Post-processing and visualization techniques in 2D boundary element analysis

Most post-processors for boundary element (BE) analysis use an auxiliary domain mesh to display domain results, working against the profitable modelling process of a pure boundary discretization. This paper introduces a novel visualization technique which preserves the basic properties of the boundary element methods. The proposed algorithm does not require any domain discretization and is based on the direct and automatic identification of isolines. Another critical aspect of the visualization of domain results in BE analysis is the effort required to evaluate results in interior points. In order to tackle this issue, the present article also provides a comparison between the performance of two different BE formulations (conventional and hybrid). In addition, this paper presents an overview of the most common post-processing and visualization techniques in BE analysis, such as the classical algorithms of scan line and the interpolation over a domain discretization. The results presented herein show that the proposed algorithm offers a very high performance compared with other visualization procedures.

Hybrid and multi-field variational principles for geometrically exact three-dimensional beams

This paper addresses the development of several alternative novel hybrid/multi-field variational formulations of the geometrically exact three-dimensional elastostatic beam boundary-value problem. In the framework of the complementary energy-based formulations, a Legendre transformation is used to introduce the complementary energy density in the variational statements as a function of stresses only. The corresponding variational principles are shown to feature stationarity within the framework of the boundary-value problem. Both weak and linearized weak forms of the principles are presented. The main features of the principles are highlighted, giving special emphasis to their relationships from both theoretical and computational standpoints. (C) 2010 Elsevier Ltd. All rights reserved.

Mean sea-level rise impacts on Santos Bay, Southeastern Brazil - physical modelling study

The greenhouse effect and resulting increase in the Earth`s temperature may accelerate the mean sea-level rise. The natural response of bays and estuaries to this rise, such as this case study of Santos Bay (Brazil), will include change in shoreline position, land flooding and wetlands impacts. The main impacts of this scenario were studied in a physical model built in the Coastal and Harbour Division of Hydraulic Laboratory, University of Sao Paulo, and the main conclusions are presented in this paper. The model reproduces near 1,000 km(2) of the study area, including Santos, Sao Vicente, Praia Grande, Cubatao, Guaruja and Bertioga cities.

Toward Optimal Design of Piezoelectric Transducers Based on Multifunctional and Smoothly Graded Hybrid Material Systems

This work explores the design of piezoelectric transducers based on functional material gradation, here named functionally graded piezoelectric transducer (FGPT). Depending on the applications, FGPTs must achieve several goals, which are essentially related to the transducer resonance frequency, vibration modes, and excitation strength at specific resonance frequencies. Several approaches can be used to achieve these goals; however, this work focuses on finding the optimal material gradation of FGPTs by means of topology optimization. Three objective functions are proposed: (i) to obtain the FGPT optimal material gradation for maximizing specified resonance frequencies; (ii) to design piezoelectric resonators, thus, the optimal material gradation is found for achieving desirable eigenvalues and eigenmodes; and (iii) to find the optimal material distribution of FGPTs, which maximizes specified excitation strength. To track the desirable vibration mode, a mode-tracking method utilizing the `modal assurance criterion` is applied. The continuous change of piezoelectric, dielectric, and elastic properties is achieved by using the graded finite element concept. The optimization algorithm is constructed based on sequential linear programming, and the concept of continuum approximation of material distribution. To illustrate the method, 2D FGPTs are designed for each objective function. In addition, the FGPT performance is compared with the non-FGPT one.

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.

Modelling grain boundary migration during geometric dynamic recrystallization

High-angle grain boundary migration is predicted during geometric dynamic recrystallization (GDRX) by two types of mathematical models. Both models consider the driving pressure due to curvature and a sinusoidal driving pressure owing to subgrain walls connected to the grain boundary. One model is based on the finite difference solution of a kinetic equation, and the other, on a numerical technique in which the boundary is subdivided into linear segments. The models show that an initially flat boundary becomes serrated, with the peak and valley migrating into both adjacent grains, as observed during GDRX. When the sinusoidal driving pressure amplitude is smaller than 2 pi, the boundary stops migrating, reaching an equilibrium shape. Otherwise, when the amplitude is larger than 2 pi, equilibrium is never reached and the boundary migrates indefinitely, which would cause the protrusions of two serrated parallel boundaries to impinge on each other, creating smaller equiaxed grains.

Single Axis Controlled Hybrid Magnetic Bearing for Left Ventricular Assist Device: Hybrid Core and Closed Magnetic Circuit

In previous studies, we presented main strategies for suspending the rotor of a mixed-flow type (centrifugal and axial) ventricular assist device (VAD), originally presented by the Institute Dante Pazzanese of Cardiology (IDPC), Brazil. Magnetic suspension is achieved by the use of a magnetic bearing architecture in which the active control is executed in only one degree of freedom, in the axial direction of the rotor. Remaining degrees of freedom, excepting the rotation, are restricted only by the attraction force between pairs of permanent magnets. This study is part of a joint project in development by IDPC and Escola Politecnica of Sao Paulo University, Brazil. This article shows advances in that project, presenting two promising solutions for magnetic bearings. One solution uses hybrid cores as electromagnetic actuators, that is, cores that combine iron and permanent magnets. The other solution uses actuators, also of hybrid type, but with the magnetic circuit closed by an iron core. After preliminary analysis, a pump prototype has been developed for each solution and has been tested. For each prototype, a brushless DC motor has been developed as the rotor driver. Each solution was evaluated by in vitro experiments and guidelines are extracted for future improvements. Tests have shown good results and demonstrated that one solution is not isolated from the other. One complements the other for the development of a single-axis-controlled, hybrid-type magnetic bearing for a mixed-flow type VAD.

A hybrid commodity price-forecasting model applied to the sugar-alcohol sector

Accurate price forecasting for agricultural commodities can have significant decision-making implications for suppliers, especially those of biofuels, where the agriculture and energy sectors intersect. Environmental pressures and high oil prices affect demand for biofuels and have reignited the discussion about effects on food prices. Suppliers in the sugar-alcohol sector need to decide the ideal proportion of ethanol and sugar to optimise their financial strategy. Prices can be affected by exogenous factors, such as exchange rates and interest rates, as well as non-observable variables like the convenience yield, which is related to supply shortages. The literature generally uses two approaches: artificial neural networks (ANNs), which are recognised as being in the forefront of exogenous-variable analysis, and stochastic models such as the Kalman filter, which is able to account for non-observable variables. This article proposes a hybrid model for forecasting the prices of agricultural commodities that is built upon both approaches and is applied to forecast the price of sugar. The Kalman filter considers the structure of the stochastic process that describes the evolution of prices. Neural networks allow variables that can impact asset prices in an indirect, nonlinear way, what cannot be incorporated easily into traditional econometric models.

Thermodynamic modelling of an Al(2)O(3)-MnO system using the ionic model

The thermodynamic assessment of an Al(2)O(3)-MnO pseudo-binary system has been carried out with the use of an ionic model. The use of the electro-neutrality principles in addition to the constitutive relations, between site fractions of the species on each sub-lattice, the thermodynamics descriptions of each solid phase has been determined to make possible the solubility description. Based on the thermodynamics descriptions of each phase in addition to thermo-chemical data obtained from the literature, the Gibbs energy functions were optimized for each phase of the Al(2)O(3)-MnO system with the support of PARROT(R) module from ThemoCalc(R) package. A thermodynamic database was obtained, in agreement with the thermo-chemical data extracted from the literature, to describe the Al(2)O(3)-MnO system including the solubility description of solid phases. (C) 2009 Elsevier Ltd. All rights reserved.

Inverse aerodynamic design applications using the MGM hybrid formulation

The well-known modified Garabedian-Mcfadden (MGM) method is an attractive alternative for aerodynamic inverse design, for its simplicity and effectiveness (P. Garabedian and G. Mcfadden, Design of supercritical swept wings, AIAA J. 20(3) (1982), 289-291; J.B. Malone, J. Vadyak, and L.N. Sankar, Inverse aerodynamic design method for aircraft components, J. Aircraft 24(2) (1987), 8-9; Santos, A hybrid optimization method for aerodynamic design of lifting surfaces, PhD Thesis, Georgia Institute of Technology, 1993). Owing to these characteristics, the method has been the subject of several authors over the years (G.S. Dulikravich and D.P. Baker, Aerodynamic shape inverse design using a Fourier series method, in AIAA paper 99-0185, AIAA Aerospace Sciences Meeting, Reno, NV, January 1999; D.H. Silva and L.N. Sankar, An inverse method for the design of transonic wings, in 1992 Aerospace Design Conference, No. 92-1025 in proceedings, AIAA, Irvine, CA, February 1992, 1-11; W. Bartelheimer, An Improved Integral Equation Method for the Design of Transonic Airfoils and Wings, AIAA Inc., 1995). More recently, a hybrid formulation and a multi-point algorithm were developed on the basis of the original MGM. This article discusses applications of those latest developments for airfoil and wing design. The test cases focus on wing-body aerodynamic interference and shock wave removal applications. The DLR-F6 geometry is picked as the baseline for the analysis.

On the use of correlated beta random variables with animal population modelling

We give reasons why demographic parameters such as survival and reproduction rates are often modelled well in stochastic population simulation using beta distributions. In practice, it is frequently expected that these parameters will be correlated, for example with survival rates for all age classes tending to be high or low in the same year. We therefore discuss a method for producing correlated beta random variables by transforming correlated normal random variables, and show how it can be applied in practice by means of a simple example. We also note how the same approach can be used to produce correlated uniform triangular, and exponential random variables. (C) 2008 Elsevier B.V. All rights reserved.

Modelling the potential distribution of the invasive tomato red spider mite, Tetranychus evansi (Acari: Tetranychidae)

Predicting the potential geographical distribution of a species is particularly important for pests with strong invasive abilities. Tetranychus evansi Baker & Pritchard, possibly native to South America, is a spider mite pest of solanaceous crops. This mite is considered an invasive species in Africa and Europe. A CLIMEX model was developed to predict its global distribution. The model results fitted the known records of T. evansi except for some records in dry locations. Dryness as well as excess moisture stresses play important roles in limiting the spread of the mite in the tropics. In North America and Eurasia its potential distribution appears to be essentially limited by cold stress. Detailed potential distribution maps are provided for T. evansi in the Mediterranean Basin and in Japan. These two regions correspond to climatic borders for the species. Mite establishment in these areas can be explained by their relatively mild winters. The Mediterranean region is also the main area where tomato is grown in open fields in Europe and where the pest represents a threat. According to the model, the whole Mediterranean region has the potential to be extensively colonized by the mite. Wide expansion of the mite to new areas in Africa is also predicted. Agricultural issues highlighted by the modelled distribution of the pest are discussed.

Parametric and nonparametric statistical modelling of crop yield: implications for pricing crop insurance contracts

This article considers alternative methods to calculate the fair premium rate of crop insurance contracts based on county yields. The premium rate was calculated using parametric and nonparametric approaches to estimate the conditional agricultural yield density. These methods were applied to a data set of county yield provided by the Statistical and Geography Brazilian Institute (IBGE), for the period of 1990 through 2002, for soybean, corn and wheat, in the State of Paran. In this article, we propose methodological alternatives to pricing crop insurance contracts resulting in more accurate premium rates in a situation of limited data.

Inheritance of resistance to Puccinia psidii G. Winter in a eucalyptus interspecific hybrid progeny evaluated under conditions of natural infection

Inheritance of resistance to Puccinia psidii G. Winter in a eucalyptus interspecific hybrid progeny evaluated under conditions of natural infection Rust caused by the fungus Puccinia psidii is currently the most important disease of eucalyptus. It is widely disseminated in Brazil, and causes serious damage in nurseries and plantation areas. The identification of resistant germplasm along with knowledge of the genetic basis of resistance heredity are the first requirements for the success of breeding programs aiming to develop resistant varieties. Earlier studies carried out under controlled conditions suggested a monogenic control as well as the participation of at least two genes promoting resistance to rust. The goal of this study was to evaluate the resistance to P. psidii under field conditions in fourteen progenies from controlled crosses and self-crosses among four hybrid clones of Eucalyptus grandis Hill ex Maiden x Eucalyptus urophylla ST Blake that contrast for resistance to the fungus. Results indicated that resistance could be explained by one locus with main effects and at least three different alleles. However, loci with minor effects may influence the resistance, since variation on severity classes was observed. Differences in segregation of resistance between reciprocal crosses were not observed, indicating absence of cytoplasmic effects.

Modelling the progress of Asiatic citrus canker on Tahiti lime in relation to temperature and leaf wetness

The combined effect of temperature (15A degrees C, 20A degrees C, 25A degrees C, 30A degrees C, 35A degrees C, 40A degrees C and 42A degrees C) and leaf wetness duration (0, 4, 8 12, 16, 20 and 24 h) on infection and development of Asiatic citrus canker (Xanthomonas citri subsp. citri) on Tahiti lime plant was examined in growth chambers. No disease developed at 42A degrees C and zero hours of leaf wetness. Periods of leaf wetness as short as 4 h were sufficient for citrus canker infection. However, a longer leaf duration wetness (24 h) did not result in much increase in the incidence of citrus canker, but led to twice the number of lesions and four times the disease severity. Temperature was the greatest factor influencing disease development. At optimum temperatures (25-35A degrees C), there was 100% disease incidence. Maximum disease development was observed at 30-35A degrees C, with up to a 12-fold increase in lesion density, a 10-fold increase in lesion size and a 60-fold increase in disease severity.