442 resultados para effective linear solver


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Water-filled portable road safety barriers are a common fixture in road works, however their use of water can be problematic, both in terms of the quantity of water used and the transportation of the water to the installation site. This project aims to develop a new design of portable road safety barrier, which will make novel use of composite and foam materials in order to reduce the barrier’s reliance on water in order to control errant vehicles. The project makes use of finite element (FE) techniques in order to simulate and evaluate design concepts. FE methods and models that have previously been tested and validated will be used in combination in order to provide the most accurate numerical simulations available to drive the project forward. LS-DYNA code is as highly dynamic, non-linear numerical solver which is commonly used in the automotive and road safety industries. Several complex materials and physical interactions are to be simulated throughout the course of the project including aluminium foams, composite laminates and water within the barrier during standardised impact tests. Techniques to be used include FE, smoothed particle hydrodynamics (SPH) and weighted multi-parameter optimisation techniques. A detailed optimisation of several design parameters with specific design goals will be performed with LS-DYNA and LS-OPT, which will require a large number of high accuracy simulations and advanced visualisation techniques. Supercomputing will play a central role in the project, enabling the numerous medium element count simulations necessary in order to determine the optimal design parameters of the barrier to be performed. Supercomputing will also allow the development of useful methods of visualisation results and the production of highly detailed simulations for end-product validation purposes. Efforts thus far have been towards integrating various numerical methods (including FEM, SPH and advanced materials models) together in an efficient and accurate manner. Various designs of joining mechanisms have been developed and are currently being developed into FE models and simulations.

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Areal bone mineral density (aBMD) is the most common surrogate measurement for assessing the bone strength of the proximal femur associated with osteoporosis. Additional factors, however, contribute to the overall strength of the proximal femur, primarily the anatomical geometry. Finite element analysis (FEA) is an effective and widely used computerbased simulation technique for modeling mechanical loading of various engineering structures, providing predictions of displacement and induced stress distribution due to the applied load. FEA is therefore inherently dependent upon both density and anatomical geometry. FEA may be performed on both three-dimensional and two-dimensional models of the proximal femur derived from radiographic images, from which the mechanical stiffness may be redicted. It is examined whether the outcome measures of two-dimensional FEA, two-dimensional, finite element analysis of X-ray images (FEXI), and three-dimensional FEA computed stiffness of the proximal femur were more sensitive than aBMD to changes in trabecular bone density and femur geometry. It is assumed that if an outcome measure follows known trends with changes in density and geometric parameters, then an increased sensitivity will be indicative of an improved prediction of bone strength. All three outcome measures increased non-linearly with trabecular bone density, increased linearly with cortical shell thickness and neck width, decreased linearly with neck length, and were relatively insensitive to neck-shaft angle. For femoral head radius, aBMD was relatively insensitive, with two-dimensional FEXI and threedimensional FEA demonstrating a non-linear increase and decrease in sensitivity, respectively. For neck anteversion, aBMD decreased non-linearly, whereas both two-dimensional FEXI and three dimensional FEA demonstrated a parabolic-type relationship, with maximum stiffness achieved at an angle of approximately 15o. Multi-parameter analysis showed that all three outcome measures demonstrated their highest sensitivity to a change in cortical thickness. When changes in all input parameters were considered simultaneously, three and twodimensional FEA had statistically equal sensitivities (0.41±0.20 and 0.42±0.16 respectively, p = ns) that were significantly higher than the sensitivity of aBMD (0.24±0.07; p = 0.014 and 0.002 for three-dimensional and two-dimensional FEA respectively). This simulation study suggests that since mechanical integrity and FEA are inherently dependent upon anatomical geometry, FEXI stiffness, being derived from conventional two-dimensional radiographic images, may provide an improvement in the prediction of bone strength of the proximal femur than currently provided by aBMD.

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Effective knowledge transfer can prevent the reinvention of systems and ideas as well as the repetition of errors. Doing so will save substantial time, as well as contribute to better performance of projects and project-based organisations (PBOs). Despite the importance of knowledge, PBOs face serious barriers to the effective transfer of knowledge, while their characteristics, such as unique and innovative approaches taken during every project, mean they have much to gain from knowledge transfer. As each new project starts, there is the strong potential to reinvent the process, rather than utilise learning from previous projects. In fact, rework is one of the primary factors contributing to construction industry's poor performance and productivity. Current literature has identified several barriers to knowledge transfer in organisational settings in general, and not specifically PBOs. However, PBOs significantly differ from other types of organisations. PBOs operate mainly on temporary projects, where time is a crucial factor and people are more mobile than in other organisational settings. The aim of this research is to identify the key barriers that prevent effective knowledge transfer for PBOs, exclusively. Interviews with project managers and senior managers of PBOs complement the analysis of the literature and provide professional expertise. This research is crucial to gaining a better understanding of obstacles that hinder knowledge transfer in projects. The main contribution of this research is exclusive for PBO, list of key barriers that organisation and project managers need to consider to ensure effective knowledge transfer and better project management.

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Australia needs highly skilled workers to sustain a healthy economy. Current employment-based training models have limitations in meeting the demands for highly skilled labour supply. The research explored current and emerging models of employment-based training to propose more effective models at higher VET qualifications that can maintain a balance between institution and work-based learning.

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Supervision probably does have benefits both for the maintenance and improvement of clinical skills and for job satisfaction, but the data are very thin and almost non-existent in the area of alcohol and other drugs ser vices. Because of the potential complexity of objectives and roles in super vision, a structured agreement appears to be an important part of the effective supervision relationship. Because sessions can degenerate easily into unstructured socialization, agendas and session objectives may also be important. While a working alliance based on mutual respect and trust is an essential base for the supervision relationship, procedures for direct observation of clinical skills, demonstration of new procedures and skills practice with detailed feedback appear critical to super vision’s impact on practice. To ensure effective supervision, there needs not only to be a minimum of personnel and resources, but also a compatibility with the values and procedures of management and staff, access to supervision training and consultation and sufficient incentives to ensure it continues.

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Effective information and knowledge management (IKM) is critical to corporate success; yet, its actual establishment and management is not yet fully understood. We identify ten organizational elements that need to be addressed to ensure the effective implementation and maintenance of information and knowledge management within organizations. We define these elements and provide key characterizations. We then discuss a case study that describes the implementation of an information system (designed to support IKM) in a medical supplies organization. We apply the framework of organizational elements in our analysis to uncover the enablers and barriers in this systems implementation project. Our analysis suggests that taking the ten organizational elements into consideration when implementing information systems will assist practitioners in managing information and knowledge processes more effectively and efficiently. We discuss implications for future research.

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Effective focusing of electromagnetic (EM) energy to nanoscale regions is one of the major challenges in nano-photonics and plasmonics. The strong localization of the optical energy into regions much smaller than allowed by the diffraction limit, also called nanofocusing, offers promising applications in nano-sensor technology, nanofabrication, near-field optics or spectroscopy. One of the most promising solutions to the problem of efficient nanofocusing is related to surface plasmon propagation in metallic structures. Metallic tapered rods, commonly used as probes in near field microscopy and spectroscopy, are of a particular interest. They can provide very strong EM field enhancement at the tip due to surface plasmons (SP’s) propagating towards the tip of the tapered metal rod. A large number of studies have been devoted to the manufacturing process of tapered rods or tapered fibers coated by a metal film. On the other hand, structures such as metallic V-grooves or metal wedges can also provide strong electric field enhancements but manufacturing of these structures is still a challenge. It has been shown, however, that the attainable electric field enhancement at the apex in the V-groove is higher than at the tip of a metal tapered rod when the dissipation level in the metal is strong. Metallic V-grooves also have very promising characteristics as plasmonic waveguides. This thesis will present a thorough theoretical and numerical investigation of nanofocusing during plasmon propagation along a metal tapered rod and into a metallic V-groove. Optimal structural parameters including optimal taper angle, taper length and shape of the taper are determined in order to achieve maximum field enhancement factors at the tip of the nanofocusing structure. An analytical investigation of plasmon nanofocusing by metal tapered rods is carried out by means of the geometric optics approximation (GOA), which is also called adiabatic nanofocusing. However, GOA is applicable only for analysing tapered structures with small taper angles and without considering a terminating tip structure in order to neglect reflections. Rigorous numerical methods are employed for analysing non-adiabatic nanofocusing, by tapered rod and V-grooves with larger taper angles and with a rounded tip. These structures cannot be studied by analytical methods due to the presence of reflected waves from the taper section, the tip and also from (artificial) computational boundaries. A new method is introduced to combine the advantages of GOA and rigorous numerical methods in order to reduce significantly the use of computational resources and yet achieve accurate results for the analysis of large tapered structures, within reasonable calculation time. Detailed comparison between GOA and rigorous numerical methods will be carried out in order to find the critical taper angle of the tapered structures at which GOA is still applicable. It will be demonstrated that optimal taper angles, at which maximum field enhancements occur, coincide with the critical angles, at which GOA is still applicable. It will be shown that the applicability of GOA can be substantially expanded to include structures which could be analysed previously by numerical methods only. The influence of the rounded tip, the taper angle and the role of dissipation onto the plasmon field distribution along the tapered rod and near the tip will be analysed analytically and numerically in detail. It will be demonstrated that electric field enhancement factors of up to ~ 2500 within nanoscale regions are predicted. These are sufficient, for instance, to detect single molecules using surface enhanced Raman spectroscopy (SERS) with the tip of a tapered rod, an approach also known as tip enhanced Raman spectroscopy or TERS. The results obtained in this project will be important for applications for which strong local field enhancement factors are crucial for the performance of devices such as near field microscopes or spectroscopy. The optimal design of nanofocusing structures, at which the delivery of electromagnetic energy to the nanometer region is most efficient, will lead to new applications in near field sensors, near field measuring technology, or generation of nanometer sized energy sources. This includes: applications in tip enhanced Raman spectroscopy (TERS); manipulation of nanoparticles and molecules; efficient coupling of optical energy into and out of plasmonic circuits; second harmonic generation in non-linear optics; or delivery of energy to quantum dots, for instance, for quantum computations.

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Childcare workers play a significant role in the learning and development of children in their care. This has major implications for the training of workers. Under new reforms of the childcare industry the Australian government now requires all workers to obtain qualifications from a vocational education and training provider (eg. Technical and Further Education) or university. Effective models of employment-based training are critical to provide training to highly competent workers. This paper presents findings from a study that examined current and emerging models of employment-based training in the childcare sector, particularly at the Diploma level. Semi-structured interviews were conducted with a sample of 16 participants who represented childcare directors, employers, and workers located in childcare services in urban, regional and remote locations in the State of Queensland. The study proposes a ‘best-fit’ employment-based training approach that is characterised by a compendium of five models instead of a ‘one size fits all’. Issues with successful implementation of the EBT models are also discussed

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Over the years, people have often held the hypothesis that negative feedback should be very useful for largely improving the performance of information filtering systems; however, we have not obtained very effective models to support this hypothesis. This paper, proposes an effective model that use negative relevance feedback based on a pattern mining approach to improve extracted features. This study focuses on two main issues of using negative relevance feedback: the selection of constructive negative examples to reduce the space of negative examples; and the revision of existing features based on the selected negative examples. The former selects some offender documents, where offender documents are negative documents that are most likely to be classified in the positive group. The later groups the extracted features into three groups: the positive specific category, general category and negative specific category to easily update the weight. An iterative algorithm is also proposed to implement this approach on RCV1 data collections, and substantial experiments show that the proposed approach achieves encouraging performance.

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This study considers the solution of a class of linear systems related with the fractional Poisson equation (FPE) (−∇2)α/2φ=g(x,y) with nonhomogeneous boundary conditions on a bounded domain. A numerical approximation to FPE is derived using a matrix representation of the Laplacian to generate a linear system of equations with its matrix A raised to the fractional power α/2. The solution of the linear system then requires the action of the matrix function f(A)=A−α/2 on a vector b. For large, sparse, and symmetric positive definite matrices, the Lanczos approximation generates f(A)b≈β0Vmf(Tm)e1. This method works well when both the analytic grade of A with respect to b and the residual for the linear system are sufficiently small. Memory constraints often require restarting the Lanczos decomposition; however this is not straightforward in the context of matrix function approximation. In this paper, we use the idea of thick-restart and adaptive preconditioning for solving linear systems to improve convergence of the Lanczos approximation. We give an error bound for the new method and illustrate its role in solving FPE. Numerical results are provided to gauge the performance of the proposed method relative to exact analytic solutions.

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Work experience which is integrated into an undergraduate law degree has a vital role to play in assisting law students to develop the skills and attributes they need in order to be effective legal practitioners. Work integrated learning provides a context for students to develop their skills, to see the link between theory and practice and supports students in making the transition from university to practice. The literature in Australian legal education has given little consideration to the design of legal internship subjects (as distinct from legal clinic programs). Accordingly the design of internship subjects needs to be carefully considered to ensure alignment of learning objectives, learning tasks and assessment. This paper will examine the literature relating to internships, particularly in a legal context, and will propose some principles for the design of legal internships. These principles will be considered in light of an evaluation of a newly designed undergraduate legal internship subject.

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Intuitively, any `bag of words' approach in IR should benefit from taking term dependencies into account. Unfortunately, for years the results of exploiting such dependencies have been mixed or inconclusive. To improve the situation, this paper shows how the natural language properties of the target documents can be used to transform and enrich the term dependencies to more useful statistics. This is done in three steps. The term co-occurrence statistics of queries and documents are each represented by a Markov chain. The paper proves that such a chain is ergodic, and therefore its asymptotic behavior is unique, stationary, and independent of the initial state. Next, the stationary distribution is taken to model queries and documents, rather than their initial distri- butions. Finally, ranking is achieved following the customary language modeling paradigm. The main contribution of this paper is to argue why the asymptotic behavior of the document model is a better representation then just the document's initial distribution. A secondary contribution is to investigate the practical application of this representation in case the queries become increasingly verbose. In the experiments (based on Lemur's search engine substrate) the default query model was replaced by the stable distribution of the query. Just modeling the query this way already resulted in significant improvements over a standard language model baseline. The results were on a par or better than more sophisticated algorithms that use fine-tuned parameters or extensive training. Moreover, the more verbose the query, the more effective the approach seems to become.

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Early in the practice-led research debate, Steven Scrivener (2000, 2002) identified some general differences in the approach of artists and designers undertaking postgraduate research. His distinctions centered on the role of the artefact in problem-based research (associated with design) and creative-production research (associated with artistic practice). Nonetheless, in broader discussions on practice-led research, 'art and design' often continues to be conflated within a single term. In particular, marked differences between art and design methodologies, theoretical framing, research goals and research claims have been underestimated. This paper revisits Scrivener's work and establishes further distinctions between art and design research. It is informed by our own experiences of postgraduate supervision and research methods training, and an empirical study of over sixty postgraduate, practice-led projects completed at the Creative Industries Faculty of QUT between 2002 and 2008. Our reflections have led us to propose that artists and designers work with differing research goals (the evocative and the effective, respectively), which are played out in the questions asked, the creative process, the role of the artefact and the way new knowledge is evidenced. Of course, research projects will have their own idiosyncrasies but, we argue, marking out the poles at each end of the spectrum of art and design provides useful insights for postgraduate candidates, supervisors and methodologists alike.

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The ability to forecast machinery failure is vital to reducing maintenance costs, operation downtime and safety hazards. Recent advances in condition monitoring technologies have given rise to a number of prognostic models for forecasting machinery health based on condition data. Although these models have aided the advancement of the discipline, they have made only a limited contribution to developing an effective machinery health prognostic system. The literature review indicates that there is not yet a prognostic model that directly models and fully utilises suspended condition histories (which are very common in practice since organisations rarely allow their assets to run to failure); that effectively integrates population characteristics into prognostics for longer-range prediction in a probabilistic sense; which deduces the non-linear relationship between measured condition data and actual asset health; and which involves minimal assumptions and requirements. This work presents a novel approach to addressing the above-mentioned challenges. The proposed model consists of a feed-forward neural network, the training targets of which are asset survival probabilities estimated using a variation of the Kaplan-Meier estimator and a degradation-based failure probability density estimator. The adapted Kaplan-Meier estimator is able to model the actual survival status of individual failed units and estimate the survival probability of individual suspended units. The degradation-based failure probability density estimator, on the other hand, extracts population characteristics and computes conditional reliability from available condition histories instead of from reliability data. The estimated survival probability and the relevant condition histories are respectively presented as “training target” and “training input” to the neural network. The trained network is capable of estimating the future survival curve of a unit when a series of condition indices are inputted. Although the concept proposed may be applied to the prognosis of various machine components, rolling element bearings were chosen as the research object because rolling element bearing failure is one of the foremost causes of machinery breakdowns. Computer simulated and industry case study data were used to compare the prognostic performance of the proposed model and four control models, namely: two feed-forward neural networks with the same training function and structure as the proposed model, but neglected suspended histories; a time series prediction recurrent neural network; and a traditional Weibull distribution model. The results support the assertion that the proposed model performs better than the other four models and that it produces adaptive prediction outputs with useful representation of survival probabilities. This work presents a compelling concept for non-parametric data-driven prognosis, and for utilising available asset condition information more fully and accurately. It demonstrates that machinery health can indeed be forecasted. The proposed prognostic technique, together with ongoing advances in sensors and data-fusion techniques, and increasingly comprehensive databases of asset condition data, holds the promise for increased asset availability, maintenance cost effectiveness, operational safety and – ultimately – organisation competitiveness.

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In this paper, we consider the following non-linear fractional reaction–subdiffusion process (NFR-SubDP): Formula where f(u, x, t) is a linear function of u, the function g(u, x, t) satisfies the Lipschitz condition and 0Dt1–{gamma} is the Riemann–Liouville time fractional partial derivative of order 1 – {gamma}. We propose a new computationally efficient numerical technique to simulate the process. Firstly, the NFR-SubDP is decoupled, which is equivalent to solving a non-linear fractional reaction–subdiffusion equation (NFR-SubDE). Secondly, we propose an implicit numerical method to approximate the NFR-SubDE. Thirdly, the stability and convergence of the method are discussed using a new energy method. Finally, some numerical examples are presented to show the application of the present technique. This method and supporting theoretical results can also be applied to fractional integrodifferential equations.