950 resultados para Finite mixture modelling


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The growth behaviour of the vibrational wear phenomenon known as rail corrugation is investigated analytically and numerically using mathematical models. A simplified feedback model for wear-type rail corrugation that includes a wheel pass time delay is developed with an aim to analytically distil the most critical interaction occurring between the wheel/rail structural dynamics, rolling contact mechanics and rail wear. To this end, a stability analysis on the complete system is performed to determine the growth of wear-type rail corrugations over multiple wheelset passages. This analysis indicates that although the dynamical behaviour of the system is stable for each wheel passage, over multiple wheelset passages, the growth of wear-type corrugations is shown to be the result of instability due to feedback interaction between the three primary components of the model. The corrugations are shown analytically to grow for all realistic railway parameters. From this analysis an analytical expression for the exponential growth rate of corrugations in terms of known parameters is developed. This convenient expression is used to perform a sensitivity analysis to identify critical parameters that most affect corrugation growth. The analytical predictions are shown to compare well with results from a benchmarked time-domain finite element model. (C) 2004 Elsevier B.V. All rights reserved.

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This paper considers a model-based approach to the clustering of tissue samples of a very large number of genes from microarray experiments. It is a nonstandard problem in parametric cluster analysis because the dimension of the feature space (the number of genes) is typically much greater than the number of tissues. Frequently in practice, there are also clinical data available on those cases on which the tissue samples have been obtained. Here we investigate how to use the clinical data in conjunction with the microarray gene expression data to cluster the tissue samples. We propose two mixture model-based approaches in which the number of components in the mixture model corresponds to the number of clusters to be imposed on the tissue samples. One approach specifies the components of the mixture model to be the conditional distributions of the microarray data given the clinical data with the mixing proportions also conditioned on the latter data. Another takes the components of the mixture model to represent the joint distributions of the clinical and microarray data. The approaches are demonstrated on some breast cancer data, as studied recently in van't Veer et al. (2002).

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Finite mixture models are being increasingly used to model the distributions of a wide variety of random phenomena. While normal mixture models are often used to cluster data sets of continuous multivariate data, a more robust clustering can be obtained by considering the t mixture model-based approach. Mixtures of factor analyzers enable model-based density estimation to be undertaken for high-dimensional data where the number of observations n is very large relative to their dimension p. As the approach using the multivariate normal family of distributions is sensitive to outliers, it is more robust to adopt the multivariate t family for the component error and factor distributions. The computational aspects associated with robustness and high dimensionality in these approaches to cluster analysis are discussed and illustrated.

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Glass reinforced plastic (GRP) is now an established material for the fabrication of sonar windows. Its good mechanical strength, light weight, resistance to corrosion and acoustic transparency, are all properties which fit it for this application. This thesis describes a study, undertaken at the Royal Naval Engineering College, Plymouth, into the mechanical behaviour of a circular cylindrical sonar panel. This particular type of panel would be used to cover a flank array sonar in a ship or submarine. The case considered is that of a panel with all of its edges mechanically clamped and subject to pressure loading on its convex surface. A comprehensive program of testing, to determine the orthotropic elastic properties of the laminated composite panel material is described, together with a series of pressure tests on 1:5 scale sonar panels. These pressure tests were carried out in a purpose designed test rig, using air pressure to provide simulated hydrostatic and hydrodynamic loading. Details of all instrumentation used in the experimental work are given in the thesis. The experimental results from the panel testing are compared with predictions of panel behaviour obtained from both the Galerkin solution of Flugge's cylindrical shell equations (orthotropic case), and finite element modelling of the panels using PAFEC. A variety of appropriate panel boundary conditions are considered in each case. A parametric study, intended to be of use as a preliminary design tool, and based on the above Galerkin solution, is also presented. This parametric study considers cases of boundary conditions, material properties, and panel geometry, outside of those investigated in the experimental work Final conclusions are drawn and recommendations made regarding possible improvements to the procedures for design, manufacture and fixing of sonar panels in the Royal Navy.

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In this paper we investigate whether consideration of store-level heterogeneity in marketing mix effects improves the accuracy of the marketing mix elasticities, fit, and forecasting accuracy of the widely-applied SCAN*PRO model of store sales. Models with continuous and discrete representations of heterogeneity, estimated using hierarchical Bayes (HB) and finite mixture (FM) techniques, respectively, are empirically compared to the original model, which does not account for store-level heterogeneity in marketing mix effects, and is estimated using ordinary least squares (OLS). The empirical comparisons are conducted in two contexts: Dutch store-level scanner data for the shampoo product category, and an extensive simulation experiment. The simulation investigates how between- and within-segment variance in marketing mix effects, error variance, the number of weeks of data, and the number of stores impact the accuracy of marketing mix elasticities, model fit, and forecasting accuracy. Contrary to expectations, accommodating store-level heterogeneity does not improve the accuracy of marketing mix elasticities relative to the homogeneous SCAN*PRO model, suggesting that little may be lost by employing the original homogeneous SCAN*PRO model estimated using ordinary least squares. Improvements in fit and forecasting accuracy are also fairly modest. We pursue an explanation for this result since research in other contexts has shown clear advantages from assuming some type of heterogeneity in market response models. In an Afterthought section, we comment on the controversial nature of our result, distinguishing factors inherent to household-level data and associated models vs. general store-level data and associated models vs. the unique SCAN*PRO model specification.

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Dynamic positron emission tomography (PET) imaging can be used to track the distribution of injected radio-labelled molecules over time in vivo. This is a powerful technique, which provides researchers and clinicians the opportunity to study the status of healthy and pathological tissue by examining how it processes substances of interest. Widely used tracers include 18F-uorodeoxyglucose, an analog of glucose, which is used as the radiotracer in over ninety percent of PET scans. This radiotracer provides a way of quantifying the distribution of glucose utilisation in vivo. The interpretation of PET time-course data is complicated because the measured signal is a combination of vascular delivery and tissue retention effects. If the arterial time-course is known, the tissue time-course can typically be expressed in terms of a linear convolution between the arterial time-course and the tissue residue function. As the residue represents the amount of tracer remaining in the tissue, this can be thought of as a survival function; these functions been examined in great detail by the statistics community. Kinetic analysis of PET data is concerned with estimation of the residue and associated functionals such as ow, ux and volume of distribution. This thesis presents a Markov chain formulation of blood tissue exchange and explores how this relates to established compartmental forms. A nonparametric approach to the estimation of the residue is examined and the improvement in this model relative to compartmental model is evaluated using simulations and cross-validation techniques. The reference distribution of the test statistics, generated in comparing the models, is also studied. We explore these models further with simulated studies and an FDG-PET dataset from subjects with gliomas, which has previously been analysed with compartmental modelling. We also consider the performance of a recently proposed mixture modelling technique in this study.

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The goal of this research is to produce a system for powering medical implants to increase the lifetime of the implanted devices and reduce the battery size. The system consists of a number of elements – the piezoelectric material for generating power, the device design, the circuit for rectification and energy storage. The piezoelectric material is analysed and a process for producing a repeatable high quality piezoelectric material is described. A full width half maximum (FWHM) of the rocking curve X-Ray diffraction (XRD) scan of between ~1.5° to ~1.7° for test wafers was achieved. This is state of the art for AlN on silicon and means devices with good piezoelectric constants can be fabricated. Finite element modelling FEM) was used to design the structures for energy harvesting. The models developed in this work were established to have an accuracy better than 5% in terms of the difference between measured and modelled results. Devices made from this material were analysed for power harvesting ability as well as the effect that they have on the flow of liquid which is an important consideration for implantable devices. The FEM results are compared to experimental results from laser Doppler vibrometry (LDV), magnetic shaker and perfusion machine tests. The rectifying circuitry for the energy harvester was also investigated. The final solution uses multiple devices to provide the power to augment the battery and so this was a key feature to be considered. Many circuits were examined and a solution based on a fully autonomous circuit was advanced. This circuit was analysed for use with multiple low power inputs similar to the results from previous investigations into the energy harvesting devices. Polymer materials were also studied for use as a substitute for the piezoelectric material as well as the substrate because silicon is more brittle.

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Far-field stresses are those present in a volume of rock prior to excavations being created. Estimates of the orientation and magnitude of far-field stresses, often used in mine design, are generally obtained by single-point measurements of stress, or large-scale, regional trends. Point measurements can be a poor representation of far-field stresses as a result of excavation-induced stresses and geological structures. For these reasons, far-field stress estimates can be associated with high levels of uncertainty. The purpose of this thesis is to investigate the practical feasibility, applications, and limitations of calibrating far-field stress estimates through tunnel deformation measurements captured using LiDAR imaging. A method that estimates the orientation and magnitude of excavation-induced principal stress changes through back-analysis of deformation measurements from LiDAR imaged tunnels was developed and tested using synthetic data. If excavation-induced stress change orientations and magnitudes can be accurately estimated, they can be used in the calibration of far-field stress input to numerical models. LiDAR point clouds have been proven to have a number of underground applications, thus it is desired to explore their use in numerical model calibration. The back-analysis method is founded on the superposition of stresses and requires a two-dimensional numerical model of the deforming tunnel. Principal stress changes of known orientation and magnitude are applied to the model to create calibration curves. Estimation can then be performed by minimizing squared differences between the measured tunnel and sets of calibration curve deformations. In addition to the back-analysis estimation method, a procedure consisting of previously existing techniques to measure tunnel deformation using LiDAR imaging was documented. Under ideal conditions, the back-analysis method estimated principal stress change orientations within ±5° and magnitudes within ±2 MPa. Results were comparable for four different tunnel profile shapes. Preliminary testing using plastic deformation, a rough tunnel profile, and profile occlusions suggests that the method can work under more realistic conditions. The results from this thesis set the groundwork for the continued development of a new, inexpensive, and efficient far-field stress estimate calibration method.

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The Dirichlet distribution is a multivariate generalization of the Beta distribution. It is an important multivariate continuous distribution in probability and statistics. In this report, we review the Dirichlet distribution and study its properties, including statistical and information-theoretic quantities involving this distribution. Also, relationships between the Dirichlet distribution and other distributions are discussed. There are some different ways to think about generating random variables with a Dirichlet distribution. The stick-breaking approach and the Pólya urn method are discussed. In Bayesian statistics, the Dirichlet distribution and the generalized Dirichlet distribution can both be a conjugate prior for the Multinomial distribution. The Dirichlet distribution has many applications in different fields. We focus on the unsupervised learning of a finite mixture model based on the Dirichlet distribution. The Initialization Algorithm and Dirichlet Mixture Estimation Algorithm are both reviewed for estimating the parameters of a Dirichlet mixture. Three experimental results are shown for the estimation of artificial histograms, summarization of image databases and human skin detection.

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Previous studies about the strength of the lithosphere in the Iberia centre fail to resolve the depth of earthquakes because of the rheological uncertainties. Therefore, new contributions are considered (the crustal structure from a density model) and several parameters (tectonic regime, mantle rheology, strain rate) are checked in this paper to properly examine the role of lithospheric strength in the intraplate seismicity and the Cenozoic evolution. The strength distribution with depth, the integrated strength, the effective elastic thickness and the seismogenic thickness have been calculated by a finite element modelling of the lithosphere across the Central System mountain range and the bordering Duero and Madrid sedimentary basins. Only a dry mantle under strike-slip/extension and a strain rate of 10-15 s-1, or under extension and 10-16 s-1, causes a strong lithosphere. The integrated strength and the elastic thickness are lower in the mountain chain than in the basins. These anisotropies have been maintained since the Cenozoic and determine the mountain uplift and the biharmonic folding of the Iberian lithosphere during the Alpine deformations. The seismogenic thickness bounds the seismic activity in the upper–middle crust, and the decreasing crustal strength from the Duero Basin towards the Madrid Basin is related to a parallel increase in Plio–Quaternary deformations and seismicity. However, elasto–plastic modelling shows that current African–Eurasian convergence is resolved elastically or ductilely, which accounts for the low seismicity recorded in this region.

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Densification of metallic powders by means of extrusion is regarded as a very attractive processing technique that allows obtaining a high level of relative density of the compact. However, the uniformity of the relative density depends on that of strain distribution and on the processing parameters. Several variants of extrusion can be used for compaction of metal particulates, including the conventional extrusion (CE) and equal channel angular pressing (ECAP), often referred to as equal-channel angular extrusion. Each of these processes has certain advantages and drawbacks with respect to compaction. A comparative study of these two extrusion processes influencing the relative density of compacts has been conducted by numerical simulation using commercial finite element software DEFORM2D. The results have been validated by experiments with titanium and magnesium powders and chips.

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The ‘wear mode diagram’ has been commonly used to classify the deformation regime of the soft work-piece during scratching, into three modes: ploughing, wedge formation and cutting. The scratch test is usedto evaluate wear modes and material removal associated with wear. There are different damage models in the literature used for the description of material behaviour after damage initiation under different loadingconditions. However, there has been little analysis to compare damage models during scratch test conditions. The first aim of this work is first to use a finite element modelling package (Abaqus/Explicit) to build a 3Dmodel to capture deformation modes during scratching with indenters with different attack angles. Three different damage models are incorporated into the model and patterns of damage initiation and propagation arecompared with experimental results from the literature. This work highlights the role of the damage model in accurately capturing wear modes and material removal during two body sliding interactions.

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This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.Skull structure is intimately associated with feeding ability in vertebrates, both in terms of specific performance measures and general ecological characteristics. This study quantitatively assessed variation in the shape of the cranium and mandible in varanoid lizards, and its relationship to structural performance (von Mises strain) and interspecific differences in feeding ecology. Geometric morphometric and linear morphometric analyses were used to evaluate morphological differences, and finite element analysis was used to quantify variation in structural performance (strain during simulated biting, shaking and pulling). This data was then integrated with ecological classes compiled from relevant scientific literature on each species in order to establish structure-function relationships. Finite element modelling results showed that variation in cranial morphology resulted in large differences in the magnitudes and locations of strain in biting, shaking and pulling load cases. Gracile species such as Varanus salvadorii displayed high strain levels during shaking, especially in the areas between the orbits. All models exhibit less strain during pull back loading compared to shake loading, even though a larger force was applied (pull =30N, shake = 20N). Relationships were identified between the morphology, performance, and ecology. Species that did not feed on hard prey clustered in the gracile region of cranial morphospace and exhibited significantly higher levels of strain during biting (P = 0.0106). Species that fed on large prey clustered in the elongate area of mandible morphospace. This relationship differs from those that have been identified in other taxonomic groups such as crocodiles and mammals. This difference may be due to a combination of the open 'space-frame' structure of the varanoid lizard skull, and the 'pull back' behaviour that some species use for processing large prey.