13 resultados para Cluster industrial

em Greenwich Academic Literature Archive - UK


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In the analysis of industrial processes, there is an increasing emphasis on systems governed by interacting continuum phenomena. Mathematical models of such multi-physics processes can only be achieved for practical simulations through computational solution procedures—computational mechanics. Examples of such multi-physics systems in the context of metals processing are used to explore some of the key issues. Finite-volume methods on unstructured meshes are proposed as a means to achieve efficient rapid solutions to such systems. Issues associated with the software design, the exploitation of high performance computers, and the concept of the virtual computational-mechanics modelling laboratory are also addressed in this context.

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The parallelization of existing/industrial electromagnetic software using the bulk synchronous parallel (BSP) computation model is presented. The software employs the finite element method with a preconditioned conjugate gradient-type solution for the resulting linear systems of equations. A geometric mesh-partitioning approach is applied within the BSP framework for the assembly and solution phases of the finite element computation. This is combined with a nongeometric, data-driven parallel quadrature procedure for the evaluation of right-hand-side terms in applications involving coil fields. A similar parallel decomposition is applied to the parallel calculation of electron beam trajectories required for the design of tube devices. The BSP parallelization approach adopted is fully portable, conceptually simple, and cost-effective, and it can be applied to a wide range of finite element applications not necessarily related to electromagnetics.

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This paper discusses load-balancing issues when using heterogeneous cluster computers. There is a growing trend towards the use of commodity microprocessor clusters. Although today's microprocessors have reached a theoretical peak performance in the range of one GFLOPS/s, heterogeneous clusters of commodity processors are amongst the most challenging parallel systems to programme efficiently. We will outline an approach for optimising the performance of parallel mesh-based applications for heterogeneous cluster computers and present case studies with the GeoFEM code. The focus is on application cost monitoring and load balancing using the DRAMA library.

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The factors that are driving the development and use of grids and grid computing, such as size, dynamic features, distribution and heterogeneity, are also pushing to the forefront service quality issues. These include performance, reliability and security. Although grid middleware can address some of these issues on a wider scale, it has also become imperative to ensure adequate service provision at local level. Load sharing in clusters can contribute to the provision of a high quality service, by exploiting both static and dynamic information. This paper is concerned with the presentation of a load sharing scheme, that can satisfy grid computing requirements. It follows a proactive, non preemptive and distributed approach. Load information is gathered continuously before it is needed, and a task is allocated to the most appropriate node for execution. Performance and reliability are enhanced by the decentralised nature of the scheme and the symmetric roles of the nodes. In addition, the scheme exhibits transparency characteristics that facilitate integration with the grid.

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This paper presents an Eulerian-based numerical model of particle degradation in dilute-phase pneumatic conveying systems including bends of different angles. The model shows reasonable agreement with detailed measurements from a pilot-sized pneumatic conveying system and a much larger scale pneumatic conveyor. The potential of the model to predict degradation in a large-scale conveying system from an industrial plant is demonstrated. The importance of the effect of the bend angle on the damage imparted to the particles is discussed.

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A comprehensive solution of solidification/melting processes requires the simultaneous representation of free surface fluid flow, heat transfer, phase change, nonlinear solid mechanics and, possibly, electromagnetics together with their interactions, in what is now known as multiphysics simulation. Such simulations are computationally intensive and the implementation of solution strategies for multiphysics calculations must embed their effective parallelization. For some years, together with our collaborators, we have been involved in the development of numerical software tools for multiphysics modeling on parallel cluster systems. This research has involved a combination of algorithmic procedures, parallel strategies and tools, plus the design of a computational modeling software environment and its deployment in a range of real world applications. One output from this research is the three-dimensional parallel multiphysics code, PHYSICA. In this paper we report on an assessment of its parallel scalability on a range of increasingly complex models drawn from actual industrial problems, on three contemporary parallel cluster systems.

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Distributed applications are being deployed on ever-increasing scale and with ever-increasing functionality. Due to the accompanying increase in behavioural complexity, self-management abilities, such as self-healing, have become core requirements. A key challenge is the smooth embedding of such functionality into our systems. Natural distributed systems such as ant colonies have evolved highly efficient behaviour. These emergent systems achieve high scalability through the use of low complexity communication strategies and are highly robust through large-scale replication of simple, anonymous entities. Ways to engineer this fundamentally non-deterministic behaviour for use in distributed applications are being explored. An emergent, dynamic, cluster management scheme, which forms part of a hierarchical resource management architecture, is presented. Natural biological systems, which embed self-healing behaviour at several levels, have influenced the architecture. The resulting system is a simple, lightweight and highly robust platform on which cluster-based autonomic applications can be deployed.

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The extent and gravity of the environmental degradation of the water resources in Dhaka due to untreated industrial waste is not fully recognised in international discourse. Pollution levels affect vast numbers, but the poor and the vulnerable are the worst affected. For example, rice productivity, the mainstay of poor farmers, in the Dhaka watershed has declined by 40% over a period of ten years. The study found significant correlations between water pollution and diseases such as jaundice, diarrhoea and skin problems. It was reported that the cost of treatment of one episode of skin disease could be as high as 29% of the weekly earnings of some of the poorest households. The dominant approach to deal with pollution in the SMEs is technocratic. Given the magnitude of the problem this paper argues that to control industrial pollution by SMEs and to enhance their compliance it is necessary to move from the technocratic approach to one which can also address the wider institutional and attitudinal issues. Underlying this shift is the need to adopt the appropriate methodology. The multi-stakeholder analysis enables an understanding of the actors, their influence, their capacity to participate in, or oppose change, and the existing and embedded incentive structures which allow them to pursue interests which are generally detrimental to environmental good. This enabled core and supporting strategies to be developed around three types of actors in industrial pollution, i.e., (i) principal actors, who directly contribute to industrial pollution; (ii) stakeholders who exacerbate the situation; and (iii) potential actors in mitigation. Within a carrot-and-stick framework, the strategies aim to improve environmental governance and transparency, set up a packet to incentive for industry and increase public awareness.

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The concomitant recycling of waste and carbon dioxide emissions is the subject of developing technology designed to close the industrial process loop and facilitate the bulk-re-use of waste in, for example, construction. The present work discusses a treatment step that employs accelerated carbonation to convert gaseous carbon dioxide into solid calcium carbonate through a reaction with industrial thermal residues. Treatment by accelerated carbonation enabled a synthetic aggregate to be made from thermal residues and waste quarry fines. The aggregates produced had a bulk density below 1000 kg/m3 and a high water absorption capacity. Aggregate crushing strengths were between 30% and 90% stronger than the proprietary lightweight expanded clay aggregate available in the UK. Cast concrete blocks containing the carbonated aggregate achieve compressive strengths of 24 MPa, making them suitable for use with concrete exposed to non-aggressive service environments. The energy intensive firing and sintering processes traditionally required to produce lightweight aggregates can now be augmented by a cold-bonding, low energy method that contributes to the reduction of green house gases to the atmosphere.

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The disposal of industrial waste presents major logistical, financial and environmental issues. Technologies that can reduce the hazardous properties of wastes are urgently required. In the present work, a number of industrial wastes arising from the cement, metallurgical, paper, waste disposal and energy industries were treated with accelerated carbonation. In this process carbonation was effected by exposing the waste to pure carbon dioxide gas. The paper and cement wastes chemically combined with up to 25% by weight of gas. The reactivity of the wastes to carbon dioxide was controlled by their constituent minerals, and not by their elemental composition, as previously postulated. Similarly, microstructural alteration upon carbonation was primarily influenced by mineralogy. Many of the thermal wastes tested were classified as hazardous, based upon regulated metal content and pH. Treatment by accelerated carbonation reduced the leaching of certain metals, aiding the disposal of many as stable non-reactive wastes. Significant volumes of carbon dioxide were sequestrated into the accelerated carbonated treated wastes.

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Today, the key to commercial success in manufacturing is the timely development of new products that are not only functionally fit for purpose but offer high performance and quality throughout their entire lifecycle. In principle, this demands the introduction of a fully developed and optimised product from the outset. To accomplish this, manufacturing companies must leverage existing knowledge in their current technical, manufacturing and service capabilities. This is especially true in the field of tolerance selection and application, the subject area of this research. Tolerance knowledge must be readily available and deployed as an integral part of the product development process. This paper describes a methodology and framework,currently under development in a UK manufacturer, to achieve this objective.

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Background: Personal health records were implemented with adults with learning disabilities (AWLD) to try to improve their health-care. Materials and Method: Forty GP practices were randomized to the Personal Health Profile (PHP) implementation or control group. Two hundred and one AWLD were interviewed at baseline and 163 followed up after 12 months intervention (PHP group). AWLD and carers of AWLD were employed as research interviewers. AWLD were full research participants. Results: Annual consultation rates in the intervention and control groups at baseline were low (2.3 and 2.6 visits respectively). A slightly greater increase occurred over the year in the intervention group 0.6 ()0.4 to 1.6) visits ⁄ year compared with controls. AWLD in PHP group reported more health problems at follow-up 0.9 (0.0 to 1.8). AWLD liked their PHP (92%) but only 63% AWLD and 55% carers reported PHP usage. Carers had high turnover (34%). Conclusions: No significant outcomes were achieved by the intervention.