Buckling and post-buckling of extensible rods revisited: A multiple-scale solution

An exact non-linear formulation of the equilibrium of elastic prismatic rods subjected to compression and planar bending is presented, electing as primary displacement variable the cross-section rotations and taking into account the axis extensibility. Such a formulation proves to be sufficiently general to encompass any boundary condition. The evaluation of critical loads for the five classical Euler buckling cases is pursued, allowing for the assessment of the axis extensibility effect. From the quantitative viewpoint, it is seen that such an influence is negligible for very slender bars, but it dramatically increases as the slenderness ratio decreases. From the qualitative viewpoint, its effect is that there are not infinite critical loads, as foreseen by the classical inextensible theory. The method of multiple (spatial) scales is used to survey the post-buckling regime for the five classical Euler buckling cases, with remarkable success, since very small deviations were observed with respect to results obtained via numerical integration of the exact equation of equilibrium, even when loads much higher than the critical ones were considered. Although known beforehand that such classical Euler buckling cases are imperfection insensitive, the effect of load offsets were also looked at, thus showing that the formulation is sufficiently general to accommodate this sort of analysis. (c) 2008 Elsevier Ltd. All rights reserved.

Experimental evaluation on the oil influence in capillary tubes

This work presents the results of an experimental study on pure refrigerant R-134a and refrigerant-oil mixtures flowing through capillary tubes in order to analyse the oil influence in component performance. Tests were carried out for capillary tubes internal diameters of 0.69 mm and 0.82 mm, condensing temperatures ranging from 40 degrees C to 50 degrees C, and subcooling degrees between 3 degrees C and 12 degrees C. Pure refrigerant flow measurements were compared to those for refrigerant-oil mixtures with oil concentrations of 1.0% and 3.0%. (C) 2009 Elsevier Ltd. All rights reserved.

Wake instability issues: From circular cylinders to stalled airfoils

Some recent results regarding the global dynamical behaviour of the wake of circular cylinders and airfoils with massive separation are reviewed in this paper. In order to investigate the effect of interference, the three-dimensional instability modes are analysed for the flow around two circular cylinders in tandem. In the same way, the flow around a stalled airfoil is investigated in order to provide a better understanding of the three-dimensional characteristics of wakes forming downstream of a lifting body with massive separation. These results are compared with those found for an isolated cylinder. Some fundamental differences among these flows are discussed. (C) 2011 Elsevier Ltd. All rights reserved.

Linear viscoelasticity of styrenic block copolymers-clay nanocomposites

In this work, the rheological behavior of block copolymers with different morphologies (lamellar, cylindrical, spherical, and disordered) and their clay-containing nanocomposites was studied using small amplitude oscillatory shear. The copolymers studied were one asymmetric starblock styrene-butadiene-styrene copolymer and four styrene-ethylene/butylenes-styrene copolymers with different molecular architectures, one of them being modified with maleic anhydride. The nanocomposites of those copolymers were prepared by adding organophilic clay using three different preparation techniques: melt mixing, solution casting, and a hybrid melt mixing-solution technique. The nanocomposites were characterized by X-ray diffraction and transmission electron microscopy, and their viscoelastic properties were evaluated and compared to the ones of the pure copolymers. The influence of copolymer morphology and presence of clay on the storage modulus (G`) curves was studied by the evaluation of the changes in the low frequency slope of log G` x log omega (omega: frequency) curves upon variation of temperature and clay addition. This slope may be related to the degree of liquid- or solid-like behavior of a material. It was observed that at temperatures corresponding to the ordered state, the rheological behavior of the nanocomposites depended mainly on the viscoelasticity of each type of ordered phase and the variation of the slope due to the addition of clay was small. For temperatures corresponding to the disordered state, however, the rheological behavior of the copolymer nanocomposites was dictated mostly by the degree of clay dispersion: When the clay was well dispersed, a strong solid-like behavior corresponding to large G` slope variations was observed.

Robust integration of real time optimization with linear model predictive control

Here, we study the stable integration of real time optimization (RTO) with model predictive control (MPC) in a three layer structure. The intermediate layer is a quadratic programming whose objective is to compute reachable targets to the MPC layer that lie at the minimum distance to the optimum set points that are produced by the RTO layer. The lower layer is an infinite horizon MPC with guaranteed stability with additional constraints that force the feasibility and convergence of the target calculation layer. It is also considered the case in which there is polytopic uncertainty in the steady state model considered in the target calculation. The dynamic part of the MPC model is also considered unknown but it is assumed to be represented by one of the models of a discrete set of models. The efficiency of the methods presented here is illustrated with the simulation of a low order system. (C) 2010 Elsevier Ltd. All rights reserved.

On the Filtering Problem for Continuous-Time Markov Jump Linear Systems with no Observation of the Markov Chain

We consider in this paper the optimal stationary dynamic linear filtering problem for continuous-time linear systems subject to Markovian jumps in the parameters (LSMJP) and additive noise (Wiener process). It is assumed that only an output of the system is available and therefore the values of the jump parameter are not accessible. It is a well known fact that in this setting the optimal nonlinear filter is infinite dimensional, which makes the linear filtering a natural numerically, treatable choice. The goal is to design a dynamic linear filter such that the closed loop system is mean square stable and minimizes the stationary expected value of the mean square estimation error. It is shown that an explicit analytical solution to this optimal filtering problem is obtained from the stationary solution associated to a certain Riccati equation. It is also shown that the problem can be formulated using a linear matrix inequalities (LMI) approach, which can be extended to consider convex polytopic uncertainties on the parameters of the possible modes of operation of the system and on the transition rate matrix of the Markov process. As far as the authors are aware of this is the first time that this stationary filtering problem (exact and robust versions) for LSMJP with no knowledge of the Markov jump parameters is considered in the literature. Finally, we illustrate the results with an example.

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.

Non-linear modal analysis for beams subjected to axial loads: Analytical and finite-element solutions

A rigorous derivation of non-linear equations governing the dynamics of an axially loaded beam is given with a clear focus to develop robust low-dimensional models. Two important loading scenarios were considered, where a structure is subjected to a uniformly distributed axial and a thrust force. These loads are to mimic the main forces acting on an offshore riser, for which an analytical methodology has been developed and applied. In particular, non-linear normal modes (NNMs) and non-linear multi-modes (NMMs) have been constructed by using the method of multiple scales. This is to effectively analyse the transversal vibration responses by monitoring the modal responses and mode interactions. The developed analytical models have been crosschecked against the results from FEM simulation. The FEM model having 26 elements and 77 degrees-of-freedom gave similar results as the low-dimensional (one degree-of-freedom) non-linear oscillator, which was developed by constructing a so-called invariant manifold. The comparisons of the dynamical responses were made in terms of time histories, phase portraits and mode shapes. (C) 2008 Elsevier Ltd. All rights reserved.

Linear minimum mean square filter for discrete-time linear systems with Markov jumps and multiplicative noises

In this paper we obtain the linear minimum mean square estimator (LMMSE) for discrete-time linear systems subject to state and measurement multiplicative noises and Markov jumps on the parameters. It is assumed that the Markov chain is not available. By using geometric arguments we obtain a Kalman type filter conveniently implementable in a recurrence form. The stationary case is also studied and a proof for the convergence of the error covariance matrix of the LMMSE to a stationary value under the assumption of mean square stability of the system and ergodicity of the associated Markov chain is obtained. It is shown that there exists a unique positive semi-definite solution for the stationary Riccati-like filter equation and, moreover, this solution is the limit of the error covariance matrix of the LMMSE. The advantage of this scheme is that it is very easy to implement and all calculations can be performed offline. (c) 2011 Elsevier Ltd. All rights reserved.

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.

ECONOMICAL OCCUPATION OF AGRICULTURAL AREA OF PIRACICABA (SAO PAULO STATE, BRAZIL), INCLUDING RISK THROUGH LINEAR PROGRAMMING

The economic occupation of an area of 500 ha for Piracicaba was studied with the irrigated cultures of maize, tomato, sugarcane and beans, having used models of deterministic linear programming and linear programming including risk for the Target-Motad model, where two situations had been analyzed. In the deterministic model the area was the restrictive factor and the water was not restrictive for none of the tested situations. For the first situation the gotten maximum income was of R$ 1,883,372.87 and for the second situation it was of R$ 1,821,772.40. In the model including risk a producer that accepts risk can in the first situation get the maximum income of R$ 1,883,372. 87 with a minimum risk of R$ 350 year(-1), and in the second situation R$ 1,821,772.40 with a minimum risk of R$ 40 year(-1). Already a producer averse to the risk can get in the first situation a maximum income of R$ 1,775,974.81 with null risk and for the second situation R$ 1.707.706, 26 with null risk, both without water restriction. These results stand out the importance of the inclusion of the risk in supplying alternative occupations to the producer, allowing to a producer taking of decision considered the risk aversion and the pretension of income.

A Log-Linear Regression Model for the Beta-Weibull Distribution

We introduce the log-beta Weibull regression model based on the beta Weibull distribution (Famoye et al., 2005; Lee et al., 2007). We derive expansions for the moment generating function which do not depend on complicated functions. The new regression model represents a parametric family of models that includes as sub-models several widely known regression models that can be applied to censored survival data. We employ a frequentist analysis, a jackknife estimator, and a parametric bootstrap for the parameters of the proposed model. We derive the appropriate matrices for assessing local influences on the parameter estimates under different perturbation schemes and present some ways to assess global influences. Further, for different parameter settings, sample sizes, and censoring percentages, several simulations are performed. In addition, the empirical distribution of some modified residuals are displayed and compared with the standard normal distribution. These studies suggest that the residual analysis usually performed in normal linear regression models can be extended to a modified deviance residual in the proposed regression model applied to censored data. We define martingale and deviance residuals to evaluate the model assumptions. The extended regression model is very useful for the analysis of real data and could give more realistic fits than other special regression models.

High Throughput Simultaneous Assay of Atenolol and Chlortalidone in Combined Dose Tablets by Liquid Chromatography and Capillary Zone Electrophoresis

New fast liquid chromatographic and capillary zone electrophoresis methods were developed and validated for simultaneous determination of atenolol and chlortalidone in combined dose tablets. The reversed phase HPLC method was carried out on a CN LiChrosorb (R) (125 x 4 mm, 5 mu m) column. The CZE method was carried out on an uncoated fused-silica capillary of 30 cm x 75 mu m i.d. with 25 mmol L(-1) sodium tetraborate, pH 9.4. The total analysis time was <6 and <2.5 min for HPLC and CZE methods, respectively. Both methods can be used for stability studies as well.

Determination of Atropine Enantiomers in Ophthalmic Solutions by Liquid Chromatography Using a Chiral AGP (R) Column

Many therapeutic agents are commercialized under their racemic form. The enantiomers can show differences in the pharmacokinetic and pharmacodynamic profile. The use of a pure enantiomer in pharmaceutical formulations may result in a better therapeutic index and fewer adverse effects. Atropine, an alkaloid of Atropa belladonna, is a racemic mixture of l-hyoscyamine and d-hyoscyamine. It is widely used to dilate the pupil. To quantify these enantiomers in ophthalmic solutions, an HPLC method was developed and validated using a Chiral AGP (R) column at 20 degrees C. The mobile phase consisted of a buffered phosphate solution (containing 10 mM 1-octanesulfonic acid sodium salt and 7.5 mM triethylamine, adjusted to pH 7.0 with orthophosphoric acid) and acetonitrile (99 + 1, v/v). The flow rate was 0.6 mL/min, with UV detection at 205 nm. In the concentration range of 14.0-26.0 mu g/mL, the method was found to be linear (r > 0.9999), accurate (with recovery of 100.1-100.5%), and precise (RSD system: <= 0.6%; RSD intraday: <= 1.1%; RSD interday: <= 0.9%). The method was specific, and the standard and sample solutions were stable for up to 72 h. The factorial design assures robustness with a variation of +/-10% in the mobile phase components and 2 degrees C of column temperature. The complete validation, including stress testing and factorial design, was studied and is presented in this research.

Quantitative Determination of Gemifloxacin Mesylate in Tablets by Capillary Zone Electrophoresis and High Performance Liquid Chromatography

The aim of this study was to develop and validate selective and sensitive methods for quantitative determination of an antibacterial agent, gemifloxacin, in tablets by high performance liquid chromatography (HPLC) and capillary zone electrophoresis (CZE). The HPLC method was carried out on a LiChrospher (R) 100 RP-8e, 5 mu m (125 x 4 mm) column with a mobile phase composed of tetrahydrofuran-water (25:75, v/v) with 0.5 % of triethylamine and pH adjusted to 3.0 with orthophosphoric acid. The CZE method was performed using 50 mM sodium tetraborate buffer (pH 8.6). Samples were injected hydrodynamicaly (0.5 psi, 5 s) and the electrophoretic system was operated under normal polarity, at +20 kV and capillary temperature of 18 degrees C. A fused-silica capillary 40.2 cm (30 cm effective length) x 75 mu m i.d. was used. Both, HPLC and CZE could be interesting and efficient techniques to be applied for quality control in pharmaceutical industries.