Real time optimization (RTO) with model predictive control (MPC)

This paper studies a simplified methodology to integrate the real time optimization (RTO) of a continuous system into the model predictive controller in the one layer strategy. The gradient of the economic objective function is included in the cost function of the controller. Optimal conditions of the process at steady state are searched through the use of a rigorous non-linear process model, while the trajectory to be followed is predicted with the use of a linear dynamic model, obtained through a plant step test. The main advantage of the proposed strategy is that the resulting control/optimization problem can still be solved with a quadratic programming routine at each sampling step. Simulation results show that the approach proposed may be comparable to the strategy that solves the full economic optimization problem inside the MPC controller where the resulting control problem becomes a non-linear programming problem with a much higher computer load. (C) 2010 Elsevier Ltd. All rights reserved.

Experimental and numerical investigation of dynamic heat transfer parameters in packed bed

Dynamic experiments in a nonadiabatic packed bed were carried out to evaluate the response to disturbances in wall temperature and inlet airflow rate and temperature. A two-dimensional, pseudo-homogeneous, axially dispersed plug-flow model was numerically solved and used to interpret the results. The model parameters were fitted in distinct stages: effective radial thermal conductivity (K (r)) and wall heat transfer coefficient (h (w)) were estimated from steady-state data and the characteristic packed bed time constant (tau) from transient data. A new correlation for the K (r) in packed beds of cylindrical particles was proposed. It was experimentally proved that temperature measurements using radially inserted thermocouples and a ring-shaped sensor were not distorted by heat conduction across the thermocouple or by the thermal inertia effect of the temperature sensors.

Distributed power control algorithm for multiple access systems based on Verhulst model

In this paper the continuous Verhulst dynamic model is used to synthesize a new distributed power control algorithm (DPCA) for use in direct sequence code division multiple access (DS-CDMA) systems. The Verhulst model was initially designed to describe the population growth of biological species under food and physical space restrictions. The discretization of the corresponding differential equation is accomplished via the Euler numeric integration (ENI) method. Analytical convergence conditions for the proposed DPCA are also established. Several properties of the proposed recursive algorithm, such as Euclidean distance from optimum vector after convergence, convergence speed, normalized mean squared error (NSE), average power consumption per user, performance under dynamics channels, and implementation complexity aspects, are analyzed through simulations. The simulation results are compared with two other DPCAs: the classic algorithm derived by Foschini and Miljanic and the sigmoidal of Uykan and Koivo. Under estimated errors conditions, the proposed DPCA exhibits smaller discrepancy from the optimum power vector solution and better convergence (under fixed and adaptive convergence factor) than the classic and sigmoidal DPCAs. (C) 2010 Elsevier GmbH. All rights reserved.

A Model for comparing reduced impact logging with conventional logging for an Eastern Amazonian Forest

Using data from a logging experiment in the eastern Brazilian Amazon region, we develop a matrix growth and yield model that captures the dynamic effects of harvest system choice on forest structure and composition. Multinomial logistic regression is used to estimate the growth transition parameters for a 10-year time step, while a Poisson regression model is used to estimate recruitment parameters. The model is designed to be easily integrated with an economic model of decisionmaking to perform tropical forest policy analysis. The model is used to compare the long-run structure and composition of a stand arising from the choice of implementing either conventional logging techniques or more carefully planned and executed reduced-impact logging (RIL) techniques, contrasted against a baseline projection of an unlogged forest. Results from log and leave scenarios show that a stand logged according to Brazilian management requirements will require well over 120 years to recover its initial commercial volume, regardless of logging technique employed. Implementing RIL, however, accelerates this recovery. Scenarios imposing a 40-year cutting cycle raise the possibility of sustainable harvest volumes, although at significantly lower levels than is implied by current regulations. Meeting current Brazilian forest policy goals may require an increase in the planned total area of permanent production forest or the widespread adoption of silvicultural practices that increase stand recovery and volume accumulation rates after RIL harvests. Published by Elsevier B.V.

Water Resources Assessment at Piracicaba, Capivari and Jundiai River Basins: A Dynamic Systems Approach

The Piracicaba, Capivari, and Jundiai River Basins (RB-PCJ) are mainly located in the State of So Paulo, Brazil. Using a dynamics systems simulation model (WRM-PCJ) to assess water resources sustainability, five 50-year simulations were run. WRM-PCJ was developed as a tool to aid decision and policy makers on the RB-PCJ Watershed Committee. The model has 254 variables. The model was calibrated and validated using available information from the 80s. Falkenmark Water Stress Index went from 1,403 m(3) person (-aEuro parts per thousand 1) year (-aEuro parts per thousand 1) in 2004 to 734 m(3) P (-aEuro parts per thousand 1) year (-aEuro parts per thousand 1) in 2054, and Xu Sustainability Index from 0.44 to 0.20. In 2004, the Keller River Basin Development Phase was Conservation, and by 2054 was Augmentation. The three criteria used to evaluate water resources showed that the watershed is at crucial water resources management turning point. The WRM-PCJ performed well, and it proved to be an excellent tool for decision and policy makers at RB-PCJ.

Leaf area index estimation with MODIS reflectance time series and model inversion during full rotations of Eucalyptus plantations

The leaf area index (LAI) of fast-growing Eucalyptus plantations is highly dynamic both seasonally and interannually, and is spatially variable depending on pedo-climatic conditions. LAI is very important in determining the carbon and water balance of a stand, but is difficult to measure during a complete stand rotation and at large scales. Remote-sensing methods allowing the retrieval of LAI time series with accuracy and precision are therefore necessary. Here, we tested two methods for LAI estimation from MODIS 250m resolution red and near-infrared (NIR) reflectance time series. The first method involved the inversion of a coupled model of leaf reflectance and transmittance (PROSPECT4), soil reflectance (SOILSPECT) and canopy radiative transfer (4SAIL2). Model parameters other than the LAI were either fixed to measured constant values, or allowed to vary seasonally and/or with stand age according to trends observed in field measurements. The LAI was assumed to vary throughout the rotation following a series of alternately increasing and decreasing sigmoid curves. The parameters of each sigmoid curve that allowed the best fit of simulated canopy reflectance to MODIS red and NIR reflectance data were obtained by minimization techniques. The second method was based on a linear relationship between the LAI and values of the GEneralized Soil Adjusted Vegetation Index (GESAVI), which was calibrated using destructive LAI measurements made at two seasons, on Eucalyptus stands of different ages and productivity levels. The ability of each approach to reproduce field-measured LAI values was assessed, and uncertainty on results and parameter sensitivities were examined. Both methods offered a good fit between measured and estimated LAI (R(2) = 0.80 and R(2) = 0.62 for model inversion and GESAVI-based methods, respectively), but the GESAVI-based method overestimated the LAI at young ages. (C) 2010 Elsevier Inc. All rights reserved.

An analysis of US greenhouse gas cap-and-trade proposals using a forward-looking economic model

We develop a forward-looking version of the recursive dynamic MIT Emissions Prediction and Policy Analysis (EPPA) model, and apply it to examine the economic implications of proposals in the US Congress to limit greenhouse gas (GHG) emissions. We find that shocks in the consumption path are smoothed out in the forward-looking model and that the lifetime welfare cost of GHG policy is lower than in the recursive model, since the forward-looking model can fully optimize over time. The forward-looking model allows us to explore issues for which it is uniquely well suited, including revenue-recycling and early action crediting. We find capital tax recycling to be more welfare-cost reducing than labor tax recycling because of its long-term effect on economic growth. Also, there are substantial incentives for early action credits; however, when spread over the full horizon of the policy they do not have a substantial effect on lifetime welfare costs.

Forward-looking versus recursive-dynamic modeling in climate policy analysis: A comparison

This paper develops a multi-regional general equilibrium model for climate policy analysis based on the latest version of the MIT Emissions Prediction and Policy Analysis (EPPA) model. We develop two versions so that we can solve the model either as a fully inter-temporal optimization problem (forward-looking, perfect foresight) or recursively. The standard EPPA model on which these models are based is solved recursively, and it is necessary to simplify some aspects of it to make inter-temporal solution possible. The forward-looking capability allows one to better address economic and policy issues such as borrowing and banking of GHG allowances, efficiency implications of environmental tax recycling, endogenous depletion of fossil resources, international capital flows, and optimal emissions abatement paths among others. To evaluate the solution approaches, we benchmark each version to the same macroeconomic path, and then compare the behavior of the two versions under a climate policy that restricts greenhouse gas emissions. We find that the energy sector and CO(2) price behavior are similar in both versions (in the recursive version of the model we force the inter-temporal theoretical efficiency result that abatement through time should be allocated such that the CO(2) price rises at the interest rate.) The main difference that arises is that the macroeconomic costs are substantially lower in the forward-looking version of the model, since it allows consumption shifting as an additional avenue of adjustment to the policy. On the other hand, the simplifications required for solving the model as an optimization problem, such as dropping the full vintaging of the capital stock and fewer explicit technological options, likely have effects on the results. Moreover, inter-temporal optimization with perfect foresight poorly represents the real economy where agents face high levels of uncertainty that likely lead to higher costs than if they knew the future with certainty. We conclude that while the forward-looking model has value for some problems, the recursive model produces similar behavior in the energy sector and provides greater flexibility in the details of the system that can be represented. (C) 2009 Elsevier B.V. All rights reserved.

Dynamic susceptibility investigation of maghemite nanoparticles incorporated in bovine serum albumin template

Room-temperature measurements of the magnetic susceptibility of Bovine Serum Albumin-based nanocapsules (50 to 300 nm in size) loaded with different amounts of maghemite nanoparticles (7.6 nm average diameter) have been carried out in this study The field (H) dependence of the imaginary peak susceptibility (f(P)) of the nanocomposite samples was investigated in the range of 0 to 4 kOe. From the analysis of the f(P) x H curves the concentration (N) dependence of the effective maghemite magnetocrystalline energy barrier (E) was obtained. Analysis of the E x N data was performed using a modified Morup-Tronc [Phys. Rev. Lett. 72, 3278 (1994)] model, from which a huge contribution from the magnetocrystalline surface anisotropy was observed.

Hyaluronidase Behavior at the Air/Liquid and Air/Lipid Interfaces and Improved Enzymatic Activity by Its Immobilization in a Biomembrane Model

Bovine testicular hyalurphidase (BT-HAase), a tetrameric enzyme responsible for randomly hyaluronic acid, catalytic hydrolysis, was successfully immobilized on Langmuir- Blodgett films prepared with the sodium salt of dihexadacylphosphoric acid, (DHP-Zn(II)) ending with dipalmitoylphosphatidylcholine, DPPC. Data of protein, adsorption at the air-liquid interface by means of pendant drop shipe analysis and interaction of the protein with Langmuir monolayers of DPPC, using a Langmuir trough, have provided information. about the conditions to be used in the protein immobilization. The dynamic surface pressure curves obtained from pendant drop experiments for the enzyme in buffer solutions indicate that, within the range of concentration investigated in this study, the enzyme exhibits the largest induction time at 5 mu g L(-1) attributed to diffusion processes. Nevertheless, it seems that, at this concentration, the most probable conformation should be the one which occupies the smallest area at pi -> 0. The surface pressure (pi) area curves obtained for BT-HAase and mixed DPPC- BT-HAase monolayers reveal the presence of the enzyme at the air-lipid interface up to 45 mN m(-1). Tests of enzymatic activity, using hyaluronic acid, HA, as the substrate, showed an increase of activity compared to the homogeneous medium. A simplified model of protein insertion into the lipid matrix is used to explain the obtained results.

A Comparison Between Pulse Pressure Variation and Right End Diastolic Volume Index as Guides to Resuscitation in a Model of Hemorrhagic Shock in Pigs

Background: Different hemodynamic parameters including static indicators of cardiac preload as right ventricular end-diastolic volume index (RVEDVI) and dynamic parameters as pulse pressure variation (PPV) have been used in the decision-making process regarding volume expansion in critically ill patients. The objective of this study was to compare fluid resuscitation guided by either PPV or RVEDVI after experimentally induced hemorrhagic shock. Methods: Twenty-six anesthetized and mechanically ventilated pigs were allocated into control (group I), PPV (group II), or RVEDVI (group III) group. Hemorrhagic shock was induced by blood withdrawal to target mean arterial pressure of 40 mm Hg, maintained for 60 minutes. Parameters were measured at baseline, time of shock, 60 minutes after shock, immediately after resuscitation with hydroxyethyl starch 6% (130/0.4), 1 hour and 2 hours thereafter. The endpoint of fluid resuscitation was determined as the baseline values of PPV and RVEDVI. Statistical analysis of data was based on analysis of variance for repeated measures followed by the Bonferroni test (p < 0.05). Results: Volume and time to resuscitation were higher in group III than in group II (group III = 1,305 +/- 331 mL and group II = 965 +/- 245 mL, p < 0.05; and group III = 24.8 +/- 4.7 minutes and group II = 8.8 +/- 1.3 minutes, p < 0.05, respectively). All static and dynamic parameters and biomarkers of tissue oxygenation were affected by hemorrhagic shock and nearly all parameters were restored after resuscitation in both groups. Conclusion: In the proposed model of hemorrhagic shock, resuscitation to the established endpoints was achieved within a smaller amount of time and with less volume when guided by PPV than when guided by pulmonary artery catheter-derived RVEDVI.

A fuzzy Reed-Frost model for epidemic spreading

In this paper, we present a fuzzy approach to the Reed-Frost model for epidemic spreading taking into account uncertainties in the diagnostic of the infection. The heterogeneities in the infected group is based on the clinical signals of the individuals (symptoms, laboratorial exams, medical findings, etc.), which are incorporated into the dynamic of the epidemic. The infectivity level is time-varying and the classification of the individuals is performed through fuzzy relations. Simulations considering a real problem with data of the viral epidemic in a children daycare are performed and the results are compared with a stochastic Reed-Frost generalization.

POLYETHYLENE GLYCOL ADDITION DOES NOT IMPROVE EXOGENOUS SURFACTANT FUNCTION IN AN EXPERIMENTAL MODEL OF MECONIUM ASPIRATION SYNDROME

Meconium (MEC) is a potent inactivator of pulmonary surfactant. The authors studied the effects of polyethylene glycol addition to the exogenous surfactant over the lung mechanics and volumes. Human meconium was administrated to newborn rabbits. Animals were ventilated for 20 minutes and dynamic compliance, ventilatory pressure, and tidal volume were recorded. Animals were randomized into 3 study groups: MEC group (without surfactant therapy); S100 group (100 mg/kg surfactant); and PEG group (100 mg/kg porcine surfactant plus 5% PEG). After ventilation, a pulmonary pressure-volume curve was built. Histological analysis was carried out to calculate the mean alveolar size (Lm) and the distortion index (DI). Both groups treated with surfactant showed higher values of dynamic pulmonary compliance and lower ventilatory pressure, compared with the MEC group (P .05). S100 group had a larger maximum lung volume, V30, compared with the MEC group (P .05). Lm and DI values were smaller in the groups treated with surfactant than in the MEC group (P .05). No differences were observed between the S100 and PEG groups. Animals treated with surfactant showed significant improvement in pulmonary function as compared to nontreated animals. PEG added to exogenous surfactant did not improve lung mechanics or volumes.

Comparative study of pressure- and volume-controlled ventilation on pulse pressure variation in a model of hypovolaemia in rabbits

Background and objective: Dynamic indices represented by systolic pressure variation and pulse pressure variation have been demonstrated to be more accurate than filling pressures in predicting fluid responsiveness. However, the literature is scarce concerning the impact of different ventilatory modes on these indices. We hypothesized that systolic pressure variation or pulse pressure variation could be affected differently by volume-controlled ventilation and pressure-controlled ventilation in an experimental model, during normovolaemia and hypovolaemia. Method: Thirty-two anaesthetized rabbits were randomly allocated into four groups according to ventilatory modality and volaemic status where G1-ConPCV was the pressure-controlled ventilation control group, G2-HemPCV was associated with haemorrhage, G3-ConVCV was the volume-controlled ventilation control group and G4-HemVCV was associated with haemorrhage. In the haemorrhage groups, blood was removed in two stages: 15% of the estimated blood volume withdrawal at M1, and, 30 min later, an additional 15% at M2. Data were submitted to analysis of variance for repeated measures; a value of P < 0.05 was considered to be statistically significant. Results: At MO (baseline), no significant differences were observed among groups. At M1, dynamic parameters differed significantly among the control and hypovolaemic groups (P < 0.05) but not between ventilation modes. However, when 30% of the estimated blood volume was removed (M2), dynamic parameters became significantly higher in animals under volume-controlled ventilation when compared with those under pressure-controlled ventilation. Conclusions: Under normovolaemia and moderate haemorrhage, dynamic parameters were not influenced by either ventilatory modalities. However, in the second stage of haemorrhage (30%), animals in volume-controlled ventilation presented higher values of systolic pressure variation and pulse pressure variation when compared with those submitted to pressure-controlled ventilation.

Combining two potential causes of metalloproteinase secretion causes abdominal aortic aneurysms in rats: a new experimental model

P>Progress in understanding the pathophysiology of abdominal aortic aneurysms (AAA) is dependent in part on the development and application of effective animal models that recapitulate key aspects of the disease. The objective was to produce an experimental model of AAA in rats by combining two potential causes of metalloproteinase (MMP) secretion: inflammation and turbulent blood flow. Male Wistar rats were randomly divided in four groups: Injury, Stenosis, Aneurysm and Control (40/group). The Injury group received a traumatic injury to the external aortic wall. The Stenosis group received an extrinsic stenosis at a corresponding location. The Aneurysm group received both the injury and stenosis simultaneously, and the Control group received a sham operation. Animals were euthanized at days 1, 3, 7 and 15. Aorta and/or aneurysms were collected and the fragments were fixed for morphologic, immunohistochemistry and morphometric analyses or frozen for MMP assays. AAAs had developed by day 3 in 60-70% of the animals, reaching an aortic dilatation ratio of more than 300%, exhibiting intense wall remodelling initiated at the adventitia and characterized by an obvious inflammatory infiltrate, mesenchymal proliferation, neoangiogenesis, elastin degradation and collagen deposition. Immunohistochemistry and zymography studies displayed significantly increased expressions of MMP-2 and MMP-9 in aneurysm walls compared to other groups. The haemo-dynamic alterations caused by the stenosis may have provided additional contribution to the MMPs liberation. This new model illustrated that AAA can be multifactorial and confirmed the key roles of MMP-2 and MMP-9 in this dynamic remodelling process.