Improved finite element for 3D laminate frame analysis including warping for any cross-section

The most ordinary finite element formulations for 3D frame analysis do not consider the warping of cross-sections as part of their kinematics. So the stiffness, regarding torsion, should be directly introduced by the user into the computational software and the bar is treated as it is working under no warping hypothesis. This approach does not give good results for general structural elements applied in engineering. Both displacement and stress calculation reveal sensible deficiencies for both linear and non-linear applications. For linear analysis, displacements can be corrected by assuming a stiffness that results in acceptable global displacements of the analyzed structure. However, the stress calculation will be far from reality. For nonlinear analysis the deficiencies are even worse. In the past forty years, some special structural matrix analysis and finite element formulations have been proposed in literature to include warping and the bending-torsion effects for 3D general frame analysis considering both linear and non-linear situations. In this work, using a kinematics improvement technique, the degree of freedom ""warping intensity"" is introduced following a new approach for 3D frame elements. This degree of freedom is associated with the warping basic mode, a geometric characteristic of the cross-section, It does not have a direct relation with the rate of twist rotation along the longitudinal axis, as in existent formulations. Moreover, a linear strain variation mode is provided for the geometric non-linear approach, for which complete 3D constitutive relation (Saint-Venant Kirchhoff) is adopted. The proposed technique allows the consideration of inhomogeneous cross-sections with any geometry. Various examples are shown to demonstrate the accuracy and applicability of the proposed formulation. (C) 2009 Elsevier Inc. All rights reserved.

Simplified models for cross-section stress demands on C-section purlins in uplift

The objective of this paper is to provide and verify simplified models that predict the longitudinal stresses that develop in C-section purlins in uplift. The paper begins with the simple case of flexural stress: where the force has to be applied at the shear center, or the section braced in both flanges. Restrictions on load application point and restraint of the flanges are removed until arriving at the more complex problem of bending when movement of the tension flange alone is restricted, as commonly found in purlin-sheeting systems. Winter`s model for predicting the longitudinal stresses developed due to direct torsion is reviewed, verified, and then extended to cover the case of a bending member with tension flange restraint. The developed longitudinal stresses from flexure and restrained torsion are used to assess the elastic stability behavior of typical purlin-sheeting systems. Finally, strength predictions of typical C-section purlins are provided for existing AISI methods and a newly proposed extension to the direct strength method that employs the predicted longitudinal stress distributions within the strength prediction. (C) 2009 Elsevier Ltd. All rights reserved.

GENERALIZED FINITE ELEMENT METHOD FOR NONLINEAR THREE-DIMENSIONAL ANALYSIS OF SOLIDS

The Generalized Finite Element Method (GFEM) is employed in this paper for the numerical analysis of three-dimensional solids tinder nonlinear behavior. A brief summary of the GFEM as well as a description of the formulation of the hexahedral element based oil the proposed enrichment strategy are initially presented. Next, in order to introduce the nonlinear analysis of solids, two constitutive models are briefly reviewed: Lemaitre`s model, in which damage and plasticity are coupled, and Mazars`s damage model suitable for concrete tinder increased loading. Both models are employed in the framework of a nonlocal approach to ensure solution objectivity. In the numerical analyses carried out, a selective enrichment of approximation at regions of concern in the domain (mainly those with high strain and damage gradients) is exploited. Such a possibility makes the three-dimensional analysis less expensive and practicable since re-meshing resources, characteristic of h-adaptivity, can be minimized. Moreover, a combination of three-dimensional analysis and the selective enrichment presents a valuable good tool for a better description of both damage and plastic strain scatterings.

Residence time distribution in holding tubes using generalized convection model and numerical convolution for non-ideal tracer detection

A procedure is proposed for the determination of the residence time distribution (RTD) of curved tubes taking into account the non-ideal detection of the tracer. The procedure was applied to two holding tubes used for milk pasteurization in laboratory scale. Experimental data was obtained using an ionic tracer. The signal distortion caused by the detection system was considerable because of the short residence time. Four RTD models, namely axial dispersion, extended tanks in series, generalized convection and PER + CSTR association, were adjusted after convolution with the E-curve of the detection system. The generalized convection model provided the best fit because it could better represent the tail on the tracer concentration curve that is Caused by the laminar velocity profile and the recirculation regions. Adjusted model parameters were well cot-related with the now rate. (C) 2010 Elsevier Ltd. All rights reserved.

Trapezoidal SOI FinFET analog parameters` dependence on cross-section shape

The trapezium is often a better approximation for the FinFET cross-section shape, rather than the design-intended rectangle. The frequent width variations along the vertical direction, caused by the etching process that is used for fin definition, may imply in inclined sidewalls and the inclination angles can vary in a significant range. These geometric variations may cause some important changes in the device electrical characteristics. This work analyzes the influence of the FinFET sidewall inclination angle on some relevant parameters for analog design, such as threshold voltage, output conductance, transconductance, intrinsic voltage gain (A V), gate capacitance and unit-gain frequency, through 3D numeric simulation. The intrinsic gain is affected by alterations in transconductance and output conductance. The results show that both parameters depend on the shape, but in different ways. Transconductance depends mainly on the sidewall inclination angle and the fixed average fin width, whereas the output conductance depends mainly on the average fin width and is weakly dependent on the sidewall inclination angle. The simulation results also show that higher voltage gains are obtained for smaller average fin widths with inclination angles that correspond to inverted trapeziums, i.e. for shapes where the channel width is larger at the top than at the transistor base because of the higher attained transconductance. When the channel top is thinner than the base, the transconductance degradation affects the intrinsic voltage gain. The total gate capacitances also present behavior dependent on the sidewall angle, with higher values for inverted trapezium shapes and, as a consequence, lower unit-gain frequencies.

Anomalous compressibility of ferropericlase throughout the iron spin cross-over

The thermoelastic properties of ferropericlase Mg(1-x)Fe(x)O (x = 0.1875) throughout the iron high-to-low spin cross-over have been investigated by first principles at Earth`s lower mantle conditions. This cross-over has important consequences for elasticity such as an anomalous bulk modulus (K(S)) reduction. At room temperature the anomaly is somewhat sharp in pressure but broadens with increasing temperature. Along a typical geotherm it occurs across most of the lower mantle with a more significant K(S) reduction at approximate to 1,400-1,600 km depth. This anomaly might also cause a reduction in the effective activation energy for diffusion creep and lead to a viscosity minimum in the mid-lower mantle, in apparent agreement with results from inversion of data related with mantle convection and postglacial rebound.

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.

A generalized multi-period mean-variance portfolio optimization with Markov switching parameters

In this paper, we deal with a generalized multi-period mean-variance portfolio selection problem with market parameters Subject to Markov random regime switchings. Problems of this kind have been recently considered in the literature for control over bankruptcy, for cases in which there are no jumps in market parameters (see [Zhu, S. S., Li, D., & Wang, S. Y. (2004). Risk control over bankruptcy in dynamic portfolio selection: A generalized mean variance formulation. IEEE Transactions on Automatic Control, 49, 447-457]). We present necessary and Sufficient conditions for obtaining an optimal control policy for this Markovian generalized multi-period meal-variance problem, based on a set of interconnected Riccati difference equations, and oil a set of other recursive equations. Some closed formulas are also derived for two special cases, extending some previous results in the literature. We apply the results to a numerical example with real data for Fisk control over bankruptcy Ill a dynamic portfolio selection problem with Markov jumps selection problem. (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.

The generalized log-gamma mixture model with covariates: local influence and residual analysis

In a sample of censored survival times, the presence of an immune proportion of individuals who are not subject to death, failure or relapse, may be indicated by a relatively high number of individuals with large censored survival times. In this paper the generalized log-gamma model is modified for the possibility that long-term survivors may be present in the data. The model attempts to separately estimate the effects of covariates on the surviving fraction, that is, the proportion of the population for which the event never occurs. The logistic function is used for the regression model of the surviving fraction. Inference for the model parameters is considered via maximum likelihood. Some influence methods, such as the local influence and total local influence of an individual are derived, analyzed and discussed. Finally, a data set from the medical area is analyzed under the log-gamma generalized mixture model. A residual analysis is performed in order to select an appropriate model.

A generalized modified Weibull distribution for lifetime modeling

A four parameter generalization of the Weibull distribution capable of modeling a bathtub-shaped hazard rate function is defined and studied. The beauty and importance of this distribution lies in its ability to model monotone as well as non-monotone failure rates, which are quite common in lifetime problems and reliability. The new distribution has a number of well-known lifetime special sub-models, such as the Weibull, extreme value, exponentiated Weibull, generalized Rayleigh and modified Weibull distributions, among others. We derive two infinite sum representations for its moments. The density of the order statistics is obtained. The method of maximum likelihood is used for estimating the model parameters. Also, the observed information matrix is obtained. Two applications are presented to illustrate the proposed distribution. (C) 2008 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.

Analysis of genomic and functional RFLP derived markers associated with sucrose content, fiber and yield QTLs in a sugarcane (Saccharum spp.) commercial cross

Expressed sequence tags derived markers have a great potential to be used in functional map construction and QTL tagging. In the present work, sugarcane genomic probes and expressed sequence tags having homology to genes, mostly involved in carbohydrate metabolism were used in RFLP assays to identify putative QTLs as well as their epistatic interactions for fiber content, cane yield, pol and tones of sugar per hectare, at two crop cycles in a progeny derived from a bi-parental cross of sugarcane elite materials. A hundred and twenty marker trait associations were found, of which 26 at both crop cycle and 32 only at first ratoon cane. A sucrose synthase derived marker was associated with a putative QTL having a high negative effect on cane yield and also with a QTL having a positive effect on Pol at both crop cycles. Fifty digenic epistatic marker interactions were identified for the four traits evaluated. Of these, only two were observed at both crop cycles.

Parameterization and Evaluation of Predictions of DSSAT/CANEGRO for Brazilian Sugarcane

The DSSAT/CANEGRO model was parameterized and its predictions evaluated using data from five sugarcane (Sacchetrum spp.) experiments conducted in southern Brazil. The data used are from two of the most important Brazilian cultivars. Some parameters whose values were either directly measured or considered to be well known were not adjusted. Ten of the 20 parameters were optimized using a Generalized Likelihood Uncertainty Estimation (GLUE) algorithm using the leave-one-out cross-validation technique. Model predictions were evaluated using measured data of leaf area index (LA!), stalk and aerial dry mass, sucrose content, and soil water content, using bias, root mean squared error (RMSE), modeling efficiency (Eff), correlation coefficient, and agreement index. The Decision Support System for Agrotechnology Transfer (DSSAT)/CANEGRO model simulated the sugarcane crop in southern Brazil well, using the parameterization reported here. The soil water content predictions were better for rainfed (mean RMSE = 0.122mm) than for irrigated treatment (mean RMSE = 0.214mm). Predictions were best for aerial dry mass (Eff = 0.850), followed by stalk dry mass (Eff = 0.765) and then sucrose mass (Eff = 0.170). Number of green leaves showed the worst fit (Eff = -2.300). The cross-validation technique permits using multiple datasets that would have limited use if used independently because of the heterogeneity of measures and measurement strategies.