Partial characterization of the polluting load of swine wastewater treated with an integrated biodigestion system

The stabilization of swine wastewaters from swine confined housing by the combination of a upflow anaerobic sludge blanket (UASB) reactor and waste stabilization ponds is a viable alternative to minimize the environmental impact caused by inadequate disposal of swine wastewaters. In the present study, the polluting load of pre-decanted swine wastewater treated with a series of two 0.705 m(3) UASB reactors and then in parallel in aerated and non-aerated stabilization tanks was investigated from January to July, 2000. Physicochemical and microbiological analyses were made adopting standard methods (Standard Methods for Examination of Water and Wastewater, 19th ed., American Public Health Association, Washington, DC, 1995). COD values decreased as the wastewater ran through the integrated biodigestion system dropping from about 3492 +/- 511-4094 mg l(-1) +/- 481 to 124 +/- 52-490 mg l(-1) +/- 230, while nitrate and nitrite levels increased in stabilization tanks, ranging respectively from 4 +/- 0 to 20 mg l(-1) +/- 3 and 3 +/- 1 to 11 mg l(-1) +/- 24. Although the removal of Escherichia coli was more than 97% +/- 6, the effluents of the treatment system still contained unacceptable levels of E. coli (1.6 x 10(3)-1.2 x 10(6) 100 ml(-1)) according to WHO guidelines for use of wastewater in agriculture and aquaculture. These results indicate the necessity of changes on operational characteristics of the treatment system such as an increase of the hydraulic retention time in UASB reactors or in stabilization tanks. (C) 2003 Published by Elsevier Ltd.

Analysis of efficiency and rationality in a sugar-alcohol mill using hyperboloid a-load and potency

Brazil is the world's largest producer of sugar cane and which in the state of São Paulo concentrate the greatest amount of sugar cane field of the country. The sugar-alcohol sector has the capacity to produce sufficient thermal and electrical energy to be used in their process of production and commercialize of surplus in electricity distribution network. Therefore it is necessary to evaluate the energy efficiency and rationality within the mill. Accordingly this research proposed analyze the sugar-alcohol mill's sectors globally and individually, located in the west center of the São Paulo state, using the valuation methodology employed by the Agência Nacional de Energia Elétrica (ANEEL) in the industries that do not have systems of cogeneration. In this analysis, the hyperboloids of load and potency were applied based on the indexes of potency factor and load factor that allow estimate the efficiency and rationality. © 2013 IEEE.

Immunization of Wistar female rats with 255-Gy-irradiated Toxoplasma gondii: Preventing parasite load and maternofoetal transmission

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Comparison of microbial load in immersion chilling water and poultry carcasses after 8, 16 and 24 working hours

As atividades dos estabelecimentos de abate de frangos são conhecidas por utilizarem grandes volumes de água durante seus processos, principalmente no processo de resfriamento das carcaças de frangos. Parte desse volume utilizado se faz necessário, em cumprimento à legislação que determina que cada tanque do sistema de pré-resfriadores contínuos por imersão deve ser completamente esvaziado, limpo e desinfetado no final de cada período de trabalho (oito horas). O objetivo deste estudo foi comparar a carga microbiana das águas do sistema de resfriamento e das carcaças de frango ao final de oito, dezesseis e vinte e quatro horas de trabalho do abatedouro, para possível redução do número de vezes do completo esvaziamento dos tanques do sistema de resfriamento. Foram avaliadas, por meio de métodos convencionais microbiológicos e físico-químicos, amostras da água de abastecimento (n=69), visando a evitar possível interferência nas contagens das águas do sistema de resfriamento, amostras de carcaças de frango antes (n=345) e após (n=345) sua passagem pelo sistema de resfriamento e amostras de águas do último estágio do sistema de resfriamento de carcaças (n=69). Os resultados obtidos demonstraram que não houve diferença significativa na carga microbiana das amostras entre as três jornadas de trabalho do estabelecimento, sugerindo que a redução é segura, diminuindo assim o volume de águas residuais e seu impacto no meio ambiente, bem como melhorando o uso racional do tempo de processamento.

A novel neural model to electrical load forecasting in transformers

The paper describes a novel neural model to electrical load forecasting in transformers. The network acts as identifier of structural features to forecast process. So that output parameters can be estimated and generalized from an input parameter set. The model was trained and assessed through load data extracted from a Brazilian Electric Utility taking into account time, current, tension, active power in the three phases of the system. The results obtained in the simulations show that the developed technique can be used as an alternative tool to become more appropriate for planning of electric power systems.

An efficient neural approach to economic load dispatch in power systems

A neural approach to solve the problem defined by the economic load dispatch in power systems is presented in this paper, Systems based on artificial neural networks have high computational rates due to the use of a massive number of simple processing elements and the high degree of connectivity between these elements the ability of neural networks to realize some complex nonlinear function makes them attractive for system optimization the neural networks applyed in economic load dispatch reported in literature sometimes fail to converge towards feasible equilibrium points the internal parameters of the modified Hopfield network developed here are computed using the valid-subspace technique These parameters guarantee the network convergence to feasible quilibrium points, A solution for the economic load dispatch problem corresponds to an equilibrium point of the network. Simulation results and comparative analysis in relation to other neural approaches are presented to illustrate efficiency of the proposed approach.

Neural Network-Based Approach for Identification of the Harmonic Content of a Nonlinear Load in a Single-Phase System

In this paper an alternative method based on artificial neural networks is presented to determine harmonic components in the load current of a single-phase electric power system with nonlinear loads, whose parameters can vary so much in reason of the loads characteristic behaviors as because of the human intervention. The first six components in the load current are determined using the information contained in the time-varying waveforms. The effectiveness of this method is verified by using it in a single-phase active power filter with selective compensation of the current drained by an AC controller. The proposed method is compared with the fast Fourier transform.

Effect of abutment's height and framework alloy on the load distribution of mandibular cantilevered implant-supported prosthesis

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Experience gained and difficulties in performing dynamic load test in composite piles made with steel rails

The results of dynamic instrumentation in two construction sites that used steel rails as pile foundation are presented in this paper. The first dynamic load tests were executed in piles made by single steel rails of the type TR32 and TR37. In the second group of dynamic tests, the piles were made by a composition of two and three steel rails of the same type TR37. The difficulties in placing the sensors, the effect of hammer blow eccentricity and the influence of the non-uniform welding along the pile length are presented in detail and discussed.

Influences of thermal and electric load fluctuations in the cogeneration attractiveness

The use of mean values of thermal and electric demand can be justifiable for synthesising the configuration and for estimating the economic results because it simplifies the analysis in a preliminary feasibility study of a cogeneration plant. For determining the cogeneration scheme that best fits the energetic needs of a process several cycles and combinations must be considered, and those technically feasible will be analysed according to economic models. Although interesting for a first approach, this procedure do not consider that the peaks and valleys present in the load patterns will impose additional constraints relatively to the equipment capacities. In this paper, the effects of thermal and electric load fluctuation to the cogeneration plant design were considered. An approach for modelling these load variability is proposed for comparing two competing thermal and electric parity competing schemes. A gas turbine associated to a heat recovery steam generator was then proposed and analysed for thermal- and electric-following operational strategies. Thermal-following option revealed to be more attractive for the technical and economic limits defined for this analysis. (c) 2006 Elsevier Ltd. All rights reserved.

Describing fatigue crack growth and load ratio effects in Al 2524 T3 alloy with an enhanced exponential model

The fatigue crack behavior in metals and alloys under constant amplitude test conditions is usually described by relationships between the crack growth rate da/dN and the stress intensity factor range Delta K. In the present work, an enhanced two-parameter exponential equation of fatigue crack growth was introduced in order to describe sub-critical crack propagation behavior of Al 2524-T3 alloy, commonly used in aircraft engineering applications. It was demonstrated that besides adequately correlating the load ratio effects, the exponential model also accounts for the slight deviations from linearity shown by the experimental curves. A comparison with Elber, Kujawski and "Unified Approach" models allowed for verifying the better performance, when confronted to the other tested models, presented by the exponential model. (C) 2012 Elsevier Ltd. All rights reserved.

Load compensation in four-wire electrical power systems

This work describes a methodology for power factor control and correction of the unbalanced currents in four-wire electric circuits. The methodology is based on the insertion of two compensation networks, one wye-grounded neutral and another in delta, in parallel to the load. The mathematical development has been proposed in previous work [3]. In this paper, however, the methodology was adapted to accept different power factors for the system to be compensated. on the other hand, the determination of the compensation susceptances is based on the instantaneous values of the load currents. The results are obtained using the MatLab - Simulink environment.

Electrical load forecasting formulation by a fast neural network

The objective of this work is to develop a methodology for electric load forecasting based on a neural network. Here, backpropagation algorithm is used with an adaptive process that based on fuzzy logic and using a decaying exponential function to avoid instability in the convergence process. This methodology results in fast training, when compared to the conventional formulation of backpropagation algorithm. The results are presented using data from a Brazilian Electric Company, and shows a very good performance for the proposal objective.

Electric load forecasting using a fuzzy ART&ARTMAP neural network

This work presents a neural network based on the ART architecture ( adaptive resonance theory), named fuzzy ART& ARTMAP neural network, applied to the electric load-forecasting problem. The neural networks based on the ARTarchitecture have two fundamental characteristics that are extremely important for the network performance ( stability and plasticity), which allow the implementation of continuous training. The fuzzy ART& ARTMAP neural network aims to reduce the imprecision of the forecasting results by a mechanism that separate the analog and binary data, processing them separately. Therefore, this represents a reduction on the processing time and improved quality of the results, when compared to the Back-Propagation neural network, and better to the classical forecasting techniques (ARIMA of Box and Jenkins methods). Finished the training, the fuzzy ART& ARTMAP neural network is capable to forecast electrical loads 24 h in advance. To validate the methodology, data from a Brazilian electric company is used. (C) 2004 Elsevier B.V. All rights reserved.

Multinodal Load Forecasting in Power Electric Systems using a Neural Network with Radial Basis Function

In this paper we present the results of the use of a methodology for multinodal load forecasting through an artificial neural network-type Multilayer Perceptron, making use of radial basis functions as activation function and the Backpropagation algorithm, as an algorithm to train the network. This methodology allows you to make the prediction at various points in power system, considering different types of consumers (residential, commercial, industrial) of the electric grid, is applied to the problem short-term electric load forecasting (24 hours ahead). We use a database (Centralised Dataset - CDS) provided by the Electricity Commission de New Zealand to this work.