MEASUREMENT OF ELASTIC PROPERTIES OF MATERIALS BY THE ULTRASONIC THROUGH-TRANSMISSION TECHNIQUE

The elastic mechanical behavior of elastic materials is modeled by a pair of independent constants (Young`s modulus and Poisson`s coefficient). A precise measurement for both constants is necessary in some applications, such as the quality control of mechanical elements and standard materials used for the calibration of some equipment. Ultrasonic techniques have been used because wave velocity depends on the elastic properties of the propagation medium. The ultrasonic test shows better repeatability and accuracy than the tensile and indentation test. In this work, the theoretical and experimental aspects related to the ultrasonic through-transmission technique for the characterization of elastic solids is presented. Furthermore, an amorphous material and some polycrystalline materials were tested. Results have shown an excellent repeatability and numerical errors that are less than 3% in high-purity samples.

Evidences of the evolution from solid solution to surface segregation in Ni-doped SnO(2) nanoparticles using Raman spectroscopy

Ni-doped SnO(2) nanoparticles, promising for gas-sensing applications, have been synthesized by a polymer precursor method. X-ray diffraction (XRD) and transmission electron microscopy (TEM) data analyses indicate the exclusive formation of nanosized particles with rutile-type phase (tetragonal SnO(2)) for Ni contents below 10 mol%. The mean crystallite size shows a progressive reduction with the Ni content. Room-temperature Raman spectra of Ni-doped SnO(2) nanoparticles show the presence of Raman active modes and modes activated by size effects. From the evolution of the A(1g) mode with the Ni content, a solubility limit at similar to 2 mol% was estimated. Below that content, Raman results are consistent with the occurrence of solid solution (ss) and surface segregation (seg.) of Ni ions. Above similar to 2 mol% Ni, the redshift of A(1g) mode suggests that the surface segregation of Ni ions takes place. Disorder-activated bands were determined and their integrated intensity evolution with the Ni content suggest that the solid-solution regime favors the increase of disorder; meanwhile, that disorder becomes weaker as the Ni content is increased. Copyright (C) 2010 John Wiley & Sons, Ltd.

High-resolution transmission electron microscopy and electron backscatter diffraction in nanoscaled ferritic and ferritic-martensitic oxide dispersion strengthened-steels

For specific blanket and divertor applications in future fusion power reactors a replacement of presently considered reduced activation ferritic martensitic (RAFM) steels as a structural material by suitable oxide dispersion strengthened ferritic martensitic steels would allow a substantial increase of the operating temperature from similar to 823 to about 923 K. Due to this reason the RAFM-alloy ODS-Eurofer has already been developed and produced with industrial partners. In the He-cooled modular divertor concept, where temperatures above 923 K will arise, an ODS-steel with a purely ferritic matrix is advantageous, because of missing phase transitions. Due to this reason, a special ferritic ODS-steel is being manufactured as well. In this work the microstructures of these two ODS-alloy types, analysed mainly by high resolution TEM are compared, with respect to different manufacturing processes. In addition first results of high resolution EBSD scans together with determined orientation maps of the RAFM steel ODS-Eurofer will also be presented. (C) 2008 Elsevier B.V. All rights reserved.

Experimental data and modeling of the thermodynamic properties of bread dough at refrigeration and freezing temperatures

Thermodynamic properties of bread dough (fusion enthalpy, apparent specific heat, initial freezing point and unfreezable water) were measured at temperatures from -40 degrees C to 35 degrees C using differential scanning calorimetry. The initial freezing point was also calculated based on the water activity of dough. The apparent specific heat varied as a function of temperature: specific heat in the freezing region varied from (1.7-23.1) J g(-1) degrees C(-1), and was constant at temperatures above freezing (2.7 J g(-1) degrees C(-1)). Unfreezable water content varied from (0.174-0.182) g/g of total product. Values of heat capacity as a function of temperature were correlated using thermodynamic models. A modification for low-moisture foodstuffs (such as bread dough) was successfully applied to the experimental data. (C) 2010 Elsevier Ltd. All rights reserved.

Effects of mechanical properties, residual stress and indenter tip geometry on instrumented indentation data in thin films

In this work, an axisymmetric two-dimensional finite element model was developed to simulate instrumented indentation testing of thin ceramic films deposited onto hard steel substrates. The level of film residual stress (sigma(r)), the film elastic modulus (E) and the film work hardening exponent (n) were varied to analyze their effects on indentation data. These numerical results were used to analyze experimental data that were obtained with titanium nitride coated specimens, in which the substrate bias applied during deposition was modified to obtain films with different levels of sigma(r). Good qualitative correlation was obtained when numerical and experimental results were compared, as long as all film properties are considered in the analyses, and not only sigma(r). The numerical analyses were also used to further understand the effect of sigma(r) on the mechanical properties calculated based on instrumented indentation data. In this case, the hardness values obtained based on real or calculated contact areas are similar only when sink-in occurs, i.e. with high n or high ratio VIE, where Y is the yield strength of the film. In an additional analysis, four ratios (R/h(max)) between indenter tip radius and maximum penetration depth were simulated to analyze the combined effects of R and sigma(r) on the indentation load-displacement curves. In this case, or did not significantly affect the load curve exponent, which was affected only by the indenter tip radius. On the other hand, the proportional curvature coefficient was significantly affected by sigma(r) and n. (C) 2010 Elsevier B.V. All rights reserved.

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.

Bias-corrected Pearson estimating functions for Taylor`s power law applied to benthic macrofauna data

Estimation of Taylor`s power law for species abundance data may be performed by linear regression of the log empirical variances on the log means, but this method suffers from a problem of bias for sparse data. We show that the bias may be reduced by using a bias-corrected Pearson estimating function. Furthermore, we investigate a more general regression model allowing for site-specific covariates. This method may be efficiently implemented using a Newton scoring algorithm, with standard errors calculated from the inverse Godambe information matrix. The method is applied to a set of biomass data for benthic macrofauna from two Danish estuaries. (C) 2011 Elsevier B.V. All rights reserved.

Different Approaches for Modeling Grouped Survival Data: A Mango Tree Study

Interval-censored survival data, in which the event of interest is not observed exactly but is only known to occur within some time interval, occur very frequently. In some situations, event times might be censored into different, possibly overlapping intervals of variable widths; however, in other situations, information is available for all units at the same observed visit time. In the latter cases, interval-censored data are termed grouped survival data. Here we present alternative approaches for analyzing interval-censored data. We illustrate these techniques using a survival data set involving mango tree lifetimes. This study is an example of grouped survival data.

Log-modified Weibull regression models with censored data: Sensitivity and residual analysis

This paper proposes a regression model considering the modified Weibull distribution. This distribution can be used to model bathtub-shaped failure rate functions. Assuming censored data, we consider maximum likelihood and Jackknife estimators for the parameters of the model. We derive the appropriate matrices for assessing local influence on the parameter estimates under different perturbation schemes and we also present some ways to perform global influence. Besides, for different parameter settings, sample sizes and censoring percentages, various simulations are performed and the empirical distribution of the modified deviance residual is displayed and compared with the standard normal distribution. These studies suggest that the residual analysis usually performed in normal linear regression models can be straightforwardly extended for a martingale-type residual in log-modified Weibull regression models with censored data. Finally, we analyze a real data set under log-modified Weibull regression models. A diagnostic analysis and a model checking based on the modified deviance residual are performed to select appropriate models. (c) 2008 Elsevier B.V. All rights reserved.

Regression models for grouped survival data: Estimation and sensitivity analysis

In this study, regression models are evaluated for grouped survival data when the effect of censoring time is considered in the model and the regression structure is modeled through four link functions. The methodology for grouped survival data is based on life tables, and the times are grouped in k intervals so that ties are eliminated. Thus, the data modeling is performed by considering the discrete models of lifetime regression. The model parameters are estimated by using the maximum likelihood and jackknife methods. To detect influential observations in the proposed models, diagnostic measures based on case deletion, which are denominated global influence, and influence measures based on small perturbations in the data or in the model, referred to as local influence, are used. In addition to those measures, the local influence and the total influential estimate are also employed. Various simulation studies are performed and compared to the performance of the four link functions of the regression models for grouped survival data for different parameter settings, sample sizes and numbers of intervals. Finally, a data set is analyzed by using the proposed regression models. (C) 2010 Elsevier B.V. All rights reserved.

The exponentiated generalized gamma distribution with application to lifetime data

A four-parameter extension of the generalized gamma distribution capable of modelling a bathtub-shaped hazard rate function is defined and studied. The beauty and importance of this distribution lies in its ability to model monotone and non-monotone failure rate functions, which are quite common in lifetime data analysis and reliability. The new distribution has a number of well-known lifetime special sub-models, such as the exponentiated Weibull, exponentiated generalized half-normal, exponentiated gamma and generalized Rayleigh, among others. We derive two infinite sum representations for its moments. We calculate the density of the order statistics and two expansions for their moments. The method of maximum likelihood is used for estimating the model parameters and the observed information matrix is obtained. Finally, a real data set from the medical area is analysed.

Double generalized linear model for tissue culture proportion data: a Bayesian perspective

Joint generalized linear models and double generalized linear models (DGLMs) were designed to model outcomes for which the variability can be explained using factors and/or covariates. When such factors operate, the usual normal regression models, which inherently exhibit constant variance, will under-represent variation in the data and hence may lead to erroneous inferences. For count and proportion data, such noise factors can generate a so-called overdispersion effect, and the use of binomial and Poisson models underestimates the variability and, consequently, incorrectly indicate significant effects. In this manuscript, we propose a DGLM from a Bayesian perspective, focusing on the case of proportion data, where the overdispersion can be modeled using a random effect that depends on some noise factors. The posterior joint density function was sampled using Monte Carlo Markov Chain algorithms, allowing inferences over the model parameters. An application to a data set on apple tissue culture is presented, for which it is shown that the Bayesian approach is quite feasible, even when limited prior information is available, thereby generating valuable insight for the researcher about its experimental results.

Vector within-host feeding preference mediates transmission of a heterogeneously distributed pathogen

2. We documented the within-host distribution of two vector species that differ in transmission efficiency, the leafhoppers Draeculacephala minerva and Graphocephala atropunctata, and which are free to move throughout entirely caged alfalfa plants. The more efficient vector D. minerva fed preferentially at the base of the plant near the soil surface, whereas the less efficient G. atropunctata preferred overwhelming the top of the plant. 3. Next we documented X. fastidiosa heterogeneity in mechanically inoculated plants. Infection rates were up to 50% higher and mean bacterial population densities were 100-fold higher near the plant base than at the top or in the taproot. 4. Finally, we estimated transmission efficiency of the two leafhoppers when they were confined at either the base or top of inoculated alfalfa plants. Both vectors were inefficient when confined at the top of infected plants and were 20-60% more efficient when confined at the plant base. 5. These results show that vector transmission efficiency is determined by the interaction between leafhopper within-plant feeding behaviour and pathogen within-plant distribution. Fine-scale vector and pathogen overlap is likely to be a requirement generally for efficient transmission of vector-borne pathogens.

Transmission efficiency of Xylella fastidiosa by sharpshooters (Hemiptera : Cicadellidae) in coffee and citrus

Xylella fastidiosa (Wells, Raju, Hung, Weisburg, Mandelco-Paul, and Brenner) is a bacteria] pathogen transmitted by several Sharpshooters in two tribes of Cicadellinae (Proconiini and Cicadellini). Here, we compared the transmission efficiency of X. fastidiosa in coffee (Coffea arabica L) and citrus [Citrus sinensis (L) Osbeck] by Cicadellini [Bucephalogonia xanthophis (Berg) and Dilobopterus costalimai Young] and Proconiini [Homalodisca ignorata Melichar and Oncometopia facialis (Signoret) I sharpshooters that Occur in both crops. At different seasons, healthy adults of each species were submitted to a 48-h acquisition access period on citrus or coffee source plants infected with X. fastidiosa isolates that cause Citrus variegated chlorosis (CVC) and Coffee leaf scorch (CLS), respectively, and then confined on healthy seedlings of the corresponding host plant for a 48-h inoculation access period. No significant effect of inoculation season was observed when comparing infection rates of citrus or coffee plants inoculated by vectors at different times of the year. In Citrus, the transmission rate by single insects was significantly higher for H. ignorata (30%) in relation to B. xanthophis (5%) and O. facialis (1.1%) but there was no difference among vector species in coffee, whose transmission rates ranged from 1.2 to 7.2%. Comparing host plants, H. ignorata was more effective in transmitting X. fastidiosa to citrus (30%) in relation to coffee (2.2%), whereas the other vectors transmitted the bacterium to both hosts with similar efficiencies. Despite these variations. vector efficiency in coffee and Citrus is lower than that reported in other hosts.

Evaluation of FAO Penman-Monteith and alternative methods for estimating reference evapotranspiration with missing data in Southern Ontario, Canada

Grass reference evapotranspiration (ETo) is an important agrometeorological parameter for climatological and hydrological studies, as well as for irrigation planning and management. There are several methods to estimate ETo, but their performance in different environments is diverse, since all of them have some empirical background. The FAO Penman-Monteith (FAD PM) method has been considered as a universal standard to estimate ETo for more than a decade. This method considers many parameters related to the evapotranspiration process: net radiation (Rn), air temperature (7), vapor pressure deficit (Delta e), and wind speed (U); and has presented very good results when compared to data from lysimeters Populated with short grass or alfalfa. In some conditions, the use of the FAO PM method is restricted by the lack of input variables. In these cases, when data are missing, the option is to calculate ETo by the FAD PM method using estimated input variables, as recommended by FAD Irrigation and Drainage Paper 56. Based on that, the objective of this study was to evaluate the performance of the FAO PM method to estimate ETo when Rn, Delta e, and U data are missing, in Southern Ontario, Canada. Other alternative methods were also tested for the region: Priestley-Taylor, Hargreaves, and Thornthwaite. Data from 12 locations across Southern Ontario, Canada, were used to compare ETo estimated by the FAD PM method with a complete data set and with missing data. The alternative ETo equations were also tested and calibrated for each location. When relative humidity (RH) and U data were missing, the FAD PM method was still a very good option for estimating ETo for Southern Ontario, with RMSE smaller than 0.53 mm day(-1). For these cases, U data were replaced by the normal values for the region and Delta e was estimated from temperature data. The Priestley-Taylor method was also a good option for estimating ETo when U and Delta e data were missing, mainly when calibrated locally (RMSE = 0.40 mm day(-1)). When Rn was missing, the FAD PM method was not good enough for estimating ETo, with RMSE increasing to 0.79 mm day(-1). When only T data were available, adjusted Hargreaves and modified Thornthwaite methods were better options to estimate ETo than the FAO) PM method, since RMSEs from these methods, respectively 0.79 and 0.83 mm day(-1), were significantly smaller than that obtained by FAO PM (RMSE = 1.12 mm day(-1). (C) 2009 Elsevier B.V. All rights reserved.