Dynamic characterisation of four nine-story large-panel R.C. buildings in Bishkek (Kyrgyzstan): A comparison between experimental ambient vibration analysis and numerical finite element modeling

With the outlook of improving seismic vulnerability assessment for the city of Bishkek (Kyrgyzstan), the global dynamic behaviour of four nine-storey r.c. large-panel buildings in elastic regime is studied. The four buildings were built during the Soviet era within a serial production system. Since they all belong to the same series, they have very similar geometries both in plan and in height. Firstly, ambient vibration measurements are performed in the four buildings. The data analysis composed of discrete Fourier transform, modal analysis (frequency domain decomposition) and deconvolution interferometry, yields the modal characteristics and an estimate of the linear impulse response function for the structures of the four buildings. Then, finite element models are set up for all four buildings and the results of the numerical modal analysis are compared with the experimental ones. The numerical models are finally calibrated considering the first three global modes and their results match the experimental ones with an error of less then 20%.

Mixture modeling for joint analysis of survival, discrete, and continuous data

Mixture modeling is commonly used to model categorical latent variables that represent subpopulations in which population membership is unknown but can be inferred from the data. In relatively recent years, the potential of finite mixture models has been applied in time-to-event data. However, the commonly used survival mixture model assumes that the effects of the covariates involved in failure times differ across latent classes, but the covariate distribution is homogeneous. The aim of this dissertation is to develop a method to examine time-to-event data in the presence of unobserved heterogeneity under a framework of mixture modeling. A joint model is developed to incorporate the latent survival trajectory along with the observed information for the joint analysis of a time-to-event variable, its discrete and continuous covariates, and a latent class variable. It is assumed that the effects of covariates on survival times and the distribution of covariates vary across different latent classes. The unobservable survival trajectories are identified through estimating the probability that a subject belongs to a particular class based on observed information. We applied this method to a Hodgkin lymphoma study with long-term follow-up and observed four distinct latent classes in terms of long-term survival and distributions of prognostic factors. Our results from simulation studies and from the Hodgkin lymphoma study demonstrated the superiority of our joint model compared with the conventional survival model. This flexible inference method provides more accurate estimation and accommodates unobservable heterogeneity among individuals while taking involved interactions between covariates into consideration.^

The role of material characterisation in the crush modelling of thermoplastic composite structures

The predictive capability of high fidelity finite element modelling, to accurately capture damage and crush behaviour of composite structures, relies on the acquisition of accurate material properties, some of which have necessitated the development of novel approaches. This paper details the measurement of interlaminar and intralaminar fracture toughness, the non-linear shear behaviour of carbon fibre (AS4)/thermoplastic Polyetherketoneketone (PEKK) composite laminates and the utilisation of these properties for the accurate computational modelling of crush. Double-cantilever-beam (DCB), four-point end-notched flexure (4ENF) and Mixed-mode bending (MMB) test configurations were used to determine the initiation and propagation fracture toughness in mode I, mode II and mixed-mode loading, respectively. Compact Tension (CT) and Compact Compression (CC) test samples were employed to determine the intralaminar longitudinal tensile and compressive fracture toughness. V-notched rail shear tests were used to measure the highly non-linear shear behaviour, associated with thermoplastic composites, and fracture toughness. Corresponding numerical models of these tests were developed for verification and yielded good correlation with the experimental response. This also confirmed the accuracy of the measured values which were then employed as input material parameters for modelling the crush behaviour of a corrugated test specimen.

Mixture of time-dependent growth models with an application to blue swimmer crab length-frequency data

Understanding how aquatic species grow is fundamental in fisheries because stock assessment often relies on growth dependent statistical models. Length-frequency-based methods become important when more applicable data for growth model estimation are either not available or very expensive. In this article, we develop a new framework for growth estimation from length-frequency data using a generalized von Bertalanffy growth model (VBGM) framework that allows for time-dependent covariates to be incorporated. A finite mixture of normal distributions is used to model the length-frequency cohorts of each month with the means constrained to follow a VBGM. The variances of the finite mixture components are constrained to be a function of mean length, reducing the number of parameters and allowing for an estimate of the variance at any length. To optimize the likelihood, we use a minorization–maximization (MM) algorithm with a Nelder–Mead sub-step. This work was motivated by the decline in catches of the blue swimmer crab (BSC) (Portunus armatus) off the east coast of Queensland, Australia. We test the method with a simulation study and then apply it to the BSC fishery data.

A simple way to introduce fibers into FEM models

This communication proposes a simple way to introduce fibers into finite element modelling. This is a promising formulation to deal with fiber-reinforced composites by the finite element method (FEM), as it allows the consideration of short or long fibers placed arbitrarily inside a continuum domain (matrix). The most important feature of the formulation is that no additional degree of freedom is introduced into the pre-existent finite element numerical system to consider any distribution of fiber inclusions. In other words, the size of the system of equations used to solve a non-reinforced medium is the same as the one used to solve the reinforced counterpart. Another important characteristic is the reduced work required by the user to introduce fibers, avoiding `rebar` elements, node-by-node geometrical definitions or even complex mesh generation. An additional characteristic of the technique is the possibility of representing unbounded stresses at the end of fibers using a finite number of degrees of freedom. Further studies are required for non-linear applications in which localization may occur. Along the text the linear formulation is presented and the bounded connection between fibers and continuum is considered. Four examples are presented, including non-linear analysis, to validate and show the capabilities of the formulation. Copyright (c) 2007 John Wiley & Sons, Ltd.

Effects of hot intrusions on pore-fluid flow and heat transfer in fluid-saturated rocks

We use the finite element method to solve coupled problems between pore-fluid flow and heat transfer in fluid-saturated porous rocks. In particular, we investigate the effects of both the hot pluton intrusion and topographically driven horizontal flow on the distributions of the pore-flow velocity and temperature in large-scale hydrothermal systems. Since general mineralization patterns are strongly dependent on distributions of both the pore-fluid velocity and temperature fields, the modern mineralization theory has been used to predict the general mineralization patterns in several realistic hydrothermal systems. The related numerical results have demonstrated that: (1) The existence of a hot intrusion can cause an increase in the maximum value of the pore-fluid velocity in the hydrothermal system. (2) The permeability of an intruded pluton is one of the sensitive parameters to control the pore-fluid flow, heat transfer and ore body formation in hydrothermal systems. (3) The maximum value of the pore-fluid velocity increases when the bottom temperature of the hydrothermal system is increased. (4) The topographically driven flow has significant effects on the pore-fluid flow, temperature distribution and precipitation pattern of minerals in hydrothermal systems. (5) The size of the computational domain may have some effects on the pore-fluid flow and heat transfer, indicating that the size of a hydrothermal system may affect the pore-fluid flow and heat transfer within the system. (C) 2003 Elsevier Science B.V. All rights reserved.

Cenozoic continental weathering and its implications for the palaeoclimate: evidence from Ar-40/Ar-39 geochronology of supergene K-Mn oxides in Mt Tabor, central Queensland, Australia

One hundred and twenty-five mineral grains from 45 visually pure K-bearing Mn oxide (hollandite group) samples collected from weathering profiles in the Mt Tabor region of central Queensland, Australia, were analysed by the Ar-40/Ar-39 laser probe technique. These K-Mn oxides precipitated mainly through a process of cavity filling (direct precipitation from weathering solution), with botryoidal texture formed by micrometric mineral bands. Well-defined and reproducible plateau ages have been obtained for most samples, ranging from 27.2 +/- 0.8 to 6.8 +/- 0.5 Ma (2 sigma). Statistical analysis of the geochronological results by mixture modelling suggests an episodic mineral precipitation history, with two major peaks at 20.2 +/- 0.22 Ma and 16.5 +/- 0.17 Ma. The geochronological results, when combined with information on paragenetic relationships and mineralogical textures obtained from petrographic, scanning electron microscopy, and electron microprobe investigations, indicate that warm and humid palaeoclimatic conditions favourable to intense chemical weathering prevailed in central Queensland from late Oligocene to middle Miocene, particularly in the early Miocene. These results, in conjunction with previous and ongoing investigations in NW and eastern Queensland, suggest that most of Queensland was dominated by humid climates during the Miocene. (C) 2002 Elsevier Science BN. All rights reserved.

Powder forging of a sintered Al-3.8Cu-1Mg-0.8Si-O.1Sn alloy

The forging characteristics of an Al-Cu-Mg-Si-Sn alloy are examined using it new testing strategy which incorporates a double truncated cone specimen and finite element modelling. This sample geometry produces controlled strain distributions within a single specimen and can readily identify the specific strain required to achieve a specific microstructural event by matching the metallographic data with the strain profiles calculated from finite element software, The friction conditions were determined using the conventional friction ring test, which was evaluated using finite element software. The rheological properties of the alloy, evaluated from compression testing of right cylinders, are similar to the properties of conventional aluminium forgings. A hoop strain develops at the outer diameter of the truncated cones and this leads to pore opening at the outer few millimetres. The porosity is effectively removed when the total strain equals the net compressive strain. The strain profiles that develop in the truncated cones are largely independent of the processing temperature and the strain rate although the strain required for pore closure increases as the forging temperature is reduced. This suggests that the microstructure and the strain rate sensitivity may also be important factors controlling pore behaviour. (C) 2002 Elsevier Science B.V. All rights reserved.

Model-based clustering in gene expression microarrays: An application to breast cancer data

In microarray studies, the application of clustering techniques is often used to derive meaningful insights into the data. In the past, hierarchical methods have been the primary clustering tool employed to perform this task. The hierarchical algorithms have been mainly applied heuristically to these cluster analysis problems. Further, a major limitation of these methods is their inability to determine the number of clusters. Thus there is a need for a model-based approach to these. clustering problems. To this end, McLachlan et al. [7] developed a mixture model-based algorithm (EMMIX-GENE) for the clustering of tissue samples. To further investigate the EMMIX-GENE procedure as a model-based -approach, we present a case study involving the application of EMMIX-GENE to the breast cancer data as studied recently in van 't Veer et al. [10]. Our analysis considers the problem of clustering the tissue samples on the basis of the genes which is a non-standard problem because the number of genes greatly exceed the number of tissue samples. We demonstrate how EMMIX-GENE can be useful in reducing the initial set of genes down to a more computationally manageable size. The results from this analysis also emphasise the difficulty associated with the task of separating two tissue groups on the basis of a particular subset of genes. These results also shed light on why supervised methods have such a high misallocation error rate for the breast cancer data.

Categorical data clustering using a minimum message length criterion

Research on cluster analysis for categorical data continues to develop, new clustering algorithms being proposed. However, in this context, the determination of the number of clusters is rarely addressed. We propose a new approach in which clustering and the estimation of the number of clusters is done simultaneously for categorical data. We assume that the data originate from a finite mixture of multinomial distributions and use a minimum message length criterion (MML) to select the number of clusters (Wallace and Bolton, 1986). For this purpose, we implement an EM-type algorithm (Silvestre et al., 2008) based on the (Figueiredo and Jain, 2002) approach. The novelty of the approach rests on the integration of the model estimation and selection of the number of clusters in a single algorithm, rather than selecting this number based on a set of pre-estimated candidate models. The performance of our approach is compared with the use of Bayesian Information Criterion (BIC) (Schwarz, 1978) and Integrated Completed Likelihood (ICL) (Biernacki et al., 2000) using synthetic data. The obtained results illustrate the capacity of the proposed algorithm to attain the true number of cluster while outperforming BIC and ICL since it is faster, which is especially relevant when dealing with large data sets.

Determining the number of clusters in categorical data

Cluster analysis for categorical data has been an active area of research. A well-known problem in this area is the determination of the number of clusters, which is unknown and must be inferred from the data. In order to estimate the number of clusters, one often resorts to information criteria, such as BIC (Bayesian information criterion), MML (minimum message length, proposed by Wallace and Boulton, 1968), and ICL (integrated classification likelihood). In this work, we adopt the approach developed by Figueiredo and Jain (2002) for clustering continuous data. They use an MML criterion to select the number of clusters and a variant of the EM algorithm to estimate the model parameters. This EM variant seamlessly integrates model estimation and selection in a single algorithm. For clustering categorical data, we assume a finite mixture of multinomial distributions and implement a new EM algorithm, following a previous version (Silvestre et al., 2008). Results obtained with synthetic datasets are encouraging. The main advantage of the proposed approach, when compared to the above referred criteria, is the speed of execution, which is especially relevant when dealing with large data sets.

Clustering and selecting categorical features

In data clustering, the problem of selecting the subset of most relevant features from the data has been an active research topic. Feature selection for clustering is a challenging task due to the absence of class labels for guiding the search for relevant features. Most methods proposed for this goal are focused on numerical data. In this work, we propose an approach for clustering and selecting categorical features simultaneously. We assume that the data originate from a finite mixture of multinomial distributions and implement an integrated expectation-maximization (EM) algorithm that estimates all the parameters of the model and selects the subset of relevant features simultaneously. The results obtained on synthetic data illustrate the performance of the proposed approach. An application to real data, referred to official statistics, shows its usefulness.

The effects of clinical support surfaces on pressure as a risk factor in the development of pressure ulcers, from a radiographical perspective: a narrative literature review

Purpose: Pressure ulcers are a high cost, high volume issue for health and medical care providers, having a detrimental effect on patients and relatives. Pressure ulcer prevention is widely covered in the literature, but little has been published regarding the risk to patients in the radiographical setting. This review of the current literature is to identify findings relevant to radiographical context. Methods: Literature searching was performed using Science Direct and Medline databases. The search was limited to articles published in the last ten years to remain current and excluded studies containing participants less than 17 years of age. In total 14 studies were acquired; three were excluded as they were not relevant. The remaining 11 studies were compared and reviewed. Discussion: Eight of the studies used ‘healthy’ participants and three used symptomatic participants. Nine studies explored interface pressure with a range of pressure mat technologies, two studies measured shear (MRI finite element modelling, and a non-invasive instrument), and one looked at blood flow and haemoglobin oxygenation. A range of surfaces were considered from trauma, nursing and surgical backgrounds for their ability to reduce pressure including standard mattresses, high specification mattresses, rigid and soft layer spine boards, various overlays (gel, air filled, foam). Conclusion: The current literature is not appropriate for the radiographic patient and cannot be extrapolated to a radiologic context. Sufficient evidence is presented in this review to support the need for further work specific to radiography in order to minimise the development of PU in at risk patients.

The Influence of Damping on Vibration Induced by High-Speed Trains

Passage of high-speed trains may induce high ground and track vibrations, which, besides increasing wheel, rail and track deterioration, may have a negative impact on the vehicle stability and on the passengers comfort. In this paper two distinct analyses are presented. The first one is dedicated to efficient decoupling of rail and soil vibrations by suggesting new interface materials in rail-sleeper fixing system, i.e. in the part where damping efficiency can be directly controlled and tested. The second analysis concerns with an adequate model of soils damping. Proper understanding and correct numerical simulation of this behaviour can help in suggesting soil improvement techniques.

Development of hybrid composite plate (HCP) for strengthening and repair of RC structures

Tese de Doutoramento em Engenharia Civil