17 resultados para dynamic time warping (DTW)

em Greenwich Academic Literature Archive - UK


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Self-alignment of soldered electronic components such as flip-chips (FC), ball grid arrays (BGA) and optoelectronic devices during solder reflow is important as it ensures good alignment between components and substrates. Two uncoupled analytical models are presented which provide estimates of the dynamic time scales of both the chip and the solder in the self-alignment process. These predicted time scales can be used to decide whether a coupled dynamic analysis is required for the analysis of the chip motion. In this paper, we will show that for flip-chips, the alignment dynamics can be described accurately only when the chip motion is coupled with the solder motion because the two have similar time-scale values. To study this coupled phenomenon, a dynamic modeling method has been developed. The modeling results show that the uncoupled and coupled calculations result in significantly different predictions. The calculations based on the coupled model predict much faster rates of alignment than those predicted using the uncoupled approach.

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SMARTFIRE is a fire field model based on an open architecture integrated CFD code and knowledge-based system. It makes use of the expert system to assist the user in setting up the problem specification and new computational techniques such as Group Solvers to reduce the computational effort involved in solving the equations. This paper concentrates on recent research into the use of artificial intelligence techniques to assist in dynamic solution control of fire scenarios being simulated using fire field modelling techniques. This is designed to improve the convergence capabilities of the software while further decreasing the computational overheads. The technique automatically controls solver relaxations 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 enhanced solution reliability due to obtaining acceptable convergence within each time step unlike some of the comparison simulations.

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Computational modelling of dynamic fluid-structure interaction (DFSI) is problematical since conventionally computational fluid dynamics (CFD) is solved using finite volume (FV) methods and computational structural mechanics (CSM) is based entirely on finite element (FE) methods. Hence, progress in modelling the emerging multi-physics problem of dynamic fluid-structure interaction in a consistent manner is frustrated and significant problems in computation convergence may be encountered in transferring and filtering data from one mesh and solution procedure to another, unless the fluid-structure coupling is either one way, very weak or both. This paper sets out the solution procedure for modelling the multi-physics dynamic fluid-structure interaction problem within a single software framework PHYSICA, using finite volume, unstructured mesh (FV-UM) procedures and will focus upon some of the problems and issues that have to be resolved for time accurate closely coupled dynamic fluid-structure flutter analysis.

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A procedure for evaluating the dynamic structural response of elastic solid domains is presented. A prerequisite for the analysis of dynamic fluid–structure interaction is the use of a consistent set of finite volume (FV) methods on a single unstructured mesh. This paper describes a three-dimensional (3D) FV, vertex-based method for dynamic solid mechanics. A novel Newmark predictor–corrector implicit scheme was developed to provide time accurate solutions and the scheme was evaluated on a 3D cantilever problem. By employing a small amount of viscous damping, very accurate predictions of the fundamental natural frequency were obtained with respect to both the amplitude and period of oscillation. This scheme has been implemented into the multi-physics modelling software framework, PHYSICA, for later application to full dynamic fluid structure interaction.

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Computational modelling of dynamic fluid–structure interaction (DFSI) is a considerable challenge. Our approach to this class of problems involves the use of a single software framework for all the phenomena involved, employing finite volume methods on unstructured meshes in three dimensions. This method enables time and space accurate calculations in a consistent manner. One key application of DFSI simulation is the analysis of the onset of flutter in aircraft wings, where the work of Yates et al. [Measured and Calculated Subsonic and Transonic Flutter Characteristics of a 45° degree Sweptback Wing Planform in Air and Freon-12 in the Langley Transonic Dynamic Tunnel. NASA Technical Note D-1616, 1963] on the AGARD 445.6 wing planform still provides the most comprehensive benchmark data available. This paper presents the results of a significant effort to model the onset of flutter for the AGARD 445.6 wing planform geometry. A series of key issues needs to be addressed for this computational approach. • The advantage of using a single mesh, in order to eliminate numerical problems when applying boundary conditions at the fluid-structure interface, is counteracted by the challenge of generating a suitably high quality mesh in both the fluid and structural domains. • The computational effort for this DFSI procedure, in terms of run time and memory requirements, is very significant. Practical simulations require even finer meshes and shorter time steps, requiring parallel implementation for operation on large, high performance parallel systems. • The consistency and completeness of the AGARD data in the public domain is inadequate for use in the validation of DFSI codes when predicting the onset of flutter.

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Fluid structure interaction, as applied to flexible structures, has wide application in diverse areas such as flutter in aircraft, flow in elastic pipes and blood vessels and extrusion of metals through dies. However a comprehensive computational model of these multi-physics phenomena is a considerable challenge. Until recently work in this area focused on one phenomenon and represented the behaviour of the other more simply even to the extent in metal forming, for example, that the deformation of the die is totally ignored. More recently, strategies for solving the full coupling between the fluid and soild mechanics behaviour have developed. Conventionally, the computational modelling of fluid structure interaction is problematical since computational fluid dynamics (CFD) is solved using finite volume (FV) methods and computational structural mechanics (CSM) is based entirely on finite element (FE) methods. In the past the concurrent, but rather disparate, development paths for the finite element and finite volume methods have resulted in numerical software tools for CFD and CSM that are different in almost every respect. Hence, progress is frustrated in modelling the emerging multi-physics problem of fluid structure interaction in a consistent manner. Unless the fluid-structure coupling is either one way, very weak or both, transferring and filtering data from one mesh and solution procedure to another may lead to significant problems in computational convergence. Using a novel three phase technique the full interaction between the fluid and the dynamic structural response are represented. The procedure is demonstrated on some challenging applications in complex three dimensional geometries involving aircraft flutter, metal forming and blood flow in arteries.

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This paper presents an investigation into dynamic self-adjustment of task deployment and other aspects of self-management, through the embedding of multiple policies. Non-dedicated loosely-coupled computing environments, such as clusters and grids are increasingly popular platforms for parallel processing. These abundant systems are highly dynamic environments in which many sources of variability affect the run-time efficiency of tasks. The dynamism is exacerbated by the incorporation of mobile devices and wireless communication. This paper proposes an adaptive strategy for the flexible run-time deployment of tasks; to continuously maintain efficiency despite the environmental variability. The strategy centres on policy-based scheduling which is informed by contextual and environmental inputs such as variance in the round-trip communication time between a client and its workers and the effective processing performance of each worker. A self-management framework has been implemented for evaluation purposes. The framework integrates several policy-controlled, adaptive services with the application code, enabling the run-time behaviour to be adapted to contextual and environmental conditions. Using this framework, an exemplar self-managing parallel application is implemented and used to investigate the extent of the benefits of the strategy

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This paper presents innovative work in the development of policy-based autonomic computing. The core of the work is a powerful and flexible policy-expression language AGILE, which facilitates run-time adaptable policy configuration of autonomic systems. AGILE also serves as an integrating platform for other self-management technologies including signal processing, automated trend analysis and utility functions. Each of these technologies has specific advantages and applicability to different types of dynamic adaptation. The AGILE platform enables seamless interoperability of the different technologies to each perform various aspects of self-management within a single application. The various technologies are implemented as object components. Self-management behaviour is specified using the policy language semantics to bind the various components together as required. Since the policy semantics support run-time re-configuration, the self-management architecture is dynamically composable. Additional benefits include the standardisation of the application programmer interface, terminology and semantics, and only a single point of embedding is required.

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Using thermosetting epoxy based conductive adhesive films for the flip chip interconnect possess a great deal of attractions to the electronics manufacturing industries due to the ever increasing demands for miniaturized electronic products. Adhesive manufacturers have taken many attempts over the last decade to produce a number of types of adhesives and the coupled anisotropic conductive-nonconductive adhesive film is one of them. The successful formation of the flip chip interconnection using this particular type of adhesive depends on, among factors, how the physical properties of the adhesive changes during the bonding process. Experimental measurements of the temperature in the adhesive have revealed that the temperature becomes very close to the required maximum bonding temperature within the first 1s of the bonding time. The higher the bonding temperature the faster the ramp up of temperature is. A dynamic mechanical analysis (DMA) has been carried out to investigate the nature of the changes of the physical properties of the coupled anisotropic conductive-nonconductive adhesive film for a range of bonding parameters. Adhesive samples that are pre-cured at 170, 190 and 210°C for 3, 5 and 10s have been analyzed using a DMA instrument. The results have revealed that the glass transition temperature of this type of adhesive increases with the increase in the bonding time for the bonding temperatures that have been used in this work. For the curing time of 3 and 5s, the maximum glass transition temperature increases with the increase in the bonding temperature, but for the curing time of 10s the maximum glass transition temperature has been observed in the sample which is cured at 190°C. Based on these results it has been concluded that the optimal bonding temperature and time for this kind of adhesive are 190°C and 10s, respectively.

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This paper describes a methodology for deploying flexible dynamic configuration into embedded systems whilst preserving the reliability advantages of static systems. The methodology is based on the concept of decision points (DP) which are strategically placed to achieve fine-grained distribution of self-management logic to meet application-specific requirements. DP logic can be changed easily, and independently of the host component, enabling self-management behavior to be deferred beyond the point of system deployment. A transparent Dynamic Wrapper mechanism (DW) automatically detects and handles problems arising from the evaluation of self-management logic within each DP and ensures that the dynamic aspects of the system collapse down to statically defined default behavior to ensure safety and correctness despite failures. Dynamic context management contributes to flexibility, and removes the need for design-time binding of context providers and consumers, thus facilitating run-time composition and incremental component upgrade.

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This paper describes an autonomics development tool which serves as both a powerful and flexible policy-expression language and a policy-based framework that supports the integration and dynamic composition of several autonomic computing techniques including signal processing, automated trend analysis and utility functions. Each of these technologies has specific advantages and applicability to different types of dynamic adaptation. The AGILE platform enables seamless interoperability of the different technologies to each perform various aspects of self-management within a single application. Self-management behaviour is specified using the policy language semantics to bind the various technologies together as required. Since the policy semantics support run-time re-configuration, the self-management architecture is dynamically composable. The policy language and implementation library have integrated support for self-stabilising behaviour, enabling oscillation and other forms of instability to be handled at the policy level with very little effort on the part of the application developer. Example applications are presented to illustrate the integration of different autonomics techniques, and the achievement of dynamic composition.

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This paper describes a methodology for embedding dynamic behaviour into software components. The implications and system architecture requirements to support this adaptivity are discussed. This work is part of a European Commission funded and industry supported project to produce a reconfigurable middleware for use in automotive systems. Such systems must be trustable against illegal internal behaviour and activity with external origins, additional devices for example. Policy-based computing is used here as an example of embedded logic. A key contribution of this work is the way in which static and dynamic aspects of the system are interfaced, such that the behaviour can be changed very flexibly (even during run-time), without modification, recompilation or redeployment of the embedded application code. An implementation of these concepts is presented, focussing on achieving trust in the use of dynamic behaviour.

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This paper describes a highly flexible component architecture, primarily designed for automotive control systems, that supports distributed dynamically- configurable context-aware behaviour. The architecture enforces a separation of design-time and run-time concerns, enabling almost all decisions concerning runtime composition and adaptation to be deferred beyond deployment. Dynamic context management contributes to flexibility. The architecture is extensible, and can embed potentially many different self-management decision technologies simultaneously. The mechanism that implements the run-time configuration has been designed to be very robust, automatically and silently handling problems arising from the evaluation of self- management logic and ensuring that in the worst case the dynamic aspects of the system collapse down to static behavior in totally predictable ways.

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Melting of metallic samples in a cold crucible causes inclusions to concentrate on the surface owing to the action of the electromagnetic force in the skin layer. This process is dynamic, involving the melting stage, then quasi-stationary particle separation, and finally the solidification in the cold crucible. The proposed modeling technique is based on the pseudospectral solution method for coupled turbulent fluid flow, thermal and electromagnetic fields within the time varying fluid volume contained by the free surface, and partially the solid crucible wall. The model uses two methods for particle tracking: (1) a direct Lagrangian particle path computation and (2) a drifting concentration model. Lagrangian tracking is implemented for arbitrary unsteady flow. A specific numerical time integration scheme is implemented using implicit advancement that permits relatively large time-steps in the Lagrangian model. The drifting concentration model is based on a local equilibrium drift velocity assumption. Both methods are compared and demonstrated to give qualitatively similar results for stationary flow situations. The particular results presented are obtained for iron alloys. Small size particles of the order of 1 μm are shown to be less prone to separation by electromagnetic field action. In contrast, larger particles, 10 to 100 μm, are easily “trapped” by the electromagnetic field and stay on the sample surface at predetermined locations depending on their size and properties. The model allows optimization for melting power, geometry, and solidification rate.