Performance analysis of an optical network employing waveband and traffic grooming

This paper analyses an optical network architecture composed by an arrangement of nodes equipped with multi-granular optical cross-connects (MG-OXCs) in addition to the usual optical cross-connects (OXCs). Then, selected network nodes can perform both waveband as well as traffic grooming operations and our goal is to assess the improvement on network performance brought by these additional capabilities. Specifically, the influence of the MG-OXC multi-granularity on the blocking probability is evaluated for 16 classes of service over a network based on the NSFNet topology. A mechanism of fairness in bandwidth capacity is also added to the connection admission control to manage the blocking probabilities of all kind of bandwidth requirements. Comprehensive computational simulation are carried out to compare eight distinct node architectures, showing that an adequate combination of waveband and single-wavelength ports of the MG-OXCs and OXCs allow a more efficient operation of a WDM optical network carrying multi-rate traffic.

Neural network model for designing automotive devices using SMD LED

The advantages offered by the electronic component LED (Light Emitting Diode) have resulted in a quick and extensive application of this device in the replacement of incandescent lights. In this combined application, however, the relationship between the design variables and the desired effect or result is very complex and renders it difficult to model using conventional techniques. This paper consists of the development of a technique using artificial neural networks that makes it possible to obtain the luminous intensity values of brake lights using SMD (Surface Mounted Device) LEDs from design data. This technique can be utilized to design any automotive device that uses groups of SMD LEDs. The results of industrial applications using SMD LED are presented to validate the proposed technique.

Neural network-based H(infinity) control for fully actuated and underactuated cooperative manipulators

This paper develops H(infinity) control designs based on neural networks for fully actuated and underactuated cooperative manipulators. The neural networks proposed in this paper only adapt the uncertain dynamics of the robot manipulators. They work as a complement of the nominal model. The H(infinity) performance index includes the position errors as well the squeeze force errors between the manipulator end-effectors and the object, which represents a complete disturbance rejection scenario. For the underactuated case, the squeeze force control problem is more difficult to solve due to the loss of some degrees of manipulator actuation. Results obtained from an actual cooperative manipulator, which is able to work as a fully actuated and an underactuated manipulator, are presented. (C) 2008 Elsevier Ltd. All rights reserved.

AnSBBR Applied to a Personal Care Industry Wastewater Treatment: Effects of Fill Time, Volume Treated Per Cycle, and Organic Load

A study was performed regarding the effect of the relation between fill time, volume treated per cycle, and influent concentration at different applied organic loadings on the stability and efficiency of an anaerobic sequencing batch reactor containing immobilized biomass on polyurethane foam with recirculation of the liquid phase (AnSBBR) applied to the treatment of wastewater from a personal care industry. Total cycle length of the reactor was 8 h (480 min). Fill times were 10 min in the batch operation, 4 h in the fed-batch operation, and a 10-min batch followed by a 4-h fed batch in the mixed operation. Settling time was not necessary since the biomass was immobilized and decant time was 10 min. Volume of liquid medium in the reactor was 2.5 L, whereas volume treated per cycle ranged from 0.88 to 2.5 L in accordance with fill time. Influent concentration varied from 300 to 1,425 mg COD/L, resulting in an applied volumetric organic load of 0.9 and 1.5 g COD/L.d. Recirculation flow rate was 20 L/h, and the reactor was maintained at 30 A degrees C. Values of organic matter removal efficiency of filtered effluent samples were below 71% in the batch operations and above 74% in the operations of fed batch followed by batch. Feeding wastewater during part of the operational cycle was beneficial to the system, as it resulted in indirect control over the conversion of substrate into intermediates that would negatively interfere with the biochemical reactions regarding the degradation of organic matter. As a result, the average substrate consumption increased, leading to higher organic removal efficiencies in the fed-batch operations.

Characterization of micro-bubble size distribution and flow configuration in DAF contact zone by a non-intrusive image analysis system and tracer tests

This paper aims to investigate the influence of some dissolved air flotation (DAF) process variables (specifically: the hydraulic detention time in the contact zone and the supplied dissolved air concentration) and the pH values, as pretreatment chemical variables, on the micro-bubble size distribution (BSD) in a DAF contact zone. This work was carried out in a pilot plant where bubbles were measured by an appropriate non-intrusive image acquisition system. The results show that the obtained diameter ranges were in agreement with values reported in the literature (10-100mm), quite independently of the investigated conditions. The linear average diameter varied from 20 to 30mm, or equivalently, the Sauter (d(3,2)) diameter varied from 40 to 50mm. In all investigated conditions, D(50) was between 75% and 95%. The BSD might present different profile (with a bimodal curve trend), however, when analyzing the volumetric frequency distribution (in some cases with the appearance of peaks in diameters ranging from 90-100mm). Regarding volumetric frequency analysis, all the investigated parameters can modify the BSD in DAF contact zone after the release point, thus potentially causing changes in DAF kinetics. This finding prompts further research in order to verify the effect of these BSD changes on solid particle removal efficiency by DAF.

The influence of immobilized biomass and particle size on the fluid dynamics of an anaerobic fluidized bed reactor

Fluid dynamic analysis is an important branch of several chemical engineering related areas, such as drying processes and chemical reactors. However, aspects concerning fluid dynamics in wastewater treatment bioreactors still require further investigation, as they highly influence process efficiency. Therefore, it is essential to evaluate the influence of biofilm on the reactor fluid dynamic behavior, through the analysis of a few important parameters, such as minimum fluidization velocity, bed expansion and porosity, and particle terminal velocity. The main objective of the present work was to investigate the fluid dynamics of an anaerobic fluidized bed reactor, having activated carbon particles as support media for biomass immobilization. Reactor performance was tested using synthetic residual water, which was prepared using the solution employed in BOD determination. The results showed that the presence of immobilized biomass increased particle density and altered the main fluid dynamic parameters investigated.

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.

Particle size effect on abrasion resistance of mottled cast iron with different retained austenite contents

Effects of particle abrasive sizes on wear resistance of mottled cast iron with different retained austenite contents were studied. Abrasive wear tests using a pin test on alumina paper were carried out, using abrasive sizes between 16 mu m and 192 mu m. Retained austenite content of the matrix was determined by X-ray diffraction. The wear surface of samples and the alumina paper were examined by scanning electron microscopy for identifying the wear micromechanism. The results show that at lower abrasive sizes the mass loss was similar for the iron with different austenite contents. However, at higher abrasive sizes the samples with higher retained austenite content presented higher abrasion resistance. For lower abrasive sizes tested, samples with higher and lower retained austenite content both presented microcutting. On the other hand, the main wear micromechanism for the samples with higher retained austenite content and higher abrasive sizes was microploughing. The samples with lower retained austenite content presented microcutting and wedge formation at higher abrasive sizes. Higher abrasive size induced more microcutting in samples with lower retained austenite. The iron with lower retained austenite content presented wider grooves for the different abrasive sizes measured. SEM on the abrasive paper used on samples with higher retained austenite showed continuous and discontinuous microchips and the samples with lower retained austenite showed discontinuous microchips at 66 and 141 mu m. This research demonstrates the relation between abrasive size, wear resistance, groove width and wear micromechanism for mottled cast iron with different retained austenite contents. (C) 2009 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.

Combining Mager and Steinmetz: The Effect of Grain Size and Maximum Induction on Hysteresis Energy Loss

Twelve samples with different grain sizes were prepared by normal grain growth and by primary recrystallization, and the hysteresis dissipated energy was measured by a quasi-static method. Results showed a linear relation between hysteresis energy loss and the inverse of grain size, which is here called Mager`s law, for maximum inductions from 0.6 to 1.5 T, and a Steinmetz power law relation between hysteresis loss and maximum induction for all samples. The combined effect is better described by a Mager`s law where the coefficients follow Steinmetz law.

Influence of Temperature, Basiscity and Particle Size on MnO Reduction

The aim of this work is to study MnO reduction by solid carbon. The influence of size of carbon particles, slag basicity, and bath temperature on MnO reduction was investigated. Fine Manganese ore particles were used as a source of MnO. Three sizes of carbon particles were used; 0.230 mm, 0.162 mm and 0.057 mm, binary basicity of 1 and 1.5 and temperatures of 1550, 1550 and 1600 degrees C. Curves were drawn for Mn content in the bath as a function of time and temperature for the several studied parameters. The MnO reduction rates were determined using these data. [doi:10.2320/matertrans.M2011007]

In-Line Monitoring of Particle Size during Emulsion Polymerization under Different Operational Conditions using NIR Spectroscopy

In the present work, the sensitivity of NIR spectroscopy toward the evolution of particle size was studied during emulsion homopolymerization of styrene (Sty) and emulsion copolymerization of vinyl acetate-butyl acrylate conducted in a semibatch stirred tank and a tubular pulsed sieve plate reactor, respectively. All NIR spectra were collected online with a transflectance probe immersed into the reaction medium. The spectral range used for the NIR monitoring was from 9 500 to 13 000 cm(-1), where the absorbance of the chemical components present is minimal and the changes in the NIR spectrum can be ascribed to the effects of light scattering by the polymer particles. Off-line measurements of the average diameter of the polymer particles by DLS were used as reference values for the development of the multi-variate NIR calibration models based on partial least squares. Results indicated that, in the spectral range studied, it is possible to monitor the evolution of the average size of the polymer particles during emulsion polymerization reactions. The inclusion of an additional spectral range, from 5 701 to 6 447 cm(-1), containing information on absorbances (""chemical information"") in the calibration models was also evaluated.

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.

Scatter search for a real-life heterogeneous fleet vehicle routing problem with time windows and split deliveries in Brazil

In this paper, we consider a real-life heterogeneous fleet vehicle routing problem with time windows and split deliveries that occurs in a major Brazilian retail group. A single depot attends 519 stores of the group distributed in 11 Brazilian states. To find good solutions to this problem, we propose heuristics as initial solutions and a scatter search (SS) approach. Next, the produced solutions are compared with the routes actually covered by the company. Our results show that the total distribution cost can be reduced significantly when such methods are used. Experimental testing with benchmark instances is used to assess the merit of our proposed procedure. (C) 2008 Published by Elsevier B.V.