Applied models to biodegradation kinetics of lubricant and vegetable oils in wastewater

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

Importantes características de chuva para a conservação do solo e da água no município de São Manuel (SP)

Os modelos matemáticos preditivos da erosão do solo, como a Equação Universal de Perda de Solo (EUPS), são de muita valia no planejamento de uso agrícola da terra. Tal equação, desenvolvida para estimar as perdas médias anuais de solo esperadas em dado local, para determinado sistema de manejo, apresenta como variáveis os fatores erosividade da chuva (R), erodibilidade do solo (K), comprimento do declive (L), grau do declive (S), cobertura e manejo (C) e práticas conservacionistas de suporte (P). Com o objetivo de contribuir para o planejamento conservacionista de uso do solo local, foi estimado, de forma simplificada, o fator erosividade da chuva (R) da EUPS para o município de São Manuel (SP), para uma série pluviométrica contínua de 49 anos de dados de chuva diária. Além disso, foram também calculados o período de retorno, a freqüência de ocorrência dos índices de erosividade anuais e as quantidades máximas diárias das chuvas necessárias para o dimensionamento mais adequado de canais de terraços agrícolas em nível. O valor calculado do fator R foi de 7.487 MJ mm ha-1 h-1 ano-1, esperado ocorrer no local, pelo menos, uma vez a cada 2,33 anos, com uma probabilidade de 42,92 %. Observou-se uma concentração de 81,48 % do valor total deste fator no semestre de outubro a março, indicando que, potencialmente, as maiores perdas anuais de solo por erosão são esperadas neste período. Os valores anuais do índice EI30, esperados para os períodos de retorno de 2, 5, 10, 20, 50 e 100 anos, foram de 7.216, 8.675, 9.641, 10.568, 11.768 e 12.667 MJ mm ha-1 h-1 ano-1, respectivamente. Com relação às quantidades máximas de chuva diária, para os mesmos períodos de retorno, os valores foram de 73, 98, 115, 131, 151 e 167 mm, respectivamente.

Non-linear growth models for bullfrog tadpoles

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

Evaluation and identification of lightning models by artificial neural networks

This paper describes a novel approach for mapping lightning models using artificial neural networks. The networks acts as identifier of structural features of the lightning models so that output parameters can be estimated and generalized from an input parameter set. Simulation examples are presented to validate the proposed approach. More specifically, the neural networks are used to compute electrical field intensity and critical disruptive voltage taking into account several atmospheric and structural factors, such as pressure, temperature, humidity, distance between phases, height of bus bars, and wave forms. A comparative analysis with other approaches is also provided to illustrate this new methodology.

Analysis of aluminum plates under heating in electrical and natural gas furnaces

This paper analyzes the thermal storage characteristics of aluminum plates in furnaces during their heating for lamination under two sources of heat: an electrical resistance bank and a combustion process carried out with natural gas. The set of equations to model the furnace under operation with electrical energy, for air as the fluid, is presented. This supports the theoretical analysis for the system under operation with natural gas combustion products. A numerical procedure, using the software ANSYS, is applied to determine the convection heat transfer coefficients for heating by the air flow. Temperatures measured in a plate inside a real furnace are used as parameters to determine these coefficients. Then convection and radiation heat transfer coefficients are determined for the natural gas combustion products. Results are compared, indicating a possible gain of 5.5 h in relation to a 19.5 h period of conventional electrical heating per plate.

Distribution line models analysis for loss calculation within three-phase three-wire power flow algorithms

Three-phase three-wire power flow algorithms, as any tool for power systems analysis, require reliable impedances and models in order to obtain accurate results. Kron's reduction procedure, which embeds neutral wire influence into phase wires, has shown good results when three-phase three-wire power flow algorithms based on current summation method were used. However, Kron's reduction can harm reliabilities of some algorithms whose iterative processes need loss calculation (power summation method). In this work, three three-phase three-wire power flow algorithms based on power summation method, will be compared with a three-phase four-wire approach based on backward-forward technique and current summation. Two four-wire unbalanced medium-voltage distribution networks will be analyzed and results will be presented and discussed. © 2004 IEEE.

Remarks on orthotropic elastic models applied to wood

Wood is generally considered an anisotropic material. In terms of engineering elastic models, wood is usually treated as an orthotropic material. This paper presents an analysis of two principal anisotropic elastic models that are usually applied to wood. The first one, the linear orthotropic model, where the material axes L (Longitudinal), R(radial) and T(tangential) are coincident with the Cartesian axes (x, y, z), is more accepted as wood elastic model. The other one, the cylindrical orthotropic model is more adequate of the growth caracteristics of wood but more mathematically complex to be adopted in practical terms. Specifically due to its importance in wood elastic parameters, this paper deals with the fiber orientation influence in these models through adequate transformation of coordinates. As a final result, some examples of the linear model, which show the variation of elastic moduli, i.e., Young's modulus and shear modulus, with fiber orientation are presented.

Damage detection in a benchmark structure using AR-ARX models and statistical pattern recognition

Structural health monitoring (SHM) is related to the ability of monitoring the state and deciding the level of damage or deterioration within aerospace, civil and mechanical systems. In this sense, this paper deals with the application of a two-step auto-regressive and auto-regressive with exogenous inputs (AR-ARX) model for linear prediction of damage diagnosis in structural systems. This damage detection algorithm is based on the. monitoring of residual error as damage-sensitive indexes, obtained through vibration response measurements. In complex structures there are. many positions under observation and a large amount of data to be handed, making difficult the visualization of the signals. This paper also investigates data compression by using principal component analysis. In order to establish a threshold value, a fuzzy c-means clustering is taken to quantify the damage-sensitive index in an unsupervised learning mode. Tests are made in a benchmark problem, as proposed by IASC-ASCE with different damage patterns. The diagnosis that was obtained showed high correlation with the actual integrity state of the structure. Copyright © 2007 by ABCM.

Optimal Boussinesq model for shallow-water waves interacting with a microstructure

In this paper, we consider the propagation of water waves in a long-wave asymptotic regime, when the bottom topography is periodic on a short length scale. We perform a multiscale asymptotic analysis of the full potential theory model and of a family of reduced Boussinesq systems parametrized by a free parameter that is the depth at which the velocity is evaluated. We obtain explicit expressions for the coefficients of the resulting effective Korteweg-de Vries (KdV) equations. We show that it is possible to choose the free parameter of the reduced model so as to match the KdV limits of the full and reduced models. Hence the reduced model is optimal regarding the embedded linear weakly dispersive and weakly nonlinear characteristics of the underlying physical problem, which has a microstructure. We also discuss the impact of the rough bottom on the effective wave propagation. In particular, nonlinearity is enhanced and we can distinguish two regimes depending on the period of the bottom where the dispersion is either enhanced or reduced compared to the flat bottom case. © 2007 The American Physical Society.

Generating VHDL-AMS models of digital-to-analogue converters from MATLAB®/SIMULINK®

Today, the trend within the electronics industry is for the use of rapid and advanced simulation methodologies in association with synthesis toolsets. This paper presents an approach developed to support mixed-signal circuit design and analysis. The methodology proposed shows a novel approach to the problem of developing behvioural model descriptions of mixed-signal circuit topologies, by construction of a set of subsystems, that supports the automated mapping of MATLAB®/SIMULINK® models to structural VHDL-AMS descriptions. The tool developed, named MS 2SV, reads a SIMULINK® model file and translates it to a structural VHDL-AMS code. It also creates the file structure required to simulate the translated model in the System Vision™. To validate the methodology and the developed program, the DAC08, AD7524 and AD5450 data converters were studied and initially modelled in MATLAB®/ SIMULINK®. The VHDL-AMS code generated automatically by MS 2SV, (MATLAB®/SIMULINK® to System Vision™), was then simulated in the System Vision™. The simulation results show that the proposed approach, which is based on VHDL-AMS descriptions of the original model library elements, allows for the behavioural level simulation of complex mixed-signal circuits.

A genetic algorithm for crop rotation

In the last few years, crop rotation has gained attention due to its economic, environmental and social importance which explains why it can be highly beneficial for farmers. This paper presents a mathematical model for the Crop Rotation Problem (CRP) that was adapted from literature for this highly complex combinatorial problem. The CRP is devised to find a vegetable planting program that takes into account green fertilization restrictions, the set-aside period, planting restrictions for neighboring lots and for crop sequencing, demand constraints, while, at the same time, maximizing the profitability of the planted area. The main aim of this study is to develop a genetic algorithm and test it in a real context. The genetic algorithm involves a constructive heuristic to build the initial population and the operators of crossover, mutation, migration and elitism. The computational experiment was performed for a medium dimension real planting area with 16 lots, considering 29 crops of 10 different botanical families and a two-year planting rotation. Results showed that the algorithm determined feasible solutions in a reasonable computational time, thus proving its efficacy for dealing with this practical application.

Analysis of ensemble models in the medium term hydropower scheduling

The medium term hydropower scheduling (MTHS) problem involves an attempt to determine, for each time stage of the planning period, the amount of generation at each hydro plant which will maximize the expected future benefits throughout the planning period, while respecting plant operational constraints. Besides, it is important to emphasize that this decision-making has been done based mainly on inflow earliness knowledge. To perform the forecast of a determinate basin, it is possible to use some intelligent computational approaches. In this paper one considers the Dynamic Programming (DP) with the inflows given by their average values, thus turning the problem into a deterministic one which the solution can be obtained by deterministic DP (DDP). The performance of the DDP technique in the MTHS problem was assessed by simulation using the ensemble prediction models. Features and sensitivities of these models are discussed. © 2012 IEEE.

Índice de área foliar e produtividade do tomate sob condições de ambiente protegido

The tomato cultivation in the greenhouse has been expanded in the last years, mainly, in the South and Southeast regions of Brazil, whose purpose is to improve the productivity and the quality of the agricultural products, offering regularity in the production. The present study aimed to determine, along the crop cycle, the relationship between the leaf area index and the productivity, and at the end of the cycle, the components of production of the tomato in the greenhouse. The models were generated through polynomial equations of 1st and 2nd order, having as independent variable the number of days after the transplanting. It was verified that it is possible to determine, in the greenhouse, through mathematical models, the leaf area index of the tomato crop considering the days after the transplanting. Basing on values of leaf area index, the productivity of the crop and the period of the maximum productivity can be determined, aiding the farmers to determine the best sowing and transplanting time of the tomato crop.

Local attractors, degeneracy and analyticity: Symmetry effects on the locally coupled Kuramoto model

In this work we study the local coupled Kuramoto model with periodic boundary conditions. Our main objective is to show how analytical solutions may be obtained from symmetry assumptions, and while we proceed on our endeavor we show apart from the existence of local attractors, some unexpected features resulting from the symmetry properties, such as intermittent and chaotic period phase slips, degeneracy of stable solutions and double bifurcation composition. As a result of our analysis, we show that stable fixed points in the synchronized region may be obtained with just a small amount of the existent solutions, and for a class of natural frequencies configuration we show analytical expressions for the critical synchronization coupling as a function of the number of oscillators, both exact and asymptotic. © 2013 Elsevier Ltd. All rights reserved.

Propriedades físico-químicas de abacate submetido à secagem convectiva e desidratação osmótica

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)