Degradation of Poly(ethylene glycol) in Aqueous Solution by Photo-Fenton and H(2)O(2)/UV Processes

This article reports experimental results obtained in a laboratory-scale photochemical reactor on the photodegradation of poly(ethylene glycol) (PEG) in aqueous solutions by means of the photo-Fenton and H(2)O(2)/UV processes. Dilute water solutions of PEG were fed to a batch reactor, mixed with pertinent reactants, and allowed to react under different conditions. Reaction progress was evaluated by sampling and analyzing the concentration of the total organic carbon (TOC) in solution as a function of the reaction time. Organic acids formed during oxidation were determined by HPLC analyses. The main acids detected in both processes were acetic and formic. Glycolic acid was detected only in the photo-Fenton process, and malonic acid was detected only in the H(2)O(2)/UV treatment, indicating that different reaction paths occur in these processes. The characteristics of both processes are discussed, based on the evolution of the TOC-time curves and the concentration profiles of the monitored organic acids. The experimental results constitute a contribution to the design of industrial processes for the treatment of wastewaters containing soluble polymers with similar properties.

Treatment of Aqueous Effluents Containing Phenol by the O(3), O(3)-UV, and O(3)-H(2)O(2) Processes: Experimental Study and Neural Network Modeling

In this work, the oxidation of the model pollutant phenol has been studied by means of the O(3), O(3)-UV, and O(3)-H(2)O(2) processes. Experiments were carried out in a fed-batch system to investigate the effects of initial dissolved organic carbon concentration, initial, ozone concentration in the gas phase, the presence or absence of UVC radiation, and initial hydrogen peroxide concentration. Experimental results were used in the modeling of the degradation processes by neural networks in order to simulate DOC-time profiles and evaluate the relative importance of process variables.

Stable Model Predictive Control for Integrating Systems with Optimizing Targets

This paper concern the development of a stable model predictive controller (MPC) to be integrated with real time optimization (RTO) in the control structure of a process system with stable and integrating outputs. The real time process optimizer produces Optimal targets for the system inputs and for Outputs that Should be dynamically implemented by the MPC controller. This paper is based oil a previous work (Comput. Chem. Eng. 2005, 29, 1089) where a nominally stable MPC was proposed for systems with the conventional control approach where only the outputs have set points. This work is also based oil the work of Gonzalez et at. (J. Process Control 2009, 19, 110) where the zone control of stable systems is studied. The new control for is obtained by defining ail extended control objective that includes input targets and zone controller the outputs. Additional decision variables are also defined to increase the set of feasible solutions to the control problem. The hard constraints resulting from the cancellation of the integrating modes Lit the end of the control horizon are softened,, and the resulting control problem is made feasible to a large class of unknown disturbances and changes of the optimizing targets. The methods are illustrated with the simulated application of the proposed,approaches to a distillation column of the oil refining industry.

Enlarging the domain of attraction of stable MPC controllers, maintaining the output performance

This work presents an alternative way to formulate the stable Model Predictive Control (MPC) optimization problem that allows the enlargement of the domain of attraction, while preserving the controller performance. Based on the dual MPC that uses the null local controller, it proposed the inclusion of an appropriate set of slacked terminal constraints into the control problem. As a result, the domain of attraction is unlimited for the stable modes of the system, and the largest possible for the non-stable modes. Although this controller does not achieve local optimality, simulations show that the input and output performances may be comparable to the ones obtained with the dual MPC that uses the LQR as a local controller. (C) 2009 Elsevier Ltd. All rights reserved.

A stable MPC with zone control

Several MPC applications implement a control strategy in which some of the system outputs are controlled within specified ranges or zones, rather than at fixed set points [J.M. Maciejowski, Predictive Control with Constraints, Prentice Hall, New Jersey, 2002]. This means that these outputs will be treated as controlled variables only when the predicted future values lie outside the boundary of their corresponding zones. The zone control is usually implemented by selecting an appropriate weighting matrix for the output error in the control cost function. When an output prediction is inside its zone, the corresponding weight is zeroed, so that the controller ignores this output. When the output prediction lies outside the zone, the error weight is made equal to a specified value and the distance between the output prediction and the boundary of the zone is minimized. The main problem of this approach, as long as stability of the closed loop is concerned, is that each time an output is switched from the status of non-controlled to the status of controlled, or vice versa, a different linear controller is activated. Thus, throughout the continuous operation of the process, the control system keeps switching from one controller to another. Even if a stabilizing control law is developed for each of the control configurations, switching among stable controllers not necessarily produces a stable closed loop system. Here, a stable M PC is developed for the zone control of open-loop stable systems. Focusing on the practical application of the proposed controller, it is assumed that in the control structure of the process system there is an upper optimization layer that defines optimal targets to the system inputs. The performance of the proposed strategy is illustrated by simulation of a subsystem of an industrial FCC system. (C) 2008 Elsevier Ltd. All rights reserved.

USE OF SOLAR ENERGY IN THE TREATMENT OF WATER CONTAMINATED WITH PHENOL BY PHOTOCHEMICAL PROCESSES

The solar driven photo-Fenton process for treating water containing phenol as a contaminant has been evaluated by means of pilot-scale experiments with a parabolic trough solar reactor (PTR). The effects of Fe(II) (0.04-1.0 mmol L(-1)), H(2)O(2) (7-270 mmol L(-1)), initial phenol concentration (100 and 500 mg C L(-1)), solar radiation, and operation mode (batch and fed-batch) on the process efficiency were investigated. More than 90% of the dissolved organic carbon (DOC) was removed within 3 hours of irradiation or less, a performance equivalent to that of artificially-irradiated reactors, indicating that solar light can be used either as an effective complementary or as an alternative source of photons for the photo-Fenton degradation process. A non-linear multivariable model based on a neural network was fit to the experimental results of batch-mode experiments in order to evaluate the relative importance of the process variables considered on the DOC removal over the reaction time. This included solar radiation, which is not a controlled variable. The observed behavior of the system in batch-mode was compared with fed-batch experiments carried out under similar conditions. The main contribution of the study consists of the results from experiments under different conditions and the discussion of the system behavior. Both constitute important information for the design and scale-up of solar radiation-based photodegradation processes.

Electro-optically sensitive diamond-like carbon thin films deposited by reactive magnetron sputtering for electronic device applications

The goal of this work is to study and relate electrical and optical properties of diamond-like carbon (DLC) thin films for applications in electronic devices. DLC films were deposited in a reactive RF magnetron sputtering system on p-type silicon and glass substrates. The target was a 99.9999% pure, 6 in. diameter graphite plate and methane was used as processing gas. Eight DLC films were produced for each substrate, varying deposition time, the reactor pressure between 5 mTorr and 10 mTorr while the RF power was applied at 13.56 MHz and varied between 100, 150, 200 and 250W. After deposition, the films were analyzed by I-V and C-V measurements (Cheng et al. (2004) [1]) in order to determine the electric resistivity, photo-current response and dielectric constant, optical transmittance, used to find the optical gap by the Tauc method; and by photoluminescence analysis to determine the photoemission and confirm the optical band gap. These characteristics are compared and the influence of the deposition parameters is discussed. (C) 2011 Published by Elsevier B.V.

Vibratory noise to the fingertip enhances balance improvement associated with light touch

Light touch of a fingertip on an external stable surface greatly improves the postural stability of standing subjects. The hypothesis of the present work was that a vibrating surface could increase the effectiveness of fingertip signaling to the central nervous system (e.g., by a stochastic resonance mechanism) and hence improve postural stability beyond that achieved by light touch. Subjects stood quietly over a force plate while touching with their right index fingertip a surface that could be either quiescent or randomly vibrated at two low-level noise intensities. The vibratory noise of the contact surface caused a significant decrease in postural sway, as assessed by center of pressure measures in both time and frequency domains. Complementary experiments were designed to test whether postural control improvements were associated with a stochastic resonance mechanism or whether attentional mechanisms could be contributing. A full curve relating body sway parameters and different levels of vibratory noise resulted in a U-like function, suggesting that the improvement in sway relied on a stochastic resonance mechanism. Additionally, no decrease in postural sway was observed when the vibrating contact surface was attached to the subject`s body, suggesting that no attentional mechanisms were involved. These results indicate that sensory cues obtained from the fingertip need not necessarily be associated with static contact surfaces to cause improvement in postural stability. A low-level noisy vibration applied to the contact surface could lead to a better performance of the postural control system.

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.

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.

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.

Transport Barkhausen-like noise in uniaxially pressed Bi(1.65)Pb(0.35)Sr(2)Ca(2)Cu(3)O(10+delta) ceramic samples

We report on the detection of the transport Barkhausen-like noise (TBN) in polycrystalline samples of Bi(1.65)Pb(0.35)Sr(2)Ca(2) Cu(3)O(10+delta) (Bi-2223) which were subjected to different uniaxial compacting pressures. The transport Barkhausen-like noise was measured when the sample was subjected to an ac triangular-shape magnetic field (f similar to 1 Hz) with maximum amplitude B(max) approximate to 5.5 mT, in order to avoid the flux penetration within the superconducting grains. Analysis of the TBN signal, measured for several values of excitation current density, indicated that the applied magnetic field in which the noise signal first appears, B(a)(t(i)), is closely related to the magnetic-flux pinning capability of the material. The combined results are consistent with the existence of three different superconducting levels within the samples: (i) the superconducting grains; (ii) the superconducting clusters; and (iii) the weak-links. We finally argue that TBN measurements constitute a powerful tool for probing features of the intergranular transport properties in polycrystalline samples of high-T(c) superconductors. (C) 2010 Elsevier B.V. All rights reserved.

Closed-loop model re-identification of processes under MPC with zone control

This work deals with a procedure for model re-identification of a process in closed loop with ail already existing commercial MPC. The controller considered here has a two-layer structure where the upper layer performs a target calculation based on a simplified steady-state optimization of the process. Here, it is proposed a methodology where a test signal is introduced in a tuning parameter of the target calculation layer. When the outputs are controlled by zones instead of at fixed set points, the approach allows the continuous operation of the process without an excessive disruption of the operating objectives as process constraints and product specifications remain satisfied during the identification test. The application of the method is illustrated through the simulation of two processes of the oil refining industry. (c) 2008 Elsevier Ltd. All rights reserved.

Direct regeneration of protocorm-like bodies (PLBs) from leaf apices of Oncidium flexuosum Sims (Orchidaceae)

The present study describes the direct regeneration of protocorm-like bodies (PLBs) in leaf explants of the tropical species Oncidium flexuosum. The explants were inoculated in a solid, modified Murashige and Skoog (MS) medium with different concentrations of the growth regulator thidiazuron (TDZ) and with or without 2,4-dichlorophenoxyacetic acid (2,4-D) and naphthalene acetic acid (NAA), and kept away from light or in a 16-h photoperiod. The presence of auxins, 2,4-D, and NAA inhibited the formation of PLBs. The highest frequency of explants that regenerated PLBs (80%) was obtained when they were maintained in a culture medium containing 1.5 mu M TDZ under dark conditions. In the same culture medium but under a 16-h photoperiod, 95% of the leaf explants presented necrosis. Therefore, darkness was crucial for the regeneration of PLBs in O. flexuosum leaf explants, which is in disagreement with the literature. PLBs developed from the division of epidermal and subepidermal cells mainly on the adaxial side of the apex region of the explant. Plants with well-developed leaves and roots grew after the PLBs were transferred to growth regulator-free medium under a 16-h photoperiod.

SELF-SIMILARITY AND LAMPERTI CONVERGENCE FOR FAMILIES OF STOCHASTIC PROCESSES

We define a new type of self-similarity for one-parameter families of stochastic processes, which applies to certain important families of processes that are not self-similar in the conventional sense. This includes Hougaard Levy processes such as the Poisson processes, Brownian motions with drift and the inverse Gaussian processes, and some new fractional Hougaard motions defined as moving averages of Hougaard Levy process. Such families have many properties in common with ordinary self-similar processes, including the form of their covariance functions, and the fact that they appear as limits in a Lamperti-type limit theorem for families of stochastic processes.