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.

The natural force density method for the shape finding of taut structures

This work presents, with the aid of the natural approach, an extension of the force density method for the initial shape finding of cable and membrane structures, which leads to the solution of a system of linear equations. This method, here called the natural force density method, preserves the linearity which characterizes the original force density method. At the same time, it overcomes the difficulties that the original procedure presents to cope with irregular triangular finite element meshes. Furthermore, if this method is applied iteratively in the lines prescribed herewith, it leads to a viable initial configuration with a uniform, isotropic plane Cauchy stress state. This means that a minimal surface for the membrane can be achieved through a succession of equilibrated configurations. Several numerical examples illustrate the simplicity and robustness of the method. (C) 2008 Elsevier B.V. All rights reserved.

Comparison between detailed model simulation and artificial neural network for forecasting building energy consumption

There are several ways to attempt to model a building and its heat gains from external sources as well as internal ones in order to evaluate a proper operation, audit retrofit actions, and forecast energy consumption. Different techniques, varying from simple regression to models that are based on physical principles, can be used for simulation. A frequent hypothesis for all these models is that the input variables should be based on realistic data when they are available, otherwise the evaluation of energy consumption might be highly under or over estimated. In this paper, a comparison is made between a simple model based on artificial neural network (ANN) and a model that is based on physical principles (EnergyPlus) as an auditing and predicting tool in order to forecast building energy consumption. The Administration Building of the University of Sao Paulo is used as a case study. The building energy consumption profiles are collected as well as the campus meteorological data. Results show that both models are suitable for energy consumption forecast. Additionally, a parametric analysis is carried out for the considered building on EnergyPlus in order to evaluate the influence of several parameters such as the building profile occupation and weather data on such forecasting. (C) 2008 Elsevier B.V. All rights reserved.

MODELLING AND CONTROL OF ERSW PROCESSES BY NEURONAL NETWORK

A study on the use of artificial intelligence (AI) techniques for the modelling and subsequent control of an electric resistance spot welding process (ERSW) is presented. The ERSW process is characterized by the coupling of thermal, electrical, mechanical, and metallurgical phenomena. For this reason, early attempts to model it using computational methods established as the methods of finite differences, finite element, and finite volumes, ask for simplifications that lead the model obtained far from reality or very costly in terms of computational costs, to be used in a real-time control system. In this sense, the authors have developed an ERSW controller that uses fuzzy logic to adjust the energy transferred to the weld nugget. The proposed control strategies differ in the speed with which it reaches convergence. Moreover, their application for a quality control of spot weld through artificial neural networks (ANN) is discussed.

Application of the essential work of fracture method in ranking the performance in service of high-density polyethylene resins employed in pressure pipes

High-density polyethylene resins have increasingly been used in the production of pipes for water- and gas-pressurized distribution systems and are expected to remain in service for several years, but they eventually fail prematurely by creep fracture. Usual standard methods used to rank resins in terms of their resistance to fracture are expensive and non-practical for quality control purposes, justifying the search for alternative methods. Essential work of fracture (EWF) method provides a relatively simple procedure to characterize the fracture behavior of ductile polymers, such as polyethylene resins. In the present work, six resins were analyzed using the EWF methodology. The results show that the plastic work dissipation factor, beta w(p), is the most reliable parameter to evaluate the performance. Attention must be given to specimen preparation that might result in excessive dispersion in the results, especially for the essential work of fracture w(e).

Effect of precracking method on K(Ic) results for medium-density polyethylene tested under cryogenic condition

The effect of different precracking methods on the results of linear elastic K(Ic) fracture toughness testing with medium-density polyethylene (MDPE) was investigated. Cryogenic conditions were imposed in order to obtain valid K(Ic) values from specimens of suitable size. Most conservative K(Ic) values were obtained by slow pressing a fresh razor blade at the notch root of the specimen. Due to the low deformation level imposed on the crack tip region, the slow pressing razor blade technique also produced less scatter in fracture toughness results. It has been shown that the slow stable crack growth preceding catastrophic brittle failure during K(Ic) tests in MOPE under cryogenic conditions should not be disregarded as it has relevant physical meaning and may affect the fracture toughness results. (C) 2010 Elsevier Ltd. All rights reserved.

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.

Distributed Estimation Over an Adaptive Incremental Network Based on the Affine Projection Algorithm

We study the problem of distributed estimation based on the affine projection algorithm (APA), which is developed from Newton`s method for minimizing a cost function. The proposed solution is formulated to ameliorate the limited convergence properties of least-mean-square (LMS) type distributed adaptive filters with colored inputs. The analysis of transient and steady-state performances at each individual node within the network is developed by using a weighted spatial-temporal energy conservation relation and confirmed by computer simulations. The simulation results also verify that the proposed algorithm provides not only a faster convergence rate but also an improved steady-state performance as compared to an LMS-based scheme. In addition, the new approach attains an acceptable misadjustment performance with lower computational and memory cost, provided the number of regressor vectors and filter length parameters are appropriately chosen, as compared to a distributed recursive-least-squares (RLS) based method.

Influence of substrate surface topography in the deposition of nanostructured diamond-like carbon films by high density plasma chemical vapor deposition

In this work, we have studied the influence of the substrate surface condition on the roughness and the structure of the nanostructured DLC films deposited by High Density Plasma Chemical Vapor Deposition. Four methods were used to modify the silicon wafers surface before starting the deposition processes of the nanostructured DLC films: micro-diamond powder dispersion, micro-graphite powder dispersion, and roughness generation by wet chemical etching and roughness generation by plasma etching. The reference wafer was only submitted to a chemical cleaning. It was possible to see that the final roughness and the sp(3) hybridization degree strongly depend on the substrate surface conditions. The surface roughness was observed by AFM and SEM and the hybridization degree of the DLC films was analyzed by Raman Spectroscopy. In these samples, the final roughness and the sp(3) hybridization quantity depend strongly on the substrate surface condition. Thus, the effects of the substrate surface on the DLC film structure were confirmed. These phenomena can be explained by the fact that the locally higher surface energy and the sharp edges may induce local defects promoting the nanostructured characteristics in the DLC films. (C) 2008 Elsevier B.V. All rights reserved.

Improved effective charge density in MOS capacitors with PECVD SiOxNy dielectric layer obtained at low RF power

In this work SiOxNy films are produced and characterized. Series of samples were deposited by the plasma enhanced chemical vapor deposition (PECVD) technique at low temperatures from silane (SiH4), nitrous oxide (N2O) and helium (He) precursor gaseous mixtures, at different deposition power in order to analyze the effect of this parameter on the films structural properties, on the SiOxNy/Si interface quality and on the SiOxNy effective charge density. In order to compare the film structural properties with the interface (SiOxNy/Si) quality and effective charge density, MOS capacitors were fabricated using these films as dielectric layer. X-ray absorption near-edge spectroscopy (XANES), at the Si-K edge, was utilized to investigate the structure of the films and the material bonding characteristics were analyzed through Fourier transform infrared spectroscopy (FTIR). The MOS capacitors were characterized by low and high frequency capacitance (C-V) measurements, in order to obtain the interface state density (D-it) and the effective charge density (N-ss). An effective charge density linear reduction for decreasing deposition power was observed, result that is attributed to the smaller amount of ions present in the plasma for low RF power. (C) 2008 Elsevier B.V. All rights reserved.

Who should wear mask against airborne infections? Altering the contact network for controlling the spread of contagious diseases

There are several ways of controlling the propagation of a contagious disease. For instance, to reduce the spreading of an airborne infection, individuals can be encouraged to remain in their homes and/or to wear face masks outside their domiciles. However, when a limited amount of masks is available, who should use them: the susceptible subjects, the infective persons or both populations? Here we employ susceptible-infective-recovered (SIR) models described in terms of ordinary differential equations and probabilistic cellular automata in order to investigate how the deletion of links in the random complex network representing the social contacts among individuals affects the dynamics of a contagious disease. The inspiration for this study comes from recent discussions about the impact of measures usually recommended by health public organizations for preventing the propagation of the swine influenza A (H1N1) virus. Our answer to this question can be valid for other eco-epidemiological systems. (C) 2010 Elsevier BM. All rights reserved.

Network of phase-locking oscillators and a possible model for neural synchronization

In order to model the synchronization of brain signals, a three-node fully-connected network is presented. The nodes are considered to be voltage control oscillator neurons (VCON) allowing to conjecture about how the whole process depends on synaptic gains, free-running frequencies and delays. The VCON, represented by phase-locked loops (PLL), are fully-connected and, as a consequence, an asymptotically stable synchronous state appears. Here, an expression for the synchronous state frequency is derived and the parameter dependence of its stability is discussed. Numerical simulations are performed providing conditions for the use of the derived formulae. Model differential equations are hard to be analytically treated, but some simplifying assumptions combined with simulations provide an alternative formulation for the long-term behavior of the fully-connected VCON network. Regarding this kind of network as models for brain frequency signal processing, with each PLL representing a neuron (VCON), conditions for their synchronization are proposed, considering the different bands of brain activity signals and relating them to synaptic gains, delays and free-running frequencies. For the delta waves, the synchronous state depends strongly on the delays. However, for alpha, beta and theta waves, the free-running individual frequencies determine the synchronous state. (C) 2011 Elsevier B.V. All rights reserved.

Route to chaos in a third-order phase-locked loop network

Phase-locked loops (PLLs) are widely used in applications related to control systems and telecommunication networks. Here we show that a single-chain master-slave network of third-order PLLs can exhibit stationary, periodic and chaotic behaviors, when the value of a single parameter is varied. Hopf, period-doubling and saddle-saddle bifurcations are found. Chaos appears in dissipative and non-dissipative conditions. Thus, chaotic behaviors with distinct dynamical features can be generated. A way of encoding binary messages using such a chaos-based communication system is suggested. (C) 2009 Elsevier B.V. All rights reserved.

Optimized network structure for full-synchronization

A network of Kuramoto oscillators with different natural frequencies is optimized for enhanced synchronizability. All node inputs are normalized by the node connectivity and some important properties of the network Structure are determined in this case: (i) optimized networks present a strong anti-correlation between natural frequencies of adjacent nodes: (ii) this anti-correlation should be as high as possible since the average path length between nodes is maintained as small as in random networks: and (iii) high anti-correlation is obtained without any relation between nodes natural frequencies and the degree of connectivity. We also propose a network construction model with which it is shown that high anti-correlation and small average paths may be achieved by randomly rewiring a fraction of the links of a totally anti-correlated network, and that these networks present optimal synchronization properties. (C) 2008 Elsevier B.V. All rights reserved.

On the basic reproduction number and the topological properties of the contact network: An epidemiological study in mainly locally connected cellular automata

We study the spreading of contagious diseases in a population of constant size using susceptible-infective-recovered (SIR) models described in terms of ordinary differential equations (ODEs) and probabilistic cellular automata (PCA). In the PCA model, each individual (represented by a cell in the lattice) is mainly locally connected to others. We investigate how the topological properties of the random network representing contacts among individuals influence the transient behavior and the permanent regime of the epidemiological system described by ODE and PCA. Our main conclusions are: (1) the basic reproduction number (commonly called R(0)) related to a disease propagation in a population cannot be uniquely determined from some features of transient behavior of the infective group; (2) R(0) cannot be associated to a unique combination of clustering coefficient and average shortest path length characterizing the contact network. We discuss how these results can embarrass the specification of control strategies for combating disease propagations. (C) 2009 Elsevier B.V. All rights reserved.