Comparison of friction models applied to a control valve

Eight different models to represent the effect of friction in control valves are presented: four models based on physical principles and four empirical ones. The physical models, both static and dynamic, have the same structure. The models are implemented in Simulink/Matlab (R) and compared, using different friction coefficients and input signals. Three of the models were able to reproduce the stick-slip phenomenon and passed all the tests, which were applied following ISA standards. (C) 2008 Elsevier Ltd. All rights reserved.

Adequacy of Cold Rolling Models to Upgrade Set-up Generation Systems

This paper presents two strategies for the upgrade of set-up generation systems for tandem cold mills. Even though these mills have been modernized mainly due to quality requests, their upgrades may be made intending to replace pre-calculated reference tables. In this case, Bryant and Osborn mill model without adaptive technique is proposed. As a more demanding modernization, Bland and Ford model including adaptation is recommended, although it requires a more complex computational hardware. Advantages and disadvantages of these two systems are compared and discussed and experimental results obtained from an industrial cold mill are shown.

Dynamic models for computer viruses

Computer viruses are an important risk to computational systems endangering either corporations of all sizes or personal computers used for domestic applications. Here, classical epidemiological models for disease propagation are adapted to computer networks and, by using simple systems identification techniques a model called SAIC (Susceptible, Antidotal, Infectious, Contaminated) is developed. Real data about computer viruses are used to validate the model. (c) 2008 Elsevier Ltd. All rights reserved.

The generalized inverse Weibull distribution

The inverse Weibull distribution has the ability to model failure rates which are quite common in reliability and biological studies. A three-parameter generalized inverse Weibull distribution with decreasing and unimodal failure rate is introduced and studied. We provide a comprehensive treatment of the mathematical properties of the new distribution including expressions for the moment generating function and the rth generalized moment. The mixture model of two generalized inverse Weibull distributions is investigated. The identifiability property of the mixture model is demonstrated. For the first time, we propose a location-scale regression model based on the log-generalized inverse Weibull distribution for modeling lifetime data. In addition, we develop some diagnostic tools for sensitivity analysis. Two applications of real data are given to illustrate the potentiality of the proposed regression model.

Residuals for log-Burr XII regression models in survival analysis

In this paper, we compare three residuals to assess departures from the error assumptions as well as to detect outlying observations in log-Burr XII regression models with censored observations. These residuals can also be used for the log-logistic regression model, which is a special case of the log-Burr XII regression model. For different parameter settings, sample sizes and censoring percentages, various simulation studies are performed and the empirical distribution of each 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 to the modified martingale-type residual in log-Burr XII regression models with censored data.

Influence diagnostics for polyhazard models in the presence of covariates

In this paper, we present various diagnostic methods for polyhazard models. Polyhazard models are a flexible family for fitting lifetime data. Their main advantage over the single hazard models, such as the Weibull and the log-logistic models, is to include a large amount of nonmonotone hazard shapes, as bathtub and multimodal curves. Some influence methods, such as the local influence and total local influence of an individual are derived, analyzed and discussed. A discussion of the computation of the likelihood displacement as well as the normal curvature in the local influence method are presented. Finally, an example with real data is given for illustration.

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.

On estimation and influence diagnostics for zero-inflated negative binomial regression models

The zero-inflated negative binomial model is used to account for overdispersion detected in data that are initially analyzed under the zero-Inflated Poisson model A frequentist analysis a jackknife estimator and a non-parametric bootstrap for parameter estimation of zero-inflated negative binomial regression models are considered In addition an EM-type algorithm is developed for performing maximum likelihood estimation Then the appropriate matrices for assessing local influence on the parameter estimates under different perturbation schemes and some ways to perform global influence analysis are derived In order to study departures from the error assumption as well as the presence of outliers residual analysis based on the standardized Pearson residuals is discussed The relevance of the approach is illustrated with a real data set where It is shown that zero-inflated negative binomial regression models seems to fit the data better than the Poisson counterpart (C) 2010 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.

Material properties and nondestructive evaluation of laminated veneer lumber (LVL) made from Pinus oocarpa and P. kesiya

This study aimed at evaluating the mechanical, physical and biological properties of laminated veneer lumber (LVL) made from Pinus oocarpa Schiede ex Schltdl (PO) and Pinus kesiya Royle ex Gordon (PK) and at providing a nondestructive characterization thereof. Four PO and four PK LVL boards from 22 randomly selected 2-mm thickness veneers were produced according to the following characteristics: phenol-formaldehyde (190 g/m(2)), hot-pressing at 150A degrees C for 45 min and 2.8 N/mm(2) of specific pressure. After board production, nondestructive evaluation was conducted, and stress wave velocity (v (0)) and dynamic modulus of elasticity (E (Md) ) were determined. The following mechanical and physical properties were then evaluated: static bending modulus of elasticity (E (M) ), modulus of rupture (f (M) ), compression strength parallel to grain (f (c,0)), shear strength parallel to glue-line (f (v,0)), shear strength perpendicular to glue-line (f (v,90)), thickness swelling (TS), water absorption (WA), and permanent thickness swelling (PTS) for 2, 24, and 96-hour of water immersion. Biological property was also evaluated by measuring the weight loss by Trametes versicolor (Linnaeus ex Fries) Pilat (white-rot) and Gloeophyllum trabeum (Persoon ex Fries.) Murrill (brown-rot). After hot-pressing, no bubbles, delamination nor warping were observed for both species. In general, PK boards presented higher mechanical properties: E (M) , E (Md) , f (M) , f (c,0) whereas PO boards were dimensionally more stable, with lower values of WA, TS and PTS in the 2, 24, and 96-hour immersion periods. Board density, f (v,0), f (v,90) and rot weight loss were statistically equal for PO and PK LVL. The prediction of flexural properties of consolidated LVL by the nondestructive method used was not very efficient, and the fitted models presented lower predictability.

Fungal pathogens as classical biological control agents against arthropods

Fungal entomopathogens have been used more frequently than other types of pathogens for classical biological control. Among 136 programs using different groups of arthropod pathogens, 49.3% have introduced fungal pathogens (including both the traditional fungi and microsporidia). The most commonly introduced species was Metarhizium anisopliae (Metschnikoff) Sorokin, with 13 introductions, followed by Entomophaga maimaiga Humber, Shimazu & Soper, which was released seven times. The majority of introduction programs have focused on controlling invasive species of insects or mites (70.7%) rather than on native hosts (29.4%). Almost half of the introductions of traditional fungi targeted species of Hemiptera and 75% of the microsporidia introduced have been introduced against lepidopteran species. The United States was the country where most introductions of fungi took place (n = 24). From 1993 to 2007, no arthropod pathogens were released in the US due to the rigorous regulatory structure, but in 2008 two species of microsporidia were introduced against the gypsy moth, Lymantria dispar (L.). Establishment of entomopathogenic fungi in programs introducing traditional fungi was 32.1% and establishment was 50.0% for programs introducing microsporidia. In some programs, releases have resulted in permanent successful establishment with no non-target effects. In summary, classical biological control using fungal entomopathogens can provide a successful and environmentally friendly avenue for controlling arthropod pests, including the increasing numbers of invasive non-native species.

Biological characteristics and thermal requirements of a Brazilian strain of the parasitoid Trichogramma pretiosum reared on eggs of Pseudoplusia includens and Anticarsia gemmatalis

A new strain of the parasitoid Trichogramma pretiosum, was collected in Rio Verde County, State of Goias, Central Brazil, and designated as T. pretiosum RV. This strain was then found to be the most effective one among several different strains of T. pretiosum tested in a parasitoid selection assay. Therefore, its biological characteristics and thermal requirements were studied, aiming at allowing its multiplication under controlled environmental conditions in the laboratory. The parasitoid was reared on eggs of Pseudoplusia includens and Anticarsia gemmatalis at different constant temperatures within an 18-32 degrees C temperature range. The number of annual generations of the parasitoid was also estimated at those temperatures. Results have shown that T. pretiosum RV developmental time, from egg to adult, was influenced by all temperatures tested within the range, varying from 6.8 to 20.3 days and 6.0 to 17.0 days on eggs of P. includens and A. gemmatalis, respectively. The emergence of T. pretiosum RV from eggs of A. gemmatalis was higher than 94% at all temperatures tested. When this variable was evaluated on eggs of P. includens, however, the figures were higher than that within the 18-30 degrees C range (more than 98%), and were also statistically higher than the emergence observed at 32 degrees C (90.2%). The sex ratio of the parasitoids emerged from eggs of A. gemmatalis decreased from 0.55 to 0.29 at 18-32 degrees C, respectively. However, for those emerged from eggs of P. includens, the sex ratio was similar (0.73, 0.72 and 0.71) at 20, 28 and 32 degrees C, respectively. The lower temperature threshold (Tb) and thermal constant (K) were 10.65 degrees C and 151.25 degree-days when the parasitoid was reared on eggs of P. includens; and 11.64 degrees C and 127.60 degree-days when reared on eggs of A. gemmatalis. The number of generations per month increased from 1.45 to 4.23 and from 1.49 to 4.79 when the parasitoid was reared on eggs of P. includens and A. gemmatalis, respectively, following the increases in the temperature. (C) 2009 Elsevier Inc. All rights reserved.

Spatial portability of numerical models of leaf wetness duration based on empirical approaches

Leaf wetness duration (LWD) models based on empirical approaches offer practical advantages over physically based models in agricultural applications, but their spatial portability is questionable because they may be biased to the climatic conditions under which they were developed. In our study, spatial portability of three LWD models with empirical characteristics - a RH threshold model, a decision tree model with wind speed correction, and a fuzzy logic model - was evaluated using weather data collected in Brazil, Canada, Costa Rica, Italy and the USA. The fuzzy logic model was more accurate than the other models in estimating LWD measured by painted leaf wetness sensors. The fraction of correct estimates for the fuzzy logic model was greater (0.87) than for the other models (0.85-0.86) across 28 sites where painted sensors were installed, and the degree of agreement k statistic between the model and painted sensors was greater for the fuzzy logic model (0.71) than that for the other models (0.64-0.66). Values of the k statistic for the fuzzy logic model were also less variable across sites than those of the other models. When model estimates were compared with measurements from unpainted leaf wetness sensors, the fuzzy logic model had less mean absolute error (2.5 h day(-1)) than other models (2.6-2.7 h day(-1)) after the model was calibrated for the unpainted sensors. The results suggest that the fuzzy logic model has greater spatial portability than the other models evaluated and merits further validation in comparison with physical models under a wider range of climate conditions. (C) 2010 Elsevier B.V. All rights reserved.

Alternative Analytical Expressions for the General van Genuchten-Mualem and van Genuchten-Burdine Hydraulic Conductivity Models

The van Genuchten expressions for the unsaturated soil hydraulic properties, first published in 1980, are used frequently in various vadose zone flow and transport applications assuming a specific relationship between the m and n soil hydraulic parameters. By comparison, probably because of the complexity of the hydraulic conductivity equations, the more general solutions with independent m and n values are rarely used. We expressed the general van Genuchten-Mualem and van Genuchten-Burdine hydraulic conductivity equations in terms of hypergeometric functions, which can be approximated by infinite series that converge rapidly for relatively large values of the van Genuchten-Mualem parameter n but only very slowly when n is close to one. Alternative equations were derived that provide very close approximations of the analytical results. The newly proposed equations allow the use of independent values of the parameters m and n in the soil water retention model of van Genuchten for subsequent prediction of the van Genuchten-Mualem and van Genuchten-Burdine hydraulic conductivity models, thus providing more flexibility in fitting experimental pressure-head-dependent water content, theta(h), and hydraulic conductivity, K(h), or K(theta) data.

Forecasting fuel ethanol consumption in Brazil by time series models: 2006-2012

This article analysed scenarios for Brazilian consumption of ethanol for the period 2006 to 2012. The results show that if the country`s GDP sustains a 4.6% a year growth, domestic consumption of fuel ethanol could increase to 25.16 billion liters in this period, which is a volume relatively close to the forecasted gasoline consumption of 31 billion liters. At a lower GDP growth of 1.22% a year, gasoline consumption would be reduced and domestic ethanol consumption in Brazil would be no higher than 18.32 billion liters. Contrary to the current situation, forecasts indicated that hydrated ethanol consumption could become much higher than anhydrous consumption in Brazil. The former is being consumed in cars moved exclusively by ethanol and flex-fuel cars, successfully introduced in the country at 2003. Flex cars allow Brazilian consumers to choose between gasoline and hydrated ethanol and immediately switch to whichever fuel presents the most favourable relative price.