81 resultados para computational fluid dynamics (CFD)


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A commercial pyrometallurgical process for the extraction of platinum-group metals (PGM) from a feedstock slag was analysed with the use of a model based on computational fluid dynamics. The results of the modelling indicate that recovery depends on the behaviour of the collector phase. A possible method is proposed for estimation of the rate at which PGM particles in slag are absorbed into an iron collector droplet that falls through it. Nanoscale modelling techniques (for particle migration or capture) are combined with a diffusion-controlled mass-transfer model to determine the iron collector droplet size needed for >95% PGM recovery in a typical process bath (70 mm deep) in a realistic time-scale (<1 h). The results show that an iron droplet having a diameter in the range 0.1–0.3 mm gives good recovery (>90%) within a reasonable time. This finding is compatible with published experimental data. Pyrometallurgical processes similar to that investigated should be applicable to other types of waste that contain low levels of potentially valuable metals.

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Virtual manufacturing and design assessment increasingly involve the simulation of interacting phenomena, sic. multi-physics, an activity which is very computationally intensive. This chapter describes an attempt to address the parallel issues associated with a multi-physics simulation approach based upon a range of compatible procedures operating on one mesh using a single database - the distinct physics solvers can operate separately or coupled on sub-domains of the whole geometric space. Moreover, the finite volume unstructured mesh solvers use different discretization schemes (and, particularly, different ‘nodal’ locations and control volumes). A two-level approach to the parallelization of this simulation software is described: the code is restructured into parallel form on the basis of the mesh partitioning alone, that is, without regard to the physics. However, at run time, the mesh is partitioned to achieve a load balance, by considering the load per node/element across the whole domain. The latter of course is determined by the problem specific physics at a particular location.

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The first phase in the sign, development and implementation of a comprehensive computational model of a copper stockpile leach process is presented. The model accounts for transport phenomena through the stockpile, reaction kinetics for the important mineral species, oxgen and bacterial effects on the leach reactions, plus heat, energy and acid balances for the overall leach process. The paper describes the formulation of the leach process model and its implementation in PHYSICA+, a computational fluid dynamic (CFD) software environment. The model draws on a number of phenomena to represent the competing physical and chemical features active in the process model. The phenomena are essentially represented by a three-phased (solid liquid gas) multi-component transport system; novel algorithms and procedures are required to solve the model equations, including a methodology for dealing with multiple chemical species with different reaction rates in ore represented by multiple particle size fractions. Some initial validation results and application simulations are shown to illustrate the potential of the model.

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Compuational fluid dynamics (CFD) is used to help understand the gas flow characteristics in the wave soldering process. CFD has the ability to calculate (1) heal transfer, (2) fluid dynamics, and (3) oxygen concentration throughout the wave soldering machine. Understanding the impact of fluid dynamics on oxygen concentration is important as excessive oxygen at the solder bath can lead to high dross contents and hence poor solder joint quality on the printed circuit board. This paper describes the CFD modelling approach and illustrates its capability for a machine which has nitrogen injectors near the solder bath. Different magnitiutes of nitrogen flow rates are investigated and it is demonstrated how these effect the oxygen concentration at the bath surface.

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Nitrogen is now used in wave soldering machines to help lower the amount of dross that can be formed on the solder bath surface. The paper provides details on the use of computational fluid dynamics in helping understand the flow profiles of nitrogen in a wave soldering machine and to predict the concentration of nitrogen and oxygen around the solder bath.

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This paper presents the results of a packaging process based on the stencil printing of isotropic conductive adhesives (ICAs) that form the interconnections of flip-chip bonded electronic packages. Ultra-fine pitch (sub-100-mum), low temperature (100degC), and low cost flip-chip assembly is demonstrated. The article details recent advances in electroformed stencil manufacturing that use microengineering techniques to enable stencil fabrication at apertures sizes down to 20mum and pitches as small as 30mum. The current state of the art for stencil printing of ICAs and solder paste is limited between 150-mum and 200-mum pitch. The ICAs-based interconnects considered in this article have been stencil printed successfully down to 50-mum pitch with consistent printing demonstrated at 90-mum pitch size. The structural integrity or the stencil after framing and printing is also investigated through experimentation and computational modeling. The assembly of a flip-chip package based on copper column bumped die and ICA deposits stencil printed at sub-100-mum pitch is described. Computational fluid dynamics modeling of the print performance provides an indicator on the optimum print parameters. Finally, an organic light emitting diode display chip is packaged using this assembly process

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With the growth in computing power, and advances in numerical methods for the solution of partial differential equations, modeling technologies based around computational fluid dynamics, finite element analysis and optimisation are now being widely used by researchers and industry. Polymer and adhesive materials are now being widely used in electronic and photonic devices. This paper will illustrate the use of modeling tools to predict the behaviour of these materials from product assembly to its performance and reliability.

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The use of unstructured mesh codes on parallel machines is one of the most effective ways to solve large computational mechanics problems. Completely general geometries and complex behaviour can be modelled and, in principle, the inherent sparsity of many such problems can be exploited to obtain excellent parallel efficiencies. However, unlike their structured counterparts, the problem of distributing the mesh across the memory of the machine, whilst minimising the amount of interprocessor communication, must be carefully addressed. This process is an overhead that is not incurred by a serial code, but is shown to rapidly computable at turn time and tailored for the machine being used.

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The difficulties encountered in implementing large scale CM codes on multiprocessor systems are now fairly well understood. Despite the claims of shared memory architecture manufacturers to provide effective parallelizing compilers, these have not proved to be adequate for large or complex programs. Significant programmer effort is usually required to achieve reasonable parallel efficiencies on significant numbers of processors. The paradigm of Single Program Multi Data (SPMD) domain decomposition with message passing, where each processor runs the same code on a subdomain of the problem, communicating through exchange of messages, has for some time been demonstrated to provide the required level of efficiency, scalability, and portability across both shared and distributed memory systems, without the need to re-author the code into a new language or even to support differing message passing implementations. Extension of the methods into three dimensions has been enabled through the engineering of PHYSICA, a framework for supporting 3D, unstructured mesh and continuum mechanics modeling. In PHYSICA, six inspectors are used. Part of the challenge for automation of parallelization is being able to prove the equivalence of inspectors so that they can be merged into as few as possible.

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This chapter describes a parallel optimization technique that incorporates a distributed load-balancing algorithm and provides an extremely fast solution to the problem of load-balancing adaptive unstructured meshes. Moreover, a parallel graph contraction technique can be employed to enhance the partition quality and the resulting strategy outperforms or matches results from existing state-of-the-art static mesh partitioning algorithms. The strategy can also be applied to static partitioning problems. Dynamic procedures have been found to be much faster than static techniques, to provide partitions of similar or higher quality and, in comparison, involve the migration of a fraction of the data. The method employs a new iterative optimization technique that balances the workload and attempts to minimize the interprocessor communications overhead. Experiments on a series of adaptively refined meshes indicate that the algorithm provides partitions of an equivalent or higher quality to static partitioners (which do not reuse the existing partition) and much more quickly. The dynamic evolution of load has three major influences on possible partitioning techniques; cost, reuse, and parallelism. The unstructured mesh may be modified every few time-steps and so the load-balancing must have a low cost relative to that of the solution algorithm in between remeshing.

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The industrial production of aluminium is an electrolysis process where two superposed horizontal liquid layers are subjected to a mainly vertical electric current supplied by carbon electrodes. The lower layer consists of molten aluminium and lies on the cathode. The upper layer is the electrolyte and is covered by the anode. The interface between the two layers is often perturbed, leading to oscillations, or waves, similar to the waves on the surface of seas or lakes. The presence of electric currents and the resulting magnetic field are responsible for electromagnetic (Lorentz) forces within the fluid, which can amplify these oscillations and have an adverse influence on the process. The electrolytic bath vertical to horizontal aspect ratio is such, that it is advantageous to use the shallow water equations to model the interface motion. These are the depth-averaging the Navier-Stokes equations so that nonlinear and dispersion terms may be taken into account. Although these terms are essential to the prediction of wave dynamics, they are neglected in most of the literature on interface instabilities in aluminium reduction cells where only the linear theory is usually considered. The unknown variables are the two horizontal components of the fluid velocity, the height of the interface and the electric potential. In this application, a finite volume resolution of the double-layer shallow water equations including the electromagnetic sources has been developed, for incorporation into a generic three-dimensional computational fluid dynamics code that also deals with heat transfer within the cell.

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A method is outlined for optimising graph partitions which arise in mapping un- structured mesh calculations to parallel computers. The method employs a combination of iterative techniques to both evenly balance the workload and minimise the number and volume of interprocessor communications. They are designed to work efficiently in parallel as well as sequentially and when combined with a fast direct partitioning technique (such as the Greedy algorithm) to give an initial partition, the resulting two-stage process proves itself to be both a powerful and flexible solution to the static graph-partitioning problem. The algorithms can also be used for dynamic load-balancing and a clustering technique can additionally be employed to speed up the whole process. Experiments indicate that the resulting parallel code can provide high quality partitions, independent of the initial partition, within a few seconds.

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Unstructured mesh codes for modelling continuum physics phenomena have evolved to provide the facility to model complex interacting systems. Parallelisation of such codes using single Program Multi Data (SPMD) domain decomposition techniques implemented with message passing has been demonstrated to provide high parallel efficiency, scalability to large numbers of processors P and portability across a wide range of parallel platforms. High efficiency, especially for large P requires that load balance is achieved in each parallel loop. For a code in which loops span a variety of mesh entity types, for example, elements, faces and vertices, some compromise is required between load balance for each entity type and the quantity of inter-processor communication required to satisfy data dependence between processors.

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This paper describes two new techniques designed to enhance the performance of fire field modelling software. The two techniques are "group solvers" and automated dynamic control of the solution process, both of which are currently under development within the SMARTFIRE Computational Fluid Dynamics environment. The "group solver" is a derivation of common solver techniques used to obtain numerical solutions to the algebraic equations associated with fire field modelling. The purpose of "group solvers" is to reduce the computational overheads associated with traditional numerical solvers typically used in fire field modelling applications. In an example, discussed in this paper, the group solver is shown to provide a 37% saving in computational time compared with a traditional solver. The second technique is the automated dynamic control of the solution process, which is achieved through the use of artificial intelligence techniques. This is designed to improve the convergence capabilities of the software while further decreasing the computational overheads. The technique automatically controls solver relaxation using an integrated production rule engine with a blackboard to monitor and implement the required control changes during solution processing. Initial results for a two-dimensional fire simulation are presented that demonstrate the potential for considerable savings in simulation run-times when compared with control sets from various sources. Furthermore, the results demonstrate the potential for enhanced solution reliability due to obtaining acceptable convergence within each time step, unlike some of the comparison simulations.

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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.