21 resultados para rotational bands

em Deakin Research Online - Australia


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The giant lantern shark, Etmopterus baxteri, is taken as bycatch of commercial fisheries that operate in deepwater off southeastern Australia. Bands on the second dorsal spine were used to obtain age estimates. The number of bands on the external surface of the spine and within the inner dentine layer increased with animal length. Most spines had more bands on the external surface, and the rate of band formation was significantly different between the external surface and the inner dentine layer. Females had a maximum of 57 external bands and 26 internal bands, while males had up to 48 external bands and 22 internal bands. Age estimates from external bands suggest maturity (A 50) at 20 years for males and 30 years for females. Internal band age estimates suggest maturity at 10.5 years for males and 11.5 years for females. Although there is a large discrepancy between these two preliminary (i.e., unvalidated) age estimates, they both suggest that E. baxteri is a long-lived and late maturing species that is likely to be susceptible to over fishing.

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Bands on the external surface of the second dorsal-fin spine proved to be a novel method of estimating the age and growth of Centroselachus crepidater. Bands that followed the shape of the spine base were enhanced with an alizarin red derivative. Internal bands in spine cross sections were also examined. The number of both external and internal bands increased with animal size, although most spines had more external than internal bands. External bands were more reliable and were assumed to be annuli. The rate of band formation differed after five bands had been formed, and internal bands ceased forming after 30 years. Females to 54 years old and males to 34 years old were examined. Maturity occurred over a wide age range, with estimates of 20 years for females and 9 years for males. The youngest pregnant female was 27 years old. The Francis reparameterized von Bertalanffy growth model found similar growth for males and females, and the von Bertalanffy equations were Lt = 96.12(1 – e(–0.072(t+6.13))) for females and Lt = 73.22(1 – e(–0.141(t+2.99))) for males.

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The paper introduces four families of three-DOFs translational-rotational Parallel-Kinematics Mechanisms (PKMs) as well as the mobility analysis of such families using Lie group theory. Two of these families are mechanisms with one-rotational two-translational degrees of freedom (DOFs) and each of the other two has one-translational two-rotational DOFs. Four novel mechanisms are presented and discussed as representatives of these four families. Although these mechanisms are asymmetric, the components used to realise them are very similar and, hence, there is no great departure from the favourable modularity of parallel-kinematics mechanisms.


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The paper introduces a family of three-DOFs translational-rotational Parallel-Kinematics Mechanisms (PKMs) as well as the mobility analysis of such family using Lie-group theory. Each member of this family has two-rotational one-translational DOFs. A novel mechanism is presented and analyzed as a representative of that family. The use and the practical value of that modular mechanism are emphasized.


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The recent successful development of the equal channel angular pressing (ECAP) process in metals provides a feasible solution to produce ultra-fine or nano-grained bulk: materials with tailored material properties. However, ECAP is difficult to scale up commercially due to excessive load requirements. In this paper, a new Multi-ECAP process with die rotation is considered to obtain ultra-fine grain structured materials under a moderate deformation force. It is shown that an addition of torsion results in a reduction in the pressing force and an increase in severity of plastic deformation. An analysis using the upper bound method is found to be useful in predicting the pressing load and flow pattern of ECAP with and without rotational dies. Solutions are obtained for different inclined channel angles under different angular velocities of dies. Relative pressures are presented and some computed solutions are compared with those found by FEM simulation. The theoretical predictions of the pressing load are in good agreement with the simulation results. The amount of plastic deformation is determined by the inclined angle between the two intersecting channels, and the velocity ratio between the angular velocity of dies and the normal component of the punch velocity.

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The main aim of this work is application of the developed cellular automata (CA) model to investigate influence of the micro shear bands that are present in the heavily deformed material on the static recrystallization. This initial work is the results of recent experimental analyses indicating that the micro shear bands are preferred sites for nucleation of the recrystallization. The procedure of creation of the initial microstructure with features such as grains and micro shear bands as well as basis of the developed CA code for the static recrystallization are also presented in the paper. Finally, the simulation results obtained from different recrystallization temperatures for the microstructures with and without micro shear bands are compared with each other and differences are discussed.

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Shear bands formed during both cold and hot plastic deformation have been linked with several proposed mechanisms for the formation of ultrafine grains. The aim of the present work was to undertake a detailed investigation of the microstructural and crystallographic characteristics of the shear bands formed during hot deformation of a 22Cr-19Ni-3Mo (mass%) austenitic stainless steel and a Fe-30 mass%Ni based austenitic model alloy. These alloys were subjected to deformation in torsion and plane strain compression (PSC), respectively, at temperatures of 900°C and 950°C and strain rates of 0.7s-1 and 10s-1, respectively. Transmission electron microscopy and electron backscatter diffraction in conjunction with scanning electron microscopy were employed in the investigation. It has been observed that shear bands already started to form at moderate strains in a matrix of pre-existing microbands and were composed of fine, slightly elongated subgrains (fragments). These bands propagated along a similar macroscopic path and the subgrains, present within their substructure, were rotated relative to the surrounding matrix about axes approximately parallel to the sample radial and transverse directions for deformation in torsion and PSC, respectively. The subgrain boundaries were largely observed to be non-crystallographic, suggesting that the subgrains generally formed via multiple slip processes. Shear bands appeared to form through a co-operative nucleation of originally isolated subgrains that gradually interconnected with the others to form long, thin bands that subsequently thickened via the formation of new subgrains. The observed small dimensions of the subgrains present within shear bands and their large misorientations clearly indicate that these subgrains can serve as potent nucleation sites for the formation of ultrafine grain structures during both subsequent recrystallisation, as observed during the present PSC experiments, and phase transformation.

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RF MEMS plays an important role in microwave switching. The high performance of RF MEMS shunt such as high bandwidth, low insertion loss, and high isolation have made these switches well suitable for high performing microwave and millimeter wave circuits. This paper presents a RF MEMS shunt capacitive switch for Ka and V band application. This paper investigates the effect of various geometrical parameters on RF characteristics of the switch. The simulation results are presented and discussed.

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Thermal analysis, impedance spectroscopy, NMR and Raman spectroscopy have been used to investigate the plastic crystal dimethylpyrrolidinium thiocyanate in order to gain further insight into the properties of organic ionic plastic crystals. This compound has a solid–solid phase transition at 82 °C, and melts at 122 °C. A step increase in conductivity of about one order of magnitude is observed at the phase transition, followed by a decrease in activation energy for conduction. A large entropy gain occurs at the II → I transition, and 1H NMR linewidth measurements together with second moment calculations showed that the dimethylpyrrolidinium cation goes from a static state, to full isotropic tumbling. Raman measurements confirm that the cation as well as the anion exhibit increased rotational mobility when entering phase I.

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In a nonparametric setting, the functional form of the relationship between the response variable and the associated predictor variables is assumed to be unknown when data is fitted to the model. Non-parametric regression models can be used for the same types of applications such as estimation, prediction, calibration, and optimization that traditional regression models are used for. The main aim of nonparametric regression is to highlight an important structure in the data without any assumptions about the shape of an underlying regression function. Hence the nonparametric approach allows the data to speak for itself. Applications of sequential procedures to a nonparametric regression model at a given point are considered.

The primary goal of sequential analysis is to achieve a given accuracy by using the smallest possible sample sizes. These sequential procedures allow an experimenter to make decisions based on the smallest number of observations without compromising accuracy. In the nonparametric regression model with a random design based on independent and identically distributed pairs of observations (X ,Y ), where the regression function m(x) is given bym(x) = E(Y X = x), estimation of the Nadaraya-Watson kernel estimator (m (x)) NW and local linear kernel estimator (m (x)) LL for the curve m(x) is considered. In order to obtain asymptotic confidence intervals form(x), two stage sequential procedure is used under which some asymptotic properties of Nadaraya-Watson and local linear estimators have been obtained.

The proposed methodology is first tested with the help of simulated data from linear and nonlinear functions. Encouraged by the preliminary findings from simulation results, the proposed method is applied to estimate the nonparametric regression curve of CAPM.

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We consider a random design model based on independent and identically distributed (iid) pairs of observations (Xi, Yi), where the regression function m(x) is given by m(x) = E(Yi|Xi = x) with one independent variable. In a nonparametric setting the aim is to produce a reasonable approximation to the unknown function m(x) when we have no precise information about the form of the true density, f(x) of X. We describe an estimation procedure of non-parametric regression model at a given point by some appropriately constructed fixed-width (2d) confidence interval with the confidence coefficient of at least 1−. Here, d(> 0) and 2 (0, 1) are two preassigned values. Fixed-width confidence intervals are developed using both Nadaraya-Watson and local linear kernel estimators of nonparametric regression with data-driven bandwidths.

The sample size was optimized using the purely and two-stage sequential procedure together with asymptotic properties of the Nadaraya-Watson and local linear estimators. A large scale simulation study was performed to compare their coverage accuracy. The numerical results indicate that the confidence bands based on the local linear estimator have the best performance than those constructed by using Nadaraya-Watson estimator. However both estimators are shown to have asymptotically correct coverage properties.

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We consider a random design model based on independent and identically distributed pairs of observations (Xi, Yi), where the regression function m(x) is given by m(x) = E(Yi|Xi = x) with one independent variable. In a nonparametric setting the aim is to produce a reasonable approximation to the unknown function m(x) when we have no precise information about the form of the true density, f(x) of X. We describe an estimation procedure of non-parametric regression model at a given point by some appropriately constructed fixed-width (2d) confidence interval with the confidence coefficient of at least 1−. Here, d(> 0) and 2 (0, 1) are two preassigned values. Fixed-width confidence intervals are developed using both Nadaraya-Watson and local linear kernel estimators of nonparametric regression with data-driven bandwidths. The sample size was optimized using the purely and two-stage sequential procedures together with asymptotic properties of the Nadaraya-Watson and local linear estimators. A large scale simulation study was performed to compare their coverage accuracy. The numerical results indicate that the confi dence bands based on the local linear estimator have the better performance than those constructed by using Nadaraya-Watson estimator. However both estimators are shown to have asymptotically correct coverage properties.