A ductile damage criterion at various stress triaxialities

The paper discusses the effect of stress triaxiality on the onset and evolution of damage in ductile metals. A series of tests including shear tests and experiments oil smooth and pre-notched tension specimens wits carried Out for it wide range of stress triaxialities. The underlying continuum damage model is based oil kinematic definition of damage tensors. The modular structure of the approach is accomplished by the decomposition of strain rates into elastic, plastic and damage parts. Free energy functions with respect to fictitious undamaged configurations as well as damaged ones are introduced separately leading to elastic material laws which are affected by increasing damage. In addition, a macroscopic yield condition and a flow rule are used to adequately describe the plastic behavior. Numerical simulations of the experiments are performed and good correlation of tests and numerical results is achieved. Based oil experimental and numerical data the damage criterion formulated in stress space is quantified. Different branches of this function are taken into account corresponding to different damage modes depending oil stress triaxiality and Lode parameter. In addition, identification of material parameters is discussed ill detail. (C) 2007 Elsevier Ltd. All rights reserved.

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.

Miniaturized structures for removal or selection of particles from liquid flow

The aim of this work was the development of miniaturized structures useful for retention and/or selection of particles and viscous substances from a liquid flow. The proposed low costs structures are similar to macroscopic wastewater treatment systems, named baffles, and allow disassemble. They were simulated using FEMLAB 3.2b package and manufactured in acrylic with conventional tools. Tests for retention or selection of particles in water or air and viscous fluids in water were carried out. Either in air or water particles with 50 mu m diameter will be retained but not with 13 mu m diameter. In aqueous flow, it is also possible the retention of viscous samples, such as silicone 350 cSt. The simulated results showed good agreement with experimental measurements. These miniaturized structures can be useful in sample pretreatment for chemical analysis and microorganism manipulation. (C) 2007 Elsevier B.V. All rights reserved.

Discrete-time mean variance optimal control of linear systems with Markovian jumps and multiplicative noise

In this article, we consider the stochastic optimal control problem of discrete-time linear systems subject to Markov jumps and multiplicative noise under three kinds of performance criterions related to the final value of the expectation and variance of the output. In the first problem it is desired to minimise the final variance of the output subject to a restriction on its final expectation, in the second one it is desired to maximise the final expectation of the output subject to a restriction on its final variance, and in the third one it is considered a performance criterion composed by a linear combination of the final variance and expectation of the output of the system. We present explicit sufficient conditions for the existence of an optimal control strategy for these problems, generalising previous results in the literature. We conclude this article presenting a numerical example of an asset liabilities management model for pension funds with regime switching.

Generalized Coupled Algebraic Riccati Equations for Discrete-time Markov Jump with Multiplicative Noise Systems

In this paper we consider the existence of the maximal and mean square stabilizing solutions for a set of generalized coupled algebraic Riccati equations (GCARE for short) associated to the infinite-horizon stochastic optimal control problem of discrete-time Markov jump with multiplicative noise linear systems. The weighting matrices of the state and control for the quadratic part are allowed to be indefinite. We present a sufficient condition, based only on some positive semi-definite and kernel restrictions on some matrices, under which there exists the maximal solution and a necessary and sufficient condition under which there exists the mean square stabilizing solution fir the GCARE. We also present a solution for the discounted and long run average cost problems when the performance criterion is assumed be composed by a linear combination of an indefinite quadratic part and a linear part in the state and control variables. The paper is concluded with a numerical example for pension fund with regime switching.

Determining the effect of grain size and maximum induction upon coercive field of electrical steels

Although theoretical models have already been proposed, experimental data is still lacking to quantify the influence of grain size upon coercivity of electrical steels. Some authors consider a linear inverse proportionality, while others suggest a square root inverse proportionality. Results also differ with regard to the slope of the reciprocal of grain size-coercive field relation for a given material. This paper discusses two aspects of the problem: the maximum induction used for determining coercive force and the possible effect of lurking variables such as the grain size distribution breadth and crystallographic texture. Electrical steel sheets containing 0.7% Si, 0.3% Al and 24 ppm C were cold-rolled and annealed in order to produce different grain sizes (ranging from 20 to 150 mu m). Coercive field was measured along the rolling direction and found to depend linearly on reciprocal of grain size with a slope of approximately 0.9 (A/m)mm at 1.0 T induction. A general relation for coercive field as a function of grain size and maximum induction was established, yielding an average absolute error below 4%. Through measurement of B(50) and image analysis of micrographs, the effects of crystallographic texture and grain size distribution breadth were qualitatively discussed. (C) 2011 Elsevier B.V. All rights reserved.

Obtaining and selection of hexokinases-less strains of Saccharomyces cerevisiae for production of ethanol and fructose from sucrose

Saccharomyces cerevisiae hexokinase-less strains were produced to study the production of ethanol and fructose from sucrose. These strains do not have the hexokinases A and B. Twenty-three double-mutant strains were produced, and then, three were selected for presenting a smaller growth in yeast extract-peptone-fructose. In fermentations with a medium containing sucrose (180.3 g L-1) and with cell recycles, simulating industrial conditions, the capacity of these mutant yeasts in inverting sucrose and fermenting only glucose was well characterized. Besides that, we could also see their great tolerance to the stresses of fermentative recycles, where fructose production (until 90 g L-1) and ethanol production (until 42.3 g L-1) occurred in cycles of 12 h, in which hexokinase-less yeasts performed high growth (51.2% of wet biomass) and viability rates (77% of viable cells) after nine consecutive cycles.

The Kumaraswamy Weibull distribution with application to failure data

For the first time, we introduce and study some mathematical properties of the Kumaraswamy Weibull distribution that is a quite flexible model in analyzing positive data. It contains as special sub-models the exponentiated Weibull, exponentiated Rayleigh, exponentiated exponential, Weibull and also the new Kumaraswamy exponential distribution. We provide explicit expressions for the moments and moment generating function. We examine the asymptotic distributions of the extreme values. Explicit expressions are derived for the mean deviations, Bonferroni and Lorenz curves, reliability and Renyi entropy. The moments of the order statistics are calculated. We also discuss the estimation of the parameters by maximum likelihood. We obtain the expected information matrix. We provide applications involving two real data sets on failure times. Finally, some multivariate generalizations of the Kumaraswamy Weibull distribution are discussed. (C) 2010 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.

Using a New Criterion to Identify Sites for Mean Soil Water Storage Evaluation

Establishing a few sites in which measurements of soil water storage (SWS) are time stable significantly reduces the efforts involved in determining average values of SWS. This study aimed to apply a new criterion the mean absolute bias error (MABE)-to identify temporally stable sites for mean SWS evaluation. The performance of MABE was compared with that of the commonly used criterion, the standard deviation of relative difference (SDRD). From October 2004 to October 2008, SWS of four soil layers (0-1.0, 1.0-2.0,2.0-3.0, and 3.0-4.0 m) was measured, using a neutron probe, at 28 sites on a hillslope of the Loess Plateau, China. A total of 37 SWS data sets taken over time were divided into two subsets, the first consisting of 22 dates collected during the calibration period from October 2004 to September 2006, and the second with 15 dates collected during the validation period from October 2006 to October 2008. The results showed that if a critical value of 5% for MABE was defined, more than half the sites were temporally stable for both periods, and the number of temporally stable sires generally increased with soil depth. Compared with SDRD, MABE was more suitable for the identification of time-stable sites for mean SS prediction. Since the absolute prediction error of drier sites is more sensitive to changes in relative difference in terms of mean SWS prediction, the sites of wet sectors should be preferable for mean SWS prediction for the same changes in relative difference.

Technical and economical evaluation of a harvester, working under different spacing and planting arrangement conditions in eucalypts plantations

Plantation spacing selection has the primary objective of assigning each tree enough space for maximum growth and best quality to be attained with a minimum cost. From the harvest standpoint, an increase in stand density directly implies a decrease of individual tree volume, reducing also harvester productive capacity. The objective of this research is to assess the effects of several initial spacings and arrangements in eucalyptus plantations on production capacity, operational capacity and costs of forest harvester. Real operational data were collected from two eucalypt plantations at different initial spacing of 6.0, 7.5, 9.0, 12 and 18 m(2) per tree. Simulation data were obtained from a forest harvester simulator. Using spacing (E), mean tree volume (MV), diameter at breast height (DBH) and height (H) values, a stepwise regression test procedure was run, and correlations computed in order to measure their participation in operational capacity. Operational costs were computed with an accounting method proposed by FAO. Mean tree volume (MV) explained 88% of forest harvester operational capacity. Spacing (E) affected 8.5% of harvester operational capacity; wider spacings were related to higher individual tree volumes. Harvesting operation costs were lower in wider spaced treatments.

Pricing farm-level agricultural insurance: a Bayesian approach

This paper applies Hierarchical Bayesian Models to price farm-level yield insurance contracts. This methodology considers the temporal effect, the spatial dependence and spatio-temporal models. One of the major advantages of this framework is that an estimate of the premium rate is obtained directly from the posterior distribution. These methods were applied to a farm-level data set of soybean in the State of the Parana (Brazil), for the period between 1994 and 2003. The model selection was based on a posterior predictive criterion. This study improves considerably the estimation of the fair premium rates considering the small number of observations.

Establishing a soybean germplasm core collection

Core collections are of strategic importance as they allow the use of a small part of a germplasm collection that is representative of the total collection. The objective of this study was to develop a soybean core collection of the USDA Soybean Germplasm Collection by comparing the results of random, proportional, logarithmic, multivariate proportional and multivariate logarithmic sampling strategies. All but the random sampling strategy used stratification of the entire collection based on passport data and maturity group classification. The multivariate proportional and multivariate logarithmic strategies made further use of qualitative and quantitative trait data to select diverse accessions within each stratum. The 18 quantitative trait data distribution parameters were calculated for each core and for the entire collection for pairwise comparison to validate the sampling strategies. All strategies were adequate for assembling a core collection. The random core collection best represented the entire collection in statistical terms. Proportional and logarithmic strategies did not maximize statistical representation but were better in selecting maximum variability. Multivariate proportional and multivariate logarithmic strategies produced the best core collections as measured by maximum variability conservation. The soybean core collection was established using the multivariate proportional selection strategy. (C) 2010 Elsevier B.V. All rights reserved.

Genetic potential of a maize population from Southern Brazil for the modified convergent-divergent selection scheme

Maize (Zea mays L.) is a very important cereal to world-wide economy which is also true for Brazil, particularly in the South region. Grain yield and plant height have been chosen as important criteria by breeders and farmers from Santa Catarina State (SC), Brazil. The objective of this work was to estimate genetic-statistic parameters associated with genetic gain for grain yield and plant height, in the first cycle of convergent-divergent half-sib selection in a maize population (MPA1) cultivated by farmers within the municipality of Anchieta (SC). Three experiments were carried out in different small farms at Anchieta using low external agronomic inputs; each experiment represented independent samples of half-sib families, which were evaluated in randomized complete blocks with three replications per location. Significant differences among half-sib families were observed for both variables in all experiments. The expected responses to truncated selection of the 25% better families in each experiment were 5.1, 5.8 and 5.2% for reducing plant height and 3.9, 5.7 and 5.0% for increasing grain yield, respectively. The magnitudes of genetic-statistic parameters estimated evidenced that the composite population MPA1 exhibits enough genetic variability to be used in cyclical process of recurrent selection. There were evidences that the genetic structure of the base population MPA1, as indicated by its genetic variability, may lead to expressive changes in the traits under selection, even under low selection pressure.

An integrated molecular map of yellow passion fruit based on simultaneous maximum-likelihood estimation of linkage and linkage phases

The development of genetic maps for auto-incompatible species, such as the yellow passion fruit (Passiflora edulis Sims f.flavicarpa Deg.) is restricted due to the unfeasibility of obtaining traditional mapping populations based on inbred lines. For this reason, yellow passion fruit linkage maps were generally constructed using a strategy known as two-way pseudo-testeross, based on monoparental dominant markers segregating in a 1:1 fashion. Due to the lack of information from these markers in one of the parents, two individual (parental) maps were obtained. However, integration of these maps is essential, and biparental markers can be used for such an operation. The objective of our study was to construct an integrated molecular map for a full-sib population of yellow passion fruit combining different loci configuration generated from amplified fragment length polymorphisms (AFLPs) and microsatellite markers and using a novel approach based on simultaneous maximum-likelihood estimation of linkage and linkage phases, specially designed for outcrossing species. Of the total number of loci, approximate to 76%, 21%, 0.7%, and 2.3% did segregate in 1:1, 3:1, 1:2:1, and 1:1:1:1 ratios, respectively. Ten linkage groups (LGs) were established with a logarithm of the odds (LOD) score >= 5.0 assuming a recombination fraction : <= 0.35. On average, 24 markers were assigned per LG, representing a total map length of 1687 cM, with a marker density of 6.9 cM. No markers were placed as accessories on the map as was done with previously constructed individual maps.

Does using stepwise variable selection to build sequential path analysis models make sense?

Causal inference methods - mainly path analysis and structural equation modeling - offer plant physiologists information about cause-and-effect relationships among plant traits. Recently, an unusual approach to causal inference through stepwise variable selection has been proposed and used in various works on plant physiology. The approach should not be considered correct from a biological point of view. Here, it is explained why stepwise variable selection should not be used for causal inference, and shown what strange conclusions can be drawn based upon the former analysis when one aims to interpret cause-and-effect relationships among plant traits.