal supervision of discontinuous chemical processes. The application of this technique in the optimization of the batch-suspension polymerization of vinyl chloride is also described. The chapter discusses its application to the optimization and nonlinear control of the batch-suspension polymerization of vinyl chloride (VCM). This system involves four phases––monomer, polymer, aqueous, and gas––and a heterogeneous reaction. Various kinetic models have been proposed to describe the process, with significant differences at the level of complexity and detail given to various chemical and physical phenomena taking place. The results obtained with a batch-suspension polymerization reactor clearly illustrate the advantages and possible improvements in the operation of discontinuous processes, associated with a more generalized use of theses methodologies.

Bio-alcohols are produced from biomass by fermentation, and distillation is commonly used to separate the alcohol from the aqueous phase. This is, however, a high energy consumption process, and alternative approaches to this separation are being pursued. In this work, the use of phosphonium-based ionic liquids (ILs) for the extraction of ethanol from fermentation broths is investigated. Ternary phase diagrams, necessary for the design and to implement an alternative liquid–liquid extraction process for the alcohol recovery, were determined for seven ionic liquids. The modelling of the equilibrium data was performed using the COSMO-RS and NRTL models; the first aiming at screening other ionic liquids not experimentally studied, and the latter aiming at designing a separation process. The gathered data indicate that phosphonium-based ionic liquids are the best yet reported to perform water–ethanol separations. Based on the most promising phase diagrams, an analysis of the alcohol and ionic liquid recovery steps was carried out and a liquid–liquid extraction stage coupled to an extractive fermentation, where the ionic liquid is continuously recycled to the fermentator and the ethanol concentration is carried out by pervaporation, is here proposed as an alternative to distillation.

This study extends the multistep Newton-type methods for nonlinear constrained process control. It is shown that a generalization of the quadratic index used in the original formulation results in better performance and in a larger domain of applicability of the method. The stability characteristics of the method for constrained asymptotically stable systems are demonstrated and some guidelines for the treatment of open-loop unstable systems are also given. Finally the presence of model mismatch and disturbances is addressed.

Left ventricular systolic dysfunction (LVSD) following acute myocardial infarction (AMI), by decreasing renal blood flow, may interfere with renal L-DOPA availability and, consequently, dopamine synthesis. Dopamine of renal origin exerts local natriuretic effects. We studied 17 post-AMI patients with asymptomatic LVSD (ejection fraction40%) and 14 without (ejection fractionor = 40%), measuring 24-h urinary excretions of L-DOPA, dopamine and its metabolites, and plasma levels of the amines, amine derivatives and type-B natriuretic peptide (BNP). Baseline characteristics were well balanced between the two groups. No differences were observed in urinary volume and sodium and creatinine excretions. The group with asymptomatic LVSD presented lower urinary excretion of L-DOPA (66.8 +/- 10.1 versus 115.3 +/- 21.9 nmol x day(-1), P = 0.04), whereas plasma levels of L-DOPA were identical in both groups. Urinary dopamine was similar in the two groups (1124.2 +/- 172.4 versus 1049.0 +/- 146.4 nmol x day(-1), P = 0.86), resulting in higher urinary dopamine/L-DOPA ratios in patients with asymptomatic LVSD (20.4 +/- 3.0 versus 9.9 +/- 0.8, P0.001). Plasma levels of BNP were higher in the asymptomatic LVSD group (348.5 +/- 47.3 versus 146.8 +/- 21.9 microg x ml(-1), P = 0.003). Ejection fraction was negatively correlated with both plasma levels of BNP and urinary dopamine/L-DOPA ratios. Renal dopamine production is well preserved in patients with asymptomatic LVSD and increased neurohumoral activation, despite reduced urinary excretion of its precursor. This suggests that renal uptake and/or decarboxylation of L-DOPA is enhanced in this condition, as a compensatory mechanism, contributing to preservation of urinary sodium excretion.

In this paper, the authors recall and systemize the restrictions to the application of Job's method, illustrate its use associated to proton magnetic resonance spectral intensities, and present some results of a computer program they developed for the case of multiple equilibria.

A proton, carbon-13, and vanadium-51 nuclear magnetic resonance study is reported on the number, stoichiometry, geometry, and relative stability of the complexes that form when vanadate(V) solutions are mixed with each one of the following organic α-hydroxyacids in the pH range ~2.5 – ~7: glycolic, lactic, chloro-3- and phenyl-3-lactic, mandelic, glyceric, and malic acids. The predominant complexes have 1:1 composition (almost certainly in a polymeric structure) in contrast with the 1:2 (metal:ligand) stoichiometry of the corresponding Mo(VI) and W(VI) complexes.

The aim of this study is to obtain a model that can simulate the performance of an industrial Fluidised Catalytic Cracking (FCC) unit in steady and dynamic state and which will subsequently be used in studies of control and real time optimisation. In this paper, a dynamic model for a R2R type FCC unit is presented. The model includes the riser, the stripper/disengager, the regeneration system and the catalyst transport lines. Mass, energy and pressure balances are performed for each of these sections. Simulation results for steady and dynamic states are presented and compared qualitatively with those from previous FCC models.