Implementation of a Control Loop Experiment in a Network-Based Control System With LonWorks Technology and IP Networks

Considering the increasing popularity of network-based control systems and the huge adoption of IP networks (such as the Internet), this paper studies the influence of network quality of service (QoS) parameters over quality of control parameters. An example of a control loop is implemented using two LonWorks networks (CEA-709.1) interconnected by an emulated IP network, in which important QoS parameters such as delay and delay jitter can be completely controlled. Mathematical definitions are provided according to the literature, and the results of the network-based control loop experiment are presented and discussed.

A survey on key management mechanisms for distributed Wireless Sensor Networks

Wireless Sensor Networks (WSNs) have a vast field of applications, including deployment in hostile environments. Thus, the adoption of security mechanisms is fundamental. However, the extremely constrained nature of sensors and the potentially dynamic behavior of WSNs hinder the use of key management mechanisms commonly applied in modern networks. For this reason, many lightweight key management solutions have been proposed to overcome these constraints. In this paper, we review the state of the art of these solutions and evaluate them based on metrics adequate for WSNs. We focus on pre-distribution schemes well-adapted for homogeneous networks (since this is a more general network organization), thus identifying generic features that can improve some of these metrics. We also discuss some challenges in the area and future research directions. (C) 2010 Elsevier B.V. All rights reserved.

A Taxonomy for Locality Algorithms on Peer-to-Peer Networks

The continuous growth of peer-to-peer networks has made them responsible for a considerable portion of the current Internet traffic. For this reason, improvements in P2P network resources usage are of central importance. One effective approach for addressing this issue is the deployment of locality algorithms, which allow the system to optimize the peers` selection policy for different network situations and, thus, maximize performance. To date, several locality algorithms have been proposed for use in P2P networks. However, they usually adopt heterogeneous criteria for measuring the proximity between peers, which hinders a coherent comparison between the different solutions. In this paper, we develop a thoroughly review of popular locality algorithms, based on three main characteristics: the adopted network architecture, distance metric, and resulting peer selection algorithm. As result of this study, we propose a novel and generic taxonomy for locality algorithms in peer-to-peer networks, aiming to enable a better and more coherent evaluation of any individual locality algorithm.

A New Approach for Video Adaptation through Overlay Services Networks

Video adaptation is an extensively explored content providing technique aimed at appropriately suiting several usage scenarios featured by different network requirements and constraints, user`s terminal and preferences. However, its usage in high-demand video distribution systems, such as CNDs, has been badly approached, ignoring several aspects of optimization of network use. To address such deficiencies, this paper presents an approach for implementing the adaptation service by exploring the concept of overlay services networks. As a result of demonstrate the benefits of this proposal, it is made a comparison of this proposed adaptation service with other strategies of video adaptation.

Hybrid Method to Assess Sensitive Process Interruption Costs Due to Faults in Electric Power Distribution Networks

This paper shows a new hybrid method for risk assessment regarding interruptions in sensitive processes due to faults in electric power distribution systems. This method determines indices related to long duration interruptions and short duration voltage variations (SDVV), such as voltage sags and swells in each customer supplied by the distribution network. Frequency of such occurrences and their impact on customer processes are determined for each bus and classified according to their corresponding magnitude and duration. The method is based on information regarding network configuration, system parameters and protective devices. It randomly generates a number of fault scenarios in order to assess risk areas regarding long duration interruptions and voltage sags and swells in an especially inventive way, including frequency of events according to their magnitude and duration. Based on sensitivity curves, the method determines frequency indices regarding disruption in customer processes that represent equipment malfunction and possible process interruptions due to voltage sags and swells. Such approach allows for the assessment of the annual costs associated with each one of the evaluated power quality indices.

Reconfiguration of distribution networks to minimize loss and disruption costs using genetic algorithms

In this paper a computational implementation of an evolutionary algorithm (EA) is shown in order to tackle the problem of reconfiguring radial distribution systems. The developed module considers power quality indices such as long duration interruptions and customer process disruptions due to voltage sags, by using the Monte Carlo simulation method. Power quality costs are modeled into the mathematical problem formulation, which are added to the cost of network losses. As for the EA codification proposed, a decimal representation is used. The EA operators, namely selection, recombination and mutation, which are considered for the reconfiguration algorithm, are herein analyzed. A number of selection procedures are analyzed, namely tournament, elitism and a mixed technique using both elitism and tournament. The recombination operator was developed by considering a chromosome structure representation that maps the network branches and system radiality, and another structure that takes into account the network topology and feasibility of network operation to exchange genetic material. The topologies regarding the initial population are randomly produced so as radial configurations are produced through the Prim and Kruskal algorithms that rapidly build minimum spanning trees. (C) 2009 Elsevier B.V. All rights reserved.

Transmission lines distance protection using artificial neural networks

This work presents the development and implementation of an artificial neural network based algorithm for transmission lines distance protection. This algorithm was developed to be used in any transmission line regardless of its configuration or voltage level. The described ANN-based algorithm does not need any topology adaptation or ANN parameters adjustment when applied to different electrical systems. This feature makes this solution unique since all ANN-based solutions presented until now were developed for particular transmission lines, which means that those solutions cannot be implemented in commercial relays. (c) 2011 Elsevier Ltd. All rights reserved.

Approximate algorithms for credal networks with binary variables

This paper presents a family of algorithms for approximate inference in credal networks (that is, models based on directed acyclic graphs and set-valued probabilities) that contain only binary variables. Such networks can represent incomplete or vague beliefs, lack of data, and disagreements among experts; they can also encode models based on belief functions and possibilistic measures. All algorithms for approximate inference in this paper rely on exact inferences in credal networks based on polytrees with binary variables, as these inferences have polynomial complexity. We are inspired by approximate algorithms for Bayesian networks; thus the Loopy 2U algorithm resembles Loopy Belief Propagation, while the Iterated Partial Evaluation and Structured Variational 2U algorithms are, respectively, based on Localized Partial Evaluation and variational techniques. (C) 2007 Elsevier Inc. All rights reserved.

Comparison of adsorbent films obtained by plasma polymerization of oxygenated organic compounds

Thin films obtained by plasma polymerization of ethyl ether, methyl or ethyl acetate, acetaldehyde, acetone and 2-propanol were compared. Infrared spectroscopy (FFIR), resistance to chemicals, contact angle measurements, X-ray photoelectron spectroscopy (XPS), optical and scanning electron microscopy (SEM), and quartz crystal microbalance (QCM) were carried out. For all films FTIR showed high intensity for polar bonds yet the films are not resistant to polar solvents. Contact angle measurements revealed hydrophilic and organophilic surfaces and XPS pointed out a high proportion of oxygenated bonds. All films showed good step coverage and peeling was significant only with acetone and 2-propanol. All films are adsorbent for organic compounds in a large scale of polarity but acetaldehyde and 2-propanol act like a selective membrane. Also, deposition of these films on hydrophobic substrates leads to island formation. A possible model to explain the results must consider the hydrogen bridge formation on 2-propanol and acetaldehyde films. Ethyl ether, ethyl and methyl acetate showed good characteristics for development of sensor and sample pretreatment using miniaturized devices. (C) 2007 Elsevier B.V. All rights reserved.

Influence of the Type of Quaternary Ammonium Salt Used in the Organic Treatment of Montmorillonite on the Properties of Poly(Styrene-co-Butyl Acrylate)/Layered Silicate Nanocomposites Prepared by In Situ Miniemulsion Polymerization

Hybrid latices of poly(styrene-co-butyl acrylate) were synthesized via in situ miniemulsion polymerization in the presence of 3 and 6 wt % organically modified montmorillonite (OMMT). Three different ammonium salts: cetyl trimethyl ammonium chloride (CTAC), alkyl dimethyl benzyl ammonium chloride (Dodigen), and distearyl dimethyl ammonium chloride (Praepagen), were investigated as organic modifiers. Increased affinity for organic liquids was observed after organic modification of the MMT. Stable hybrid latices were obtained even though miniemulsion stability was disturbed to some extent by the presence of the OMMTs during the synthesis. Highly intercalated and exfoliated polymer-MMT nanocomposites films were produced with good MMT dispersion throughout the polymeric matrix. Materials containing MMT modified with the 16 carbons alkyl chain salt (CTAC) resulted in the largest increments of storage modulus, indicating that single chain quaternary salts provide higher increments on mechanical properties. Films presenting exfoliated structure resulted in the largest increments in the onset temperature of decomposition. For the range of OMMT loading studied, the nanocomposite structure influenced more significantly the thermal stability properties of the hybrid material than did the OMMT loading. The film containing 3 wt % MMT modified with the two 18 carbons alkyl chains salt (Praepagen) provided the highest increment of onset temperature of decomposition. (C) 2010 Wiley Periodicals, Inc. J Appl Polym Sci 119: 3658-3669, 2011

MODELING ELECTRODIALYSIS AND A PHOTOCHEMICAL PROCESS FOR THEIR INTEGRATION IN SALINE WASTEWATER TREATMENT

Oxidation processes can be used to treat industrial wastewater containing non-biodegradable organic compounds. However, the presence of dissolved salts may inhibit or retard the treatment process. In this study, wastewater desalination by electrodialysis (ED) associated with an advanced oxidation process (photo-Fenton) was applied to an aqueous NaCl solution containing phenol. The influence of process variables on the demineralization factor was investigated for ED in pilot scale and a correlation was obtained between the phenol, salt and water fluxes with the driving force. The oxidation process was investigated in a laboratory batch reactor and a model based on artificial neural networks was developed by fitting the experimental data describing the reaction rate as a function of the input variables. With the experimental parameters of both processes, a dynamic model was developed for ED and a continuous model, using a plug flow reactor approach, for the oxidation process. Finally, the hybrid model simulation could validate different scenarios of the integrated system and can be used for process optimization.

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.

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.

Optimal synthesis of Fenton reactor networks for phenol degradation

There is an increasing need to treat effluents contaminated with phenol with advanced oxidation processes (AOPs) to minimize their impact on the environment as well as on bacteriological populations of other wastewater treatment systems. One of the most promising AOPs is the Fenton process that relies on the Fenton reaction. Nevertheless, there are no systematic studies on Fenton reactor networks. The objective of this paper is to develop a strategy for the optimal synthesis of Fenton reactor networks. The strategy is based on a superstructure optimization approach that is represented as a mixed integer non-linear programming (MINLP) model. Network superstructures with multiple Fenton reactors are optimized with the objective of minimizing the sum of capital, operation and depreciation costs of the effluent treatment system. The optimal solutions obtained provide the reactor volumes and network configuration, as well as the quantities of the reactants used in the Fenton process. Examples based on a case study show that multi-reactor networks yield decrease of up to 45% in overall costs for the treatment plant. (C) 2010 The Institution of Chemical Engineers. Published by Elsevier B.V. All rights reserved.

Porous silicon optical cavity structure applied to high sensitivity organic solvent sensor

The present work reports the thermal annealing process, the number of layer and electrochemical process effect in the optical response quality of Bragg and microcavity devices that were applied as organic solvent sensors. These devices have been obtained by using porous silicon (PS) technology. The optical characterization of the Bragg reflector, before annealing, showed a broad photonic band-gap structure with blue shifted and narrowed after annealing process. The electrochemical process used to obtain the PS-based device imposes the limit in the number of layers because of the chemical dissolution effect. The interface roughness minimizations in the devices have been achieved by using the double electrochemical cell setup. The microcavity devices showed to have a good sensibility for organic solvent detection. The thermal annealed device showed better sensibility feature and this result was attributed to passivation of the surface devices. (c) 2007 Elsevier Ltd. All rights reserved.