Artificial neural networks analysis of Sao Paulo subway tunnel settlement data

Artificial neural networks have been used to analyze a number of engineering problems, including settlement caused by different tunneling methods in various types of ground mass. This paper focuses on settlement over shotcrete- supported tunnels on Sao Paulo subway line 2 (West Extension) that were excavated in Tertiary sediments using the sequential excavation method. The adjusted network is a good tool for predicting settlement above new tunnels to be excavated in similar conditions. The influence of network training parameters on the quality of results is also discussed. (C) 2007 Elsevier Ltd. All rights reserved.

Dynamics of sulfidogenesis associated to methanogenesis in horizontal-flow anaerobic immobilized biomass reactor

Two bench-scale horizontal anaerobic fixed bed reactors were tested to remove both sulfate and organic matter from wastewater. First, the reactors (R1 and R2) were supplied with synthetic wastewater containing sulfate and a solution of ethanol and volatile fatty acids. Subsequently, RI and R2 were fed with only ethanol or acetate, respectively. The substitution to ethanol in R1 increased the sulfate reduction efficiency from 83% to nearly 100% for a chemical oxygen demand to sulfate (COD/sulfate) ratio of 3.0. In contrast, in R2, the switch in carbon source to acetate strongly decreased sulfidogenesis and the maximum sulfate reduction achieved was 47%. Process stability in long-term experiments and high removal efficiencies of both organic matter and sulfate were achieved with ethanol as the sole carbon source. The results allow concluding that syntrophism instead of competition between the sulfate reducing bacteria and acetoclastic methanogenic archaeal populations prevailed in the reactor. (C) 2009 Elsevier Ltd. All rights reserved.

Performance of a horizontal-flow anaerobic immobilized biomass (HAIB) reactor and dynamics of the microbial community during degradation of pentachlorophenol (PCP)

The anaerobic biological treatment of pentachlorophenol (PCP) and methanol as the main carbon source was investigated in a horizontal-flow anaerobic immobilized biomass (HAIB) reactor at 30 +/- 1 degrees C, during a 220-day trial period. The reactor biomass was developed as an attached biofilm on polyurethane foam particles, with 24 h of hydraulic retention time. The PCP concentrations, which ranged from 2.0 to 13.0 mg/L, were controlled by adding synthetic substrate. The HAIB reactor reduced 97% of COD and removed 99% of PCP. The microbial biofilm communities of the HAIB reactor amended with PCP, without previous acclimatization, were characterized by polymerase chain reaction (PCR) and amplified ribosomal DNA restriction analysis (ARDRA) with specific Archaea oligonucleotide primers. The ARDRA technique provided an adequate analysis of the community, revealing the profile of the selected population along the reactor. The biomass activities in the HAIB reactor at the end of the experiments indicated the development of PCP degraders and the maintenance of the population of methanogenic Archaea, ensuring the high efficiency of the system treating PCP with added methanol as the cosubstrate. The use of the simplified ARDRA method enabled us to monitor the microbial population with the addition of high concentrations of toxic compounds and highlighting a selection of microorganisms in the biofilm. (C) 2008 Published by Elsevier Ltd.

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.

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.

An exact conserving algorithm for nonlinear dynamics with rotational DOFs and general hyperelasticity. Part 2: shells

Following the approach developed for rods in Part 1 of this paper (Pimenta et al. in Comput. Mech. 42:715-732, 2008), this work presents a fully conserving algorithm for the integration of the equations of motion in nonlinear shell dynamics. We begin with a re-parameterization of the rotation field in terms of the so-called Rodrigues rotation vector, allowing for an extremely simple update of the rotational variables within the scheme. The weak form is constructed via non-orthogonal projection, the time-collocation of which ensures exact conservation of momentum and total energy in the absence of external forces. Appealing is the fact that general hyperelastic materials (and not only materials with quadratic potentials) are permitted in a totally consistent way. Spatial discretization is performed using the finite element method and the robust performance of the scheme is demonstrated by means of numerical examples.

An exact conserving algorithm for nonlinear dynamics with rotational DOFs and general hyperelasticity. Part 1: Rods

A fully conserving algorithm is developed in this paper for the integration of the equations of motion in nonlinear rod dynamics. The starting point is a re-parameterization of the rotation field in terms of the so-called Rodrigues rotation vector, which results in an extremely simple update of the rotational variables. The weak form is constructed with a non-orthogonal projection corresponding to the application of the virtual power theorem. Together with an appropriate time-collocation, it ensures exact conservation of momentum and total energy in the absence of external forces. Appealing is the fact that nonlinear hyperelastic materials (and not only materials with quadratic potentials) are permitted without any prejudice on the conservation properties. Spatial discretization is performed via the finite element method and the performance of the scheme is assessed by means of several numerical simulations.

Study of the influence of simultaneous variation of magnetic material microstructural features on domain wall dynamics

The magnetic Barkhausen noise (MBN) is a phenomenon sensitive to several kinds of magnetic material microstructure changes, as well as to variations in material plastic deformation and stress. This fact stimulates the development of MBN-based non-destructive testing (NDT) techniques for analyzing magnetic materials, being the proposition of such a method, the main objective of the present study. The behavior of the MBN signal envelope, under simultaneous variations of carbon content and plastic deformation, is explained by the domain wall dynamics. Additionally, a non-destructive parameter for the characterization of each of these factors is proposed and validated through the experimental results. (C) 2010 Elsevier B.V. All rights reserved.

Flow Visualization in Arteriovenous Fistula and Aneurysm Using Computational Fluid Dynamics

The arteriovenous fistula (AVF) is characterized by enhanced blood flow and is the most widely used vascular access for chronic haemodialysis (Sivanesan et al., 1998). A large proportion of the AVF late failures are related to local haemodynamics (Sivanesan et al., 1999a). As in AVF, blood flow dynamics plays an important role in growth, rupture, and surgical treatment of aneurysm. Several techniques have been used to study the flow patterns in simplified models of vascular anastomose and aneurysm. In the present investigation, Computational Fluid Dynamics (CFD) is used to analyze the flow patterns in AVF and aneurysm through the velocity waveform obtained from experimental surgeries in dogs (Galego et al., 2000), as well as intra-operative blood flow recordings of patients with radiocephalic AVF ( Sivanesan et al., 1999b) and physiological pulses (Aires, 1991), respectively. The flow patterns in AVF for dog and patient surgeries data are qualitatively similar. Perturbation, recirculation and separation zones appeared during cardiac cycle, and these were intensified in the diastole phase for the AVF and aneurysm models. The values of wall shear stress presented in this investigation of AVF and aneurysm models oscillated in the range that can both cause damage to endothelial cells and develop atherosclerosis.

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.

DEVELOPMENT OF STATIC MIXERS FOR MISCIBLE FLUIDS IN LAMINAR FLOW WITH THE USE OF COMPUTATIONAL FLUID DYNAMICS (CFD)

Static mixers with improved performance were developed from CFD simulations in a stepwise approach. The relevant geometric features of simple mixer designs and the corresponding mixing mechanisms-laminar shear, elongational flow, and distributive mixing-were identified first. This information was used to formulate guidelines for the development of new geometries. The solid elements of the static mixer should: (a) provide restrictions to the flow; (b) deflect the flow; (c) be sequentially rotated around the flow direction to provide symmetry; (d) extend from the center of the pipe to the vicinity of the walls to avoid short-circuiting; and (e) distribute and remix the flow. Based on these guidelines, two improved mixer designs were developed: the DS A-I mixer has a good mixing efficiency and an acceptable pressure drop; the Fins 35 degrees mixer is more efficient and compact, but requires a larger pressure drop. Their performance indicates that their use is possible on industrial applications.

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.

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.

Computational fluid dynamics investigation of a centrifugal blood pump

In the development of a ventricular assist device, computational fluid dynamics (CFD) analysis is an efficient tool to obtain the best design before making the final prototype. In this study, different designs of a centrifugal blood pump were developed to investigate flow characteristics and performance. This study assumed the blood flow as being an incompressible homogeneous Newtonian fluid. A constant velocity was applied at the inlet; no slip boundary conditions were applied at device wall; and pressure boundary conditions were applied at the outlet. The CFD code used in this work was based on the finite volume method. In the future, the results of CFD analysis can be compared with flow visualization and hemolysis tests.

Using indicators of deforestation and land-use dynamics to support conservation strategies: A case study of central Rondonia, Brazil

In Rondonia State, Brazil, settlement processes have cleared 68,000 km 2 of tropical forests since the 1970s. The intensity of deforestation has differed by region depending on driving factors like roads and economic activities. Different histories of land-use activities and rates of change have resulted in mosaics of forest patches embedded in an agricultural matrix. Yet, most assessments of deforestation and its effects on vegetation, soil and water typically focus on landscape patterns of current conditions, yet historical deforestation dynamics can influence current conditions strongly. Here, we develop and describe the use of four land-use dynamic indicators to capture historical land-use changes of catchments and to measure the rate of deforestation (annual deforestation rate), forest regeneration level (secondary forest mean proportion), time since disturbance (mean time since deforestation) and deforestation profile (deforestation profile curvature). We used the proposed indices to analyze a watershed located in central Rondonia. Landsat TM and ETM+ images were used to produce historical land-use maps of the last 18 years, each even year from 1984 to 2002 for 20 catchments. We found that the land-use dynamics indicators are able to distinguish catchments with different land-use change profiles. Four categories of historical land-use were identified: old and dominant pasture cover on small properties, recent deforestation and dominance of secondary growth, old extensive pastures and large forest remnants and, recent deforestation, pasture and large forest remnants. Knowing historical deforestation processes is important to develop appropriate conservation strategies and define priorities and actions for conserving forests currently under deforestation. (C) 2009 Elsevier B.V. All rights reserved.