5 resultados para Mathematical Techniques - Integration

em Greenwich Academic Literature Archive - UK


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This account provides an overview of the study day, entitled 'Topics in the History of Financial Mathematics: Early commerce to chaos in modern stock markets,' held by the British Society for the History of Mathematics jointly with Gresham College, at Gresham College, London on 25th April 2008. The series of talks explored the development of mathematics and mathematical techniques in a commercial and financial context.

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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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For sensitive optoelectronic components, traditional soldering techniques cannot be used because of their inherent sensitivity to thermal stresses. One such component is the Optoelectronic Butterfly Package which houses a laser diode chip aligned to a fibre-optic cable. Even sub-micron misalignment of the fibre optic and laser diode chip can significantly reduce the performance of the device. The high cost of each unit requires that the number of damaged components, via the laser soldering process, are kept to a minimum. Mathematical modelling is undertaken to better understand the laser soldering process and to optimize operational parameters such as solder paste volume, copper pad dimensions, laser solder times for each joint, laser intensity and absorption coefficient. Validation of the model against experimental data will be completed, and will lead to an optimization of the assembly process, through an iterative modelling cycle. This will ultimately reduce costs, improve the process development time and increase consistency in the laser soldering process.

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In this paper, a method for the integration of several numerical analytical techniques that are used in microsystems design and failure analysis is presented. The analytical techniques are categorized into four groups in the discussion, namely the high-fidelity analytical tools, i.e. finite element (FE) method, the fast analytical tools referring to reduced order modeling (ROM); the optimization tools, and probability based analytical tools. The characteristics of these four tools are investigated. The interactions between the four tools are discussed and a methodology for the coupling of these four tools is offered. This methodology consists of three stages, namely reduced order modeling, deterministic optimization and probabilistic optimization. Using this methodology, a case study for optimization of a solder joint is conducted. It is shown that these analysis techniques have mutual relationship of interaction and complementation. Synthetic application of these techniques can fully utilize the advantages of these techniques and satisfy various design requirements. The case study shows that the coupling method of different tools provided by this paper is effective and efficient and it is highly relevant in the design and reliability analysis of microsystems

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A design methodology based on numerical modelling, integrated with optimisation techniques and statistical methods, to aid the process control of micro and nano-electronics based manufacturing processes is presented in this paper. The design methodology is demonstrated for a micro-machining process called Focused Ion Beam (FIB). This process has been modelled to help understand how a pre-defined geometry of micro- and nano- structures can be achieved using this technology. The process performance is characterised on the basis of developed Reduced Order Models (ROM) and are generated using results from a mathematical model of the Focused Ion Beam and Design of Experiment (DoE) methods. Two ion beam sources, Argon and Gallium ions, have been used to compare and quantify the process variable uncertainties that can be observed during the milling process. The evaluations of the process performance takes into account the uncertainties and variations of the process variables and are used to identify their impact on the reliability and quality of the fabricated structure. An optimisation based design task is to identify the optimal process conditions, by varying the process variables, so that certain quality objectives and requirements are achieved and imposed constraints are satisfied. The software tools used and developed to demonstrate the design methodology are also presented.